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Matteo VialeView profile

Professor

• Mathematical Logic
• Set Theory
• Forcing Axioms
• +3 more

Matteo Viale is a Full Professor in the Department of Mathematics at the University of Torino. He specializes in mathematical logic with a focus on set theory, forcing axioms, and generic absoluteness. He is an active member of the Turin Logic Group and maintains international collaborations in foundational mathematics. His research explores advanced topics in set theory including forcing techniques, large cardinals, cardinal arithmetic, and their applications to mathematical foundations. Recent work investigates connections between forcing axioms and category theory, as well as absoluteness principles across different mathematical structures. Viale has advised numerous graduate students on theses covering boolean-valued models, forcing techniques, set-theoretic topology, and applications of logic to functional analysis. His pedagogical contributions include comprehensive lecture notes on forcing iterations, model companionship, and semiproper forcing. Notable recognitions include the Kurt Gödel Research Prize Fellowship (2010), Premio Fubini (2010), and Sacks Prize (2006) for his doctoral thesis on forcing axioms and cardinal arithmetic.

Alan DowView profile

Professor

• Topology
• Set Theory
• Set-Theoretic Topology
• +3 more

Alan Dow is a Professor of Mathematics at the University of North Carolina at Charlotte (UNC Charlotte), affiliated with the Mathematics & Statistics Department within the College of Liberal Arts and Sciences. His research focuses on advanced areas of topology, set theory, and their intersections, including topics like ultrafilters, compactifications, forcing axioms, and cardinal invariants. He has collaborated extensively with researchers such as Saharon Shelah, K.P. Hart, and Osvaldo Guzman, producing groundbreaking work on spaces like N*, S-spaces, and the Stone-Čech compactification. His work often employs set-theoretic methods, exploring properties of topological spaces under different axiomatic frameworks such as Martin's Axiom (MA) and Proper Forcing Axiom (PFA). Key contributions include studies on automorphisms of Boolean algebras, pseudoradial spaces, and the structure of compact spaces under varying continuum hypotheses. His research also addresses foundational questions in topology, such as the existence of Efimov spaces and the behavior of topological invariants like weight and tightness. Dr. Dow’s publications frequently appear in journals like *Topology and its Applications*, *Fundamenta Mathematicae*, and *Israel Journal of Mathematics*. His research trends emphasize the interplay between set theory and topology, with a focus on constructing and analyzing spaces that test limits of classical topological principles under various set-theoretic assumptions. He has received no explicitly listed scientific awards but maintains an active research agenda with numerous collaborations. His academic contributions include advising and mentoring, though specific student names are not documented here. Office: Fretwell 390J, Email: adow@uncc.edu.

Elchanan MosselView profile

Professor

• Probability Theory
• Combinatorics
• Machine Learning
• +4 more

Elchanan Mossel is a Professor of Mathematics at the Massachusetts Institute of Technology (MIT), with a joint appointment at the Institute for Data, Systems, and Society (IDSS). His research focuses on probability, combinatorics, statistical inference, and their applications to computer science and social choice theory. He earned his B.Sc. from the Open University of Israel, and both his M.Sc. (1997) and Ph.D. (2000) in Mathematics from the Hebrew University of Jerusalem. Before joining MIT in 2016, he was a faculty member at UC Berkeley and held visiting positions at the Weizmann Institute and the Wharton School of the University of Pennsylvania. Mossel's work bridges theoretical foundations and applied problems, including computational complexity, randomized algorithms, Markov random fields, and evolutionary biology. He has made significant contributions to the theory of social choice, game theory, and the mathematical underpinnings of machine learning. Notable achievements include resolving the Majority Is Stablest conjecture and advancing phylogenetic reconstruction methods. His awards include the Sloan Fellowship and Miller Fellowship. He has mentored numerous graduate students, including Sebastien Roch, Allan Sly, and Miklos Racz, and has held editorial roles in journals like the Electronic Journal of Probability . Mossel's teaching spans topics from introductory probability to advanced courses on social networks and game theory.

