Snir Ben Ovadia is a Senior Lecturer (equivalent to Assistant Professor) at the Einstein Institute of Mathematics, Hebrew University of Jerusalem. He was previously affiliated with Pennsylvania State University as an Assistant Research Professor in the Department of Mathematics. His research focuses on the interplay between mathematical physics, chaotic systems, and dynamical structures. Key interests include non-uniformly hyperbolic dynamics, thermodynamic formalism, entropy theory, and the geometric properties of dynamical systems. His work bridges theoretical mathematics with applications in complex system behavior. Recent publications (2018–2025) demonstrate a consistent focus on hyperbolic dynamics, symbolic representations of chaotic systems, and measure-theoretic approaches to ergodic theory. Common themes include invariant measures, entropy optimization, and geometric properties of Anosov systems.
Associate Professor Louise Mewton is a public health researcher affiliated with the Matilda Centre at the University of Sydney’s Faculty of Medicine and Health. She also holds a visiting role at the Centre for Healthy Brain Ageing, UNSW Sydney, and collaborates with the COSMIC Collaborators and the Institute for Health Metrics and Evaluation (IHME). Her research focuses on alcohol use disorders across the lifespan, emphasizing their cognitive impacts in gestation, adolescence, and older adulthood. She leads projects on Fetal Alcohol Spectrum Disorders (FASD) teacher resources, neurodevelopmental studies using ABCD Study data, and global dementia epidemiology via COSMIC cohort harmonization. Mewton has secured $16M in funding from NHMRC, NIH, and other bodies to support her work. Her research interests include population neuroscience, comorbidity between mental health and substance use disorders, diagnostic models of psychopathology, and biostatistical methods. Key projects include a randomized controlled trial of an online alcohol intervention in older adults and a large-scale study on the general factor of psychopathology in adolescents. Mewton’s work also addresses pandemic mental health, particularly emotion regulation strategies during the 2020 pandemic year. Awards & Honours : 2024 Fulbright Scholar UNSW Scientia Career Development Fellowship (2019–2022) Young Tall Poppy Science Award (2017) Multiple national and international grants (e.g., NIH, NHMRC) Grants and advising: Mewton leads the $16M-funded ‘Rethink My Drink’ trial targeting older adults and collaborates on global dementia initiatives. She advises research students like Nicholas HOY on transdiagnostic mental health models. Her grants include the Matilda Centre-UCSD Compact for adolescent health research and NIH-supported projects exploring alcohol-dementia links. She also contributed to the Climate Schools Combined Trial, a long-term prevention program. Labs and teams: She is part of the Matilda Centre, Brain and Mind Centre, and COSMIC collaboration. Her work bridges clinical research, population health, and digital intervention design.
Dr. Deepa Purushothaman is a Research Fellow in the Department of Psychiatry at Yale School of Medicine, serving as the Early Detection and Assessment Coordinator (EDAC) for DMHAS Region 5 within the Specialized Treatment for Early Psychosis (STEP) program. She holds an MD in Psychiatry and a Postdoctoral Fellowship in Schizophrenia from NIMHANS, Bangalore. Her clinical focus is on general adult psychiatry, with expertise in schizophrenia spectrum disorders. Her research explores social cognitive deficits in schizophrenia, early psychosis detection, and the neurobiology of mental illness, alongside interests in the history of psychiatry and integrative therapies like yoga and Ayurveda. Education: Postdoctoral Fellowship in Schizophrenia, National Institute of Mental Health and Neurosciences (NIMHANS), 2020 MD in Psychiatry, National Institute of Mental Health and Neurosciences (NIMHANS), 2019 Research Interests: Her work spans social cognition deficits in schizophrenia, early psychosis intervention strategies, and the application of yoga and Ayurveda in mental healthcare. She has published extensively on topics such as tele-yoga efficacy, integrative treatment guidelines for schizophrenia, and the neurobiological underpinnings of delusions. Recent Contributions: Her 2025 study on fNIRS-based social disconnect analysis in psychosis and 2024 meta-analysis on yoga therapy for schizophrenia cognition highlight her focus on innovative diagnostic tools and complementary interventions. She co-developed culturally adapted counseling modules using ancient Indian texts and contributed to global treatment guidelines (INTEGRATE). Awards: Young Investigator Award from Schizophrenia Research Foundation (2018) Advisory & Collaborations: She leads the STEP program's early detection efforts and collaborates with interdisciplinary teams on projects like the 'Integrative Approach for Managing Tardive Dyskinesia.' Her lab engages in translational research bridging neuroimaging, epigenetics, and clinical outcomes. Labs/Teams: Active in the STEP program and associated with the Whisk Cup Streamline initiative, focusing on early psychosis intervention and integrative care models.
