Shirshendu Ganguly is an Associate Professor in the Department of Statistics at the University of California, Berkeley. His research focuses on probability theory, statistical physics, and their applications, including percolation models, phase transitions, Markov chains, and random graphs. He holds a PhD in Mathematics from the University of Washington and has held postdoctoral positions at UC Berkeley. Ganguly has been recognized with the 2019 Sloan Research Fellowship. Education: PhD in Mathematics, University of Washington, 2011–2016 Miller Postdoctoral Fellow, UC Berkeley, 2016–2018 Research Interests: Probability Theory, Statistical Mechanics, Markov Chains, Random Graphs, Percolation Theory, Sparse Combinatorial Structures His work explores geometric and probabilistic phenomena in disordered systems, including polymer models, self-organized criticality, and random matrix theory. He has advised multiple PhD students and contributes to teaching advanced probability courses at Berkeley. Awards: 2019 Sloan Research Fellowship
Alfonso Giuseppe Tortorella is a Tenure Track Assistant Professor in the Department of Mathematics at the University of Salerno since October 31, 2022. Previously, he held research positions at CMUC (Center of Mathematics of the University of Coimbra), CMUP (Center of Mathematics of the University of Porto), and KU Leuven. He received his PhD in Mathematics from the University of Florence in 2017 under the supervision of Luca Vitagliano and Paolo de Bartolomeis. His educational background includes an MSc in Mathematics from the University of Salerno (2013) with honors, where he completed his thesis titled "Geometric methods of Hamiltonian mechanics" under Luca Vitagliano's guidance. Tortorella's research focuses on Poisson geometry in the broadest sense, with particular emphasis on deformation theory of coisotropic submanifolds in Jacobi manifolds, multiplicative structures on Lie groupoids, and VB-groupoids. His work explores the intersection of differential geometry, mathematical physics, and algebraic structures, developing sophisticated theoretical frameworks to understand geometric structures and their deformations. He has made significant contributions to understanding symplectic foliations, contact dual pairs, and the algebraic structures underlying Jacobi geometry. His most recent publications (2023-2025) demonstrate a consistent focus on deformation problems in Poisson and related geometries, with particular attention to coisotropic submanifolds in contact geometry, symplectic foliations, and the application of L∞ algebras to geometric deformation problems. His work shows increasing sophistication in handling higher structures and their applications to geometric problems. Abilitazione Scientifica Nazionale for Professore Associato in Geometria e Algebra (01/A2 - II Fascia) (May 24, 2021 - May 24, 2030) Qualification aux fonctions de Maître de conférences, section 25 - Mathématiques (December 31, 2018 - December 31, 2022) PhD internship at IM PAN awarded by WCMCS (December 2014) PhD scholarship from INdAM (October 2013) Scholarship from SMI (June 2013) Tortorella has advised multiple PhD, MSc, and BSc students, including Vanessa Oliveira (PhD, University of Porto), Antonio Maglio (PhD, University of Salerno), and Rodrigo de Oliveira Baptista (MSc, University of Porto). He has served on examination committees and as a reviewer for numerous prestigious mathematics journals. His collaborative work extends across international boundaries, with research stays at institutions in Italy, Portugal, Belgium, Poland, France, Germany, and Brazil. He is an active organizer of conferences and workshops, particularly in the field of Poisson geometry, serving on the organizing committees for events like Poisson 2024 and the INdAM Intensive Period on Poisson Geometry & Mathematical Physics.
