The Wolf Prize laureates

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Venkatesan Sundaresan

Wolf Prize Laureate in Agriculture 2024

Martin Rees

 

Affiliation at the time of the award:

Cambridge University, England

 

Award citation:

“for fundamental contributions to high-energy astrophysics, galaxies and structure formation, and cosmology”.

 

Prize share:

None

 

Lord Martin Rees (born in England in 1942) is one of the most distinguished theoretical physicists of our time, with seminal contributions in a large number of areas, from cosmology and the formation of the first stars and galaxies to high-energy astrophysics, to the formation and evolution of massive black holes in the centers of galaxies, tidal disruption of stars in the vicinity of such black holes, and more. These contributions shaped our deepest understanding of the Universe.

From a young age, with a strong background in mathematics, Rees discovered his attraction to astrophysics, which was, at that time, one of the fastest-growing areas of science, full of unexplained phenomena waiting to be explored. His first position as a professor at Sussex University, in 1973, soon brought him to the Institute of Astronomy in Cambridge, where he became the director of the institute, the Plumian Professor of Astronomy and Experimental Philosophy, and the Master of Trinity College. In later years, Rees became a Fellow, then the Royal Society President, and a House of Lords member in 2005. Since 1995, he has held the honorary title “The UK’s Astronomer Royal”.
Marin Rees has pioneered many ideas that are shaping our understanding of the Universe. In cosmology, he was the first to propose polarization measurements as a tool to probe the origin of fluctuations in the cosmic microwave background. This is now accepted as a key diagnostic tool of the very early universe. He was also an initiator of the field of 21cm cosmology, now becoming a very important tool for understanding the conditions in the universe prior to the birth of the first stars and galaxies. Another area where he made fundamental contributions is high-energy astrophysics. This includes the explanation of the physical processes driving extremely powerful Gamma-ray bursts from colliding neutron stars and a certain type of supernova, as well as the understanding of powerful radio jets from various types of galaxies. Later observations have confirmed Rees’s early theoretical works on the properties of such objects. Massive black holes in the centers of galaxies have been another area where Rees made numerous fundamental contributions, from suggesting various ways to explain the formation of individual black holes to ideas of how they produce their extremely high luminosity that can exceed the luminosity of entire galaxies and how the black hole population in the universe evolves in parallel to the cosmic evolution of galaxies. Such theoretical ideas are now being studied and confirmed by the most advanced ground-based and space borne telescopes. Other theoretical papers that have become timely because of recent observations are binary black hole mergers and the tidal disruption of stars by massive black holes, which have been discovered in dozens of galaxies.
Marin Rees is well known for his unusual ability to convey complex scientific concepts to the public. Over the years, he has delivered hundreds of public lectures and television interviews. He has written numerous general articles and popular science books on cosmology, life in the universe, black holes, and other topics of 21st-century science. The title of his recent book, from 2022, is “If Science is to Save Us.” In recent years, he has been spending much of his time in efforts to safeguard the global environment. He co-founded the “Centre for the Study of Existential Risk at the University of Cambridge,” an interdisciplinary research center that studies existential risks and fosters a global community to safeguard humanity.
Martin Rees is awarded the Wolf Prize for shaping our deepest understanding of the Universe. His outstanding contributions range from high-energy astrophysics, including mechanisms for gamma-ray bursts, powerful radio jets, and black hole formation in galactic nuclei, to cosmic structure formation and the physics of the earliest stars and galaxies at the end of the “dark age.” He was the first to propose polarization measurements as a tool to probe the origin of fluctuations and anisotropy in the cosmic microwave background (CMB), and an initiator of the field of 21cm cosmology.

Noga Alon

Wolf Prize Laureate in Mathematics 2024

Martin Rees

 

Affiliation at the time of the award:

Cambridge University, England

 

Award citation:

“for fundamental contributions to high-energy astrophysics, galaxies and structure formation, and cosmology”.

 

Prize share:

None

 

Lord Martin Rees (born in England in 1942) is one of the most distinguished theoretical physicists of our time, with seminal contributions in a large number of areas, from cosmology and the formation of the first stars and galaxies to high-energy astrophysics, to the formation and evolution of massive black holes in the centers of galaxies, tidal disruption of stars in the vicinity of such black holes, and more. These contributions shaped our deepest understanding of the Universe.

From a young age, with a strong background in mathematics, Rees discovered his attraction to astrophysics, which was, at that time, one of the fastest-growing areas of science, full of unexplained phenomena waiting to be explored. His first position as a professor at Sussex University, in 1973, soon brought him to the Institute of Astronomy in Cambridge, where he became the director of the institute, the Plumian Professor of Astronomy and Experimental Philosophy, and the Master of Trinity College. In later years, Rees became a Fellow, then the Royal Society President, and a House of Lords member in 2005. Since 1995, he has held the honorary title “The UK’s Astronomer Royal”.
Marin Rees has pioneered many ideas that are shaping our understanding of the Universe. In cosmology, he was the first to propose polarization measurements as a tool to probe the origin of fluctuations in the cosmic microwave background. This is now accepted as a key diagnostic tool of the very early universe. He was also an initiator of the field of 21cm cosmology, now becoming a very important tool for understanding the conditions in the universe prior to the birth of the first stars and galaxies. Another area where he made fundamental contributions is high-energy astrophysics. This includes the explanation of the physical processes driving extremely powerful Gamma-ray bursts from colliding neutron stars and a certain type of supernova, as well as the understanding of powerful radio jets from various types of galaxies. Later observations have confirmed Rees’s early theoretical works on the properties of such objects. Massive black holes in the centers of galaxies have been another area where Rees made numerous fundamental contributions, from suggesting various ways to explain the formation of individual black holes to ideas of how they produce their extremely high luminosity that can exceed the luminosity of entire galaxies and how the black hole population in the universe evolves in parallel to the cosmic evolution of galaxies. Such theoretical ideas are now being studied and confirmed by the most advanced ground-based and space borne telescopes. Other theoretical papers that have become timely because of recent observations are binary black hole mergers and the tidal disruption of stars by massive black holes, which have been discovered in dozens of galaxies.
Marin Rees is well known for his unusual ability to convey complex scientific concepts to the public. Over the years, he has delivered hundreds of public lectures and television interviews. He has written numerous general articles and popular science books on cosmology, life in the universe, black holes, and other topics of 21st-century science. The title of his recent book, from 2022, is “If Science is to Save Us.” In recent years, he has been spending much of his time in efforts to safeguard the global environment. He co-founded the “Centre for the Study of Existential Risk at the University of Cambridge,” an interdisciplinary research center that studies existential risks and fosters a global community to safeguard humanity.
Martin Rees is awarded the Wolf Prize for shaping our deepest understanding of the Universe. His outstanding contributions range from high-energy astrophysics, including mechanisms for gamma-ray bursts, powerful radio jets, and black hole formation in galactic nuclei, to cosmic structure formation and the physics of the earliest stars and galaxies at the end of the “dark age.” He was the first to propose polarization measurements as a tool to probe the origin of fluctuations and anisotropy in the cosmic microwave background (CMB), and an initiator of the field of 21cm cosmology.