Dr. Sarah Hayes-Skelton is an Associate Professor in the Department of Psychology at the University of Massachusetts Boston and serves as the Graduate Program Director. She leads the Anxiety Mechanisms and Processes Lab, focusing on psychotherapy for anxiety disorders through cognitive-behavioral and mindfulness-based approaches. PhD, University of Nebraska – Lincoln Her research explores mechanisms and processes of therapeutic change, with a specific emphasis on cultural sensitivity in evidence-based treatments for social and generalized anxiety disorders. She also investigates perinatal anxiety and develops prevention programs for this demographic. Recent publications highlight her work on mindfulness, acceptance-based therapies, and cultural adaptation of interventions. Key themes include decentering, emotional processing, and systemic factors in anxiety treatment. Labs: Principal Investigator, Anxiety Mechanisms and Processes Lab
Roles: Tutor in Economics Research at Merton College, University of Oxford. Serves as Tutorial Fellow specializing in economic theory and quantitative methods. Affiliations: Merton College, Department of Economics (via University of Oxford) Research Interests: Focuses on game theory fundamentals, particularly pure equilibrium existence ( epsilon-equilibrium and satisficing equilibrium ), adaptive dynamics in large games, and applications to environmental policy and social network formation. Explores theoretical boundaries of Nash equilibria in random games and differential fertility's impact on economic dynamics. Article Trends: Recent work emphasizes large-game asymptotics, showing most large games admit near-equilibrium stability even with bounded rationality. Earlier contributions include carbon tax modeling in production networks and network formation dynamics with overlapping social groups. Grants/Advising: No specific grants or advisees listed in provided materials. Collaborations evident with researchers like Bary Pradelski, Alex Teytelboym, and Michael Savery. Labs/Teams: No dedicated lab mentioned. Research conducted through Oxford's economics department and Merton College.
Honorary Professor Anders Cervin holds the Garnett Passe and Rodney Williams Foundation Chair in Otolaryngology at the University of Queensland, where he is affiliated with the UQ Centre for Clinical Research within the Faculty of Health, Medicine and Behavioural Sciences. With over 50 peer-reviewed publications and numerous book chapters, Professor Cervin has established himself as a leading expert in sino-nasal disorders and upper airway research. Professor Cervin's research interests focus on chronic sinusitis , otitis media , and the alternative treatment with probiotics . His work explores mucociliary function in the upper airways, the role of Nitric Oxide in chronic sinusitis, the use of macrolide antibiotics as immune modulators, and health economic perspectives on sino-nasal disease. Recent research has addressed the role of probiotics in airway infection and inflammation, with a particular focus on identifying beneficial bacteria that can interfere with pathogenic bacteria common in chronic sinusitis and recurrent ear disease. Analysis of Professor Cervin's recent publications (2021-2025) reveals a strong focus on microbiome research (particularly probiotics like Lactobacillus), chronic rhinosinusitis , and otitis media . His work spans basic science (in vitro studies of bacterial interactions), clinical trials (probiotic interventions), and epidemiological studies (microbiota across seasons and populations). Notably, his research has increasingly focused on Indigenous health, examining the upper respiratory tract microbiome of Aboriginal and Torres Strait Islander children. Professor Cervin is actively involved in mentoring the next generation of researchers. He currently supervises a Master's student working on "Testing a sinonasal microbiome transplant as a therapy for Chronic Rhinosinusitis by randomised controlled trial" and previously supervised a PhD student who researched "The microbiome of otitis media and development of a probiotic to prevent otitis media in Indigenous Australian children." His research is supported by significant funding, including an NHMRC MRFF grant (2021-2026) for testing sinonasal microbiome transplants and the Garnett Passe and Rodney Williams Memorial Foundation Chair (2017-2027). Professor Cervin's research group focuses on developing novel treatments for chronic upper airway infections that could reduce antibiotic use and combat antibiotic resistance. Their work on identifying "friendly bacteria" that maintain health rather than targeting disease-causing pathogens represents a paradigm shift in treating upper airway infections.
