Ewain Gwynne is a Professor of Mathematics at the University of Chicago, affiliated with the Committee on Computational and Applied Mathematics (CCAM) and the Statistics Department. He previously held postdoctoral positions at the University of Cambridge and earned his Ph.D. from MIT in 2018 under Scott Sheffield. His research focuses on probability theory, particularly random geometric structures in statistical mechanics, including Schramm-Loewner evolution (SLE), Liouville quantum gravity (LQG), and random planar maps. Education: Ph.D. in Mathematics, MIT (2018); M.Sc., MIT (2015); B.Sc., Northwestern University (2013). Research Interests: Random geometric objects in statistical mechanics Liouville quantum gravity and its metric properties Random planar maps and their scaling limits SLE and its relationship with LQG Random walks on random planar maps Percolation and permutons His recent articles explore topics such as supercritical LQG, Gaussian curvature on random maps, and harmonic balls in LQG. He has advised multiple Ph.D. students and serves as an associate editor for Probability and Mathematical Physics . His work bridges probability theory, geometry, and mathematical physics, with applications to understanding critical phenomena in random systems.
Nils Fleischhacker is an Assistant Professor for Cryptography at Ruhr University Bochum, where he leads the Theoretical Cryptography group within the Faculty of Computer Science. His research focuses on foundational aspects of cryptography with particular emphasis on zero-knowledge proofs, digital signatures, and secure computation. Prior to joining Ruhr University, he held postdoctoral positions at Johns Hopkins University and Carnegie Mellon University. Dr. Fleischhacker received his PhD in Computer Science from Saarland University in February 2017, advised by Dominique Schröder. During his doctoral studies, he was a research intern at Microsoft Research with Chris Brzuska and a research visitor at the University of Maryland, College Park with Jonathan Katz and Dana Dachman-Soled. His research spans theoretical cryptography with significant contributions to zero-knowledge proofs, multi-signature schemes, property-preserving hash functions, and security proofs for cryptographic primitives. Fleischhacker's work often addresses fundamental questions about the limits and possibilities of cryptographic constructions, with particular attention to black-box separations and lower bounds. His recent publications demonstrate a strong focus on lattice-based cryptography and post-quantum secure protocols. Fleischhacker's publications over the past five years reveal a consistent research trajectory focused on improving the efficiency and security of cryptographic primitives, with particular emphasis on signature schemes, zero-knowledge protocols, and secure computation frameworks. His work frequently appears in top-tier cryptography venues including CRYPTO, EUROCRYPT, and CCS. Dr. Fleischhacker actively mentors PhD students, with numerous successful graduations spanning from 2010 to 2024. His former PhD students include Önder Askin (2024), Floyd Zweydinger (2023), and Lars Schlieper (2022), among others. His research is supported through various academic channels and collaborations. He is affiliated with several prominent research organizations including the Horst Görtz Institute (HGI) for Information Security, the DFG Excellence Cluster CASA, the EU Marie Curie Network QSI, and the International Association for Cryptologic Research (IACR). These affiliations provide a strong institutional framework for his theoretical cryptography research.
Shane G. Henderson is the Charles W. Lake, Jr. Professor in Productivity at Cornell University's School of Operations Research and Information Engineering (ORIE). His research focuses on the intersection of optimization and simulation, with applications to complex systems such as bike-sharing networks, medical scheduling, and ambulance deployment. He emphasizes practical societal relevance, addressing challenges in healthcare, transportation, and parallel computing environments. Education: B.Sc. (Mathematics), University of Auckland (1992) M.S. (Statistics), Stanford University (1995) Ph.D. (Operations Research), Stanford University (1997) Research Interests: Structured simulation optimization, parallel computing applications, applied probability, and case-driven problem-solving. Recent work includes MRI scheduling, radiation treatment planning, and land/air ambulance systems. He advocates for methodologies that leverage convexity or quasi-convexity to enhance algorithmic efficiency and robustness. Awards and Recognition: 2016 Tau Beta Pi Professor of the Year 2014 Sonny Yau '72 Excellence in Teaching Award 2011 Hess Research & Education Award NSF CAREER Award (1999) Teaching & Service: Courses in probability, simulation, and mathematical modeling using case-based learning. Served on award committees for INFORMS Nicholson Prize, Pierskalla Prize, and Impact Prize. Organized major conferences including the 2009 INFORMS Applied Probability Society conference and multiple Winter Simulation Conferences. Currently co-edits simulation-optimization testbeds for experimental comparisons. Labs & Collaborations: Active in Cornell's collaborative research environment, focusing on interdisciplinary projects with industry partners like Motivate (bike-sharing systems). Engaged in advancing methodologies for complex systems through data-driven approaches.