Kay Jin Lim serves as Senior Lecturer and Director of the MSc (Analytics) program at Nanyang Technological University's School of Physical & Mathematical Sciences, where he contributes significantly to both academic leadership and mathematical research within the Division of Mathematical Sciences. His educational foundation includes a B.Sc. (2005), M.Sc. (2007), and Ph.D. (2009) from the National University of Singapore, followed by doctoral research at the University of Aberdeen under David John Benson's supervision. Lim's research centers on representation theory of finite dimensional algebras, with deep connections to algebraic combinatorics and algebraic geometry. His work explores modular representation theory of symmetric groups, Specht modules, and Lie modules, emphasizing combinatorial structures and geometric interpretations in positive characteristic settings. This specialized focus has established him as a contributor to advanced algebraic frameworks. Analysis of his publication trajectory (2013-2025) reveals consistent advancement in understanding module complexities, rank varieties, and symmetric group representations, with increasing emphasis on interdisciplinary connections between algebraic combinatorics and geometric methods. His collaborative approach with international researchers like Karin Erdmann and David Benson demonstrates engagement with cutting-edge developments in the field. Scientific awards: No awards, fellowships, or major prizes are documented in the available information. Lim maintains an active supervisory role with four doctoral students: Yu Jiang (graduated May 5, 2021), Jialin Wang (graduated March 31, 2024), and current candidates Kua Hao Yan Manzu and Chen Siyuan. His teaching portfolio spans foundational to advanced algebra courses including MH2220 Algebra I, MH3220 Algebra II, and specialized topics in Homological Algebra, reflecting his commitment to mathematical education at multiple levels. He operates within NTU's vibrant mathematical research ecosystem, maintaining significant collaborations with leading algebraists globally while directing the MSc (Analytics) program to integrate theoretical mathematics with practical analytical applications.
Asaf Ferber is Associate Professor in Mathematics at University of California, Irvine, School of Physical Sciences. His research spans discrete mathematics including combinatorial games, random graphs, extremal hypergraph theory, and quantum computation. Research explores Hamiltonian cycles in random graphs, structural properties of pseudorandom graphs, and quantum algorithms for combinatorial problems. Recent work develops quantum approaches to graph learning and sparse recovery in random matrices. Awards: NSF CAREER Award Sloan Fellowship Distinguished Early Career Faculty Award for Research Air Force Research Grant NSF-BSF Grant Organizes conferences including SoCalDM Symposium and Desert Discrete Math Workshop, mentoring graduate students through UCI's Probability and Combinatorics Seminar.
Silviu Pufu is a Professor of Physics at Princeton University, where he earned both his A.B. (2007) and Ph.D. (2011) in Physics. Prior to his faculty position, he was a Pappalardo Postdoctoral Fellow at MIT (2011–2013). His research focuses on quantum field theory, string theory, and gravity, with emphasis on conformal field theory, gauge/gravity duality, and lattice gauge theory. He has received the Alfred P. Sloan Research Fellowship (2017) and led the Simons Collaboration for Nonperturbative Bootstrap (2016–2023). His work explores advanced topics such as AdS/CFT correspondence, M-theory corrections, and non-perturbative bootstrap methods. Pufu advises three graduate students: Ross Dempsey, Debaditya Pramanik, and Benjamin Søgaard. His research outputs span theoretical frameworks like super-Yang-Mills theories, M-theory orbifolds, and lattice Hamiltonian formulations of QCD. His 2020–2025 publications highlight contributions to bootstrap techniques, holographic calculations, and precision studies of strongly coupled systems.
Sanjit A. Seshia is the Cadence Founders Chair Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley . He is affiliated with the Group in Logic and the Methodology of Science and participates in centers like the Industrial Cyber-Physical Systems Center , Berkeley AI Research , and the Simons Institute for the Theory of Computing . Research interests include formal methods for automated verification and synthesis of dependable systems, with applications to cyber-physical systems , AI-based autonomy , and computer security . His work spans SMT solving, model counting, syntax-guided synthesis, and algorithmic improvisation, with tools like UCLID5 , VerifAI , and Scenic for verifying autonomous systems and educational platforms like CPSGrader . Students and collaborators include notable researchers such as Dorsa Sadigh (Stanford), Daniel Fremont (UC Santa Cruz), and Hazem Torfah (Chalmers). He has co-founded startups like Decyphir and 20ⁿ Labs based on his research.
