Renjie Feng is a Research Fellow in Mathematics and AI at the School of Mathematics and Statistics and the Sydney Mathematical Research Institute , University of Sydney. His work bridges probability theory, statistics, and applications in machine learning, deep learning, and artificial intelligence. His research interests focus on probability theory and its applications to machine learning , random matrix theory , and statistical physics . He investigates extreme value problems, spectral properties of random matrices, and topological features of random fields over Riemannian manifolds. Recent publications highlight trends in random matrix theory (GUE, GOE, GSE), extreme gap problems , determinantal point processes , and Wiener chaos . Collaborative works with F. Götze, D. Yao, and R. Adler emphasize U-statistics , multivariate linear statistics , and random topology inspired by Poisson point process studies.
Annina Iseli is a Lecturer in the Department of Mathematics at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the College of Basic Sciences. She holds dual roles as both a Scientist and Lecturer, contributing to research and teaching within the Institute of Mathematics (MATH-GE). Her work bridges pure and applied mathematics, focusing on geometric and analytical properties of fractals. University: École Polytechnique Fédérale de Lausanne (EPFL) School: College of Basic Sciences Department: Institute of Mathematics (MATH-GE) Role: Lecturer and Scientist Research interests span multiple areas in mathematics: Fractal geometry and its connections to complex dynamics Geometric measure theory applications to projections in normed spaces Conformal and quasiconformal geometry Analysis in metric spaces Her publications include work on projection theorems, fractal dimensions, and hyperbolic space properties. She co-organizes the Quasiworld Seminar and EPFL Geometry Seminar, collaborating with researchers like Mario Bonk, Nicolas Monod, and Zoltán Balogh. Contact: annina.iseli@epfl.ch
Johnny Golding is a Professor at the Royal College of Art (RCA), School of Arts & Humanities. His career spans roles such as Director of the Centre for Fine Art Research at Birmingham City University, Professor of Philosophy in the Visual Arts & Communication Technologies (2000–2012), and honorary Professorship in Philosophy and Imaging at Dundee School of Art (2009). Born in New York, he holds a PhD from the Universities of Toronto and Cambridge. Education : - PhD in Philosophy from the Universities of Toronto and Cambridge. - Earlier studies in Toronto and New York. Research Interests : Golding’s work explores post-Newtonian analytics, new materialisms, and the erotics of sense as 'radical matter.' His interdisciplinary approach bridges art, philosophy, and 'wild sciences' like AI, robotics, and quantum theory. Key themes include data proliferation's societal impact, emergent systems, and the interplay between art and technology. Recent Articles & Projects : Focus on Data Loam (2020), exploring future knowledge systems through art and science collaborations. Recent works address radical empathy, distributed intelligence, and the ethics of AI. His 2018 opera Entanglement: The Opera and installations like Of The Thick and the Raw exemplify his practice-led philosophy. Grants & Leadership : - Led the Data Loam project (FWF-PEEK funded), involving over 20 artists and scholars. - PI for AiDesign Labs on generative AI at RCA. Labs & Collaborations : - Radical Matter Lab (2017–2018), a pedagogical experiment at RCA. - Collaborations with institutions like the University of Applied Arts Vienna and the British Library.
