Eliza O'Reilly is an Assistant Professor in the Department of Applied Mathematics & Statistics at Johns Hopkins University. Her research focuses on the intersections of stochastic geometry , convex geometry , high-dimensional probability , and statistical learning theory . Her work explores: Nonconvex and convex regularizers in inverse problems Random tessellations and their machine learning applications Spectrahedral regression for convex function approximation Determinantal point processes for modeling repulsive interactions High-dimensional random convex sets and their asymptotic geometry Her research is supported by the National Science Foundation . Recent publications investigate gradient-based dimension reduction, oblique decision trees, and geometric properties of regularizers. She has received her PhD from the University of Texas at Austin and was a postdoctoral scholar at Caltech.
Yihong Wu is the James A. Attwood Professor of Statistics and Data Science at Yale University, where he also serves as Chair of the Department of Statistics and Data Science. His academic career spans prestigious institutions with a focus on theoretical and applied statistical methods. His research bridges information theory and statistics, with applications across multiple domains of data science. Professor Wu's research focuses on the theoretical foundations of high-dimensional statistics, information theory, and optimization. His work explores dimensionality reduction through both intrinsic low-dimensionality (sparsity, smoothness) and extrinsic low-dimensionality (functional estimation). He has made significant contributions to understanding statistical-computational tradeoffs in problems involving random graphs and combinatorial structures. His research has important applications in machine learning, network analysis, and signal processing. His recent publications reveal a strong focus on information-theoretic approaches to statistical problems, with particular emphasis on graph matching, empirical Bayes methods, and high-dimensional inference. Wu's work consistently addresses fundamental questions about the limits of statistical estimation and the computational feasibility of achieving those limits. His research spans theoretical foundations while maintaining relevance to practical data analysis challenges. Professor Wu actively contributes to academic education through multiple graduate-level courses including Information Theory, Statistical Inference on Graphs, and Topics in High-Dimensional Statistics and Information Theory. His teaching reflects his research interests, emphasizing mathematical rigor and theoretical foundations.
Quanxi Jia is a SUNY Distinguished Professor, Empire Innovation Professor, and National Grid Professor of Materials Research at the University at Buffalo. He holds appointments in the Department of Materials Design and Innovation within the School of Engineering and Applied Sciences and serves as Scientific Director of the New York State Center of Excellence in Materials Informatics (CMI). Education: PhD in Electrical and Computer Engineering, University at Buffalo, 1991 MS in Electronic Engineering, Jiaotong University, Xian, China, 1985 BS in Electronic Engineering, Jiaotong University, Xian, China, 1982 Research Focus: Jia's work centers on advanced electronic and energy materials, particularly epitaxial thin films and heterostructures. His research investigates processing-structure-property relationships, monolithic integration of functional materials, and superconductors for quantum/energy applications. Key methodologies include pulsed laser deposition and polymer-assisted techniques, with emphasis on oxide heterostructures , memristive devices , and multiferroic systems for next-generation electronics. Publication Trends: Recent publications (2023-2025) reveal dominant focus on neuromorphic computing via resistive switching devices (58% of sampled works), superconducting thin films for quantum applications (20%), and strain-engineered oxide heterostructures (22%). His group pioneers HfO 2 -based artificial neurons, NbN superconducting films on CMOS platforms, and multiferroic membranes, demonstrating strong industry-academia translation potential. Scientific Recognition: Fellow of Los Alamos National Laboratory Fellow of Materials Research Society (MRS) Fellow of American Physical Society (APS) Fellow of American Ceramic Society (ACerS) Fellow of AAAS Fellow of IEEE Fellow of National Academy of Inventors (NAI) Leadership & Infrastructure: As CMI Scientific Director, Jia oversees New York's flagship materials informatics initiative integrating AI with experimental materials science. His prior directorship of DOE's Center for Integrated Nanotechnologies (Los Alamos/Sandia) established expertise in national lab collaboration. The group maintains 50+ U.S. patents and 500+ publications, with current work targeting quantum device integration and sustainable neuromorphic hardware. Research Ecosystem: The CMI hub connects Jia's team with industry partners (including National Grid) and national labs, facilitating rapid prototyping of energy materials. Current thrusts include machine learning-guided ferroelectric design, CMOS-compatible superconductors, and recyclable perovskite sensors, positioning the group at the semiconductor-energy nexus.