Nectarios KozirisView profile

Professor

• Parallel and Distributed Systems
• Computer Architecture
• Systems Software
• +10 more

Nectarios Koziris is a Professor at the Department of Computer Science , National Technical University of Athens (NTUA) , and former Dean of the School of Electrical and Computer Engineering . His research focuses on Parallel and Distributed Systems , Computer Architecture , and Cloud Computing . Key Research Themes: Compiler-OS-Architecture Interaction, Datacenter Hyperconvergence, Sparse Matrix Optimization, Quantum Computing, FPGA Virtualization Leadership: Founder of ~okeanos (Europe's largest public Cloud IaaS), Co-founder of GFOSS , Member of IEEE Computer Society Greece, Advisor to Arrikto Inc. His work has led to over 180 publications with 5800+ citations (h-index 33) , including two Best Paper Awards (IPDPS 2001, CCGRID 2013) and Intel Recognition (2015). He has supervised 12 PhD students and participated in 15+ EU projects as coordinator or consortium partner. Scientific Leadership: Program Co-Chair for Europar 2012 , Organizer for IPDPS , ICPP , SC conferences, and active member in Cloud Computing Expert Groups for the European Commission.

Renaud PacaletView profile

Researcher

• Hardware Security
• Side-Channel Attacks
• Embedded Systems
• +7 more

Renaud Pacalet is a Researcher at Institut Mines-Télécom – Télécom Paris , affiliated with the Communications and Electronics (Comelec) Department and the System on Chip (LabSoc) research team under the Information Processing and Communication Laboratory (LTCI). His work spans hardware security, embedded systems, and software-defined radio (SDR) architectures. Current Research: Hardware security, side-channel attacks (power, timing, fault injection), RISC-V security analysis using gem5, FPGA scheduling for cloud data centers, and model-driven design methodologies. Past Research: Hardware acceleration for ray tracing, SDR front-end processing, SoC security, and memory bus protection (SecBus project). Teaching: Courses on Digital Systems, Computer Architecture, and Hardware Security at EURECOM, including lab sessions on side-channel attacks and fault analysis. Email: renaud.pacalet@telecom-paris.fr Contact: Télécom ParisTech, Campus SophiaTech, 450 route des Chappes 06410 Biot, France

Arijit BishnuView profile

Associate Professor

• Theoretical Computer Science
• Randomized Algorithms
• Approximation Algorithms
• +6 more

Arijit Bishnu is an Associate Professor at the Indian Statistical Institute in the Advanced Computing and Microelectronics Unit (ACMU). He has taught courses such as Design and Analysis of Algorithms , Randomized Algorithms , Computational Geometry , and Algorithms for Big Data over multiple years (2008–2025), focusing on theoretical and applied aspects of computer science. Research Interests: His work spans Theoretical Computer Science , Randomized and Approximation Algorithms , Computational Geometry , and Combinatorics . He explores problems in sublinear algorithms, streaming computation, geometric data analysis, and complexity theory. Publications: Recent papers include contributions to STOC 2025 , RANDOM 2025 , and APPROX 2024 , covering topics like property testing, triangle counting complexity, and streaming algorithms. Collaborations with researchers like Sourav Chakraborty, Gopinath Mishra, and Sayantan Sen highlight his interdisciplinary approach. Academic Leadership: He has co-organized research courses such as Approximation Algorithms and Topics in Algorithms and Complexity , emphasizing mentorship and knowledge dissemination in theoretical computer science. His comprehensive work integrates algorithmic innovation with rigorous mathematical analysis, advancing computational techniques for large-scale and geometric data.

Christian IkenmeyerView profile

Professor

• Computational Complexity
• Algebraic Combinatorics
• Geometric Complexity Theory
• +2 more

Christian Ikenmeyer is Professor in Computer Science and Mathematics at the University of Warwick. His research focuses on algebraic complexity theory, geometric complexity theory (GCT), and representation theory, with emphasis on tensor rank, Kronecker coefficients, and polynomial identity testing. Research Focus: Dr. Ikenmeyer develops mathematical frameworks to solve fundamental problems in computational complexity, including P vs NP. His work connects representation theory with algebraic geometry to establish complexity lower bounds and classify computational hardness. Leadership: He organizes workshops on algebraic complexity and GCT, including the 2023 Algebraic Complexity Theory Workshop at ICALP. His research is funded by EPSRC and DFG grants, supporting investigations into homogeneous complexity and branching programs. Teaching: Courses include 'Groups and Representations' and programming contest coaching. He has previously taught at MIT, Texas A&M, and Saarland University, developing lecture notes on GCT.

