Max Lau is an Assistant Professor in the Department of Biostatistics and Bioinformatics and the Department of Epidemiology at Emory University. His research focuses on integrating machine learning and computational methods with epidemiological and genomic data to study infectious disease dynamics. He teaches courses such as BIOS 790R (Advanced Seminar in Biostatistics) and DATA 534 (Applied Machine Learning). Dr. Lau's work emphasizes scalable Bayesian inference, graph neural networks, and stochastic modeling to address challenges in disease transmission, outbreak control, and pathogen evolution. His recent research includes developing tools like ScITree and Epilearn, and he has contributed to understanding measles dynamics, tuberculosis treatment, and livestock disease management. His academic contributions span over 30 publications since 2010, with a particular focus on phylodynamics, epidemic modeling, and vaccine strategy evaluation. His interdisciplinary approach bridges computational methods with public health applications, aiming to enhance disease prediction and intervention efficacy.
Stanislaw Jarecki is an Associate Professor of Computer Science at the Donald Bren School of Information and Computer Sciences (ICS) at the University of California, Irvine (UCI). He joined UCI in 2003 after earning his Ph.D. in Computer Science from MIT in 2001 under Prof. Shafi Goldwasser. His research focuses on applied and distributed cryptography, with significant contributions to threshold cryptography, secure computation, and password-authenticated key exchange (PAKE) protocols such as OPAQUE, which secures 2 billion WhatsApp users. He also worked at Intertrust’s StarLab and Stanford’s applied cryptography group under Prof. Dan Boneh. Education: Ph.D., Massachusetts Institute of Technology, 2001. Research Interests: Distributed cryptography, secure multi-party computation, privacy-preserving protocols, threshold security, blockchain applications, and efficient cryptographic primitives. His work emphasizes practical solutions for real-world systems, including protocols resilient to server compromises and scalable encryption methods. Awards: 2023 IACR Fellow for contributions to distributed cryptography and efficient secure computation. Advising and Grants: Jarecki’s research has been supported by grants including NSF SaTC programs. He advises students on cryptographic protocol design and security mechanisms. His work on OPAQUE and CHIC protocols exemplifies his focus on bridging theoretical cryptography with practical implementation. Labs/Teams: Leads a research group focused on applied cryptography and security within ICS at UCI, collaborating on projects like secure computation, privacy-preserving data processing, and cryptographic protocol development.
Mohammadreza Karamad is an Assistant Professor in the School of Sustainable Energy Engineering at Simon Fraser University (SFU), with a joint appointment in the Sustainable Energy Engineering department. His research focuses on computational materials discovery, leveraging quantum-mechanical methods (e.g., DFT) and machine learning (ML) to design advanced energy materials for clean technologies like hydrogen storage and catalysis. He holds a Ph.D. from the Technical University of Denmark (DTU) and completed postdoctoral research at Stanford University. His academic background includes leadership roles in the CMD Lab (Computational Materials Discovery), where he explores novel materials for electrochemical energy conversion processes. Key research areas include electrochemistry, heterogeneous catalysis, and material science, with a particular emphasis on CO2 reduction, ammonia synthesis, and sustainable energy storage solutions. Dr. Karamad collaborates with industry and academic partners to advance materials discovery through high-throughput computational screening and AI-driven approaches. He actively seeks motivated students (undergraduate and graduate) to join his research program, focusing on developing next-generation energy materials. His lab is located in room B8220, and he can be reached at mkaramad@sfu.ca. Notable technical contributions include pioneering work on transition metal nitrides for CO2 reduction, single-atom catalysts for ammonia synthesis, and machine learning frameworks for predicting material properties. His research bridges fundamental theory with practical applications, addressing global challenges in sustainable energy and environmental technology.