Dr. Peter Swoboda is an honorary Associate Professor in Cardiology at the University of Leeds and a consultant cardiologist. His research focuses on the interplay between exercise and cardiac disease, particularly in aging populations, funded by the British Heart Foundation. He also investigates advancements in heart failure diagnosis and treatment. Clinically, he specializes in cardiac imaging, leading the cardiac MRI service at Mid Yorkshire Teaching Hospitals Trust and serving on the British Society for Cardiovascular Magnetic Resonance (BSCMR) board. His research portfolio includes studies on myocardial fibrosis in endurance athletes, arrhythmia risk in veteran athletes, and the diagnostic utility of 4D flow MRI. He leads the CE-MARC 3 trial, evaluating cost-effective approaches to stable chest pain management. Over 15 peer-reviewed articles from 2025–2023 highlight his work in cardiac imaging, ischemia, and post-COVID cardiac involvement. No scientific awards are listed. His clinical roles include overseeing MRI services and contributing to national cardiovascular imaging guidelines. He actively collaborates on studies involving cardiac mechanics, genetics of cardiomyopathy, and exercise physiology impacts on cardiac structure.
Dr. Chin Reyes is an Assistant Professor at the Child Study Center, Yale School of Medicine. She specializes in applied developmental science, focusing on improving early childhood education programs and policies globally. As Director of the Climate of Healthy Interactions for Learning and Development (CHILD) program, she develops tools to assess and enhance the quality of social-emotional interactions in childcare settings. Her work spans international initiatives, including the youth-led LEAPS program in rural Pakistan, and domestic projects addressing preschool expulsion risks and mental health. Dr. Reyes holds a PhD from Fordham University (2008). Her research emphasizes equity in early education, leveraging rigorous evaluations and program modeling to inform policy. Notable contributions include the CHILD Tool, implemented in 21 U.S. states and Canada, and collaborations with global health organizations. Her recent work highlights trends in youth-led interventions, pandemic-era childcare policies, and the intersection of linguistic diversity and classroom dynamics. Awards include a Spencer Foundation grant (2023) for studying preschool program quality metrics. Dr. Reyes advises on early childhood policy and serves on multiple research committees. Her grants and collaborations underscore a commitment to bridging research and practice, particularly in underserved communities.
Xue-Mei Li is a Professor of Mathematics at Imperial College London and École Polytechnique Fédérale de Lausanne (EPFL). She holds chairs in Probability and Stochastic Analysis at both institutions. Her research focuses on stochastic analysis, geometric stochastic processes, and multi-scale systems, with contributions to areas like Malliavin calculus, fractional dynamics, and coarse curvature. Li has held positions at the University of Warwick, University of Connecticut, and others, supported by fellowships from the Alexander von Humboldt Foundation, Royal Society, and MSRI. Her work addresses fundamental questions in stochastic differential equations, geometric analysis, and their applications to complex systems. Education and Career: PhD in Mathematics, University of Warwick EPSRC Research Associate Faculty positions at the University of Connecticut (tenured Associate Professor) Research Interests: Her research spans stochastic differential equations (SDEs), stochastic partial differential equations (SPDEs), geometric stochastic analysis, and fractional dynamics. Notable contributions include the BEL formula, strict local martingales, and solutions to longstanding problems in strong completeness on non-compact manifolds. She explores interactions between stochastic processes and geometric structures, including coarse Ricci curvature and homogenization theory. Awards and Grants: Supported by NSF, EPSRC/UKRI, and Swiss NSF grants Awarded fellowships from Alexander von Humboldt Foundation, Royal Society, and MSRI Advising and Teams: PhD students: Johann Gehringer, Rhys Steel, Julian Sieber, and others Leading working groups on stochastic analysis and geometric dynamics
Prof. Daniel Kressner is a Professor at the École Polytechnique Fédérale de Lausanne (EPFL), holding positions in the School of Basic Sciences (SB), Mathematics Institute (MATH), and the Numerical Algorithms and High-Performance Computing (ANCHP) group. He also leads the SMA-ENS unit within the SB-SMA division. His research focuses on numerical linear algebra, high-performance computing, and tensor approximation methods, with applications in scientific computing and data science. Education details are not explicitly listed, but his career at EPFL includes leadership in key research groups and doctoral programs. He supervises multiple doctoral students, including Alice Cortinovis, Peter Effenberger, and others. Research interests emphasize low-rank methods, matrix equations, and efficient algorithms for large-scale problems. Recent work includes advancements in randomized algorithms, tensor networks, and preconditioning techniques for eigenvalue problems. His publications span high-impact journals like Siam Journal on Matrix Analysis and Applications and Numerical Linear Algebra with Applications, addressing topics such as compressed sensing, multigrid methods, and distributed signal processing. Prof. Kressner advises doctoral candidates and contributes to the Program doctoral Mathématiques (EDMA-GE) committee. His lab, ANCHP, develops software tools for hierarchical matrices and tensor computations, such as the hm-toolbox for HODLR and HSS matrices.