Dr. Yilong Xu is an Associate Professor of Finance at the Utrecht School of Economics, Utrecht University. His work bridges Law, Economics, and Governance with a focus on Finance and multidisciplinary economics. Ph.D. in Economics, M.Sc. in Economics, Quantitative Finance, and Actuarial Science, and B.Sc. in Economics from Tilburg University. His research interests span Behavioral and Experimental Finance , Financial Decision-Making , Economic Inequality , and Ethics . He examines how psychological factors influence market behaviors, inequality perceptions, and social capital dynamics. Recent publications analyze cryptocurrency bubbles , emotion-driven environmental policies , reproducibility in finance , and behavioral public goods games . These works reflect his engagement with experimental methods, fairness, and cognitive biases. Dr. Xu teaches Multinational Corporate Finance and Next Generation Finance (Research Project) . His technical skills include Stata and MATLAB programming.
Giuseppe Durisi is a Professor at Chalmers University of Technology in Gothenburg, Sweden, specializing in information theory and communication systems. His research bridges mathematically rigorous solutions with practical engineering applications in wireless and optical communication. Primary affiliation: Communication Systems Group , Chalmers University. Research focus: Optimal information transmission, 6G network design, and theoretical foundations of deep learning. Research Interests: Durisi investigates the interplay between latency, reliability, and throughput in digital communication, particularly in millimeter-wave and optical fiber channels . He develops finite-blocklength theory for efficient coding and explores how information theory can explain deep learning performance. Recent Article Trends: His 2025–2024 work emphasizes 6G distributed MIMO networks , energy-harvesting protocols , and machine learning integration into communication theory. Key themes include random access protocols , privacy in wireless aggregation , and hardware-constrained massive MIMO . Scientific Recognition: An IEEE Senior Member, Durisi has published extensively in top journals like IEEE Transactions on Communications and IEEE Transactions on Wireless Communications . Notable Collaborations: Work with teams on radio-over-fiber fronthaul , unsourced multiple access , and time-synchronized URLLC links .
Prof. Dr. Ning Cai is a Visiting Professor at the Chair of Theoretical Information Technology at the Technical University of Munich (TUM). His research focuses on quantum communication, information theory, and secure communication systems. Key research areas include: Quantum channel capacity and coding Information-theoretic security Secure key generation with jamming Interference modeling in wireless networks Resource allocation in classical-quantum systems Compound and varying channel analysis His recent publications address challenges in classical-quantum channels with jammers, common randomness generation, and secrecy capacities in wireless systems. Collaborators include Prof. Holger Boche and other researchers at TUM.
Dr. Eleni Akrida serves as an Associate Professor in the Department of Computer Science at Durham University and holds the position of Deputy Executive Dean (Academic Student Experience) in the Faculty of Science. Since joining Durham in 2019, she has significantly contributed to academic leadership, including a term as Director of Undergraduate Studies from 2020 to 2025, shaping curriculum development and student experience across the department. Her academic foundation includes a Mathematics degree from the University of Patras, Greece, followed by Computer Science studies at the University of Liverpool, UK, establishing her interdisciplinary expertise in theoretical and applied computer science. Dr. Akrida's research bridges cutting-edge Computer Science education and theoretical algorithms. She pioneers pedagogical frameworks for abstraction skill development and investigates neurodivergent student experiences in CS education. Concurrently, her theoretical work explores probabilistic algorithms, graph complexity, and dynamic network optimization, yielding foundational insights in temporal graph theory and algorithmic game theory. Analysis of her publication trajectory reveals a strategic evolution: recent work (2023-2025) emphasizes educational innovation through frameworks for abstraction skills and neurodivergent inclusion studies, complemented by NLP contributions to plagiarism detection. Earlier research (2014-2021) established her authority in temporal graph algorithms, with seminal journal publications on connectivity, exploration, and game-theoretic models in dynamic networks. Her research impact is amplified through competitive grant funding: Exploring the Experiences of Neurodivergent Students in Computer Science Higher Education in the UK (CPHC Special Project, 2025/26) A Theoretical Computer Science Commons in the hybrid era (CPHC Special Project, 2022/23) Dr. Akrida actively mentors postgraduate researchers including Saira Richardson and leverages her leadership roles to drive educational innovation. She contributes to Durham's Pedagogical Innovations in Computer Science and Algorithms and Complexity research groups, fostering interdisciplinary collaborations that bridge theoretical rigor with practical educational applications.