Associate Professor Steven Lu is a faculty member at the University of Sydney Business School, serving as Deputy Head of Discipline (Education). He holds a PhD in Marketing from the University of Toronto, an MA in Economics from York University, and a BA from Nankai University. His research focuses on quantitative modeling, machine learning, and big data analytics applied to digital economy challenges such as digital retailing, search advertising, and blockchain. He co-directs the Consumer Insights Research Group and is affiliated with the Sydney Institute of Agriculture. Dr. Lu has published in top journals including Marketing Science , Production and Operations Management , and Journal of Retailing . His awards include the CNS Vithala Rao Award, ANZMAC Best Paper Awards (2022-2024), and the 2021 Vice Chancellor's Teaching Award. He teaches courses on machine learning in marketing, marketing research, and new product development. He leads research grants such as 'The Era of Mobile Payment' (2021) and 'Digital Transformation of Food Sensory Quality' (2017). His advising focuses on topics like neural recommender systems, e-coupon effectiveness, and heterogeneous treatment effects analysis.
Ran Spiegler is a Professor of Economics at both Tel Aviv University and University College London (UCL). He holds a PhD in Economics from Tel Aviv University (1999). His research focuses on economic theory, behavioral economics, and bounded rationality, with notable contributions to understanding decision-making under flawed causal reasoning, narrative-driven political and economic dynamics, and market behaviors influenced by limited consumer rationality. Spiegler has held roles including Member at the Institute for Advanced Study (Princeton, 2000-2001) and Prize Research Fellow at Nuffield College, Oxford (1999-2000). Education: PhD in Economics, Tel Aviv University (1999) Affiliations: Professorships at Tel Aviv University (2009–present) and UCL (2006–present) Research Interests: Spiegler’s work explores how bounded rationality shapes economic outcomes, including consumer decision-making, market competition, and the role of narratives in political mobilization. He has authored influential books like Bounded Rationality and Industrial Organization (2011) and The Curious Culture of Economic Theory (2024), which critique and expand economic theory’s methodologies. Recent Articles: His recent work examines topics such as false narratives in politics, monopolistic data practices, and competitive markets with imperfectly discerning consumers. These studies highlight interdisciplinary applications of economic theory to modern challenges like algorithmic transparency and platform economics. Awards: Prize Research Fellow, Nuffield College, Oxford (1999–2000) Grants & Labs: While specific grants are not detailed, his research is funded through institutional affiliations. He collaborates widely, with notable co-authors like Kfir Eliaz and Yair Antler.
Donald Rio holds the Richard and Rhoda Goldman Distinguished Chair in the Biological Sciences and is a Professor of Biochemistry, Biophysics, and Structural Biology. He is affiliated with the Division of Biochemistry and Molecular Biology and the Center for Integrative Genetics. His lab focuses on nucleic acid transactions, including transposable element mobilization (P elements) and RNA binding protein mechanisms controlling alternative splicing. Research highlights include studies on THAP9 proteins in humans/zebrafish, cryo-EM structural analysis of transposase-DNA complexes, and splicing regulation in neurodegenerative diseases like ALS and Parkinson’s. His work combines biochemical, genetic, and computational approaches, including the development of the Junction Usage Model (JUM) for splicing analysis. Research interests span transposition mechanisms linked to HIV integration, immune system recombination, and evolutionary genome dynamics. His team investigates how RNA binding proteins like hnRNPA1 influence splicing in disease contexts, with projects involving CRISPR-based models and patient RNA-seq data analysis. Collaborations include studies on splicing accuracy across tissues and age, and the impact of splicing defects in neurodegenerative disorders. Key awards include the Goldman Chair. His lab’s contributions bridge fundamental molecular mechanisms with translational applications in genetic disease modeling and drug discovery. Recent work focuses on isogenic stem cell models (iSCORE-PD) for Parkinson’s research and structural biology insights into transposase function. Grants and projects involve NIH funding for ALS splicing studies and collaborations with institutions like the Buck Institute. His lab actively publishes in top journals such as Genome Research , PNAS , and Nature , with a strong emphasis on cryo-EM and bioinformatic methods.