LEONG Tze Yun is a Professor in the Department of Computer Science at the School of Computing, National University of Singapore (NUS). She holds S.B., S.M., and Ph.D. degrees in Computer Science from the Massachusetts Institute of Technology (MIT). Her academic career spans both research and industry experience, with significant contributions to the fields of artificial intelligence and health informatics. Dr. Leong's educational background includes: Ph.D. in Electrical Engineering & Computer Science, Massachusetts Institute of Technology S.M. in Electrical Engineering & Computer Science, Massachusetts Institute of Technology S.B. in Computer Science & Engineering, Massachusetts Institute of Technology Her primary research interests focus on responsible AI, dynamic decision-making, neurocognitive modeling, reinforcement learning, artificial general intelligence, and biomedical and health informatics. Her work bridges the gap between theoretical AI development and practical healthcare applications, with an emphasis on ethical considerations and human-centered design. She directs the Medical Computing Laboratory at NUS, a multidisciplinary research program exploring human-aware decision modeling in complex environments. Analysis of her recent publications reveals a strong trend toward responsible AI development, with significant contributions to reinforcement learning techniques, causal inference methods, and applications of AI in healthcare. Her work increasingly integrates ethical considerations with technical AI development, particularly evident in her 2024 publications on medical AI and human values. Her scientific recognition includes: Fellow of the American College of Medical Informatics (ACMI) Founding Fellow of the International Academy of Health Sciences Informatics (IAHSI) Member of Eta Kappa Nu (Honor Society for Electrical Engineers) Dr. Leong has supervised numerous doctoral and master's students throughout her career, many of whom have gone on to prominent positions at institutions like Google, Netflix, Mayo Clinic, and academic institutions worldwide. Her advisory work extends to significant policy development, including contributions to WHO guidance on ethics and governance of AI for health. She currently serves on the World Health Organization (WHO) Expert Group on Ethics and Governance of AI for Health, the World Economic Forum (WEF) AI Governance Alliance, and the Advisory Council on AI in Uzbekistan. Her laboratory work focuses on developing adaptive systems that evolve with changing technical functionalities, system infrastructures, usage patterns, and operational contexts, with applications spanning prediction and decision analytics, human-aware robotics, game artificial intelligence, personalized education, and assistive care for elderly with neurocognitive disorders.
Alexis Battle is an Associate Professor at Johns Hopkins University with appointments in Biomedical Engineering , Computer Science , and Genetic Medicine (secondary). She directs the Malone Center for Engineering in Healthcare and serves as Deputy Director of the Data Science and AI Institute . Educated at Stanford University (PhD in Computer Science, 2013), Battle transitioned to academia after leadership roles at Google. Research Focus: Battle’s work bridges genomics and machine learning , emphasizing the impact of genetic variation on human health. Her lab develops tools like Watershed to predict functional effects of rare variants, aiming to enhance rare disease diagnosis. Key themes include non-coding DNA analysis , personalized genomics , and systems biology , with applications in cardiovascular disease and neurodegenerative disorders . Publications & Awards: Over 60 peer-reviewed articles in journals like Nature , Science , and Genome Biology , with recent emphasis on single-cell transcriptomics , multiomics integration , and telomere biology . Recipient of the President’s Frontier Award (2022), Microsoft Investigator Fellowship (2019), and Searle Scholar (2016). Scientific Awards: 2022 President’s Frontier Award 2019 Microsoft Investigator Fellowship 2019 Johns Hopkins Discovery Award 2017 Johns Hopkins Catalyst Award 2016 Searle Scholar Advising & Funding: Mentors 11 PhD students, 3 undergraduates, and postdoctoral fellows. Her research is funded by NIH, Searle Scholars, and institutional grants. The Battle Lab collaborates on projects like the GTEx Consortium , focusing on gene regulation and clinical genomics .
