Tomer Koren

Krill Prize 2023
Tel-Aviv University

Tomer Koren

 

Affiliation at the time of the award:

Tel Aviv University

The Sackler Faculty of Exact Sciences,

Blavatnik School of Computer Science

 

Award citation:

“for unique contributions in the field of computer learning, understanding algorithms and their improvement”.

 

Dr. Tomer Koren’s research deals with theory and algorithms for mathematical optimization and their properties and uses in computer learning and reinforcement learning. Optimization methods are currently at the heart of the work in the field of Artificial Intelligence – AI, and are used to train almost any learning-based system in a wide variety of fields and applications.

Despite this, there is still much that is still unknown in regards to the generalization properties of these algorithms, and especially their surprising ability to provide insights and predictions about information details that they have never seen before. One of Dr. Koren’s main research goals is to strengthen the theoretical foundations behind the breakthrough successes of computer learning in recent years. This reinforcement is essential to better understand why the learning methods we use today succeed above and beyond expectations (that is, beyond what classical theory promises), and how they can be improved and optimized.

Yotam Drier

Krill Prize 2023
The Hebrew University

Yotam Drier

 

Affiliation at the time of the award:

The Hebrew University of Jerusalem

Faculty of Medicine, Department of Immunology and Cancer Research

 

Award citation:

“for original contributions in the field of cancer research and their combination with the development of new algorithms for data analysis, the development of new experimental methods and the prediction of relevant changes”.

 

Cells tightly regulate the levels of each gene, and dysregulation can lead to diseases such as cancer. Dysregulation can be caused by genetic alterations, epigenetic alterations (chemical modifications on the DNA), or changes in chromosomal folding. Our chromosomes are extremely long linear DNA molecules, folded neatly into the cell nucleus, and this structure is important for proper gene regulation. While the role of genetic alterations in genes in disease is well understood, much less is known about epigenetic and structural alterations

In Dr. Dreyer’s laboratory, they aim to fill this knowledge gap by studying these alterations in multiple cancer types and a few genetic diseases. They combine experimental techniques to systematically characterize epigenomes and chromosomal folding, computational algorithms to integrate these data and predict events that drive disease, and experimental validation of these predictions.

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.

Aviv Tamar

Krill Prize 2023
Technion

Aviv Tamar

 

Affiliation at the time of the award:

Technion

Faculty of Electrical and Computer Engineering named after Viterbi

 

Award citation:

“for the development of algorithms for automatic robotic learning using reinforcements”.

 

A robot that washes the dishes in the sink for you, folds the laundry and takes the dog out for a walk, this is not a dream – in a laboratory for robotic learning, Dr. Aviv Tamar investigates how machines can learn to perform tasks automatically by “reinforcement learning”. His research might have a great impact on our lives in the coming decade.

Dr. Tamar’s research deals with teaching robots how to learn and act in human natural environments. That is, how robots can learn new tasks quickly and using prior knowledge, and how can they learn about the physical world through playing with their surroundings.

To achieve these goals, Dr. Tamar’s research group develops fundamental learning algorithms that uses a technique called reinforcement learning. In the laboratory, these algorithms are applied to a variety of robotic tasks, including motion planning, object manipulation, and assembly.
One of Dr. Tamar’s main contributions is in the development of algorithms that allow robots to explore their environment automatically, making their learning in new tasks simpler and faster. Through research collaborations, Dr. Tamar’s lab team is working to discover how to use reinforcement learning to solve Real-world problems outside of robotics, including improving Internet performance and strengthening blockchain security.

Leeat Keren

Krill Prize 2023
Weizmann

Leeat Keren

 

Affiliation at the time of the award:

Weizmann Institute of science

Faculty of Biology, Department of Molecular Biology of the Cell

 

Award citation:

“for the development of innovative technologies for molecular imaging and for revealing the defense mechanisms of cancer tumor cells against an immune response, with the aim of developing innovative treatments for cancer”.

 

The development of cancer is a complex process that depends on the interrelationships between the individual cells of the tumor, the cells around it and the immune system – which can act both to promote and to suppress the invasion and development of the tumor. All participants are thought to be important in tumor biology, yet their interactions and relative contributions are largely unknown.