• Theoretical Computer Science
• Design and Analysis of Algorithms
• Discrete Optimization
• +7 more

Nikhil Bansal holds the prestigious Patrick C. Fischer Professorship of Theoretical Computer Science in the Department of Computer Science & Engineering at the University of Michigan's College of Engineering. His research program has established him as a leading figure in theoretical computer science, with significant contributions to algorithm design and analysis, particularly in discrete optimization problems. Bansal's research focuses on theoretical computer science with emphasis on design and analysis of algorithms for discrete optimization problems. His work spans multiple areas including discrepancy theory, approximation algorithms, randomized algorithms, combinatorial optimization, complexity theory, machine learning theory, and probability. He has made significant contributions to understanding the limits of approximation algorithms and developing novel techniques for combinatorial optimization problems. Analysis of Bansal's recent publications reveals a strong focus on discrepancy theory, online algorithms, and combinatorial optimization. His work often bridges theoretical computer science with discrete mathematics and probability theory. A recurring theme across his publications is the development of novel algorithmic techniques for solving NP-hard problems with provable guarantees. His research has evolved from foundational work in approximation algorithms to more recent contributions in quantum computing complexity and stochastic optimization. Patrick C. Fischer Professor of Theoretical Computer Science Bansal has advised numerous PhD students including Marek Elias, Shashwat Garg, and Greg Koumoutsous, as well as mentoring several postdoctoral researchers. He has served on editorial boards for top journals including Journal of the ACM, Theory of Computing, and Stochastic Models, and has been active on program committees for major conferences such as STOC, FOCS, SODA, and ICALP, including serving as chair for ICALP 2021. Bansal has organized multiple academic workshops including the STOC 2020 Workshop on Recent Advances in Discrepancy and Applications, several SDP Days at CWI Amsterdam, and the Semester on Bridging Continuous and Discrete Optimization at UC Berkeley in Fall 2017.

Nikhil BansalView profile

Professor

• Theoretical Computer Science
• Design and Analysis of Algorithms
• Discrete Mathematics
• +3 more

Nikhil Bansal is a Professor in Theoretical Computer Science at the University of Michigan, Ann Arbor. He earned his PhD from Carnegie Mellon University and previously worked at IBM Research, TU Eindhoven, and CWI Amsterdam. His research focuses on algorithm design, discrepancy theory, and combinatorial optimization. Education: PhD, Carnegie Mellon University Bansal's work bridges classical and quantum computing, with recent publications exploring k -Forrelation, vector balancing, and stochastic scheduling. His algorithmic approaches often combine geometric insights and probabilistic methods. Scientific Awards: Patrick C. Fischer Professor of Theoretical Computer Science NSF Career Award (2023) He has advised numerous PhD and postdoctoral researchers, including Marek Elias, Shashwat Garg, and Makrand Sinha. Bansal actively contributes to program committees (ICALP 2021, STOC 2020, FOCS 2018) and organizes workshops on discrepancy theory and optimization.