Adi Shamir

Wolf Prize Laureate in Mathematics 2024

Martin Rees

 

Affiliation at the time of the award:

Cambridge University, England

 

Award citation:

“for fundamental contributions to high-energy astrophysics, galaxies and structure formation, and cosmology”.

 

Prize share:

None

 

Lord Martin Rees (born in England in 1942) is one of the most distinguished theoretical physicists of our time, with seminal contributions in a large number of areas, from cosmology and the formation of the first stars and galaxies to high-energy astrophysics, to the formation and evolution of massive black holes in the centers of galaxies, tidal disruption of stars in the vicinity of such black holes, and more. These contributions shaped our deepest understanding of the Universe.

From a young age, with a strong background in mathematics, Rees discovered his attraction to astrophysics, which was, at that time, one of the fastest-growing areas of science, full of unexplained phenomena waiting to be explored. His first position as a professor at Sussex University, in 1973, soon brought him to the Institute of Astronomy in Cambridge, where he became the director of the institute, the Plumian Professor of Astronomy and Experimental Philosophy, and the Master of Trinity College. In later years, Rees became a Fellow, then the Royal Society President, and a House of Lords member in 2005. Since 1995, he has held the honorary title “The UK’s Astronomer Royal”.
Marin Rees has pioneered many ideas that are shaping our understanding of the Universe. In cosmology, he was the first to propose polarization measurements as a tool to probe the origin of fluctuations in the cosmic microwave background. This is now accepted as a key diagnostic tool of the very early universe. He was also an initiator of the field of 21cm cosmology, now becoming a very important tool for understanding the conditions in the universe prior to the birth of the first stars and galaxies. Another area where he made fundamental contributions is high-energy astrophysics. This includes the explanation of the physical processes driving extremely powerful Gamma-ray bursts from colliding neutron stars and a certain type of supernova, as well as the understanding of powerful radio jets from various types of galaxies. Later observations have confirmed Rees’s early theoretical works on the properties of such objects. Massive black holes in the centers of galaxies have been another area where Rees made numerous fundamental contributions, from suggesting various ways to explain the formation of individual black holes to ideas of how they produce their extremely high luminosity that can exceed the luminosity of entire galaxies and how the black hole population in the universe evolves in parallel to the cosmic evolution of galaxies. Such theoretical ideas are now being studied and confirmed by the most advanced ground-based and space borne telescopes. Other theoretical papers that have become timely because of recent observations are binary black hole mergers and the tidal disruption of stars by massive black holes, which have been discovered in dozens of galaxies.
Marin Rees is well known for his unusual ability to convey complex scientific concepts to the public. Over the years, he has delivered hundreds of public lectures and television interviews. He has written numerous general articles and popular science books on cosmology, life in the universe, black holes, and other topics of 21st-century science. The title of his recent book, from 2022, is “If Science is to Save Us.” In recent years, he has been spending much of his time in efforts to safeguard the global environment. He co-founded the “Centre for the Study of Existential Risk at the University of Cambridge,” an interdisciplinary research center that studies existential risks and fosters a global community to safeguard humanity.
Martin Rees is awarded the Wolf Prize for shaping our deepest understanding of the Universe. His outstanding contributions range from high-energy astrophysics, including mechanisms for gamma-ray bursts, powerful radio jets, and black hole formation in galactic nuclei, to cosmic structure formation and the physics of the earliest stars and galaxies at the end of the “dark age.” He was the first to propose polarization measurements as a tool to probe the origin of fluctuations and anisotropy in the cosmic microwave background (CMB), and an initiator of the field of 21cm cosmology.

José-Alain Sahel

Wolf Prize Laureate in Medicine 2024

Martin Rees

 

Affiliation at the time of the award:

Cambridge University, England

 

Award citation:

“for fundamental contributions to high-energy astrophysics, galaxies and structure formation, and cosmology”.

 

Prize share:

None

 

Lord Martin Rees (born in England in 1942) is one of the most distinguished theoretical physicists of our time, with seminal contributions in a large number of areas, from cosmology and the formation of the first stars and galaxies to high-energy astrophysics, to the formation and evolution of massive black holes in the centers of galaxies, tidal disruption of stars in the vicinity of such black holes, and more. These contributions shaped our deepest understanding of the Universe.

From a young age, with a strong background in mathematics, Rees discovered his attraction to astrophysics, which was, at that time, one of the fastest-growing areas of science, full of unexplained phenomena waiting to be explored. His first position as a professor at Sussex University, in 1973, soon brought him to the Institute of Astronomy in Cambridge, where he became the director of the institute, the Plumian Professor of Astronomy and Experimental Philosophy, and the Master of Trinity College. In later years, Rees became a Fellow, then the Royal Society President, and a House of Lords member in 2005. Since 1995, he has held the honorary title “The UK’s Astronomer Royal”.
Marin Rees has pioneered many ideas that are shaping our understanding of the Universe. In cosmology, he was the first to propose polarization measurements as a tool to probe the origin of fluctuations in the cosmic microwave background. This is now accepted as a key diagnostic tool of the very early universe. He was also an initiator of the field of 21cm cosmology, now becoming a very important tool for understanding the conditions in the universe prior to the birth of the first stars and galaxies. Another area where he made fundamental contributions is high-energy astrophysics. This includes the explanation of the physical processes driving extremely powerful Gamma-ray bursts from colliding neutron stars and a certain type of supernova, as well as the understanding of powerful radio jets from various types of galaxies. Later observations have confirmed Rees’s early theoretical works on the properties of such objects. Massive black holes in the centers of galaxies have been another area where Rees made numerous fundamental contributions, from suggesting various ways to explain the formation of individual black holes to ideas of how they produce their extremely high luminosity that can exceed the luminosity of entire galaxies and how the black hole population in the universe evolves in parallel to the cosmic evolution of galaxies. Such theoretical ideas are now being studied and confirmed by the most advanced ground-based and space borne telescopes. Other theoretical papers that have become timely because of recent observations are binary black hole mergers and the tidal disruption of stars by massive black holes, which have been discovered in dozens of galaxies.
Marin Rees is well known for his unusual ability to convey complex scientific concepts to the public. Over the years, he has delivered hundreds of public lectures and television interviews. He has written numerous general articles and popular science books on cosmology, life in the universe, black holes, and other topics of 21st-century science. The title of his recent book, from 2022, is “If Science is to Save Us.” In recent years, he has been spending much of his time in efforts to safeguard the global environment. He co-founded the “Centre for the Study of Existential Risk at the University of Cambridge,” an interdisciplinary research center that studies existential risks and fosters a global community to safeguard humanity.
Martin Rees is awarded the Wolf Prize for shaping our deepest understanding of the Universe. His outstanding contributions range from high-energy astrophysics, including mechanisms for gamma-ray bursts, powerful radio jets, and black hole formation in galactic nuclei, to cosmic structure formation and the physics of the earliest stars and galaxies at the end of the “dark age.” He was the first to propose polarization measurements as a tool to probe the origin of fluctuations and anisotropy in the cosmic microwave background (CMB), and an initiator of the field of 21cm cosmology.