Christoph Bostedt holds dual appointments as a Professor of Physical Chemistry at the Ecole Polytechnique Fédérale de Lausanne (EPFL) and as Head of the Laboratory for Synchrotron Radiation and Femtochemistry (LSF) at the Paul Scherrer Institut (PSI). He leads strategic operations for the LSF, managing five research groups and overseeing four beamlines at the Swiss Light Source and the Alvra Endstation at SwissFEL. His research focuses on ultrafast x-ray science, including single-shot imaging, non-linear x-ray spectroscopy, and femtosecond pump-probe techniques. He collaborates globally on initiatives like the Athos project, aiming to advance ultrafast x-ray technologies. Bostedt has over 150 publications and is a Fellow of the American Physical Society, recipient of the Röntgen Prize. Education: Ph.D. from the University of Hamburg with research at Lawrence Livermore and Berkeley National Laboratories. Prior roles include leadership at Argonne National Laboratory and SLAC National Accelerator Laboratory. Research Interests: Single-particle imaging and coherent diffraction X-ray free-electron laser applications Ultrafast dynamics in nanoparticles and molecular systems Non-linear x-ray spectroscopy Time-resolved x-ray pump-probe methods Awards: Fellow of the American Physical Society Röntgen Prize (University of Giessen) Labs & Projects: Spearheads the Athos beamline project at SwissFEL, developing the Maloja endstation for ultrafast x-ray studies. Oversees the Laboratory for Femtochemistry and collaborates on advanced imaging techniques for nanoscale science.
Vera Liao is a Principal Researcher at Microsoft Research, where she is part of the FATE (Fairness, Accountability, Transparency, and Ethics of AI) group. She will join the University of Michigan Computer Science and Engineering department as an Associate Professor in fall 2025. Her work focuses on human-AI interaction, explainable AI, and responsible computing. Liao has made significant contributions to IBM products such as AI Explainability 360 and Uncertainty Quantification 360 during her time at IBM T.J. Watson Research Center. Dr. Liao received her education from the University of Illinois at Urbana-Champaign and Tsinghua University. Her academic journey has positioned her at the intersection of human-computer interaction and artificial intelligence, with a strong emphasis on creating AI systems that are transparent, accountable, and user-centered. Vera Liao's research primarily centers around human-centered AI explainability and transparency. She investigates how to design AI systems that effectively communicate their capabilities, limitations, and decision-making processes to users. Her work examines the intersection of AI transparency with trust, control, and user experience. Liao has pioneered approaches to bridging the socio-technical gap in AI evaluation and has developed frameworks for contextualized evaluation of explainable AI systems. Her research spans multiple domains including conversational interfaces, data storytelling, and creative work with generative AI. Liao's publications reveal a clear trend toward addressing the challenges of large language models and their impact on human-AI interaction. Her recent work focuses on understanding how uncertainty communication affects user trust, how to design for appropriate reliance on AI systems, and how to create authentic co-creation experiences with generative models. She has been examining the risks in AI-infused information ecosystems and developing methods for human-centered evaluation of language technologies. Her scientific contributions have been recognized with multiple honors: Best Paper Award, Honorable Mention at CHI 2025 (two papers) Best Paper Award at CHI 2024 Best Paper Award, Honorable Mention at FAccT 2023 Best Paper Award, Honorable Mention at HCOMP 2022 Best Paper Award, Honorable Mention at CHI 2021 Best Paper Award, Honorable Mention at CHI 2014 Outstanding Paper Award at IUI 2019 Dr. Liao is an active mentor, having guided numerous research interns from top universities including Cornell, Princeton, CMU, Stanford, and MIT. She serves in editorial roles as Co-Editor-in-Chief of the Springer Human-Computer Interaction Book Series and as an Editor for ACM CSCW. Liao has secured research funding through her work at Microsoft Research and previously at IBM, focusing on projects related to AI explainability, transparency, and responsible AI development. As part of Microsoft Research's FATE group, Liao collaborates with a multidisciplinary team of researchers focused on the ethical implications of AI technologies. Her work bridges the gap between technical AI development and human-centered design principles, ensuring that AI systems are developed with user needs and societal impacts in mind.
Kingsley Fong is an Associate Professor of Finance at the UNSW Business School , specifically within the School of Banking and Finance . He holds a PhD from the University of Sydney and a BCom (Hons) from UNSW. His research focuses on market microstructure , investment , household finance , and sustainable finance , and he co-founded the RISE Finance Lab to explore finance's role in societal well-being. He also developed the DATKIS framework for systemic coherence in financial practices. Research Interests : Market microstructure, household finance, sustainable finance, and empirical finance. Teaching : Courses such as WEALTH MANAGEMENT AND CLIENT ENGAGEMENT , SUSTAINABLE INVESTING , and SUSTAINABLE FINANCE . Key Trends in Research : His work spans liquidity proxies, algorithmic trading impacts, broker-client dynamics, and sustainable finance innovations. Notable collaborations include studies on market quality, tax-driven trading, and household investment behavior. Scientific Awards : 2017 Review of Finance Spängler IQAM Prize 2021 Aspen Institute Ideas Worth Teaching Award 2022 S&P Global Decarbonisation Hackathon Engagement : Co-Founder of UNSW RISE Finance Lab (2025) Australian Sustainable Finance Institute Reference Group (2024) Deputy Head of School Banking and Finance (2011–2019) Contact : k.fong@unsw.edu.au | Location : UNSW Business School, Ref E12, Level 3, Room 344B.