Sihem MesnagerView profile

Professor

• Symmetric Cryptography
• Coding Theory
• Finite Fields
• +10 more

Sihem Mesnager is a University Professor of Mathematics at the University of Paris VIII, affiliated with the Laboratory of Analysis, Geometry and Applications (LAGA) at Paris XIII (CNRS) and the AGC3 research group (Algebra, Geometry, Combinatorics) . She holds an adjunct professorship at Télécom Paris within the MIC2 Mathematics team of the Computer Science and Networks department (INFRES). Her work bridges pure mathematics and applied cryptography, focusing on Boolean functions, bent functions, and coding theory for secure communication and data protection. PhD in Mathematics, University of Pierre and Marie Curie (Paris VI), Sorbonne University (2002) Habilitation (HDR) in Mathematics, University of Paris VIII (2012) Research Interests Dr. Mesnager specializes in symmetric cryptography and coding theory , particularly their applications to secure digital communication, error correction, and post-quantum cryptographic protocols. Her algebraic approach employs finite fields, exponential sums, algebraic geometry, and finite geometry to analyze and construct cryptographic primitives like S-boxes, APN functions, and optimal linear codes. She also investigates algorithmic aspects of computer algebra in these domains. Scientific Awards George Boole International Prize (2020) PEDR Excellence Scientific Award (2019-2022) PEDR Excellence Scientific Award (2014-2017) Publications & Projects Her recent work includes constructing weightwise perfectly balanced Boolean functions for the FLIP cipher, optimizing Inner Product Masking schemes via coding theory, and developing post-quantum secure functional encryption using multivariate cryptography. She has contributed to Reed-Muller codes, BCH codes, and Gaussian sum-based linear codes with one-dimensional hulls, emphasizing their applications in side-channel attack resistance and quantum error correction.

Gheorghe CraciunView profile

Professor

• Mathematical Biology
• Chemical Reaction Networks
• Dynamical Systems
• +4 more

Gheorghe Craciun is a Professor in the Department of Mathematics and Department of Biomolecular Chemistry at the University of Wisconsin-Madison. His research focuses on mathematical and computational methods in biology and medicine, particularly chemical reaction networks, dynamical systems, and their applications to biochemical processes. He has organized and participated in workshops such as the Madison Workshop on Mathematics of Reaction Networks and the AIM-style Workshop on Mathematics of Reaction Networks, fostering collaborations and advancing the field. His work bridges theoretical mathematics with practical biological modeling, including studies on neurofilament transport, gene regulatory networks, and acoustic wave turbulence. Craciun's research spans diverse areas such as mass-action kinetics, graph-theoretic stability analysis, and algebraic approaches to reaction networks. He has published extensively in journals like SIAM Journal on Applied Mathematics, Bulletin of Mathematical Biology, and Journal of Mathematical Biology, often collaborating with interdisciplinary researchers. His teaching includes courses like Math 703 and involvement in the Madison Math Circle and Putnam Club.

Wilson W. WongView profile

Professor

• Synthetic Biology
• Immunotherapy
• Gene Circuit Engineering
• +5 more

Wilson W. Wong is a Professor in the Department of Biomedical Engineering at Boston University's College of Engineering. His research focuses on synthetic biology and engineering cellular therapies, particularly CAR T and CAR-NK cells for cancer, diabetes, and vaccine applications. He leads the Wilson Wong Lab, developing genetic circuits for precise control of cell functions through molecular, chemical, and optogenetic tools. Key achievements include FDA-approved drug-gated circuits, light-inducible recombinases, and saRNA platforms for reduced immunogenicity. Education: PhD in Chemical Engineering (UCLA), B.S. in Chemical Engineering (UC Berkeley). Awards include the Allen Distinguished Investigator Award (2022), NAE German-American Frontiers Invitee (2021), and NIH Director’s New Innovator Award (2013). He collaborates with institutions like MIT and Harvard on lung regeneration projects through the Allen Distinguished Investigators program. Research Highlights: Logic-gated CAR therapies, optogenetic cell patterning, and saRNA-based vaccines Lab Members: Supervises students including Cristina, Huishan, Josh, and Justin Letendre Grants: Allen Foundation, NSF CAREER Award, NIH funding His work bridges synthetic biology with clinical translation, emphasizing spatiotemporal control of cell functions for regenerative medicine and oncology. Recent breakthroughs include multiplex light-inducible circuits and saRNA modifications enhancing therapeutic efficacy.