Botond Roska

Wolf Prize Laureate in Medicine 2024

Martin Rees

 

Affiliation at the time of the award:

Cambridge University, England

 

Award citation:

“for fundamental contributions to high-energy astrophysics, galaxies and structure formation, and cosmology”.

 

Prize share:

None

 

Lord Martin Rees (born in England in 1942) is one of the most distinguished theoretical physicists of our time, with seminal contributions in a large number of areas, from cosmology and the formation of the first stars and galaxies to high-energy astrophysics, to the formation and evolution of massive black holes in the centers of galaxies, tidal disruption of stars in the vicinity of such black holes, and more. These contributions shaped our deepest understanding of the Universe.

From a young age, with a strong background in mathematics, Rees discovered his attraction to astrophysics, which was, at that time, one of the fastest-growing areas of science, full of unexplained phenomena waiting to be explored. His first position as a professor at Sussex University, in 1973, soon brought him to the Institute of Astronomy in Cambridge, where he became the director of the institute, the Plumian Professor of Astronomy and Experimental Philosophy, and the Master of Trinity College. In later years, Rees became a Fellow, then the Royal Society President, and a House of Lords member in 2005. Since 1995, he has held the honorary title “The UK’s Astronomer Royal”.
Marin Rees has pioneered many ideas that are shaping our understanding of the Universe. In cosmology, he was the first to propose polarization measurements as a tool to probe the origin of fluctuations in the cosmic microwave background. This is now accepted as a key diagnostic tool of the very early universe. He was also an initiator of the field of 21cm cosmology, now becoming a very important tool for understanding the conditions in the universe prior to the birth of the first stars and galaxies. Another area where he made fundamental contributions is high-energy astrophysics. This includes the explanation of the physical processes driving extremely powerful Gamma-ray bursts from colliding neutron stars and a certain type of supernova, as well as the understanding of powerful radio jets from various types of galaxies. Later observations have confirmed Rees’s early theoretical works on the properties of such objects. Massive black holes in the centers of galaxies have been another area where Rees made numerous fundamental contributions, from suggesting various ways to explain the formation of individual black holes to ideas of how they produce their extremely high luminosity that can exceed the luminosity of entire galaxies and how the black hole population in the universe evolves in parallel to the cosmic evolution of galaxies. Such theoretical ideas are now being studied and confirmed by the most advanced ground-based and space borne telescopes. Other theoretical papers that have become timely because of recent observations are binary black hole mergers and the tidal disruption of stars by massive black holes, which have been discovered in dozens of galaxies.
Marin Rees is well known for his unusual ability to convey complex scientific concepts to the public. Over the years, he has delivered hundreds of public lectures and television interviews. He has written numerous general articles and popular science books on cosmology, life in the universe, black holes, and other topics of 21st-century science. The title of his recent book, from 2022, is “If Science is to Save Us.” In recent years, he has been spending much of his time in efforts to safeguard the global environment. He co-founded the “Centre for the Study of Existential Risk at the University of Cambridge,” an interdisciplinary research center that studies existential risks and fosters a global community to safeguard humanity.
Martin Rees is awarded the Wolf Prize for shaping our deepest understanding of the Universe. His outstanding contributions range from high-energy astrophysics, including mechanisms for gamma-ray bursts, powerful radio jets, and black hole formation in galactic nuclei, to cosmic structure formation and the physics of the earliest stars and galaxies at the end of the “dark age.” He was the first to propose polarization measurements as a tool to probe the origin of fluctuations and anisotropy in the cosmic microwave background (CMB), and an initiator of the field of 21cm cosmology.

Elliot M. Meyerowitz

Wolf Prize Laureate in Agriculture 2024

Martin Rees

 

Affiliation at the time of the award:

Cambridge University, England

 

Award citation:

“for fundamental contributions to high-energy astrophysics, galaxies and structure formation, and cosmology”.

 

Prize share:

None

 

Lord Martin Rees (born in England in 1942) is one of the most distinguished theoretical physicists of our time, with seminal contributions in a large number of areas, from cosmology and the formation of the first stars and galaxies to high-energy astrophysics, to the formation and evolution of massive black holes in the centers of galaxies, tidal disruption of stars in the vicinity of such black holes, and more. These contributions shaped our deepest understanding of the Universe.