Florian Schäfer is an Assistant Professor at the School of Computational Science and Engineering at Georgia Tech. His research spans numerical computation, statistical inference, and competitive games, with applications in materials science, turbulence modeling, computer graphics, and computational geometry. He will join the Courant Institute at NYU in September 2025. PhD in Applied and Computational Mathematics, Caltech Bachelor’s and Master’s in Mathematics, University of Bonn His work focuses on information geometric mechanics to design structure-preserving numerical methods for continuum mechanics. This includes: State-of-the-art solvers for elliptic PDEs via Gaussian elimination and conditional independence Efficient multi-agent optimization algorithms Information geometric regularization for compressible fluid dynamics Enabling the first compressible fluid simulation exceeding 100 trillion grid cells His recent research trends integrate: Machine learning for materials science (e.g., active learning, Bayesian approaches) Stochastic modeling of microstructures and phase-field problems Neural operators for super-resolution fluid dynamics Generative models for polycrystalline material datasets Optimal transport and diffusion models for conditional density transformations High-performance computing at extreme scales Florian collaborates with researchers including Houman Owhadi, Jessie Liu, Spencer Bryngelson, Tamer Zaki, and Ali Mani. He actively presents at conferences like SIAM and UCLA seminars, and is recruiting PhD students for work at the Courant Institute starting 2025.
Clay Córdova is an Associate Professor at the University of Chicago, associated with the Enrico Fermi Institute, James Franck Institute, Kadanoff Center, and Kavli Institute. His research focuses on theoretical physics, particularly quantum field theory, non-invertible symmetries, and their applications in particle and condensed matter physics. Córdova’s work explores topological phases, gauge theories, and string theory, with recent contributions to non-invertible symmetry classification and their role in phase transitions. His research interests include categorical symmetries, topological defects, and anomaly matching in quantum field theories. He has pioneered studies on soliton-particle degeneracies, anyon condensation mechanisms, and anomalies in non-invertible symmetry frameworks. Córdova’s work bridges high-energy physics with condensed matter systems, often employing advanced mathematical techniques from category theory and algebraic topology. His 2023 Sloan Research Fellowship highlights recognition of his contributions. Key research trends span non-invertible symmetries across dimensions, topological field theory applications, and interdisciplinary methods combining machine learning with lattice gauge theory. Current projects include exploring duality defects, gapped phase obstructions, and symmetry-enriched phases in (3+1)D systems.
Prof. Igors Gorbovickis is an Associate Professor of Mathematics at the Department of Mathematics, School of Computer Science and Engineering, Constructor University (formerly Jacobs University Bremen). His research focuses on complex dynamical systems, including topics such as renormalization theory, bifurcation analysis, Julia sets, and applications to mathematical physics. He also contributes to discrete geometry, particularly exploring conjectures like the Kneser-Poulsen problem. His work bridges pure mathematics with interdisciplinary applications, emphasizing rigorous analysis of nonlinear systems and geometric configurations. Key areas of investigation include critical point accumulations, Hausdorff dimension estimates, and equidistribution phenomena in parameter spaces. Recent publications highlight advancements in understanding chaotic systems, circle maps, and the interplay between algebraic structures and dynamical behavior. Prof. Gorbovickis collaborates internationally, with co-authored papers appearing in journals like Advances in Mathematics , Ergodic Theory and Dynamical Systems , and Nonlinearity . His office is located at Research I, Room 128 on the Constructor University campus in Bremen, Germany.
Marco Castronovo serves as an Assistant Professor in the Mathematics Department at Columbia University, with his office located in Mathematics Hall 614. His academic work bridges continuous and discrete mathematical structures through the lens of symplectic geometry and topology. His research focuses on Symplectic Topology , particularly exploring symplectic structures as frameworks for quantization of classical invariants. Key interests include: Developing open-string versions of Schubert calculus Investigating cluster structures in positroid varieties Constructing Landau-Ginzburg models for Grassmannians Studying Lagrangian cobordisms and exotic tori Analyzing connections between Dubrovin spectra and Fukaya algebras His recent publications reveal a consistent trajectory toward unifying symplectic geometry with combinatorial algebraic structures, particularly through Grassmannian varieties and their mirror symmetric counterparts. The work demonstrates increasing sophistication in connecting Fukaya categories with cluster algebraic frameworks, while maintaining strong ties to quantum topological invariants. As an academic mentor, Castronovo supervises undergraduate researchers including B. Basson (Barnard Summer Research Institute) and S. Kesavan (Columbia Summer Research Fellowship). He actively contributes to the mathematical community through refereeing and co-organizing the Columbia SGGTC Seminar, demonstrating commitment to both research dissemination and academic service. His computational work manifests through three significant open-source projects: Posetroids for exploring Zariski closure orders in Grassmannians, DubrovinDynamics for visualizing spectral evolution in truncated Dubrovin operators, and ClusterExplorer for conducting random walks on cluster structures of Grassmannians. These tools have become valuable resources for researchers working at the intersection of symplectic geometry and combinatorics.
