פרופ' עמוס קורמן

2015: Habilitation à diriger des recherches (HDR) Paris Diderot University. Thesis Title: ""Distributed Decision and Distributed Biological Algorithms.""2000–2005: Direct Ph.D. in Computer Science at the Weizmann Institute of Science. Supervised by Prof. David Peleg. Thesis Title: ""Static and Dynamic Labeling Schemes."" Recipient of the Dean’s Prize for Ph.D. Students. (Degree conferred: May 8, 2006). 1998–1999: M.Sc. in Mathematics Stanford University, USA. 1995–1997: B.Sc. in Mathematics The Hebrew University of Jerusalem. Graduated Magna Cum Laude.

I am a Full Professor in the Department of Computer Science at the University of Haifa, starting in 2024. My academic career is dedicated to building bridges between theoretical computer science and the study of natural phenomena, driven by a desire to understand biological systems through an “algorithmic lens.”My academic journey began in mathematics: I completed my B.Sc. at the Hebrew University (1997) and my M.Sc. at Stanford University. Upon returning to Israel, I shifted my focus to computer science and joined the direct Ph.D. track at the Weizmann Institute of Science (2000–2005), under the supervision of Prof. David Peleg. My research on labeling schemes in networks earned the Dean’s Excellence Award. I continued my training with a postdoctoral fellowship at the Technion, working with Prof. Shay Kutten on the theory of distributed computing. In 2007, I joined the CNRS in France, where I served for 16 years as a researcher and later as a Research Director in the IRIF and FILOFOCS groups. During this time, I received international recognition, including the prestigious ERC Consolidator Grant (2015–2020), which allowed me to be among the initiators of a new research direction I call “algorithmic biology”: the study of computational mechanisms that enable groups of organisms—such as ants, bats, and humans—to solve complex problems. In 2024, I joined the faculty at the University of Haifa. My current research, supported by an ISF grant for the years 2024–2028, continues the vision of building a bridge between theoretical computer science and the understanding of complex biological systems. I see myself as a kind of “representative” of algorithmic theory within the field of biology. My aim is to equip biologists with analytical tools that enable a deep and abstract understanding of computational principles in nature, while opening a window for theoretical computer scientists into the complex and fascinating world of living systems.

I am deeply fascinated by the study of natural phenomena through an algorithmic lens, particularly in uncovering the profound interconnections between distributed computing and collective animal behavior. My overarching mission is to establish a new research field: ""Algorithmic Biology"". This emerging area aims to bridge the gap between theoretical computer science and empirical biology along three central axes:1. Theory-experiment integration: Developing methodologies that combine rigorous algorithmic analysis with the design of biological experiments. 2. Model-driven predictions: Formulating and validating meaningful predictions that emerge from algorithmic reasoning and analysis. 3. Lower bounds in nature: Exploring the insights that algorithmic lower bounds can offer into the fundamental limitations of biological and social systems. In collaboration with biologists, I investigate a wide range of biological systems—including ants, bats, and humans—alongside abstract models of multi-agent systems. My research seeks to address foundational questions such as: - Noise and competition: How do these factors affect the efficiency of groups in performing collective tasks? - Computational foraging: What computational challenges do organisms face when searching for resources, and what strategies help overcome them? - From simple rules to complex patterns: How do basic individual-level interactions give rise to rich collective dynamics at the group level? To tackle these questions, I apply analytical tools from distributed computing, game theory, and probability theory. I place strong emphasis on grounding theoretical models in empirical data, through field and laboratory behavioral experiments. I see myself as a representative of algorithmic thinking within the biological sciences. My goal is to equip the biology community with advanced analytical tools for decoding the computational logic of life, while offering computer scientists a fresh and compelling path into empirical science and the exploration of the natural world.

2026: Dijkstra Prize

2020: SIROCCO Prize for Innovation in Distributed Computing

2009: Best paper award at ICDCN 2009

2006: Dean's Prize for Ph.D. Students at the Weizmann Institute of Science2005: Best student paper award at DISC 2005

1997: Graduated at the Hebrew University with exceptional honors: Magna Cum Lauda

Selected Publications (A non-exhaustive list highlighting key interdisciplinary and theoretical results.)Interdisciplinary: Algorithmic Biology & Collective Behavior

1. ""Comparing Cooperative Geometric Puzzle Solving in Ants versus Humans"". T. Dreyer, A. Haluts, A. Korman, N. Gov, E. Fonio, and O. Feinerman.
PNAS, 2024.

Large media exposure, e.g., in Haaretz, Ynet, The Mirror (UK), and The Sun (USA) etc.

2. ""Abundant Resources can Trigger Reduced Consumption: Unveiling the Paradox of Excessive Scrounging"". R. Vacus and A. Korman (Corresponding Author)
PNAS, 2024.

3. ""Intermittent inverse-square Lévy walks are optimal for finding targets of all sizes"".
B. Guinard and A. Korman (Corresponding Author).
Science Advances, 2021.

4. ""Ant collective cognition allows for efficient navigation through disordered environments"" A. Gelblum, E. Fonio, Y. Rodeh, A. Korman, and O. Feinerman. (A. Korman and O. Feinerman are Joint Corresponding Authors).
eLife, 2020.

5. ""Reinforcement Learning Enables Resource-Partitioning in Foraging Bats"". A. Goldshtein et al. Current Biology, 2020. (A. Korman and Y. Yovel are Joint Corresponding Authors)

Media coverage: Featured in Ynet and the French CNRS INS2I.

6. ""Limits on reliable information flows through stochastic populations"". L. Boczkowski, E. Natale, O. Feinerman, and A. Korman (Corresponding Author).
PLoS Computational Biology, 2018.

7. ""The ANTS Problem"". O. Feinerman and A. Korman. Distributed Computing, 2017.

8. ""A locally-blazed ant trail achieves efficient collective navigation despite limited information"". E. Fonio et al. (A. Korman and O. Feinerman are Joint Corresponding Authors).
eLife, 2016.

Media coverage: Featured in Le Monde, Haaretz, and CNRS News.

Theoretical Computer Science & Distributed Computing

1. ""An Optimal Ancestry Labeling Scheme with Applications to XML Trees and Universal Posets"". P. Fraigniaud and A. Korman. STOC 2010, J.ACM 2016.

2. ""Parallel Exhaustive Search without Coordination"". P. Fraigniaud, A. Korman, and Y. Rodeh. STOC 2016, J.ACM 2019.

3. ""Distributed Verification and Hardness of Distributed Approximation"". A. Das Sharma et al. STOC 2011, SIAM Journal on Computing (SICOMP), 2012.

4. ""Proof Labeling Schemes"". A. Korman, S. Kutten and D. Peleg. Distributed Computing, 2010.

5.""Online Computation with Advice"". Y. Emek, P. Fraigniaud, A. Korman, and A. Rosen. ICALP 2009.