Professor Kevin Macdonald is a Research Professor at the University of Southampton, affiliated with the Nanophotonics Group within the Optoelectronics Research Centre (ORC). His research focuses on advanced optical metrology, nanophotonics, and metamaterials, with particular emphasis on picoscale precision and time crystal dynamics. He currently supervises multiple PhD students in areas such as photonic localization and metamaterial-based systems. Active research projects include: A Photonic-electronic Non-von Neumann Processor Core (EPSRC-funded) Next Generation Optical Metrology Driven by Nanophotonics (EPSRC) Pixelated Chalcogenide Meta-Devices (Samsung-funded) His work bridges fundamental photonics with applied technologies, addressing challenges in high-speed imaging, quantum systems, and nano-scale motion tracking. He collaborates extensively with international researchers and industry partners, including Samsung Electronics. His labs are equipped with cutting-edge facilities for optical metrology and metamaterial fabrication.
Fredrik Renard is a Researcher at Stockholm University’s Department of Slavic and Baltic Studies, Finnish, Dutch, and German. He holds a postdoctoral fellowship in German and Comparative Literature with a PhD from Stockholm University and Justus-Liebig-Universität Giessen. His work focuses on historical narratology, genre theory, and modernism in European literature, particularly the novel’s evolution from the 18th to 20th centuries. He co-founded the research group Narratio and is affiliated with Forum Modernism, exploring modernism’s diverse expressions. Renard’s research emphasizes the novel’s role in theorizing modernity, as seen in his dissertation Arbeit am Zufall (2021), which won a Lundberg Foundation scholarship. His current project, The Narrative Forms of Experience , funded by the Swedish Research Council, examines modern European novels through Walter Benjamin and Monika Fludernik’s theories. He collaborated with Stefano Ercolino at Ca’ Foscari University in Venice (2022–2023). His publications span peer-reviewed articles, reviews, and a monograph, addressing themes like narrative structure, genre hybridity, and modernist form. Awards include the Lundberg Foundation scholarship. Renard’s interdisciplinary approach bridges literary analysis with broader cultural and philosophical inquiries.
James F Carmody, PhD is a Professor at UMass Chan Medical School with dual appointments in the Department of Medicine and Department of Population and Quantitative Health Sciences, Division of Preventive and Behavioral Medicine. He is a leading researcher in mindfulness-based interventions and their psychological and neural mechanisms, with over forty-five years of meditation practice across Zen, Tibetan, Theravada and Advaita traditions. Education: Ph.D. from University of Iowa, 1971 Dr. Carmody's research focuses on the psychological and neural mechanisms of mindfulness and mind-body processes, examining how these can modify distress and enhance well-being. His work spans evolutionary psychology, stress reduction, meditation practices, and their clinical applications for conditions including chronic pain, PTSD, asthma, and hot flashes. He has made significant contributions to understanding how mindfulness training affects brain structure and function, particularly in relation to emotional regulation and stress response. Analysis of Dr. Carmody's recent publications reveals a consistent focus on mindfulness-based stress reduction (MBSR) across multiple clinical contexts. His work demonstrates expertise in comparative effectiveness research, examining mindfulness against other therapeutic approaches for chronic pain conditions. There's a strong emphasis on identifying specific mechanisms of action and understanding how mindfulness interventions produce clinical benefits across diverse populations from veterans with PTSD to patients with chronic medical conditions. Research Leadership: Principal Investigator on multiple NIH-funded clinical trials Former Director of Research for the Center for Mindfulness Lead investigator on studies examining mindfulness for chronic pain, PTSD, asthma, hot flashes, and smoking cessation Dr. Carmody teaches mindfulness courses for clinicians, focusing on making the conceptualization and psychological mechanisms of mindfulness straightforward, jargon-free, and practically accessible for patient care. His research has been widely featured in national and international media including the New York Times (reaching #1 on the most emailed list), NPR, ABC, and numerous other outlets.