In Dr. Keren’s laboratory, they study the way in which different cells of the tumor and the immune system communicate as a system to collectively define the development of cancer and results as a response to treatment. For this purpose, Dr. Keren’s laboratory develops innovative technologies to perform complex imaging, which provides unparalleled molecular observation both on the tumor and on immune cells. In the laboratory, samples are taken from patients to identify mechanisms that help the tumor cells to successfully escape the immune response, and also develop innovative treatments in order to direct the power of the immune system against cancer.

Jeffery W. Kelly

Wolf Prize Laureate in Chemistry 2023

Jeffery W. Kelly

 

Affiliation at the time of the award:

Scripps Research Institute, USA

 

Award citation:

“for developing a clinical strategy to ameliorate pathological protein aggregation”.

 

Prize share:

Jeffery W. Kelly

Chuan He

Hiroaki Suga

 

“for pioneering discoveries that illuminate the functions and pathological dysfunctions of RNA and proteins and for creating strategies to harness the capabilities of these biopolymers in new ways to ameliorate human diseases”.

 

Prof. Jeffery W. Kelly is the Lita Annenberg Hazen Professor of Chemistry at The Scripps Research Institute. Kelly received his BS in chemistry from the State University of New York at Fredonia, his Ph.D. in organic chemistry from the University of North Carolina at Chapel Hill (1986), and performed postdoctoral research in bio-organic chemistry at Rockefeller University (1989).

Most protein molecules must fold into defined three-dimensional structures to acquire their functional activity. However, some proteins can adopt several folding states, and their biologically active state may be only marginally stable. Misfolded proteins can form toxic aggregates, such as soluble oligomers and fibrillar amyloid deposits, which may lead to neurodegeneration in Alzheimer’s disease and many other pathologies. All cells contain an extensive protein homeostasis network of protein folding devices, such as molecular chaperones and other factors that prevent or regulate protein aggregation. These defense networks tend to decline during aging, facilitating the manifestation of aggregate deposition diseases.

Prof. Kelly’s research focuses on understanding protein folding, misfolding, and aggregation and using chemical and biological approaches to develop novel therapeutic strategies to combat diseases caused by protein misfolding and aggregation. He contributed significantly to the fight against neurodegenerative diseases by discovering the mechanism of protein aggregation in amyloid diseases that affect the heart and nervous system. He showed the mechanism by which a protein, transthyretin, unravels and agglomerates into clusters that kill cells, tissues, and ultimately patients and developed a molecular approach to stabilize this protein.
Kelly successfully synthesized the first regulatory-agency-approved drug, “tafamidis vyndaqel”. This pioneering drug, marketed worldwide, significantly slows the progression of Familial Amyloid Polyneuropathy, a neurodegenerative disease, and Familial and Sporadic TTR Cardiomyopathy disease, which causes heart failure.

Jeffery W. Kelly is awarded the Wolf prize for developing a new and clinically impactful strategy to ameliorate disease caused by pathological protein aggregation. His seminal contributions revealed fundamental features of protein homeostasis (proteostasis) at the molecular level, including the interplay among protein folding, misfolding, and aggregation. Dysregulation of proteostasis is associated with a spectrum of human diseases. Kelly’s laboratory used these fundamental insights to develop the drug “tafamidis”, which halts or slows disease progression in patients suffering from transthyretin amyloidosis. This approach may be applicable to other proteostasis-based disorders.

 

Hiroaki Suga

Wolf Prize Laureate in Chemistry 2023

Hiroaki Suga

 

Affiliation at the time of the award:

The University of Tokyo, Japan

 

Award Citation:

“For developing RNA-based catalysts that revolutionized the discovery of bioactive peptides”.

 

Prize Share:

Hiroaki Suga

Jeffery W. Kelly

Chuan He

 

“for pioneering discoveries that illuminate the functions and pathological dysfunctions of RNA and proteins and for creating strategies to harness the capabilities of these biopolymers in new ways to ameliorate human diseases.”

