Professor Thomas Astell-Burt is a Professor of Cities and Planetary Health at the University of Sydney's School of Architecture, Design and Planning. His work focuses on the intersection of urban environments, green spaces, and public health. He is a member of the Sydney Environment Institute and the Charles Perkins Centre. His research examines how urban planning and green infrastructure can mitigate health inequities, combat climate change, and improve mental/cardiometabolic health. Key areas include nature prescriptions, heat-related mortality, and the role of green spaces in reducing loneliness. Recent grants include projects on aged care workforce sustainability, nature-based strategies for loneliness reduction, and the PANDA Trial for cardiometabolic disease prevention. Over 180+ publications span peer-reviewed journals like Scientific Reports , Climate , and PloS One , with a focus on global health trends and urban environmental policies. His work bridges epidemiology, urban design, and interdisciplinary collaboration to inform evidence-based health policies. Key affiliations include leadership roles in global health initiatives and collaborations with institutions like the University of Glasgow. His research has been cited in policy frameworks addressing urban sustainability and planetary health.
Maizie Zhou is an Assistant Professor in Biomedical Engineering and Computer Science at Vanderbilt University’s School of Engineering. She holds dual PhDs in Computer Science (Stanford University) and Neuroscience (Wake Forest School of Medicine), with additional degrees from Wake Forest University and Huazhong University of Science and Technology. Her research focuses on computational genomics, bioinformatics, and machine learning applied to problems in cancer genomics, single-cell and spatial transcriptomics, and computational neuroscience. She leads the Zhou Lab, which develops algorithms for structural variant detection, neural circuit analysis, and integrative omics approaches. Recent work includes tools like VolcanoSV and stDyer, and she has received grants from NIH, Vanderbilt Brain Institute, and industry partnerships. Key achievements include VUSE Best Paper Awards, Global Engagement Travel Grants, and mentoring students in prestigious programs like the Provost’s Pathbreaking Discovery Award. Her lab also explores the neural underpinnings of cognitive maturation in primates, combining computational and experimental neuroscience. Education: PhDs in Computer Science (Stanford) and Neuroscience (Wake Forest), MS (Computer Science, Wake Forest), BS (Biotechnology, Huazhong). Research interests span computational genomics (e.g., structural variant detection, haplotype phasing), spatial transcriptomics (clustering, integration), and computational neuroscience (neural circuit dynamics, prefrontal cortex plasticity). Her lab’s tools address challenges in precision medicine, cancer genomics, and understanding adolescent brain development. Recent projects include NIH-funded work on spatial transcriptomics and collaborations with Dr. Meltzer’s lab on cancer genomics. Publications highlight advancements in bioinformatics tools and neural mechanisms, with trends toward multi-omics integration and algorithmic innovation in genomics. Awards include the Global Engagement Travel Grant and CCSB Accelerator Fund. Students under her mentorship have excelled in qualifying exams and travel grants, reflecting her impactful training program.
Marcelo Mattar is an Assistant Professor of Psychology and Neural Science at New York University, leading the Mattar Lab. His research focuses on the neural computations underlying memory, decision-making, and reinforcement learning. He holds a Ph.D. in Psychology from the University of Pennsylvania and has held academic positions at NYU, UC San Diego, and postdoctoral roles at Princeton University and the University of Cambridge. His work bridges computational neuroscience and artificial intelligence, aiming to model how the brain uses internal models for planning and decision-making. Education: Ph.D. in Psychology (Computational and Cognitive Neuroscience), University of Pennsylvania, 2016 M.A. in Statistics, University of Pennsylvania, 2016 B.A. in Electronics Engineering, Instituto Tecnologico de Aeronautica, Brazil, 2010 Research Interests: The lab develops mathematical models of learning and decision-making, leveraging reinforcement learning, Bayesian statistics, and neural networks. Experiments involve human behavioral studies and neuroimaging, with collaborations in animal electrophysiology and computational psychiatry. Key Contributions: His work explores how episodic memory and hippocampal replay support flexible decision-making. Recent studies highlight parallels between human cognition and AI systems, such as language models' metacognitive abilities and brain-inspired algorithms. Awards: Newton International Fellowship, Royal Society (2018–2019) Lab Team: The lab includes postdocs, PhD students, and undergraduates from diverse fields like cognitive science, neuroscience, and computer science. Current members are listed on the lab's website. Lab Location: Meyer Hall, 6 Washington Place, New York, NY 10003.