From a young age, with a strong background in mathematics, Rees discovered his attraction to astrophysics, which was, at that time, one of the fastest-growing areas of science, full of unexplained phenomena waiting to be explored. His first position as a professor at Sussex University, in 1973, soon brought him to the Institute of Astronomy in Cambridge, where he became the director of the institute, the Plumian Professor of Astronomy and Experimental Philosophy, and the Master of Trinity College. In later years, Rees became a Fellow, then the Royal Society President, and a House of Lords member in 2005. Since 1995, he has held the honorary title “The UK’s Astronomer Royal”.
Marin Rees has pioneered many ideas that are shaping our understanding of the Universe. In cosmology, he was the first to propose polarization measurements as a tool to probe the origin of fluctuations in the cosmic microwave background. This is now accepted as a key diagnostic tool of the very early universe. He was also an initiator of the field of 21cm cosmology, now becoming a very important tool for understanding the conditions in the universe prior to the birth of the first stars and galaxies. Another area where he made fundamental contributions is high-energy astrophysics. This includes the explanation of the physical processes driving extremely powerful Gamma-ray bursts from colliding neutron stars and a certain type of supernova, as well as the understanding of powerful radio jets from various types of galaxies. Later observations have confirmed Rees’s early theoretical works on the properties of such objects. Massive black holes in the centers of galaxies have been another area where Rees made numerous fundamental contributions, from suggesting various ways to explain the formation of individual black holes to ideas of how they produce their extremely high luminosity that can exceed the luminosity of entire galaxies and how the black hole population in the universe evolves in parallel to the cosmic evolution of galaxies. Such theoretical ideas are now being studied and confirmed by the most advanced ground-based and space borne telescopes. Other theoretical papers that have become timely because of recent observations are binary black hole mergers and the tidal disruption of stars by massive black holes, which have been discovered in dozens of galaxies.
Marin Rees is well known for his unusual ability to convey complex scientific concepts to the public. Over the years, he has delivered hundreds of public lectures and television interviews. He has written numerous general articles and popular science books on cosmology, life in the universe, black holes, and other topics of 21st-century science. The title of his recent book, from 2022, is “If Science is to Save Us.” In recent years, he has been spending much of his time in efforts to safeguard the global environment. He co-founded the “Centre for the Study of Existential Risk at the University of Cambridge,” an interdisciplinary research center that studies existential risks and fosters a global community to safeguard humanity.
Martin Rees is awarded the Wolf Prize for shaping our deepest understanding of the Universe. His outstanding contributions range from high-energy astrophysics, including mechanisms for gamma-ray bursts, powerful radio jets, and black hole formation in galactic nuclei, to cosmic structure formation and the physics of the earliest stars and galaxies at the end of the “dark age.” He was the first to propose polarization measurements as a tool to probe the origin of fluctuations and anisotropy in the cosmic microwave background (CMB), and an initiator of the field of 21cm cosmology.

Joanne Chory

Wolf Prize Laureate in Agriculture 2024

Martin Rees

 

Affiliation at the time of the award:

Cambridge University, England

 

Award citation:

“for fundamental contributions to high-energy astrophysics, galaxies and structure formation, and cosmology”.

 

Prize share:

None

 

Lord Martin Rees (born in England in 1942) is one of the most distinguished theoretical physicists of our time, with seminal contributions in a large number of areas, from cosmology and the formation of the first stars and galaxies to high-energy astrophysics, to the formation and evolution of massive black holes in the centers of galaxies, tidal disruption of stars in the vicinity of such black holes, and more. These contributions shaped our deepest understanding of the Universe.

From a young age, with a strong background in mathematics, Rees discovered his attraction to astrophysics, which was, at that time, one of the fastest-growing areas of science, full of unexplained phenomena waiting to be explored. His first position as a professor at Sussex University, in 1973, soon brought him to the Institute of Astronomy in Cambridge, where he became the director of the institute, the Plumian Professor of Astronomy and Experimental Philosophy, and the Master of Trinity College. In later years, Rees became a Fellow, then the Royal Society President, and a House of Lords member in 2005. Since 1995, he has held the honorary title “The UK’s Astronomer Royal”.
Marin Rees has pioneered many ideas that are shaping our understanding of the Universe. In cosmology, he was the first to propose polarization measurements as a tool to probe the origin of fluctuations in the cosmic microwave background. This is now accepted as a key diagnostic tool of the very early universe. He was also an initiator of the field of 21cm cosmology, now becoming a very important tool for understanding the conditions in the universe prior to the birth of the first stars and galaxies. Another area where he made fundamental contributions is high-energy astrophysics. This includes the explanation of the physical processes driving extremely powerful Gamma-ray bursts from colliding neutron stars and a certain type of supernova, as well as the understanding of powerful radio jets from various types of galaxies. Later observations have confirmed Rees’s early theoretical works on the properties of such objects. Massive black holes in the centers of galaxies have been another area where Rees made numerous fundamental contributions, from suggesting various ways to explain the formation of individual black holes to ideas of how they produce their extremely high luminosity that can exceed the luminosity of entire galaxies and how the black hole population in the universe evolves in parallel to the cosmic evolution of galaxies. Such theoretical ideas are now being studied and confirmed by the most advanced ground-based and space borne telescopes. Other theoretical papers that have become timely because of recent observations are binary black hole mergers and the tidal disruption of stars by massive black holes, which have been discovered in dozens of galaxies.
Marin Rees is well known for his unusual ability to convey complex scientific concepts to the public. Over the years, he has delivered hundreds of public lectures and television interviews. He has written numerous general articles and popular science books on cosmology, life in the universe, black holes, and other topics of 21st-century science. The title of his recent book, from 2022, is “If Science is to Save Us.” In recent years, he has been spending much of his time in efforts to safeguard the global environment. He co-founded the “Centre for the Study of Existential Risk at the University of Cambridge,” an interdisciplinary research center that studies existential risks and fosters a global community to safeguard humanity.
Martin Rees is awarded the Wolf Prize for shaping our deepest understanding of the Universe. His outstanding contributions range from high-energy astrophysics, including mechanisms for gamma-ray bursts, powerful radio jets, and black hole formation in galactic nuclei, to cosmic structure formation and the physics of the earliest stars and galaxies at the end of the “dark age.” He was the first to propose polarization measurements as a tool to probe the origin of fluctuations and anisotropy in the cosmic microwave background (CMB), and an initiator of the field of 21cm cosmology.

Martin Rees

Wolf Prize Laureate in Physics 2024

Martin Rees

 

Affiliation at the time of the award:

Cambridge University, England

 

Award citation:

“for fundamental contributions to high-energy astrophysics, galaxies and structure formation, and cosmology”.

 

Prize share:

None

 

Lord Martin Rees (born in England in 1942) is one of the most distinguished theoretical physicists of our time, with seminal contributions in a large number of areas, from cosmology and the formation of the first stars and galaxies to high-energy astrophysics, to the formation and evolution of massive black holes in the centers of galaxies, tidal disruption of stars in the vicinity of such black holes, and more. These contributions shaped our deepest understanding of the Universe.