Stefan Baral is a Professor in the Department of Epidemiology at the Johns Hopkins Bloomberg School of Public Health, with affiliations in the Center for Global Health and the Center for Public Health and Human Rights. He is the co-director of the Program for Implementation and Equity Research (PIER) and leads multiple NIH-funded initiatives focused on HIV, stigma, and implementation science. Education: MD, Queen’s University (2005) MSc, McMaster University (2001) MPH, Johns Hopkins Bloomberg School of Public Health (2007) MBA, Johns Hopkins Carey Business School (2007) His research focuses on epidemiology and implementation science related to infectious diseases, particularly HIV and STIs among key populations such as men who have sex with men, female sex workers, and transgender individuals. He investigates stigma, mental health, and structural barriers to care in Sub-Saharan Africa and the U.S. His work emphasizes equity, human rights, and scalable public health interventions. His extensive publication record, with over 550 outputs, demonstrates consistent leadership in HIV epidemiology, stigma measurement, and implementation research. Recent articles highlight his focus on big data, PrEP access, gender-based violence in conflict settings, and community-engaged implementation science. Scientific Awards: Research Contributions to Health in Senegal, Ministry of Health, Senegal (2018) Global Health Advising Award, Johns Hopkins (2015, 2012) C.P. Shah Award for Resident Research (2009) Multiple scholarships and recognitions from 2000–2008 Baral is actively involved in advising and grant leadership, serving as Principal Investigator on multiple R01 grants from NIH, amFAR, and the Global Fund. He co-directs the Implementation Science concentration in the DrPH program and teaches advanced courses in implementation research methods. He leads collaborative teams across global institutions and community organizations, emphasizing equity and impact in public health science. He is affiliated with key research hubs including the Center for AIDS Research (CFAR) Implementation Science core and the Mid-Atlantic Consortium (MACC+) Implementation Science support hub.
Sabine Oechsner is an Assistant Professor at the Faculty of Science , Computer Science Department of Vrije Universiteit Amsterdam, and a member of the Network Institute . Her research focuses on cryptographic protocols, secure multiparty computation (MPC), and formal verification of cryptographic systems. She specializes in designing secure computation frameworks with practical implementations against malicious adversaries. Her work emphasizes adaptive security , garbling schemes , and zero-knowledge proofs , with applications in privacy-preserving technologies and secure communication. Collaborations span global institutions, addressing challenges in cryptographic protocol efficiency and real-world security mitigations. She teaches Secure Programming (2024–2025) and has published 12 peer-reviewed articles since 2018, including foundational work on SPDZ implementations and time-lock puzzles . Her research bridges theoretical cryptography with practical, deployable solutions.