 

Prof. Suga received his Bachelor of Engineering (1986) and Master of Engineering (1989) from Okayama University, Ph.D. in Chemistry (1994) from MIT, and was a post-doctoral fellow at the Massachusetts General Hospital. Suga began his independent career at New York State University at Buffalo (1997-2003). In 2003 he moved to the Research Center for Advanced Science and Technology at the  University of Tokyo. Since 2010 Suga has been a full Professor in the department of chemistry at the University of Tokyo. Currently, he serves as the President of the Chemical Society of Japan.

Prof. Suga’s research interests include bioorganic chemistry, chemical biology, and biotechnology related to RNA, translation, and peptides. As a young researcher, he made significant advances in using RNA-based enzymes, or ribozymes, to incorporate unnatural amino acids into tRNA. This technology, known as the “Flexizyme,” greatly expanded the potential for reprogramming the genetic code. Through additional research on in vitro translation of proteins using reconstituted ribosomes, Prof. Suga could incorporate various unnatural amino acids into expressed peptides to spontaneously produce molecules that form macrocyclic peptides. Prof. Suga used oligonucleotide display and directed evolution to create the RaPID system, a platform for producing and selecting billions of macrocyclic peptides as high-affinity binders to protein targets, including many that had previously been considered undruggable.

In 2006, Prof. Suga co-founded PeptiDream to advance and apply the RaPID system, which quickly became a widely used technology for finding small molecule protein binders, particularly disrupting protein-protein interactions. His discoveries have enabled the construction of complex molecules on a large scale, not possible using conventional methods alone. Suga’s work has produced more unique non-natural molecules than other approachs, which possess the unique stereochemistry, rich functional group density, and 3D-architecture necessary for interrogating and controlling biological processes. This paved the way for a new generation of drugs. PeptiDream became a publicly traded company on the Tokyo Stock Exchange and is one of Japan’s most successful startup companies.

Hiroaki Suga is awarded the Wolf prize for developing an exceptionally innovative in-vitro selection system for cyclic peptides as inhibitors of protein-protein interactions. He invented an RNA-based catalyst, flexizyme, that transcends natural mechanisms and vastly expands the range of amino acids that can be incorporated with ribosomal machinery. Suga’s strategy enables rapid construction and screening of enormous cyclic peptide libraries. His unique discovery has established a new approach to medicinal chemistry and generated new tools for drug discovery.

Ingrid Daubechies

Wolf Prize Laureate in Mathematics 2023

Ingrid Daubechies

 

Affiliation at the time of the award:

Duke University, USA

 

Award citation:

“for work in wavelet theory and applied harmonic analysis”.

 

Prize share:

None

 

Ingrid Daubechies is a Belgian mathematician and physicist at Duke University in Durham, North Carolina. She earned her bachelor’s degree in physics from the Free University of Brussels in 1975. She then continued her research at the same university, earning her doctorate in physics with a thesis on the Representation of quantum mechanical operators by kernels on Hilbert spaces of analytic functions.

Ingrid Daubechies’ love for math and science was nurtured from a young age. Her father fostered her curiosity and interest in these subjects while she was in school. As a child, she was fascinated by how things worked and how to construct them, as well as the mechanisms behind machinery and the truth behind mathematical concepts. She would even calculate large numbers in her head when she couldn’t sleep, finding it captivating to see the numbers quickly grow.

Professor Ingrid Daubechies has made significant contributions to the field of wavelet theory. Her research has revolutionized the way images and signals are processed numerically, providing standard and flexible algorithms for data compression. This has led to a wide range of innovations in various technologies, including medical imaging, wireless communication, and even digital cinema.
The Wavelet theory, as presented by the work of Professor Daubechies, has become a crucial tool in many areas of signal and image processing. For example, it has been used to enhance and reconstruct images from the early days of the Hubble Telescope, to detect forged documents and fingerprints. In addition, wavelets are a vital component of wireless communication and are used to compress sound sequences into MP3 files.

Beyond her scientific contributions, Professor Daubechies also advocates for equal opportunities in science and math education, particularly in developing countries. As President of the International Mathematical Union, she worked to promote this cause. She is aware of the barriers women face in these fields and works to mentor young women scientists and increase representation and opportunities for them.