Fatma Kılınç-Karzan is an Associate Professor of Operations Research at Carnegie Mellon University's Tepper School of Business, with a courtesy appointment as Associate Professor of Computer Science. She is also affiliated with the Algorithms Combinatorics and Optimization (ACO) PhD Program and was a Visiting Scientist at Berkeley's Simons Institute for the Theory of Computing during Fall 2017. Her educational background includes a PhD from Georgia Institute of Technology's H. Milton Stewart School of Industrial & Systems Engineering with a minor in Mathematics, supervised by Prof. Arkadi Nemirovski. She earned her B.S. and M.S. degrees from the Industrial Engineering Department of Middle East Technical University with a minor in Information Systems. Dr. Kılınç-Karzan's research spans mathematical optimization with emphasis on convex and non-convex optimization theory, algorithms, and applications. Her work bridges theoretical foundations with practical implementations in optimization under uncertainty (robust optimization, chance constraints, distributionally robust optimization), machine learning (preference learning from limited data), and business analytics. She develops foundational theory for large-scale optimization problems with applications in decision making under uncertainty and high-dimensional statistical inference. Analysis of her recent publications reveals a strong focus on convex hull characterizations, semidefinite programming relaxations, distributionally robust optimization, and online convex optimization frameworks. Her work demonstrates increasing integration of optimization theory with machine learning applications, particularly in developing data-driven approaches for decision making under uncertainty. NSF CAREER Award (2015) INFORMS Optimization Society Young Researcher Prize (2015) INFORMS Junior Faculty Interest Group (JFIG) Best Paper Award (2014) BP Junior Faculty Chair (2014-2015) Faculty Giving Chair (2012-2013) Wimmer Fellowship (2012-2013) Dr. Kılınç-Karzan has successfully mentored numerous PhD students who have received prestigious awards, including the 2021 INFORMS Optimization Society Best Student Paper (1st prize) and multiple honorable mentions. Her research has been supported by significant grants including an NSF CAREER Award, an ONR grant (with S. Küçükyavuz), and an AFOSR grant. She serves on editorial boards for Mathematical Programming, Operations Research, Mathematics of Operations Research, and other leading journals, and has held leadership positions in professional societies including the Mathematical Optimization Society and INFORMS Computing Society. Through her affiliations with CMU's Tepper School, Computer Science Department, and ACO Program, she collaborates across disciplines to advance optimization theory and its applications. Her professional service includes committee chair roles for major INFORMS competitions and program committee leadership for international optimization conferences.
Bradley D. Olsen is a full professor in the Department of Chemical Engineering at the Massachusetts Institute of Technology (MIT), where he leads research at the intersection of polymer science, soft matter physics, and bioengineering. His work focuses on designing materials for critical applications in biotechnology, hemostasis, and sustainable polymer development while advancing fundamental understanding of polymer network mechanics and self-assembly. Education: Ph.D. in Chemical Engineering, University of California Berkeley (2007) S.B. in Chemical Engineering, Massachusetts Institute of Technology (2003) Olsen's research spans protein-based materials, block copolymer phase behavior, and mechanochemical hydrogels. He has pioneered methods for quantifying polymer network topology, developing hemostatic nanoparticles, and creating bio-inspired materials for selective biomolecular transport and medical applications. His recent publications emphasize data-driven approaches to polymer characterization and educational outreach in materials science. Scientific Awards: American Physical Society (APS) Fellow (2023) Fulbright Amazonia Scholar (2023) Alexander and I. Michael Kasser Chair in Chemical Engineering (2021) ACS Macro Letters Young Investigator Award (2021) MIT Committed to Caring Honor (2019) AIChE Owens Corning Early Career Award (2019) APS Dillon Medal (2018) Kavli Emerging Leader in Chemistry (2017) ACS Polymer Division Fellow (2016) Camille Dreyfus-Teacher Scholar (2015) Alfred P. Sloan Research Fellow (2014) NSF Career Grant (2013) NIH Postdoctoral Fellowship (2008-2009) Hertz Fellow (2003-2007) Barry M. Goldwater Scholarship (2002) Olsen has received significant grant support including NSF Career (2013) and AFOSR (2012) awards. His teaching activities include innovative international outreach like the 2025 soccer-themed science camp in Brazil. The Olsen Group at MIT explores advanced materials with applications ranging from trauma care to sustainable polymers.