• Algorithm Design
• Discrete Optimization
• Approximation Algorithms
• +2 more

Nikhil Bansal is Patrick C. Fischer Professor of Theoretical Computer Science at the University of Michigan. His research focuses on algorithms for discrete optimization problems, discrepancy theory, and scheduling. Research Contributions: Developed foundational techniques in randomized rounding and algorithmic discrepancy minimization. Current investigations include online algorithms, approximation methods for scheduling, and quantum-classical complexity separations. Teaching: Offers courses on randomized algorithms, linear algebra, and approximation algorithms. Created instructional materials on discrepancy theory and semidefinite programming. Professional Service: Serves on editorial boards for Journal of the ACM and Theory of Computing. Organized international workshops on discrepancy theory and optimization.

Stefano NicheleView profile

Professor

• Artificial Life
• Neuro-Inspired Artificial Intelligence
• Machine Learning
• +3 more

Stefano Nichele is a Professor at the Department of Computer Science and Communication, Østfold University College, Norway. He holds additional roles as Professor II at OsloMet and has served in leading academic positions since 2014. His research focuses on Artificial Life (ALife), Neuro-Inspired AI, and Machine Learning, with a particular emphasis on cellular automata, reservoir computing, and neuro-inspired substrates. Nichele co-directs the Østfold AI (ØAI) hub and is an active member of IEEE, ELLIS, and the Norwegian AI Research Consortium (NORA). He earned his PhD in Computer Science from NTNU (2015) and completed his MSc at the University of Insubria, Italy. His work bridges computational systems and biological substrates, exploring criticality in neural networks and quantum-evolutionary algorithm interactions. He has received prestigious awards, including the Young Research Talent grant (2019) and the Distinguished Early-Career Investigator award (2024). Nichele’s research spans theoretical and applied domains, with over 50 publications on cellular automata dynamics, neuro-inspired robotics, and AI ethics. His recent projects include studying in vitro neural networks for computational capacity assessment and developing frameworks for body-brain co-evolution in soft robotics. Education: PhD in Computer Science, NTNU (2015) MSc in Computer Science, University of Insubria (2009) Awards: Young Research Talent grant (2019) Distinguished Early-Career Investigator (2024) Grants & Roles: Co-director of the Østfold AI hub Board member of NORA (Norwegian AI Research Consortium) Labs & Collaborations: Focus on neuro-inspired AI systems and unconventional computing Partnerships with institutions like Simula Metropolitan and the International Society for Artificial Life (ISAL)

Violetta LonatiView profile

Assistant Professor

• Formal Languages and Automata
• Computer Science Education
• Theoretical Computer Science
• +2 more

Violetta Lonati is an Assistant Professor at the University of Milan 's Department of Computer Science since 2005. Her research spans Formal Languages and Automata (operator precedence languages, Wang automata, tiling systems) and Computer Science Education . She co-authored over 15 publications in theoretical computer science and education, focusing on 2D language recognition, logic characterization of automata, and pattern statistics in stochastic models. Education : PhD in Computer Science (2005) and Laurea in Mathematics (2001) from University of Milan Research Groups : ALaDDIn Lab for Didactics and Dissemination of Informatics, Bebras International Initiative Her work on Wang automata established their equivalence to tiling systems while introducing deterministic variants. In education, she designed workshops for schools and contributed to Italy's national computing curriculum proposal (2019). She held leadership roles at ACM ITiCSE (WG5 leader 2022), served as Associate Program Chair (2019-2022), and reviewed for top venues like ICER and SIGCSE TS. She received Google CS[4]HS and Informatics Europe awards for her educational contributions. Key Publications (2017-2001): Input-driven locally parsable languages (TCS 2017) Operator precedence logic characterization (SICOMP 2015) Snake-deterministic tiling systems (MFCS 2009) Graph fibrations and PageRank (RAIRO 2006) Pattern statistics in rational models (STACS 2005) Scientific awards include Google CS[4]HS (2011, 2017, 2019) and the Informatics Europe Best Practices in Education (2016). As part of ALaDDIn, she developed teacher training programs and graduate courses on computing education. Her teaching experience covers Algorithms & Data Structures (2013-2023), Computer Science Teaching (2014-2023), and courses for Biotechnology and Geological Sciences programs (2005-2007).