Aviv Nevo is the George A. Weiss and Lydia Bravo Weiss University Professor at the University of Pennsylvania, holding joint appointments in the Department of Economics (School of Arts and Sciences) and the Marketing Department at the Wharton School. His research focuses on empirical industrial organization, antitrust economics, marketing, and econometrics, with applications to consumer packaged goods, healthcare, telecom, and real estate. Nevo earned his Ph.D. (1997) and AM (1994) in economics from Harvard University and a BSc in mathematics and economics from Tel Aviv University (1991). He joined Penn through the Penn Integrates Knowledge (PIK) program, which recognizes scholars who bridge disciplines. His work has examined price competition, merger implications, and regulatory policy, with notable contributions to understanding market dynamics in digital platforms and telecommunications. Nevo serves as a fellow of the Econometric Society, a research associate at NBER, and co-editor of Econometrica and the RAND Journal of Economics . Nevo’s research interests span antitrust analysis, consumer behavior, and applied econometrics. His recent studies address issues such as steering incentives in telecom gatekeepers, substitution effects in streaming media, and the misuse of economic metrics in merger reviews. He has advised on high-profile cases, including the Sabre/Farelogix and Aetna-Humana mergers, integrating empirical rigor into policy debates. Awards: Fellow of the Econometric Society, NBER Research Associate, Institute for Fiscal Studies International Fellow. Editorial Roles: Co-editor of Econometrica and RAND Journal of Economics . Professional Activities: PIK University Professor, Penn Integrates Knowledge initiative participant. Nevo’s work bridges academia and policy, with a focus on real-world applications of economic theory. His teaching spans both economics and marketing disciplines, reflecting his dual departmental affiliation.
Jennifer Lynes is an Associate Professor at the University of Waterloo in the Department of Environment and Business, where she co-directs the Sustainability & Financial Management program. She also serves as Chair of REEP Green Solutions and co-founded the North American Sustainable Concerts Working Group. Current roles: Associate Professor, Co-Director (Sustainability & Financial Management), REEP Green Solutions Chair Education background: Marketing and Environmental Studies Her research bridges business and environmental sustainability, focusing on: Social and community-based green marketing Youth environmental engagement programs Residential energy conservation behavior Sustainable tourism and hospitality practices Recent publications analyze: Water efficiency programs and behavioral change Electric vehicle adoption strategies Textile waste management in fashion consumption Sustainable eating behaviors in Canadian universities Scientific recognition includes: Emerald Publishing Group Highly Commended Paper (2014) She teaches courses such as: ENBUS 102: Introduction to Environment and Business ENBUS 309: Applied Social Marketing ENBUS 630: Enterprise Strategies for Social Accountability
Nancy Kass is a Professor in the Department of Health Policy and Management at the Johns Hopkins Bloomberg School of Public Health, where she also holds the Phoebe R. Berman Professorship in Bioethics and Public Health. She serves as Vice Provost for Graduate and Professional Education at Johns Hopkins University and is the Interim Chair of the Department of Health Policy and Management. Additionally, she is Deputy Director for Public Health at the Johns Hopkins Berman Institute of Bioethics and co-directs the Johns Hopkins Fogarty African Bioethics Training Program. ScD, Johns Hopkins University, 1989 BA, Stanford University Postdoctoral Fellowship, Kennedy Institute of Ethics, Georgetown University Dr. Kass’s research focuses on the ethical dimensions of public health policy and research, with particular expertise in bioethics, research ethics, public health ethics, informed consent, learning health systems, and global health ethics . Her work addresses ethical challenges in HIV/AIDS, obesity prevention, genetics, and international research. She has developed influential frameworks for ethical oversight in public health and clinical research. Her recent publications (2024–2025) reflect a strong focus on modernizing clinical research ethics, including optimizing informed consent, integrating clinical trials with medical practice, and enhancing data infrastructure. These works emphasize ethical governance, patient-centered decision-making, and the alignment of research with real-world healthcare delivery. Her scholarship spans high-impact journals such as JAMA and Implementation Science , demonstrating sustained scholarly leadership. GBFFR Annual Award, Global Forum on Bioethics in Research, 2016 Member, National Academy of Medicine (formerly Institute of Medicine), 2008 Fellow, Hastings Center, 2007 Delta Omega Honorary Society in Public Health, 1996 AMTRA (Advising, Mentoring, and Teaching Award), Johns Hopkins, 1996 Dr. Kass has played a pivotal role in education and mentorship, having directed the PhD program in Bioethics and Health Policy for 15 years. She currently leads the Fogarty-funded African Bioethics Training Program, advancing global bioethics capacity. She has served on numerous national and international advisory bodies, including the National Cancer Institute’s central IRB, the National Academy of Medicine, and the WHO Ethics Review Committee. Her leadership extends to chairing the national Precision Medicine Initiative central IRB. She is actively involved in research projects such as the CDC Informed Consent Project, Bioethics of Quality Improvement, and Demonstrating Respect and Acceptable Consent Strategies in patient-centered outcomes research. These initiatives underscore her commitment to ethical innovation in public health and clinical practice.