Prof. Peter Scholze is a leading mathematician at the Max Planck Institute for Mathematics in Bonn, specializing in algebraic geometry and arithmetic geometry. He holds the academic rank of Professor and is part of the Arbeitsgruppe Algebraische Geometrie und Darstellungstheorie. His research focuses on foundational questions in algebraic geometry, number theory, and representation theory, particularly through the lens of the Langlands program, p-adic Hodge theory, and perfectoid spaces. Scholze has pioneered geometric approaches to the local Langlands correspondence and introduced revolutionary concepts like prismatic cohomology and condensed mathematics. He actively contributes to academia through advanced courses on topics such as geometrization of the Langlands program, étale cohomology, and condensed mathematics. His work bridges algebraic geometry with representation theory, addressing fundamental problems in arithmetic geometry and p-adic analysis. Scholze’s research outputs include seminal papers on perfectoid spaces, prismatic cohomology, and the geometrization of local Langlands correspondence. He collaborates extensively with leading mathematicians globally, contributing to collaborative research initiatives like the ARGOS seminar and the Habiro ring project. His teaching engagements include advanced lectures on algebraic geometry, representation theory, and p-adic geometry, reflecting his commitment to training the next generation of researchers. Despite no explicitly listed awards in the provided text, Scholze is widely recognized as a Fields Medalist (2018) and a leading figure in modern mathematics.
Prof. Michael Moor is a tenure-track Assistant Professor for Medical AI at ETH Zurich's Department of Biosystems Science and Engineering in Basel. Previously, he conducted postdoctoral research at Stanford University under Prof. Jure Leskovec, focusing on medical foundation models. His work spans causal learning, multimodal AI, and sepsis prediction. Moor holds an MD from the University of Basel and a PhD from ETH Zurich's Machine Learning and Computational Biology Lab under Prof. Karsten Borgwardt. Research Interests: Generalist medical AI models Multimodal medical reasoning Zero-shot and few-shot learning Clinical causal inference Retrieval-augmented language models Sepsis prediction systems Key Achievements: Published foundational work in Nature (2023) on generalist medical AI Developed Med-Flamingo multimodal model (2023) Zero-shot causal learning framework accepted to NeurIPS 2023 (Spotlight) International sepsis prediction study with 156k ICU patients (2023) Lab Activities: Leads ETH's Medical Foundation Models group, collaborating with Stanford HAI and NASA Ames. Active in creating medical AI benchmarks like AgentClinic and developing retrieval-augmented systems like Almanac.
Andrew Spakowitz is a Professor of Chemical Engineering, Materials Science and Engineering, and by courtesy, Applied Physics and Chemistry at Stanford University. He currently serves as the Senior Associate Dean for Research and Faculty Affairs and holds the Tang Family Foundation Chair of the Department of Chemical Engineering. His academic career at Stanford spans from Assistant Professor (2006-2014) to Associate Professor (2014-2020) and now Professor since 2020. Dr. Spakowitz earned his PhD in 2004, MS in 2001 from the California Institute of Technology, and his BS in Chemical Engineering from the University of Wisconsin, Madison in 1999. He completed postdoctoral training in Molecular and Cell Biology and Biophysics at UC Berkeley from 2004-2006. His research focuses on theoretical and computational approaches to understanding biological processes and complex materials. The Spakowitz lab addresses fundamental chemical and physical phenomena through four main research themes: chromosomal organization and dynamics, protein self-assembly, polymer membranes, and charge transport in conducting polymers. His group employs diverse theoretical and computational methods including analytical theory of semiflexible polymers, polymer field theory, continuum elastic mechanics, Brownian dynamics simulation, equilibrium and dynamic Monte Carlo simulations, and reaction-diffusion modeling. Analysis of his recent publications reveals a strong emphasis on epigenetics and chromatin dynamics, with significant work on DNA methylation patterns, nucleosome clustering, and chromosome organization. His research also extends to polymer physics applications in biological systems, particularly in respiratory diseases, water purification membranes, and bacterial phage interactions with human mucus. Tang Family Foundation Chair of the Department of Chemical Engineering Professor Spakowitz mentors several graduate students and postdoctoral scholars in the Chemical Engineering and Materials Science departments. His lab members work on diverse projects spanning from chromatin dynamics to polymer membranes for water purification. He teaches multiple courses including CHEMENG 120B (Energy and Mass Transport), CHEMENG 340 (Molecular Thermodynamics), CHEMENG 466 (Polymer Physics), and CHEMENG 467 (Physics of Biomacromolecules). The Spakowitz lab operates from Clark S295 at Stanford University, conducting theoretical and computational research that bridges chemistry, physics, biology, and engineering disciplines to address complex problems across multiple length and time scales.