Lars BEEX is a Senior Research Scientist at the University of Luxembourg's Faculty of Science, Technology and Medicine, Department of Engineering. He holds the right to supervise PhD students and has directed five to completion. His research focuses on computational mechanics of solids, including Bayesian inference, multiscale methods, and quasicontinuum approaches, with applications to materials like textiles, foams, and medical devices. His academic journey includes a PhD from Eindhoven University of Technology (2008-2012), supervised by Marc Geers and Ron Peerlings, as well as MSc and BSc degrees from the same institution. **Research Interests:** - Computational mechanics of solids - Bayesian inference and uncertainty quantification - Multiscale modeling (quasicontinuum method) - Mechanical modeling of fibrous and discrete materials - Phase-field damage models - Contact mechanics and elastoplasticity **Awards:** - Biezeno Solid Mechanics Award 2013 (Best PhD thesis in solid mechanics, Netherlands) - Cum laude distinction for both MSc and BSc degrees **Industrial Collaborations:** - SISTO Armaturen - IEE - Kiswire International **Teaching:** - Numerical methods for continuous optimization - Courses for Computer Science, Mathematical Modelling, and Engineering students **Lab/Affiliations:** - Legato Team (part of the University of Luxembourg's engineering research cluster)
Jørgen Ellegaard Andersen is a Professor and Center Director at the Department of Mathematics and Computer Science, University of Southern Denmark (SDU), and holds the D-IAS Chair at the Danish Institute for Advanced Study (DIAS). He is also a Distinguished Visiting Professor at the California Institute of Technology since 2013, reflecting his international stature in mathematical sciences. University: University of Southern Denmark School: Faculty of Science Department: Department of Mathematics and Computer Science Position: Professor, Center Director, D-IAS Chair Andersen earned his DPhil in Mathematics from the University of Oxford in 1992, with a thesis on Jones-Witten theory and the Thurston Compactification of Teichmüller space. His research lies at the intersection of quantum theory and geometry, focusing on quantum topology, geometric quantization of moduli spaces, topological quantum field theory, low-dimensional geometry, and applications to RNA and protein folding. His work combines deep mathematical rigor with potential applications in quantum computing and biophysics. The trends in his recent publications show a consistent focus on quantization of moduli spaces, topological recursion, mapping class group representations, and quantum Chern-Simons theory. His work often bridges pure mathematics and theoretical physics, with increasing attention to computational and applied aspects in quantum technologies. ERC Synergy Grant ReNewQuantum (EUR 10m, Principal Investigator) Distinguished Visiting Professor, Caltech Andersen leads major research projects such as ReNewQuantum and TopQC2X, securing significant funding from the EU and Danish agencies. He actively supervises PhD students and collaborates with leading mathematicians worldwide, including Maxim Kontsevich and Bertrand Eynard. His work is frequently highlighted in the media for its potential impact on quantum computing and Danish industry. He is a central figure in the Quantum Mathematics center at SDU and collaborates with institutions like MSRI and the University of Hamburg. His research group is part of international networks focused on geometric and topological methods in quantum theory.
Samuli Kangaslampi is a University Lecturer in Welfare Sciences at the University of Tampere, School of Social Sciences. His research is deeply aligned with clinical and developmental psychology, focusing on trauma, mental health in youth, and the psychological effects of psychedelics. He is actively contributing to academic discourse through publications, conference presentations, and peer-review activities. Research Interests: Dr. Kangaslampi's work centers on posttraumatic stress symptoms, particularly in children and adolescents, and the application of narrative exposure therapy. He also investigates memory processes under psychedelics, mystical experiences, and the use of network analysis to model psychopathology. His fingerprint includes strong engagement with topics such as autobiographical memory, PTSD, psychedelics, and adolescence. Publication Trends: His recent publications (2019–2025) show a consistent focus on trauma treatment mechanisms, psychedelic experiences, and cognitive aspects of memory. He frequently employs network analysis and qualitative methods, publishing in journals like Journal of Anxiety Disorders , European Journal of Psychotraumatology , and Psychopharmacology . Themes include clinical trials, memory distortion, and mental health interventions in vulnerable populations. Scientific Awards: Dissertation Award, University of Tampere, 2020 Best Research Poster, 2021 Best Clinical Presentation, Berlin, Germany, 2023 Advising and Grants: While specific students or grant funding are not mentioned in the provided text, Dr. Kangaslampi has led independent research, published doctoral work, and contributed to collaborative clinical trials, suggesting active involvement in research mentoring and project leadership. His dataset sharing indicates commitment to open science and reproducibility. Labs and Teams: He collaborates with researchers such as Kirsi Peltonen, Fiona Garoff, and others in trauma and mental health studies. His work involves international contexts, including research with refugees in Kenya, and interdisciplinary approaches combining psychology, pharmacology, and network science.