Prof. Dr. Gert-Ludwig Ingold is a Professor of Theoretical Physics at the Institute of Physics, Faculty of Mathematics, Natural Sciences, and Materials Engineering, University of Augsburg. His research spans multiple areas of theoretical physics with emphasis on quantum phenomena in nanoscale systems. His work on the Casimir effect explores interactions between various geometries including spheres, plates, and dielectric materials, with applications in nanotechnology and biophysics. His research on dissipative quantum systems investigates thermodynamic anomalies and quantum Brownian motion. In mesoscopic physics, he studies charge transport through nanoscale structures and quantum interference effects. His work on quantum systems in phase space connects classical and quantum dynamics, while his semiclassical research examines quantum revival patterns and phase-space trajectories. Prof. Ingold's publications reveal a strong focus on the Casimir effect, with numerous papers examining interactions between different geometries and materials. His work demonstrates expertise in both theoretical modeling and numerical methods, as evidenced by his development of the CaPS software for Casimir effect calculations. He frequently collaborates with international researchers, particularly with Paulo A. Maia Neto, Tanja Schoger, and Benjamin Spreng. Prof. Ingold has made significant contributions to physics education through textbooks and popular science books, including Quantentheorie: Grundlagen der modernen Physik and Die 101 wichtigsten Fragen: Moderne Physik . He has co-authored the Python-based educational resource Numerische Physik mit Python and maintains extensive online teaching materials including lecture notes and video tutorials.
Olof Bälter is a Professor in Computer Science at KTH Royal Institute of Technology, affiliated with the Division of Media Technology and Interaction Design within the School of Electrical Engineering and Computer Science. He is the founder of the Technology-Enhanced Learning research group and holds a focus on learning engineering and human-computer interaction. His research interests center on technology-enhanced learning , question-based learning , learning analytics , AI in education , and inclusive pedagogy . A consistent theme in his work is improving efficiency in education and daily life through digital tools. He developed the Pure Question-Based Learning (Pure QBL) methodology, a digital Socratic approach that enhances student engagement and learning outcomes. His work extends to wellness in education through initiatives like walking seminars, and he investigates digital interventions for mental health, such as online Cognitive Behavioral Therapy (CBT) courses. His recent publications highlight trends in AI-generated educational content , learning efficiency , digital pedagogy , and inclusive course design , with applications in computer science education, language instruction, and global development. His research often employs experimental and data-driven methods, including randomized controlled trials and learning analytics. Teacher of the Year at the Surveying program KTH's Pedagogical Prize Higher Education Hero STINT Excellence in Teaching Scholarship (2008 and 2013) Olof Bälter has supervised numerous courses in programming, computer science, media technology, and learning engineering. He has collaborated with institutions such as Stanford University, Williams College, Region Stockholm, Stockholm University, and organizations like Promobilia and Begripsam. His projects aim to scale effective learning methods globally and make education more accessible and efficient. He leads research on the effectiveness of Pure QBL for students with ADHD and is involved in developing digital tools for health literacy and professional development in Ethiopia and Rwanda. His work bridges theory and practice, aiming to transform educational delivery through innovation and evidence-based design.