Anush Tserunyan is a Professor of Mathematics at McGill University, Canada, and a Visiting Professor at the Unit of Pure and Applied Mathematics (UMPA) at École normale supérieure de Lyon from December 1, 2024, to January 31, 2025. She holds a bachelor's and master's in computer science and applied mathematics from Yerevan State University (2005–2007) and a Ph.D. in Mathematics from UCLA (2013), focusing on finite generators for group actions, equivalence relations, and recursive program complexity. Research Interests: Anush Tserunyan specializes in Ergodic Theory , Combinatorics , and Group Actions , with notable contributions to graph theory, hypergraphs, and Ramsey theory. Her work bridges combinatorial structures with analytic methods, particularly in dynamical systems and descriptive set theory. Collaborations: During her visit to UMPA, she collaborates with teams in Geometry, Groups and Dynamics , and Number Theory , alongside researchers like Benjamin Schraen and Sophie Morel. Her stay includes seminars on GGD, Number Theory, and the 'Actions!' working group. Publications: Her research spans topics like ergodic theorems, disjoint matchings in graphs, and algebraic hypergraphs, reflecting a focus on foundational mathematical structures and their applications.
Elden Elmanto is an Assistant Professor in the Department of Mathematics at the University of Toronto, affiliated with the Faculty of Arts and Science. His research focuses on advanced areas of algebraic geometry and homotopy theory, particularly through a motivic perspective. He investigates algebraic cycles, vector bundles, and motivic cohomology, often leveraging techniques from derived algebraic geometry and p-adic geometry. Recently, he co-developed a motivic cohomology theory for singular schemes with Matthew Morrow. His work spans topics like algebraic K-theory, motivic homotopy theory, and the interplay between topology and arithmetic geometry. He actively participates in seminars such as the Toronto Algebraic Geometry Seminar and has led research on topological cyclic homology, equivariant algebraic K-theory, and motivic infinite loop spaces. Elmanto collaborates widely, contributing to fields like étale motivic spectra, Voevodsky’s convergence conjecture, and the Quillen-Lichtenbaum dimension. His research emphasizes foundational questions in modern algebraic geometry, with applications to arithmetic and geometric contexts.
Brian Conrad is a Professor of Mathematics at Stanford University, specializing in number theory and arithmetic geometry. He holds a position in the Department of Mathematics and has contributed extensively to algebraic geometry, algebraic number theory, and representation theory. His research encompasses foundational work on reductive groups, pseudo-reductive groups, and their applications in arithmetic contexts. Dr. Conrad is an editor for the Journal of the AMS, Algebra and Number Theory, and IMRN. He has organized numerous learning seminars, including those on étale cohomology and the BSD conjecture, and has taught advanced courses on algebraic geometry, class field theory, and modular forms. His work bridges classical algebraic geometry with modern arithmetic applications, emphasizing foundational proofs and geometric intuition. His editorial roles and seminar leadership reflect his commitment to advancing mathematical exposition and education. Education details are not explicitly provided in the texts, but his academic trajectory includes significant contributions to the field through publications and mentorship. Dr. Conrad's research has led to advancements in areas such as the classification of algebraic groups, étale cohomology, and the arithmetic of elliptic curves. His collaborative work with mathematicians like Chai, Oort, and Prasad has produced influential monographs, including Pseudo-reductive Groups and Complex Multiplication and Lifting Problems .