From a young age, with a strong background in mathematics, Rees discovered his attraction to astrophysics, which was, at that time, one of the fastest-growing areas of science, full of unexplained phenomena waiting to be explored. His first position as a professor at Sussex University, in 1973, soon brought him to the Institute of Astronomy in Cambridge, where he became the director of the institute, the Plumian Professor of Astronomy and Experimental Philosophy, and the Master of Trinity College. In later years, Rees became a Fellow, then the Royal Society President, and a House of Lords member in 2005. Since 1995, he has held the honorary title “The UK’s Astronomer Royal”.
Marin Rees has pioneered many ideas that are shaping our understanding of the Universe. In cosmology, he was the first to propose polarization measurements as a tool to probe the origin of fluctuations in the cosmic microwave background. This is now accepted as a key diagnostic tool of the very early universe. He was also an initiator of the field of 21cm cosmology, now becoming a very important tool for understanding the conditions in the universe prior to the birth of the first stars and galaxies. Another area where he made fundamental contributions is high-energy astrophysics. This includes the explanation of the physical processes driving extremely powerful Gamma-ray bursts from colliding neutron stars and a certain type of supernova, as well as the understanding of powerful radio jets from various types of galaxies. Later observations have confirmed Rees’s early theoretical works on the properties of such objects. Massive black holes in the centers of galaxies have been another area where Rees made numerous fundamental contributions, from suggesting various ways to explain the formation of individual black holes to ideas of how they produce their extremely high luminosity that can exceed the luminosity of entire galaxies and how the black hole population in the universe evolves in parallel to the cosmic evolution of galaxies. Such theoretical ideas are now being studied and confirmed by the most advanced ground-based and space borne telescopes. Other theoretical papers that have become timely because of recent observations are binary black hole mergers and the tidal disruption of stars by massive black holes, which have been discovered in dozens of galaxies.
Marin Rees is well known for his unusual ability to convey complex scientific concepts to the public. Over the years, he has delivered hundreds of public lectures and television interviews. He has written numerous general articles and popular science books on cosmology, life in the universe, black holes, and other topics of 21st-century science. The title of his recent book, from 2022, is “If Science is to Save Us.” In recent years, he has been spending much of his time in efforts to safeguard the global environment. He co-founded the “Centre for the Study of Existential Risk at the University of Cambridge,” an interdisciplinary research center that studies existential risks and fosters a global community to safeguard humanity.
Martin Rees is awarded the Wolf Prize for shaping our deepest understanding of the Universe. His outstanding contributions range from high-energy astrophysics, including mechanisms for gamma-ray bursts, powerful radio jets, and black hole formation in galactic nuclei, to cosmic structure formation and the physics of the earliest stars and galaxies at the end of the “dark age.” He was the first to propose polarization measurements as a tool to probe the origin of fluctuations and anisotropy in the cosmic microwave background (CMB), and an initiator of the field of 21cm cosmology.

Prizes and scholarships laureates

// order posts by year $posts_by_year;

Nir Shlezinger

Krill Prize 2024
Ben-Gurion University

Shay Tamar

 

Affiliation at the time of the award:

Technion

Faculty of Mathematics

 

Award citation:

“for unique contributions in machine learning research and generalization theory”.

 

Machine learning, better known to most of us as Artificial Intelligence – AI is applied in a wide variety of fields – starting with engineering challenges such as autonomous components and ending with social political fields that include sensitive personal data such as the management and accessibility of information on social networks such as Facebook or Twitter.

Dr. Moran’s research focuses on one of the most important branches of machine learning, which is called generalization theory and aims to quantitatively understand how machine learning generalizes from the individual to the general. This branch has made a significant contribution to the revolutionary technological breakthroughs that the field has experienced in recent years.

The latest breakthroughs in generalization theory demonstrate phenomenas that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. The latest breakthroughs in generalization theory demonstrate phenomena that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. One of the main reasons for this is that the classical generalization theory is based on definitions that focus on the worst case, and is therefore too pessimistic. This means that in practical machine learning problems the input usually does not fit the worst case, and experiments show that it is often possible to successfully learn based on training on far fewer examples than the number required by the predictions of the classical theory. Dr. Moran’s research aims to develop generalization theories that complement classical theory and enable more accurately model modern learning tasks, including tasks involving sensitive data.

Chaya Keller

Krill Prize 2024
Ariel University

Shay Tamar

 

Affiliation at the time of the award:

Technion

Faculty of Mathematics

 

Award citation:

“for unique contributions in machine learning research and generalization theory”.

 

Machine learning, better known to most of us as Artificial Intelligence – AI is applied in a wide variety of fields – starting with engineering challenges such as autonomous components and ending with social political fields that include sensitive personal data such as the management and accessibility of information on social networks such as Facebook or Twitter.

Dr. Moran’s research focuses on one of the most important branches of machine learning, which is called generalization theory and aims to quantitatively understand how machine learning generalizes from the individual to the general. This branch has made a significant contribution to the revolutionary technological breakthroughs that the field has experienced in recent years.

The latest breakthroughs in generalization theory demonstrate phenomenas that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. The latest breakthroughs in generalization theory demonstrate phenomena that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. One of the main reasons for this is that the classical generalization theory is based on definitions that focus on the worst case, and is therefore too pessimistic. This means that in practical machine learning problems the input usually does not fit the worst case, and experiments show that it is often possible to successfully learn based on training on far fewer examples than the number required by the predictions of the classical theory. Dr. Moran’s research aims to develop generalization theories that complement classical theory and enable more accurately model modern learning tasks, including tasks involving sensitive data.

Raya Sorkin

Krill Prize 2024
Tel-Aviv University

Shay Tamar

 

Affiliation at the time of the award:

Technion

Faculty of Mathematics

 

Award citation:

“for unique contributions in machine learning research and generalization theory”.

 

Machine learning, better known to most of us as Artificial Intelligence – AI is applied in a wide variety of fields – starting with engineering challenges such as autonomous components and ending with social political fields that include sensitive personal data such as the management and accessibility of information on social networks such as Facebook or Twitter.

Dr. Moran’s research focuses on one of the most important branches of machine learning, which is called generalization theory and aims to quantitatively understand how machine learning generalizes from the individual to the general. This branch has made a significant contribution to the revolutionary technological breakthroughs that the field has experienced in recent years.

The latest breakthroughs in generalization theory demonstrate phenomenas that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. The latest breakthroughs in generalization theory demonstrate phenomena that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. One of the main reasons for this is that the classical generalization theory is based on definitions that focus on the worst case, and is therefore too pessimistic. This means that in practical machine learning problems the input usually does not fit the worst case, and experiments show that it is often possible to successfully learn based on training on far fewer examples than the number required by the predictions of the classical theory. Dr. Moran’s research aims to develop generalization theories that complement classical theory and enable more accurately model modern learning tasks, including tasks involving sensitive data.