Yashar Ganjali is a Professor in the Department of Computer Science at the University of Toronto , leading the Systems and Networking Group . His research spans computer networks , with a focus on data center networking , software-defined networking (SDN) , and congestion control . Education : Not explicitly detailed, but inferred from academic rank as a Professor. His work on flow consolidation , load migration in SDN controllers , and machine learning for network management has been influential. Recent projects include FORESIGHT (2025) for ML-driven scheduling and Meta-Migration (2023) to reduce switch migration latency. Scientific Awards include the IFIP Networking 2025 Best Paper Award . Collaborations with institutions like Google (2024) and Facebook (2019) highlight his industry impact. Advisees include Sepehr Abbasi Zadeh (PhD, 2024). Current projects integrate optical packet switching and eBPF-based network augmentation , aiming to address scalability, micro-bursts, and resource allocation efficiency in cloud environments.
Dr. Eiko Fried is an Associate Professor at Leiden University's Faculty of Social and Behavioural Sciences, where he works at the intersection of clinical psychology, psychiatry, epidemiology, methodology, and complexity science. His research focuses on improving psychological science through open science practices and innovative measurement approaches. PhD in clinical psychology, Free University of Berlin Postdoctoral training at KU Leuven and University of Amsterdam Promoted to Associate Professor at Leiden University in 2021 Key research areas include: Psychopathology measurement and classification Network analysis in mental health research Ecological momentary assessment (EMA) methodology Open science advocacy and implementation Dynamic systems modeling in psychology Transdiagnostic approaches to mental disorders Recent publications demonstrate expertise in: Symptom network analysis across disorders Improving depression measurement standards Transdiagnostic assessment protocols Mental health data integration challenges Psychological theory construction Methodological innovations in clinical research
Sherry Tongshuang Wu is an Assistant Professor at Carnegie Mellon University's School of Computer Science, with primary appointments in the Human-Computer Interaction Institute (HCII) and secondary affiliation with the Language Technology Institute (LTI) . Trained at the University of Washington under Jeffrey Heer and Dan Weld, she bridges HCI and NLP to study human interactions with AI systems across diverse user groups. Her educational background includes a Ph.D. (2016-22) and M.S. (2016-18) in Computer Science and Engineering from the University of Washington, and a B.Eng. (2012-16) from Hong Kong University of Science and Technology. Industry experience includes research internships at Google Brain, Microsoft Research, and Apple. Wu's research focuses on three interconnected pillars: Real-world AI Evaluation (developing frameworks like SPHERE for systematic assessment), Task-specific AI Test & Distill (optimizing general-purpose models for specific use cases), and Human-AI Task Delegation (designing optimal collaboration between humans and AI). Her work emphasizes practical deployment, user-specific net gains, and error recovery mechanisms. Analysis of her 15 most recent publications reveals a strong trend toward evaluation frameworks (35%), human-AI collaboration systems (30%), and specialized model distillation (25%), with growing emphasis on educational applications (10%). Key methodological themes include checklist-based evaluation, perspective-aware retrieval, and structural analysis of AI outputs. Google Academic Research Award (2024) Amazon Research Awards (2024) AIED 2024 Best Paper Award ACL 2020 Best Paper Award Rising Stars in EECS Workshop (2020) Wu actively mentors 19 students across PhD, Master's, and undergraduate levels, with notable projects including synthetic data generation, LLM literacy tools, and retrieval system optimization. She leads significant grant-funded work through Amazon Research Awards and Google Academic Research Awards, focusing on deployable model generation and human-AI collaboration frameworks. Her lab develops practical tools like Promp2Model and SPHERE that bridge theoretical research with industry applications.