Daubechies’s most important contribution is her introduction in 1988 of smooth compactly supported orthonormal wavelet bases. These bases revolutionized signal processing, leading to highly efficient methods for digitizing, storing, compressing, and analyzing data, such as audio and video signals, computed tomography, and magnetic resonance imaging. The compact support of these wavelets made it possible to digitize a signal in time linearly dependent on the length of the signal. This was a critical ingredient for researchers and engineers in signal processing to be able to rapidly decompose a signal as a superposition of contributions at various scales.
In subsequent joint work with A. Cohen and J.C. Feauveau, Daubechies introduced symmetrical biorthogonal wavelet bases. These wavelet bases give up orthonormality in favor of symmetry. Such bases are much more suitable for treating the discontinuities arising at the boundaries of finite-length signals and improving image quality. Her biorthogonal wavelets became the basis for the JPEG 2000 image compression and coding system.

Ingrid Daubechies is awarded the Wolf Prize for her work in the creation and development of wavelet theory and modern time-frequency analysis. Her discovery of smooth, compactly supported wavelets, and the development of biorthogonal wavelets transformed image and signal processing and filtering.
Her work is of tremendous importance in image compression, medical imaging, remote sensing, and digital photography. Daubechies has also made unparalleled contributions to developing real-world applications of harmonic analysis, introducing sophisticated image-processing techniques to fields ranging from art to evolutionary biology and beyond.

Chuan He

Wolf Prize Laureate in Chemistry 2023

Chuan He

 

Affiliation at the time of the award:

The University of Chicago, USA

 

Award citation:

“for discovering reversible RNA methylation and its role in the regulation of gene expression”.

 

Prize share:

Chuan He

Jeffery W. Kelly

Hiroaki Suga

 

“for pioneering discoveries that illuminate the functions and pathological dysfunctions of RNA and proteins and for creating strategies to harness the capabilities of these biopolymers in new ways to ameliorate human diseases”.

 

Chuan He is a Chinese-American chemical biologist, the John T. Wilson Distinguished Service Professor at the University of Chicago, and an Investigator at the Howard Hughes Medical Institute. He graduated from the University of Science and Technology of China with a B.S. in Chemistry (1994), Ph.D. at MIT, and postdoctoral research at Harvard University. He joined the Department of Chemistry at the University of Chicago in 2002 and served as the Director of the Institute for Biophysical Dynamics (2012 -2017).

More than 150 structurally distinct post-transcriptional modifications of cellular RNA molecules occur at thousands of sites. Some of these modifications are dynamic and may have critical regulatory roles analogous to protein and DNA modifications. Therefore, understanding the scope and mechanisms of dynamic RNA modifications represents an emerging research frontier in biology and medicine.

Prof. Chuan He is a world-class expert studying RNA’s post-transcriptional modifications, the role these modifications play in cellular processes, and their broad impact on mammalian development and human diseases. His research, spanning a wide range of chemical biology, nucleic acid chemistry, biology, epigenetics, and bioinorganic chemistry, focuses on understanding both RNA and DNA’s modifications and their roles in regulating gene expression.
He was the first to champion the idea that RNA modifications are reversible and can control gene expression. His work is fundamental in developing potential therapies that target RNA methylation effectors against human diseases such as cancer. His research group was the first to identify proteins that can erase, and undo changes made to RNA molecules, which sparked the emergence of the epitranscriptome field. Prof. He explained how RNA methylation functions through characterizing reader proteins—processes that play critical roles in many types of cancer, including endometrial cancer, acute myelogenous leukemia, and glioblastoma.

Chuan He is awarded the Wolf prize for his pioneering work elucidating the chemistry and functional consequences of RNA modification. He discovered reversible RNA methylation, leading to a conceptual breakthrough regarding the functional roles of RNA modifications in the regulation of gene expression. The He laboratory discovered the first RNA demethylase, an enzyme that removes the methyl group from N6-methyladenosine, the most prevalent mRNA modification in eukaryotes.