Hila Peleg

Krill Prize 2024
Technion

Shay Tamar

 

Affiliation at the time of the award:

Technion

Faculty of Mathematics

 

Award citation:

“for unique contributions in machine learning research and generalization theory”.

 

Machine learning, better known to most of us as Artificial Intelligence – AI is applied in a wide variety of fields – starting with engineering challenges such as autonomous components and ending with social political fields that include sensitive personal data such as the management and accessibility of information on social networks such as Facebook or Twitter.

Dr. Moran’s research focuses on one of the most important branches of machine learning, which is called generalization theory and aims to quantitatively understand how machine learning generalizes from the individual to the general. This branch has made a significant contribution to the revolutionary technological breakthroughs that the field has experienced in recent years.

The latest breakthroughs in generalization theory demonstrate phenomenas that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. The latest breakthroughs in generalization theory demonstrate phenomena that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. One of the main reasons for this is that the classical generalization theory is based on definitions that focus on the worst case, and is therefore too pessimistic. This means that in practical machine learning problems the input usually does not fit the worst case, and experiments show that it is often possible to successfully learn based on training on far fewer examples than the number required by the predictions of the classical theory. Dr. Moran’s research aims to develop generalization theories that complement classical theory and enable more accurately model modern learning tasks, including tasks involving sensitive data.

Itamar Harel

Krill Prize 2024
The Hebrew University

Shay Tamar

 

Affiliation at the time of the award:

Technion

Faculty of Mathematics

 

Award citation:

“for unique contributions in machine learning research and generalization theory”.

 

Machine learning, better known to most of us as Artificial Intelligence – AI is applied in a wide variety of fields – starting with engineering challenges such as autonomous components and ending with social political fields that include sensitive personal data such as the management and accessibility of information on social networks such as Facebook or Twitter.

Dr. Moran’s research focuses on one of the most important branches of machine learning, which is called generalization theory and aims to quantitatively understand how machine learning generalizes from the individual to the general. This branch has made a significant contribution to the revolutionary technological breakthroughs that the field has experienced in recent years.

The latest breakthroughs in generalization theory demonstrate phenomenas that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. The latest breakthroughs in generalization theory demonstrate phenomena that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. One of the main reasons for this is that the classical generalization theory is based on definitions that focus on the worst case, and is therefore too pessimistic. This means that in practical machine learning problems the input usually does not fit the worst case, and experiments show that it is often possible to successfully learn based on training on far fewer examples than the number required by the predictions of the classical theory. Dr. Moran’s research aims to develop generalization theories that complement classical theory and enable more accurately model modern learning tasks, including tasks involving sensitive data.

Yaniv Romano

Krill Prize 2024
Technion

Shay Tamar

 

Affiliation at the time of the award:

Technion

Faculty of Mathematics

 

Award citation:

“for unique contributions in machine learning research and generalization theory”.

 

Machine learning, better known to most of us as Artificial Intelligence – AI is applied in a wide variety of fields – starting with engineering challenges such as autonomous components and ending with social political fields that include sensitive personal data such as the management and accessibility of information on social networks such as Facebook or Twitter.

Dr. Moran’s research focuses on one of the most important branches of machine learning, which is called generalization theory and aims to quantitatively understand how machine learning generalizes from the individual to the general. This branch has made a significant contribution to the revolutionary technological breakthroughs that the field has experienced in recent years.

The latest breakthroughs in generalization theory demonstrate phenomenas that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. The latest breakthroughs in generalization theory demonstrate phenomena that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. One of the main reasons for this is that the classical generalization theory is based on definitions that focus on the worst case, and is therefore too pessimistic. This means that in practical machine learning problems the input usually does not fit the worst case, and experiments show that it is often possible to successfully learn based on training on far fewer examples than the number required by the predictions of the classical theory. Dr. Moran’s research aims to develop generalization theories that complement classical theory and enable more accurately model modern learning tasks, including tasks involving sensitive data.

Renana Gershoni-Poranne

Krill Prize 2024
Technion

Shay Tamar

 

Affiliation at the time of the award:

Technion

Faculty of Mathematics

 

Award citation:

“for unique contributions in machine learning research and generalization theory”.

 

Machine learning, better known to most of us as Artificial Intelligence – AI is applied in a wide variety of fields – starting with engineering challenges such as autonomous components and ending with social political fields that include sensitive personal data such as the management and accessibility of information on social networks such as Facebook or Twitter.

Dr. Moran’s research focuses on one of the most important branches of machine learning, which is called generalization theory and aims to quantitatively understand how machine learning generalizes from the individual to the general. This branch has made a significant contribution to the revolutionary technological breakthroughs that the field has experienced in recent years.

The latest breakthroughs in generalization theory demonstrate phenomenas that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. The latest breakthroughs in generalization theory demonstrate phenomena that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. One of the main reasons for this is that the classical generalization theory is based on definitions that focus on the worst case, and is therefore too pessimistic. This means that in practical machine learning problems the input usually does not fit the worst case, and experiments show that it is often possible to successfully learn based on training on far fewer examples than the number required by the predictions of the classical theory. Dr. Moran’s research aims to develop generalization theories that complement classical theory and enable more accurately model modern learning tasks, including tasks involving sensitive data.

Neta Shlezinger

Krill Prize 2024
The Hebrew University

Shay Tamar

 

Affiliation at the time of the award:

Technion

Faculty of Mathematics

 

Award citation:

“for unique contributions in machine learning research and generalization theory”.

 

Machine learning, better known to most of us as Artificial Intelligence – AI is applied in a wide variety of fields – starting with engineering challenges such as autonomous components and ending with social political fields that include sensitive personal data such as the management and accessibility of information on social networks such as Facebook or Twitter.

Dr. Moran’s research focuses on one of the most important branches of machine learning, which is called generalization theory and aims to quantitatively understand how machine learning generalizes from the individual to the general. This branch has made a significant contribution to the revolutionary technological breakthroughs that the field has experienced in recent years.

The latest breakthroughs in generalization theory demonstrate phenomenas that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. The latest breakthroughs in generalization theory demonstrate phenomena that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. One of the main reasons for this is that the classical generalization theory is based on definitions that focus on the worst case, and is therefore too pessimistic. This means that in practical machine learning problems the input usually does not fit the worst case, and experiments show that it is often possible to successfully learn based on training on far fewer examples than the number required by the predictions of the classical theory. Dr. Moran’s research aims to develop generalization theories that complement classical theory and enable more accurately model modern learning tasks, including tasks involving sensitive data.