Chris G. Van de Walle is the Herbert Kroemer Distinguished Professor in the Department of Materials at the University of California, Santa Barbara's College of Engineering. As a member of the National Academy of Engineering and fellow of multiple prestigious scientific societies including the American Physical Society and Materials Research Society, he leads the Computational Materials Group which is part of UCSB's strong computational science cluster within the Materials Department. His research interests focus on novel electronic materials, particularly wide-band-gap semiconductors (III-V nitrides, II-VI compounds), transparent conductors, complex oxides, loss mechanisms in light emitters, two-dimensional conductors, quantum information science, and the physics and chemistry of hydrogen interactions with solids. His group uses first-principles computational techniques to study atomic and electronic structure of crystalline, polycrystalline and amorphous materials, interfaces, surfaces, defects, and heterojunctions. Analysis of his recent publications reveals a strong focus on semiconductor materials for quantum technologies, with particular emphasis on GaN, Ga 2 O 3 , and related compounds. His work combines computational materials science with applications in optoelectronics, quantum information, and energy technologies, demonstrating consistent innovation in understanding defects and their role in material properties. Major Awards and Recognitions: Aneesur Rahman Prize for Computational Physics (APS) Materials Theory Award (MRS) Vannevar Bush Faculty Fellowship (DoD) John Bardeen Award (TMS) Medard W. Welch Award (AVS) Highly Cited Researcher (Clarivate Analytics) Professor Van de Walle has mentored numerous successful researchers, including Dr. Fangzhou Zhao (Corbett Prize winner) and Dr. Mark Turiansky (APS Nicholas Metropolis Award recipient). His group maintains strong connections with the UCSB Quantum Foundry and the Solid State Lighting and Energy Electronics Center, demonstrating collaborative research efforts across multiple disciplines. The group actively investigates defects for quantum information science, loss mechanisms in light emitters, nitride semiconductors, halide perovskites, oxides, and hydrogen interactions with materials.
Nuno Conceição serves as an Invited Assistant Professor at the Faculty of Psychology, University of Lisbon (FP-UL), where he has taught since 2011. His clinical work focuses on adults with complex trauma, personality disorders, and structural dissociation of the personality. He earned his BA (1999), MA (2006), and Ph.D. in Clinical Psychology (2011) from FP-UL, following his Abitur at the German School of Lisbon (1994). BA: FP-UL (1999) MA: FP-UL (2006) Ph.D.: FP-UL (2011) His research centers on Psychotherapy Integration, examining General Change Processes, Case Formulation, Emotional Change in Trauma Therapy, and Ecological Dimensions in Psychotherapy. He investigates how experiential processing facilitates change in personality pathology through integrative clinical decision-making. Key trends in his 2016-2023 publications reveal consistent focus on transdiagnostic mechanisms, termination processes, and musical interventions for emotional processing, primarily using qualitative case studies to advance psychotherapy integration frameworks. No scientific awards were documented in the source material. Conceição has supervised over 50 master's research projects and designed the Integrative Perspectives in Psychotherapy curriculum. He directs the Paradigmatic Complementarity Lab—a practice-based research network using process coding to train clinical skills—and serves as a therapist trainer/supervisor at OneSession.org. Supervision: >50 master's projects Curriculum Development: Integrative Perspectives in Psychotherapy Professional Training: OneSession.org The Paradigmatic Complementarity Lab drives his research agenda, utilizing process-coding methodologies to study change mechanisms in complex trauma and personality disorders within real-world clinical settings.
Steven I-Jy Chien serves as Professor and Director of the Transportation Program within the Department of Civil and Environmental Engineering at the New Jersey Institute of Technology (NJIT). His career spans academia, government, and industry with significant contributions to transportation engineering research and practice. His educational credentials include: Ph.D. in Civil and Environmental Engineering from University of Maryland-College Park (1995) M.S. in Civil and Environmental Engineering from University of Maryland-College Park (1991) B.S. in Civil Engineering from Tamkang University (1983) Professor Chien's research focuses on transportation system resilience, sustainable transit operations, and advanced traffic modeling. His work addresses critical challenges in urban rail networks, demand-responsive transit services, and energy-efficient transportation systems. He employs sophisticated computational methods including genetic algorithms, machine learning, and Bayesian approaches to solve complex transportation problems involving network vulnerability, passenger behavior, and infrastructure optimization under uncertainty. Analysis of his recent publications reveals strong emphasis on transportation resilience against cascading failures, sustainable operations for electric transit systems, and pandemic-responsive aviation scheduling. His research spans diverse geographic contexts including major Chinese metropolitan areas and U.S. transportation networks, demonstrating global applicability of his methodologies. His professional recognition includes: 2024 Keynote Speaker at Union-Tech Lecture, National Taiwan Ocean University 2022 Keynote Speaker at International Conference of Chinese Institute of Transportation 2022 Best Poster Award from New Jersey Department of Transportation Professor Chien has secured research funding from federal agencies including the Federal Highway Administration (FHWA) where he contributed to CORSIM traffic simulation software development. His industry experience with China Engineering Consultants Inc. and Information Dynamic Inc. informs his practical approach to transportation challenges. As Transportation Program Director, he oversees curriculum development and industry partnerships that prepare students for transportation sector careers. He maintains active collaboration with transportation agencies globally, particularly through his leadership in the Transportation Program at NJIT which serves as a hub for innovation in urban mobility solutions.