Ingmar R. Prucha is a Distinguished University Professor in the Department of Economics at the University of Maryland, specializing in theoretical and applied econometrics with a focus on spatial and network dependencies. He holds a PhD in Mathematical Economics from the University of Technology, Vienna (1977), and a post-graduate degree from the Institute for Advanced Studies in Vienna. Key affiliations: University of Maryland (Distinguished University Professor) Editorial roles: Associate Editor of Econometric Theory, Journal of Econometrics, Regional Science and Urban Economics, and member of Letters in Spatial and Resource Sciences editorial board His research spans spatial econometrics, dynamic panel data models with cross-sectional interactions, robust estimation methods, and productivity analysis. He has developed frameworks for spatial autoregressive models, generalized moments estimators, and peer effects modeling. Recent publications focus on network-generated dependence testing higher-order spatial interactions in simultaneous equations sequential exogeneity in dynamic panels random group effects in peer effect estimation He has contributed extensively to Stata software commands for spatial econometric analysis. While no explicit awards are listed, his long-term editorial roles and methodological innovations suggest significant recognition in econometric theory and spatial modeling. His teaching includes advanced econometrics courses (ECON624, ECON722) and mentoring in productivity/estimation research.
Guido J. Falcone, MD, ScD, MPH is an Associate Professor of Neurology at Yale School of Medicine, where he serves as Academic Chief of the Division of Neurocritical Care, Director of Clinical Research in Neurocritical Care, and Training Director of the Yale/AHA Bugher Center for Intracerebral Hemorrhage Research. As a Neurointensivist, he specializes in treating critically ill patients with neurological injuries including stroke, hemorrhage, traumatic brain injury, and seizures. Dr. Falcone's educational background includes an MD from the University of Buenos Aires School of Medicine, a Neurology Residency at F.L.E.N.I., an MPH in Quantitative Methods from Harvard School of Public Health, an ScD in Epidemiology from Harvard School of Public Health, and a Neurocritical Care Fellowship at Harvard Medical School/Massachusetts General Hospital/Brigham and Women's Hospital. His research program bridges clinical neurology, neuroimaging, population genetics, and genomic medicine to understand how genetic variation influences stroke occurrence, severity, and outcomes. He employs genetic approaches to identify novel biological mechanisms, answer epidemiological questions, and develop precision medicine tools for risk stratification. Dr. Falcone maintains an active research program within the International Stroke Genetics Consortium, collaborating with investigators worldwide. An analysis of Dr. Falcone's most recent publications reveals a strong focus on stroke genetics, particularly examining how polygenic risk factors influence intracerebral hemorrhage, response to blood pressure management, and vascular risk factor control in stroke survivors. His work increasingly integrates multiple 'omics' approaches (genomics, proteomics, transcriptomics) to identify therapeutic targets for cerebrovascular disease and related conditions. Yale Office for Postdoctoral Affairs' Annual Mentorship Award (2024) Paul Dudley White International Scholar Award (2022) Michael S. Pessin Stroke Leadership Prize (2021) Get With The Guidelines (Stroke) Early Career Investigator Award (2020) American Society of Clinical Investigation Young Physician-Scientist Award (2020) Dr. Falcone serves as Principal Investigator for the ASPIRE trial (Anticoagulation for Stroke Prevention and Recovery After ICH) and is a Sub Investigator for multiple other clinical trials including BEACH, REDUCE, and BOOST3. He has secured significant grant funding through the American Heart Association and other organizations to support his research in stroke genetics and neurocritical care. His mentorship has been recognized with Yale's Postdoctoral Affairs Annual Mentorship Award, reflecting his commitment to training the next generation of physician-scientists. Dr. Falcone leads the Falcone Lab at Yale, which focuses on integrating genetic, neuroimaging, and outcomes data to identify novel therapeutic targets and precision medicine strategies for stroke and aging-related conditions. His team employs multidisciplinary approaches to understand how common and rare genetic variation influences stroke risk, severity, and recovery trajectories.