Mor Nitzan

Krill Prize 2024
The Hebrew University

Shay Tamar

 

Affiliation at the time of the award:

Technion

Faculty of Mathematics

 

Award citation:

“for unique contributions in machine learning research and generalization theory”.

 

Machine learning, better known to most of us as Artificial Intelligence – AI is applied in a wide variety of fields – starting with engineering challenges such as autonomous components and ending with social political fields that include sensitive personal data such as the management and accessibility of information on social networks such as Facebook or Twitter.

Dr. Moran’s research focuses on one of the most important branches of machine learning, which is called generalization theory and aims to quantitatively understand how machine learning generalizes from the individual to the general. This branch has made a significant contribution to the revolutionary technological breakthroughs that the field has experienced in recent years.

The latest breakthroughs in generalization theory demonstrate phenomenas that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. The latest breakthroughs in generalization theory demonstrate phenomena that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. One of the main reasons for this is that the classical generalization theory is based on definitions that focus on the worst case, and is therefore too pessimistic. This means that in practical machine learning problems the input usually does not fit the worst case, and experiments show that it is often possible to successfully learn based on training on far fewer examples than the number required by the predictions of the classical theory. Dr. Moran’s research aims to develop generalization theories that complement classical theory and enable more accurately model modern learning tasks, including tasks involving sensitive data.

Yoav Livneh

Krill Prize 2024
Weizmann Institute

Shay Tamar

 

Affiliation at the time of the award:

Technion

Faculty of Mathematics

 

Award citation:

“for unique contributions in machine learning research and generalization theory”.

 

Machine learning, better known to most of us as Artificial Intelligence – AI is applied in a wide variety of fields – starting with engineering challenges such as autonomous components and ending with social political fields that include sensitive personal data such as the management and accessibility of information on social networks such as Facebook or Twitter.

Dr. Moran’s research focuses on one of the most important branches of machine learning, which is called generalization theory and aims to quantitatively understand how machine learning generalizes from the individual to the general. This branch has made a significant contribution to the revolutionary technological breakthroughs that the field has experienced in recent years.

The latest breakthroughs in generalization theory demonstrate phenomenas that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. The latest breakthroughs in generalization theory demonstrate phenomena that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. One of the main reasons for this is that the classical generalization theory is based on definitions that focus on the worst case, and is therefore too pessimistic. This means that in practical machine learning problems the input usually does not fit the worst case, and experiments show that it is often possible to successfully learn based on training on far fewer examples than the number required by the predictions of the classical theory. Dr. Moran’s research aims to develop generalization theories that complement classical theory and enable more accurately model modern learning tasks, including tasks involving sensitive data.

Yuval Hart

Krill Prize 2023
The Hebrew University

Shay Tamar

 

Affiliation at the time of the award:

Technion

Faculty of Mathematics

 

Award citation:

“for unique contributions in machine learning research and generalization theory”.

 

Machine learning, better known to most of us as Artificial Intelligence – AI is applied in a wide variety of fields – starting with engineering challenges such as autonomous components and ending with social political fields that include sensitive personal data such as the management and accessibility of information on social networks such as Facebook or Twitter.

Dr. Moran’s research focuses on one of the most important branches of machine learning, which is called generalization theory and aims to quantitatively understand how machine learning generalizes from the individual to the general. This branch has made a significant contribution to the revolutionary technological breakthroughs that the field has experienced in recent years.

The latest breakthroughs in generalization theory demonstrate phenomenas that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. The latest breakthroughs in generalization theory demonstrate phenomena that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. One of the main reasons for this is that the classical generalization theory is based on definitions that focus on the worst case, and is therefore too pessimistic. This means that in practical machine learning problems the input usually does not fit the worst case, and experiments show that it is often possible to successfully learn based on training on far fewer examples than the number required by the predictions of the classical theory. Dr. Moran’s research aims to develop generalization theories that complement classical theory and enable more accurately model modern learning tasks, including tasks involving sensitive data.

Tomer Koren

Krill Prize 2023
Tel-Aviv University

Shay Tamar

 

Affiliation at the time of the award:

Technion

Faculty of Mathematics

 

Award citation:

“for unique contributions in machine learning research and generalization theory”.

 

Machine learning, better known to most of us as Artificial Intelligence – AI is applied in a wide variety of fields – starting with engineering challenges such as autonomous components and ending with social political fields that include sensitive personal data such as the management and accessibility of information on social networks such as Facebook or Twitter.

Dr. Moran’s research focuses on one of the most important branches of machine learning, which is called generalization theory and aims to quantitatively understand how machine learning generalizes from the individual to the general. This branch has made a significant contribution to the revolutionary technological breakthroughs that the field has experienced in recent years.

The latest breakthroughs in generalization theory demonstrate phenomenas that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. The latest breakthroughs in generalization theory demonstrate phenomena that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. One of the main reasons for this is that the classical generalization theory is based on definitions that focus on the worst case, and is therefore too pessimistic. This means that in practical machine learning problems the input usually does not fit the worst case, and experiments show that it is often possible to successfully learn based on training on far fewer examples than the number required by the predictions of the classical theory. Dr. Moran’s research aims to develop generalization theories that complement classical theory and enable more accurately model modern learning tasks, including tasks involving sensitive data.

Inbal Talgam-Cohen

Krill Prize 2023
Technion

Shay Tamar

 

Affiliation at the time of the award:

Technion

Faculty of Mathematics

 

Award citation:

“for unique contributions in machine learning research and generalization theory”.

 

Machine learning, better known to most of us as Artificial Intelligence – AI is applied in a wide variety of fields – starting with engineering challenges such as autonomous components and ending with social political fields that include sensitive personal data such as the management and accessibility of information on social networks such as Facebook or Twitter.

Dr. Moran’s research focuses on one of the most important branches of machine learning, which is called generalization theory and aims to quantitatively understand how machine learning generalizes from the individual to the general. This branch has made a significant contribution to the revolutionary technological breakthroughs that the field has experienced in recent years.

The latest breakthroughs in generalization theory demonstrate phenomenas that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. The latest breakthroughs in generalization theory demonstrate phenomena that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. One of the main reasons for this is that the classical generalization theory is based on definitions that focus on the worst case, and is therefore too pessimistic. This means that in practical machine learning problems the input usually does not fit the worst case, and experiments show that it is often possible to successfully learn based on training on far fewer examples than the number required by the predictions of the classical theory. Dr. Moran’s research aims to develop generalization theories that complement classical theory and enable more accurately model modern learning tasks, including tasks involving sensitive data.