Andrew Postlewaite is the Harry P. Kamen Professor of Economics and Professor of Finance at the University of Pennsylvania's School of Arts and Sciences. He holds dual roles in the Department of Economics and the Ronald O. Perelman Center for Political Science and Economics. As a distinguished academic, he is a member of the American Academy of Arts and Sciences and serves as a director at the National Bureau of Economic Research (NBER). Additionally, he is the founding editor of the American Economic Journal: Microeconomics and a research associate at Penn's Population Studies Center and Institute for Law and Economics. Postlewaite's research focuses on game theory, behavioral economics, and social norms, with contributions to mechanism design, repeated games, and intergenerational transmission of preferences. His work bridges theoretical foundations with applied economic analysis, particularly in areas like consumer behavior, decision-making, and institutional design. He has held visiting positions at institutions including Caltech, Harvard, and Stanford, reflecting his academic prominence. His scholarly contributions include pioneering studies on future-oriented decision-making, interdependent valuations in markets, and equilibrium concepts in repeated games. Recent publications explore topics such as the impact of local media accessibility in the digital age and the welfare implications of consumption fluctuations. His editorial leadership at journals like Econometrica and International Economic Review underscores his influence in shaping economic discourse. Awarded prestigious fellowships and editorial roles, Postlewaite's career exemplifies a blend of rigorous theoretical research and practical applications in economics. His current research trends emphasize behavioral insights and the methodological underpinnings of economic models, reflecting a commitment to advancing both theory and real-world relevance.
Petros Koumoutsakos is the Herbert S. Winokur, Jr. Professor of Computing in Science and Engineering at Harvard University's School of Engineering and Applied Sciences (SEAS), where he also serves as Area Chair for Applied Mathematics. His research integrates machine learning with computational science to advance understanding of complex systems, including fluid dynamics, turbulence modeling, and biomedical applications. He leads the CSE Lab, focusing on high-performance computing and interdisciplinary collaborations such as a recent study with Citadel Securities and Google Cloud to simulate heart disease in cloud environments. Key research interests include reinforcement learning for turbulence closures, generative models for PDE solutions, and physics-informed AI for biomedical imaging and wildfire prediction. He was awarded the PRACE HPC Excellence Award (2023) for contributions to high-performance computing. His work bridges computational methods with real-world applications, emphasizing interpretability and scalability in multiscale systems. Grants & Collaborations: Leadership in multi-institutional projects, including turbulence modeling via reinforcement learning and cloud-based HPC studies. Labs/Teams: Director of the CSE Lab, advancing AI, computational fluid dynamics, and biomedical simulations.
Professor Jonathan Boff (FRHistS) is a leading military historian in the Department of History at the University of Birmingham. His research explores the intersection of institutions, individuals, and warfare through comparative and cross-disciplinary approaches. He has a unique background combining academic expertise with two decades of private-sector experience, primarily in Asia. PhD in War Studies, King’s College London MA in History of Warfare, King’s College London BA in PPE, Merton College, Oxford University Boff’s research focuses on Economic Statecraft , the military history of the World Wars, British strategy (1880–1945), and the psychological dynamics of combat. He bridges historical analysis with modern policy challenges, particularly in financial and strategic contexts. Recent publications highlight his expertise in First World War financial policy, battlefield tactics, and institutional adaptation. His work is recognized for its empirical rigor and interdisciplinary methodology. AHRC Fellowship in Research Leadership (2020–23) Prize-winning books: Haig's Enemy (OUP, 2018) and Winning and Losing on the Western Front (CUP, 2012) Fellow of the Royal Historical Society He supervises PhD research on topics such as economic statecraft, World War-era military strategies, and comparative studies of morale. His grants include AHRC funding for his current project on financial warfare, culminating in a 2025 monograph by Oxford University Press.