Dr. Leon Barron is a Reader in Analytical & Environmental Sciences at the School of Public Health, Imperial College London. His expertise spans chemical contaminant analysis, wastewater epidemiology, and environmental forensics. He leads the Emerging Chemical Contaminants team within the Environmental Research Group, focusing on pharmaceuticals, PFAS, and illicit drugs. Education: BSc(Hons) in Analytical Science (2001), PhD in Analytical Chemistry (2005), and a Postgraduate Certificate in Academic Practice (2011). Previously held roles at King's College London as Lecturer (2009–2015) and Senior Lecturer (2015–2020). Research interests include trace environmental analysis (LC, GC, MS), chemical risk assessment, and wastewater-based epidemiology. Key projects include global drug use monitoring via sewage analysis and PFAS removal from drinking water. His work has produced over 100 peer-reviewed articles, with recent focus on PFAS accumulation, biochar filtration, and urban pollution source apportionment. Awards include Fellowships from Royal Society of Chemistry and Chartered Society of Forensic Sciences. Supervises PhD students on topics like pesticide exposure, opioid monitoring, and machine learning in ecotoxicology. Collaborates internationally via initiatives like the Sewage Analysis CORE Group and NIHR HPRU in Environmental Exposures.
Professor Libby Porter is a leading academic and researcher in urban planning and human geography at RMIT University, Australia. As Director of the Centre for Urban Research (CUR) and Professor in the School of Global, Urban and Social Studies (GUSS), her work focuses on critical urban governance, decolonising planning practices, Indigenous rights, and urban displacement. She holds a prestigious position as a Fellow of the Higher Education Academy and has contributed extensively to international policy debates through her role as Assistant Editor for Planning Theory and Practice . Her research examines settler-colonial dynamics in urban development, public housing policy, and the intersection of planning with Indigenous sovereignty. Notable publications include Unlearning the Colonial Cultures of Planning (2010) and Planning in Indigenous Australia (2018). Libby has held academic roles in the UK and Australia and previously worked in urban planning policy for Victorian Government departments. She supervises students in Honours, Masters, and PhD programs, focusing on topics like Indigenous housing, urban displacement, and environmental policy. Her work has been featured in The Conversation , BBC News, and academic journals. Libby also leads the Critical Urban Governance Research Program and oversees the Bachelor of Urban and Regional Planning at RMIT. Awards: Fellow of the Higher Education Academy Key Roles: Director, Centre for Urban Research; Co-founder, Planners Network UK; Member, Expert Advisory Panel for Melbourne 2030 Research Themes: Property rights, urban sustainability, decolonisation, Indigenous planning, gentrification
Bertram Müller-Myhsok is a Research Professor and Research Group Leader at the Max Planck Institute of Psychiatry in Munich, Germany. His research focuses on statistical genetics and transcriptomic data analysis in psychiatric disorders, particularly major depression, PTSD, schizophrenia, and their treatment responses. He integrates machine learning with genetic and clinical data to develop predictive models and stratified treatment approaches. Professional activities include leadership roles in the International Max Planck Research School for Translational Psychiatry and collaborations with institutions like the Institut du Cerveau (Paris) and Bernhard Nocht Institute (Hamburg). His work spans genetic epidemiology, psychiatric genomics, and precision medicine, with over 400 publications in high-impact journals. Key research areas include identifying genetic risk factors for mental disorders, developing polygenic scores, and leveraging omics data to uncover disease mechanisms. He leads projects like Psych-STRATA, a Horizon Europe-funded initiative advancing personalized psychiatry through pharmacogenomics.