Prof. Baker Mohammad serves as Professor and Director of the System on Chip Lab in the Department of Computer and Information Engineering at Khalifa University. With over 15 years of industrial experience at Intel and Qualcomm designing microprocessors and DSP chips, he bridges academic research with real-world engineering challenges in high-performance computing and low-power systems. His educational background includes: Ph.D. in Electrical and Computer Engineering, University of Texas at Austin (2008) M.S. in Electrical and Computer Engineering, Arizona State University B.S. in Electrical Engineering, University of New Mexico Dr. Mohammad's research spans cutting-edge domains where VLSI design converges with AI acceleration and emerging memory technologies . His work pioneers Memristor applications in environmental sensing (radiation, vacuum, glucose) and neuromorphic computing, while advancing energy harvesting systems for wearable electronics. The integration of in-memory computing with security primitives represents a paradigm shift in hardware design, moving beyond traditional CMOS limitations. His publication trajectory reveals accelerating focus on self-powered neuromorphic systems and RRAM-based architectures, with recent work (2021-2023) emphasizing hardware-software co-design for edge AI. Over 75% of his recent publications involve cross-disciplinary collaborations spanning materials science, chemistry, and biomedical engineering. Notable scientific recognition includes: IEEE TVLSI Best Paper Award 2016 IEEE MWSCAS Myrill B. Reed Best Paper Award Qualcomm Qstar Award for Performance Leadership KUSTAR IP Excellence Award Multiple SRC Techon Best Session Papers As a dedicated mentor, he has supervised over 15 graduate students while securing competitive funding from Khalifa University, ADEK, Qualcomm, Tii, and UAE space agencies. His grant portfolio demonstrates exceptional translational impact, converting fundamental research in memristive devices into drone flight computers and medical sensors. Current projects integrate academic rigor with industrial deployment timelines. The System on Chip Lab operates as a multidisciplinary hub where semiconductor physicists collaborate with AI researchers to develop RISC-V-based secure processors and piezoelectric nanogenerator systems. Recent expansions include partnerships with Tii for aerospace applications and medical device startups for glucose monitoring technology.
Assoc Prof Ng Teng Yong is an Associate Professor at the School of Mechanical & Aerospace Engineering (NTU), specializing in numerical modeling and simulation. With a background as Research Manager at A*STAR Institute of High Performance Computing, his work spans materials science, nanotechnology, and aerospace engineering. Current focus on graphene-based desalination membranes Expertise in molecular dynamics simulations Investigates nanoscale fluid mechanics and structural dynamics Recent publications highlight advancements in energy-efficient electrodialysis, smart robotics, and nonlinear vibration analysis. His interdisciplinary approach integrates computational methods with experimental validation in additive manufacturing and soft material mechanics.
Jon Keating is a Professor at the University of Oxford affiliated with the Mathematical Institute . His research spans Mathematical Physics , Number Theory , and Stochastic Analysis , with a focus on Random Matrix Theory and its applications to quantum systems and number theory. Research Trends: His recent work explores connections between random matrices and number-theoretic functions, with contributions to understanding moments of L-functions, characteristic polynomials, and quantum chaos. Key themes include asymptotic analysis, recursive structures, and interdisciplinary applications in nonlinear systems. Publications: Highlights include studies on CUE characteristic polynomials, the Ratios Conjecture, and collaborations in Nonlinearity , International Mathematics Research Notices , and Transactions of the American Mathematical Society .