Dr. Edouard Boujo is a Scientist and Lecturer at the Swiss Federal Institute of Technology Lausanne (EPFL) , affiliated with the School of Engineering (STI) and working in the Institute of Mechanical Engineering (IGM) and Laboratory of Fluid Mechanics and Instabilities (LFMI) . He also teaches in the SGM-ENS department of the School of Engineering. Scientist at EPFL STI IGM LFMI Lecturer at EPFL STI-SGM SGM-ENS His research focuses on Fluid Dynamics with expertise in Flow Stability , Flow Control , Aeroacoustics , Thermoacoustics , Fluid-Structure Interaction , and Coating Flow Dynamics . He employs advanced mathematical modeling and computational methods to study complex fluid behaviors. Recent publications highlight his work on stochastic modeling of fluid instabilities, adjoint-based optimization of flow systems, and nonlinear dynamics of coating flows. His 15 most recent papers cover topics ranging from symmetry-breaking bifurcations to spin coating optimization and noise-induced transitions in fluid systems. Dr. Boujo actively collaborates with institutions across Europe and New Zealand, mentoring PhD student Atharva Lagwankar . He has received research funding from the Swiss National Science Foundation for two PhD theses and contributes to major fluid dynamics conferences like the European Fluid Dynamics Conference and APS Division of Fluid Dynamics meetings. His laboratory work at LFMI involves experimental and computational studies of fluid instabilities, with applications in aerospace, mechanical engineering, and industrial coating processes. He develops adjoint-based control methods for optimizing flow systems and reducing drag in various fluid configurations.
Dr. George Cantwell is an Assistant Professor in the Department of Engineering at the University of Cambridge, affiliated with Cambridge Infectious Diseases. He specializes in computational methods for inference problems, particularly in disease spreading across networks. Education: PhD in Physics from the University of Michigan; postdoctoral fellowship at the Santa Fe Institute His research focuses on network science , complex systems , and statistical inference , with an emphasis on computational approaches. His work spans theoretical and applied domains, including: Message passing algorithms for heterogeneous networks Bias correction in social network analysis (friendship paradox) Statistical inference of network structure from noisy data Modeling judicial voting behavior through network interactions Computational cognitive neuroscience of category learning Recent publications highlight interdisciplinary applications in epidemiology, physics, and cognitive science. He actively mentors students in networks, complex systems, and statistical inference.
Ali Abbas is a Senior Researcher and Methods Fellow at the MRC Epidemiology Unit within the University of Cambridge's School of Clinical Medicine. His academic background includes a PhD in Computer Science from Manchester Metropolitan University, an MSc in Media Informatics from RWTH Aachen University, and a BS in Computer Science from Mohammad Ali Jinnah University. With over two decades of research experience, he specializes in data-driven approaches including exploratory analysis, statistical modelling, and interactive visualization. His core research focuses on developing environmentally sustainable transport systems with positive public health outcomes, particularly through: Agent-based modeling of transport behaviors Cycling infrastructure and active travel interventions Health impact assessment of urban mobility policies Spatial analysis using GIS technologies Complex systems approaches to public health He leads several major research initiatives including the JIBE project (integrating transport and built environment models), GLASST (global health impact assessment), TIGTHAT (integrated global transport-health tool), National Propensity to Cycle Tool, and Impacts of Cycling Tool. His publication portfolio demonstrates consistent focus on transport-health interactions, physical activity epidemiology, and urban health modelling, with recent work emphasizing policy applications and global scalability. As an advocate for open science, he maintains active GitHub repositories of his computational models. He additionally manages junior researchers and contributes to training initiatives within his unit.
Brad Knox is a Research Associate Professor in the Department of Computer Science at the University of Texas at Austin . His work bridges machine learning, human-computer interaction, and computational cognitive science, with a focus on developing systems that learn from human feedback. Key research areas: Reinforcement Learning, Human-AI Interaction, Reward Design, Autonomous Systems Notable contributions: TAMER framework for human-guided learning, empirical studies on reward misdesign, and human preference modeling for autonomous agents Research Trends : His recent work (2023-2025) emphasizes reward alignment, safety in autonomous systems, and preference-based learning frameworks. Earlier studies (2012-2020) established foundational methods for integrating human feedback into reinforcement learning architectures and exploring behavioral signatures in decision-making. Scientific Honors : Bert Kay Dissertation Award (2013) Victor Lesser Distinguished Dissertation Award (IFAAMAS, Runner-up, 2013) NSF SBIR Grant (PI, 2016) NSF Graduate Research Fellowship (2008-2011) IEEE Intelligent Systems AI 10 to Watch (2013) Teaching & Leadership : Knox served as Principal Lecturer for MIT's Interactive Machine Learning course (2013) and held organizational roles at major conferences including Reinforcement Learning Conference (Scheduling Chair, 2025) and RLDM workshop (Co-chair, 2022).