Song Ma is a Professor of Finance and Entrepreneurship at Yale School of Management and a Faculty Research Fellow at the National Bureau of Economic Research (NBER). He is also an affiliated faculty member at Yale Law School Center for the Study of Corporate Law and Yale SOM Program on Entrepreneurship, having joined Yale SOM Faculty in 2016. His educational background includes: PhD in Finance from Duke University's Fuqua School of Business (2016) BA in Economics from Zhejiang University (2010) Professor Ma's research primarily focuses on innovation economics, entrepreneurship, financial economics, AI, and big data. His work extends to corporate strategy, industrial organization, antitrust, labor, and business law. He has made significant contributions to understanding how innovation interacts with financial markets, corporate strategy, and competition policy, particularly through his influential 'Killer Acquisitions' paper which has been cited in Congressional antitrust reports and lawsuits against major tech companies. His recent publications demonstrate an interdisciplinary approach combining finance, economics, and data science methodologies. Many papers examine the intersection of innovation and corporate finance, with increasing incorporation of AI and big data techniques as seen in his video analysis research. His work shows evolution from traditional finance topics toward more policy-relevant research with real-world impact on antitrust regulation and innovation policy. Professor Ma has received numerous prestigious awards: 2023 Best Paper Award, China International Conference in Finance 2022 Best Paper on Competition Economics, Association of Competition Economics 2022 Jerry S. Cohen Award for Antitrust Scholarship 2021 GARP Best Paper in Risk Management Award 40 Under 40 Best Business School Professors by Poets & Quants (2021) Robert F. Lanzillotti Prize for Antitrust Economics (2020) Jensen Prize for Best Paper on Corporate Finance (2019) In teaching, Professor Ma delivers popular courses including 'Entrepreneurial Finance,' 'Venture Capital and Private Equity,' and 'Finance and the Society.' He co-organizes WEFI (Workshop on Entrepreneurial Finance and Innovation), a bi-weekly virtual research forum. His research has been referenced by major regulatory bodies worldwide including the FTC, EU Competition Commission, and UK Competition and Markets Authority, and featured in leading media outlets like Wall Street Journal and New York Times. Professor Ma actively incorporates new data science technologies into his empirical economic research, focusing on unstructured data analysis and machine learning applications.
Prof. Matt Pritchard is a Professor in Earth & Atmospheric Sciences at Cornell University, based at Snee Hall. His research focuses on volcanology, geodesy, and remote sensing, with a particular emphasis on using satellite data to monitor volcanic activity, deformation, and glacial interactions. He leads studies on global volcanic systems, including Indonesia's Semeru and Raung volcanoes, Chile's Cordón Caulle, and Bolivia's Uturuncu, applying techniques like InSAR, SAR, and thermal imaging. Key research interests include volcanic eruption dynamics, magma-hydrothermal systems, and the integration of multi-sensor datasets. He has contributed to developing tools like Hotspotter for automated volcanic thermal feature detection and has explored planetary volcanism (e.g., Venus). His work bridges geophysics, glaciology, and computational methods, addressing both Earth and extraterrestrial systems. Prof. Pritchard has received recognition such as the William Bowie Lecture (2022, 2023). His projects often involve international collaborations, including the CEOS Volcano Demonstrator initiative and the EarthDEM/ArcitcDEM projects. He also engages in geothermal energy research and seismic monitoring in Ithaca, NY.
Elisabeth Prince is an Assistant Professor at the University of Waterloo, specializing in polymer chemistry and biomaterials. Her research focuses on developing advanced materials for biomedical applications, sustainable materials, and microfluidic technologies. Key areas include conductive hydrogels, cleavable polymers for recyclability, and biomimetic systems for drug delivery and cancer therapy. Her work bridges disciplines such as materials science, nanotechnology, and biomedical engineering. Recent studies involve applications in strain-stiffening hydrogels, filamentous aerogels for electromagnetic shielding, and microfluidic platforms for organoid production. These innovations aim to address challenges in regenerative medicine, environmental sustainability, and personalized cancer treatments. No scientific awards are listed in the provided materials. Research activities include collaborations on 3D-printed microfluidic devices and nanofibrillar hydrogels mimicking biological systems. No advising relationships or grants are explicitly mentioned in the text.