Nitzan Gonen

Krill Prize 2023
Bar-Ilan University

Shay Tamar

 

Affiliation at the time of the award:

Technion

Faculty of Mathematics

 

Award citation:

“for unique contributions in machine learning research and generalization theory”.

 

Machine learning, better known to most of us as Artificial Intelligence – AI is applied in a wide variety of fields – starting with engineering challenges such as autonomous components and ending with social political fields that include sensitive personal data such as the management and accessibility of information on social networks such as Facebook or Twitter.

Dr. Moran’s research focuses on one of the most important branches of machine learning, which is called generalization theory and aims to quantitatively understand how machine learning generalizes from the individual to the general. This branch has made a significant contribution to the revolutionary technological breakthroughs that the field has experienced in recent years.

The latest breakthroughs in generalization theory demonstrate phenomenas that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. The latest breakthroughs in generalization theory demonstrate phenomena that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. One of the main reasons for this is that the classical generalization theory is based on definitions that focus on the worst case, and is therefore too pessimistic. This means that in practical machine learning problems the input usually does not fit the worst case, and experiments show that it is often possible to successfully learn based on training on far fewer examples than the number required by the predictions of the classical theory. Dr. Moran’s research aims to develop generalization theories that complement classical theory and enable more accurately model modern learning tasks, including tasks involving sensitive data.

Viviane Slon

Krill Prize 2023
Tel-Aviv University

Shay Tamar

 

Affiliation at the time of the award:

Technion

Faculty of Mathematics

 

Award citation:

“for unique contributions in machine learning research and generalization theory”.

 

Machine learning, better known to most of us as Artificial Intelligence – AI is applied in a wide variety of fields – starting with engineering challenges such as autonomous components and ending with social political fields that include sensitive personal data such as the management and accessibility of information on social networks such as Facebook or Twitter.

Dr. Moran’s research focuses on one of the most important branches of machine learning, which is called generalization theory and aims to quantitatively understand how machine learning generalizes from the individual to the general. This branch has made a significant contribution to the revolutionary technological breakthroughs that the field has experienced in recent years.

The latest breakthroughs in generalization theory demonstrate phenomenas that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. The latest breakthroughs in generalization theory demonstrate phenomena that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. One of the main reasons for this is that the classical generalization theory is based on definitions that focus on the worst case, and is therefore too pessimistic. This means that in practical machine learning problems the input usually does not fit the worst case, and experiments show that it is often possible to successfully learn based on training on far fewer examples than the number required by the predictions of the classical theory. Dr. Moran’s research aims to develop generalization theories that complement classical theory and enable more accurately model modern learning tasks, including tasks involving sensitive data.

Yotam Drier

Krill Prize 2023
The Hebrew University

Shay Tamar

 

Affiliation at the time of the award:

Technion

Faculty of Mathematics

 

Award citation:

“for unique contributions in machine learning research and generalization theory”.

 

Machine learning, better known to most of us as Artificial Intelligence – AI is applied in a wide variety of fields – starting with engineering challenges such as autonomous components and ending with social political fields that include sensitive personal data such as the management and accessibility of information on social networks such as Facebook or Twitter.

Dr. Moran’s research focuses on one of the most important branches of machine learning, which is called generalization theory and aims to quantitatively understand how machine learning generalizes from the individual to the general. This branch has made a significant contribution to the revolutionary technological breakthroughs that the field has experienced in recent years.

The latest breakthroughs in generalization theory demonstrate phenomenas that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. The latest breakthroughs in generalization theory demonstrate phenomena that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. One of the main reasons for this is that the classical generalization theory is based on definitions that focus on the worst case, and is therefore too pessimistic. This means that in practical machine learning problems the input usually does not fit the worst case, and experiments show that it is often possible to successfully learn based on training on far fewer examples than the number required by the predictions of the classical theory. Dr. Moran’s research aims to develop generalization theories that complement classical theory and enable more accurately model modern learning tasks, including tasks involving sensitive data.

Ido Goldstein

Krill Prize 2023
The Hebrew University

Shay Tamar

 

Affiliation at the time of the award:

Technion

Faculty of Mathematics

 

Award citation:

“for unique contributions in machine learning research and generalization theory”.

 

Machine learning, better known to most of us as Artificial Intelligence – AI is applied in a wide variety of fields – starting with engineering challenges such as autonomous components and ending with social political fields that include sensitive personal data such as the management and accessibility of information on social networks such as Facebook or Twitter.

Dr. Moran’s research focuses on one of the most important branches of machine learning, which is called generalization theory and aims to quantitatively understand how machine learning generalizes from the individual to the general. This branch has made a significant contribution to the revolutionary technological breakthroughs that the field has experienced in recent years.

The latest breakthroughs in generalization theory demonstrate phenomenas that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. The latest breakthroughs in generalization theory demonstrate phenomena that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. One of the main reasons for this is that the classical generalization theory is based on definitions that focus on the worst case, and is therefore too pessimistic. This means that in practical machine learning problems the input usually does not fit the worst case, and experiments show that it is often possible to successfully learn based on training on far fewer examples than the number required by the predictions of the classical theory. Dr. Moran’s research aims to develop generalization theories that complement classical theory and enable more accurately model modern learning tasks, including tasks involving sensitive data.

Shay Moran

Krill Prize 2023
Technion

Shay Tamar

 

Affiliation at the time of the award:

Technion

Faculty of Mathematics

 

Award citation:

“for unique contributions in machine learning research and generalization theory”.

 

Machine learning, better known to most of us as Artificial Intelligence – AI is applied in a wide variety of fields – starting with engineering challenges such as autonomous components and ending with social political fields that include sensitive personal data such as the management and accessibility of information on social networks such as Facebook or Twitter.

Dr. Moran’s research focuses on one of the most important branches of machine learning, which is called generalization theory and aims to quantitatively understand how machine learning generalizes from the individual to the general. This branch has made a significant contribution to the revolutionary technological breakthroughs that the field has experienced in recent years.

The latest breakthroughs in generalization theory demonstrate phenomenas that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. The latest breakthroughs in generalization theory demonstrate phenomena that cannot be explained using previous techniques and sometimes even contradict classical principles in learning and statistics. One of the main reasons for this is that the classical generalization theory is based on definitions that focus on the worst case, and is therefore too pessimistic. This means that in practical machine learning problems the input usually does not fit the worst case, and experiments show that it is often possible to successfully learn based on training on far fewer examples than the number required by the predictions of the classical theory. Dr. Moran’s research aims to develop generalization theories that complement classical theory and enable more accurately model modern learning tasks, including tasks involving sensitive data.

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