Alex John London is the K&L Gates Professor of Ethics and Computational Technologies at Carnegie Mellon University, where he directs the Center for Ethics and Policy and serves as Chief Ethicist at the Block Center for Technology and Society . He co-leads the K&L Gates Initiative in Ethics and Computational Technologies and is an elected Fellow of the Hastings Center . Research Focus: Ethical and policy challenges in AI, medicine, and biotechnology; cross-national justice in research; methodological rigor in theoretical and practical ethics. Key Contributions: Author of For the Common Good: Philosophical Foundations of Research Ethics (Oxford University Press, open access) and co-editor of the widely used textbook Ethical Issues in Modern Medicine . Served on WHO expert panels for AI governance, U.S. National Academy of Medicine committees, and contributed to international guidelines like the CIOMS Ethical Guidelines and Declaration of Helsinki revisions. Recent Awards: Fellow of the Hastings Center Leadership Roles: Ethics core co-leader for the NSF AI Institute for Collaborative Assistance and Responsive Interaction for Networked Groups (AI-CARING); program committee member for major AI ethics conferences (FAccT, AIES). Public Engagement: Active in shaping biosecurity policy through the U.S. National Science Advisory Board for Biosecurity (NSABB) and consulted for NIH, WHO, and World Bank.
Yanina Shkel is an Assistant Professor at École Polytechnique Fédérale de Lausanne (EPFL) in the School of Computer and Communication Sciences. She holds appointments in the Information Processing Group, SSC-ENS, and SIN-ENS departments, with her office located at INR 131. Her academic journey includes a PhD from the University of Wisconsin-Madison (2014), postdoctoral work at Princeton University and University of Illinois at Urbana-Champaign, and prior industry experience at Morningstar Inc. and 3M Corporate Research Labs. Her research spans theoretical aspects of data science with focus on information theory applications to privacy, secrecy, and data compression. Key areas include mathematical models for privacy-aware information processing, finite blocklength data compression, secret key generation from common randomness sources, and information-theoretic methods in cryptography. She employs tools from information theory, learning theory, coding theory, statistics, and cryptography in her work. Analysis of her recent publications reveals a strong trend toward privacy-preserving information processing, with maximal leakage emerging as a central metric across multiple applications including biometric security and data compression. Her work bridges theoretical foundations with practical applications in cryptography and secure information systems, demonstrating increasing focus on quantifiable privacy metrics and their fundamental limits. Swiss NSF Starting Grant Professor Shkel leads a research lab supported by the Swiss NSF Starting Grant, mentoring doctoral students including Coban Serhat Emre, Yadav Anuj Kumar, and Çadir Cemre. Her funding history includes the NSF Center for Science of Information Postdoctoral Fellowship during her postdoctoral research. She actively recruits PhD students through EPFL's EDIC program with emphasis on theoretical data science candidates. Her laboratory focuses on theoretical data science with particular emphasis on privacy-aware information processing systems, developing mathematical frameworks for quantifying and optimizing information leakage in various applications.
Felix Herrmann is a Professor at the Georgia Institute of Technology, holding a joint appointment between the Schools of Earth & Atmospheric Sciences, Computational Science & Engineering, and Electrical & Computer Engineering within the College of Computing. He leads the Seismic Laboratory for Imaging and Modeling (SLIM) and co-directs the Center for Machine Learning for Seismic (ML4Seismic). His research focuses on computational imaging, inverse problems, and machine learning applications in geophysics, particularly in seismic and medical imaging. Herrmann has pioneered innovations in compressive sensing for time-lapse seismic data acquisition, earning the SEG Reginald Fessenden Award in 2020. His work emphasizes Bayesian inference, uncertainty quantification, and scalable computational methods for subsurface monitoring, including carbon sequestration and reservoir characterization. Education: Ph.D. in Engineering Physics (Delft University of Technology, 1997), followed by postdoctoral roles at Stanford University and MIT before joining the University of British Columbia (2002). He transitioned to Georgia Tech in 2017 as a Georgia Research Alliance Eminent Scholar in Energy. Research Interests: Herrmann’s cross-disciplinary program integrates randomized linear algebra, PDE-constrained optimization, and high-performance computing. Key areas include digital twin technologies for subsurface monitoring, generative AI for geostatistical modeling, and scalable inversion algorithms (e.g., wavefield reconstruction inversion). His methodologies aim to reduce costs and improve reliability in seismic imaging and carbon storage monitoring. Scientific Contributions: Over 150+ peer-reviewed articles, including seminal work on compressive sensing in seismic acquisition and Bayesian experimental design. His software contributions include InvertibleNetworks.jl and Devito , advancing computational geophysics. Labs & Collaborations: Directs SLIM, fostering industry partnerships through ML4Seismic to develop AI-driven seismic imaging tools. Active in cloud-based scalable workflows and event-driven seismic imaging systems.