Yaojun Zhang is an Assistant Professor in the Department of Physics & Astronomy and the Department of Biophysics at Johns Hopkins University. She earned her PhD in Physics from the University of California, San Diego (2015), followed by postdoctoral fellowships at the Princeton Center for Theoretical Science (2015-2018) and the Princeton Center for the Physics of Biological Function (2018-2021). Her research focuses on biological physics, particularly the complex behaviors of biomolecules and their assemblies across scales—from single-molecule folding to intracellular transport and biomolecular phase separation. She employs theoretical, mathematical, and computational tools to bridge biological questions with physical principles. Education PhD in Physics, University of California, San Diego (2015) Postdoctoral Fellowships: Princeton University (2015-2021) Research Interests Her group studies biomolecular condensates and liquid-liquid phase separation, exploring how microscopic interactions determine macroscopic properties of cellular compartments. Key areas include: Biomolecular condensate formation and dynamics Phase separation in cellular environments Interactions between biomolecules and cellular components Biophysics of intracellular transport Collaborations & Tools Zhang collaborates with experimentalists to validate theoretical models and develops frameworks for understanding condensate functions, such as surface tension, stoichiometry, and phase diagrams. Her work addresses challenges like condensate stability, molecular exclusion, and biological function regulation. Labs & Resources She leads the Zhang Lab , which integrates experimental and computational approaches. Her team’s research is supported by resources at the Bloomberg Center for Physics and Astronomy.
Roger Boltshauser is a Full Professor and Deputy Head at the Department of Architecture, ETH Zurich. His practice and academic work emphasize tectonic building culture, proportion, and material experimentation, diverging from mainstream German-Swiss architectural trends. He combines teaching with active architectural practice, influencing younger generations at ETH and TU Wien. Key themes: Tectonic structures, grid-based order, social responsibility in architecture, critique of modernist canons Notable projects: Hochhaus H1 Zwhatt-Areal (2025), Masterplan Zoo Basel (2025), Centre for Dental Medicine Zurich (2025) His buildings prioritize mass and permanence , evident in projects like the Kopfholz School and Rauch House . Recent works at the EPFL Solar Biennale (2025) and Architecture of Memory exhibition (2025) explore sustainable design and cultural narratives. Boltshauser’s studio on Dubsstrasse exemplifies research into load-bearing structures and urban spatial relationships.
Patrick Rinke serves as an Adjunct Professor in the Department of Applied Physics at Aalto University, Finland. His research bridges theoretical physics, materials science, and computational methodologies with a strong focus on machine learning applications. His computational work spans electronic structure theory, materials design, and atmospheric chemistry. Rinke's research integrates Bayesian optimization, active learning, and high-throughput computational screening to accelerate materials discovery, particularly in hybrid perovskites, catalysts, and biomaterials. Recent work demonstrates machine learning's transformative potential in predicting molecular properties, optimizing materials functionality, and solving complex physical chemistry problems. His scientific contributions have been recognized with multiple awards: Thesis Prize from the Institute of Physics (2003) DFG Research Scholarship (2007-2009) Outstanding Postdoctoral Achievement Award (2009) Outstanding Referee of Physical Review Letters (2014) August-Wilhelm Scheer Visiting Professorship (2017)
Olga Dontsova is a Full Professor at Moscow State University (MSU) in the Faculty of Chemistry. She serves as Head of the Division of RNA Structure and Function at the Belozersky Institute of Physico-Chemical Biology and Head of the Chair of Chemistry of Natural Compounds. Her research spans molecular biology, bioorganic chemistry, and RNA-based mechanisms. Research Focus: She investigates structure-functional relationships in ribonucleoprotein complexes, with emphasis on translation machinery, transfer-messenger RNA (tmRNA) interactions with ribosomes, RNA methyltransferases, and telomerase's role in cancer. Her team pioneered a chemical-biochemical-genetic approach to map mRNA topography in ribosomes, elucidate trans-translation dynamics, and characterize novel RNA-modifying enzymes. Scientific Contributions: Developed a molecular dynamic model for trans-translation Discovered unique yeast telomerase with unconventional properties Investigated functional roles of modified RNA residues in translation Honors: Member of Academia Europaea (2014) Corresponding Member of Russian Academy of Sciences (2006) European Academy Award for Young Scientists (1994) Grants & Leadership: Her work has been funded by HHMI, HFSP, CRDF, INTAS, RFFI, and Russian Ministry of Science and Education. She chairs the Biology Panel of the Russian Scientific Foundation and serves on editorial boards for Biochimie, Russian Journal of Molecular Biology, and Acta Naturae. Teaching: As a supervisor of 21 Ph.D. students and numerous diploma projects, she teaches advanced courses at MSU while maintaining an active research program.