Megan Kerr serves as the Katharine and Claudine Malone '63 Professor of Mathematics at Wellesley College, where she teaches across the mathematics curriculum from calculus to advanced topics in geometry. Her academic home is within the Mathematics & Statistics Department at this prestigious women's liberal arts college. Her educational journey began as an undergraduate at Wellesley College, where she later returned as faculty, completing a full circle in her academic career. She earned her Ph.D. from the University of Pennsylvania under the supervision of Wolfgang Ziller, with research focused on Homogeneous Einstein Metrics. Professor Kerr's research centers on global differential geometry, particularly exploring the interplay between curvature constraints and large symmetry groups. She specializes in homogeneous and low-cohomogeneity spaces, investigating fundamental questions about the existence of geometric structures, their rarity or commonality, and potential obstructions. Her work bridges the analytic concept of curvature with the algebraic framework of Lie groups, and she has recently expanded into geometric analysis where topology plays a significant role. Analysis of her publication record reveals a consistent focus on homogeneous Einstein metrics across three decades, with particular attention to curvature properties, symmetry constraints, and classification problems in both positive and negative curvature settings. Her research has evolved from foundational work on symmetric spaces to more complex non-symmetric examples and specialized curvature conditions, demonstrating both depth and breadth in differential geometry. Katharine and Claudine Malone '63 Professor of Mathematics Radcliffe Institute Fellowship As an alumna of Wellesley College, Professor Kerr maintains a strong commitment to encouraging women in mathematics. She teaches a diverse range of courses including calculus, linear algebra, combinatorics, real analysis, non-Euclidean geometry, differential geometry, topology, knot theory, and matrix groups as an introduction to Lie groups. Her teaching philosophy emphasizes developing mathematical understanding and confidence that benefits students regardless of their major. Her research has taken her to international destinations including Australia, Germany, and Mexico, reflecting the global nature of her scholarly collaborations.
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.
Eamonn Keogh is a Professor in the Computer Science and Engineering Department at the University of California, Riverside. His pioneering work centers on the Matrix Profile, a transformative approach to time series data mining enabling efficient solutions for motif discovery, anomaly detection, and similarity search. His algorithms (STAMP, STOMP, SCRIMP, DAMP, SCAMP) offer exact, parameter-free, and scalable solutions across domains like seismology, bioinformatics, and industrial IoT. Research areas include: Development of ultra-fast algorithms for time series joins and motif discovery at unprecedented scales (breaking the 100 million barrier) GPU acceleration for time series mining Domain-agnostic methods for semantic segmentation and anomaly detection Novel primitives like Time Series Chains, Snippets, and Consensus Motifs His work is highly cited and recognized by industry and academia, with applications ranging from NASA's Cassini mission to detecting BGP anomalies in computer networks.
Emil J. Straube is a Professor of Mathematics at Texas A&M University, where he has held the rank of Professor since 1996 and served as Department Head from 2011 to 2019. He earned his Ph.D. in Mathematics from the Swiss Federal Institute of Technology (ETH Zurich) in 1983 under Prof. K. Osterwalder. His research focuses on Several Complex Variables, with emphasis on the ∂-Neumann problem, Bergman kernel, and boundary regularity of solutions to Cauchy-Riemann equations. Education: Ph.D. in Mathematics, ETH Zurich, 1983 Diploma in Mathematics (dipl. math. ETH), ETH Zurich, 1977 Research Interests: His work bridges complex analysis, partial differential equations, and operator theory. Key topics include global regularity of the ∂-Neumann operator, compactness estimates, D’Angelo forms, and the Diederich-Fornaess index. He has contributed foundational results on Sobolev regularity and geometric conditions for subellipticity. Publications & Awards: With over 50 peer-reviewed articles, Straube has authored influential monographs such as Lectures on the L2-Sobolev Theory of the ∂-Neumann Problem . Notable accolades include the Stefan Bergman Prize (1995, jointly with H.P. Boas), AMS Fellow (2013), and Texas A&M’s Distinguished Achievement Award (1998). His work has been supported by NSF grants totaling over $3 million and international collaborations at institutions like the Erwin Schrödinger Institute (Vienna). Service & Leadership: Organized major conferences, including the 2015 Qatar Complex Analysis Conference Edited journals such as Journal of Mathematical Analysis and Applications and Complex Analysis and Its Synergies Guided 7 Ph.D. students and co-mentored numerous postdocs Current Activities: Active in teaching advanced graduate courses (e.g., Complex Variables I/II) and continues research in global regularity theory and CR geometry.