Igor Kriz is a Professor of Mathematics at the University of Michigan, specializing in algebraic topology. He is affiliated with the Department of Mathematics within the College of Literature, Science, and the Arts (LSA). His research focuses on advanced topics in algebraic topology, particularly stable homotopy theory and related areas. Kriz received his Ph.D. from Charles University in 1988. His academic journey has led him to become a prominent researcher in algebraic topology, with significant contributions to the field over several decades. Professor Kriz's primary research interests lie in algebraic topology , which studies topological spaces through algebraic invariants. He specializes in equivariant stable homotopy theory, Mackey functors, cobordism, and motivic homotopy theory . His work involves calculations of stable homotopy groups and other generalized homology theories, including Morava K-theories of classifying spaces of finite groups. He has made significant contributions to the study of operads and structures up to homotopy, with applications extending to differential geometry and physics, particularly string theory. His research often bridges multiple mathematical disciplines, creating connections between topology, algebra, and geometry. His recent publications (2022-2025) demonstrate a strong focus on equivariant topology and its connections to algebraic structures. Kriz frequently collaborates with researchers like P. Hu, P. Somberg, and others, producing work that explores the intersection of homotopy theory with representation theory and algebraic geometry. His research program shows consistent evolution from foundational work in stable homotopy to more recent applications in motivic contexts and topological Hochschild homology. Professor Kriz teaches both undergraduate and graduate courses at the University of Michigan. His teaching portfolio includes Math 425 (Introduction to Probability), Math 592 (Introduction to Algebraic Topology), and advanced graduate courses Math 695 and Math 696 (Algebraic Topology I and II). His course materials are regularly updated, reflecting his commitment to education in mathematical topology. Based in East Hall (room 3846) at the University of Michigan, Professor Kriz maintains an active research program while contributing to the academic community through teaching and mentorship. His work continues to advance our understanding of complex topological structures and their algebraic representations.
Sergei Gukov is the John D. MacArthur Professor of Theoretical Physics and Mathematics at the California Institute of Technology (Caltech), where he has been a faculty member since 2005. He serves in the Division of Physics, Mathematics and Astronomy, with primary affiliation in the Department of Mathematics. His research bridges the fields of mathematics and theoretical physics, focusing on deep connections between geometry, topology, and quantum field theory. Gukov received his B.S. from Moscow Institute of Physics and Technology in 1997, followed by an M.S. and Ph.D. from Princeton University in 2001. He joined Caltech as an Associate Professor in 2005, was promoted to Professor in 2007, and was named the John D. MacArthur Professor in 2021. His research spans several interconnected areas at the frontier of mathematics and physics. A central theme is the exploration of quantum topology and its connections to mathematical physics. He has made significant contributions to the geometric Langlands program, gauge theory, and the categorification of knot and 3-manifold invariants. His recent work increasingly incorporates machine learning approaches to mathematical problems, reflecting his interest in the intersection of traditional mathematical research and modern computational techniques. Gukov's work often reveals deep connections between seemingly disparate areas of mathematics and physics, such as the relationship between Rozansky-Witten geometry and Coulomb branches in supersymmetric gauge theories. Gukov's publications demonstrate a consistent focus on the mathematical structures underlying quantum field theories and their topological implications. His recent work shows an increasing emphasis on computational approaches to mathematical problems, particularly through his interest in mathematics and machine learning. The recurring themes across his research include the application of physical insights to solve mathematical problems and the discovery of new mathematical structures through physical reasoning. He serves on the editorial boards of several prestigious journals including the Journal of Knot Theory and Its Ramifications, Communications in Mathematical Physics, and Letters in Mathematical Physics. Gukov is also active in the academic community, having delivered plenary talks at major conferences such as the First International Congress of Basic Science and presenting at String Math 2023 on the potential impact of AI on mathematical research. Gukov teaches Ma 146 ab, Introduction to Knot Theory and Quantum Topology, a course that reflects his research interests. He also runs a seminar on Mathematics and Machine Learning, held Tuesdays from 2-3pm in East Bridge Conference room 114, demonstrating his commitment to fostering interdisciplinary research at the intersection of mathematics and computational methods.
