Dr. Emma Li is a Senior Lecturer in Responsible & Interactive Artificial Intelligence at the University of Glasgow's School of Computing Science. She directs the Interactive and Trustworthy AI Lab, developing secure human-robot collaboration frameworks for applications in healthcare, industry, and nuclear decommissioning. Her research pioneers behavioral biometric authentication methods that verify users through robotic motion patterns, enhancing security in teleoperation systems. Recent projects include cyber-physical teleoperation for nuclear decommissioning funded by the RAICo Programme. Li leads the Understandable Autonomous Systems research theme and contributes to the UKRI Centre for Doctor Training in Socially Intelligent Artificial Agents. Her publications demonstrate consistent innovation in human-robot trust establishment, adversarial robustness, and secure communication for robotic systems operating in sensitive environments.
Dean B. Carson is a researcher at Umeå University , affiliated with the Faculty of Medicine, Department of Epidemiology and Global Health , and the Arctic Research Centre . His work focuses on rural health systems, social care workforce challenges, sustainable rural development, and community-based approaches to healthcare and food security. Rural Health : Explores capacity-building in rural health research and medical education reform. Public Health : Analyzes service delivery models and co-creation frameworks for elderly care. Geography : Investigates spatial dynamics in northern peripheries, including food production networks and micro-urbanization. Recent publications (2024-2025) examine topics such as rural health research capacity frameworks , hospital-to-home transfer systems , and non-commercial food distribution networks . His studies often integrate theoretical models like Rural Nursing Theory and Beyond Periphery while emphasizing stakeholder engagement and policy translation. Grants and Collaborations : Funded by the Swedish Research Council Formas, American National Science Foundation (NSF), and Riksbankens Jubileumsfond. Collaborates with Arctic-FROST networks and Lifestyle Migration Hub researchers.
Ke Wang is a Professor in the School of Computing Science at Simon Fraser University . His research focuses on Data Mining , Database Systems , Data Privacy , and Graph and Network Data . He holds a Ph.D. and M.Sc. from the Georgia Institute of Technology (1986 and 1984, respectively). Teaching includes courses like Database Systems II , Introduction to Data Mining , and Special Topics in Databases . He has advised numerous students and alumni, many of whom now work in tech, academia, and industry. Notable awards include the 2013 Faculty of Applied Sciences Research Excellence Award and the ECIR 2019 Best System Paper . His work emphasizes privacy-preserving techniques and has led to contributions like the Introduction to Privacy-Preserving Data Publishing textbook. He has served as a conference chair for major data mining events like SDM 2015/2016 and holds editorial roles in journals like ACM TKDD. His lab, the Database and Data Mining Laboratory , focuses on actionable solutions for real-world data challenges.
Brian A. Primack is a Professor of Public Health with tenure at Oregon State University's College of Public Health and Human Sciences, serving as its dean since 2022. Previously, he was Dean of Education and Health Professions at the University of Arkansas and Dean of the Honors College at the University of Pittsburgh. His research focuses on social media's impact on mental health, including depression, anxiety, and loneliness. He has authored over 300 publications, including his book You Are What You Click , and secured over $10 million in federal research funding. Dr. Primack's research highlights both risks and opportunities of digital media. He emphasizes optimizing social media use through strategies like curating connections and mitigating negativity. His work intersects education, medicine, and public health, addressing disparities in health outcomes, such as those exacerbated during the pandemic. Notable awards include membership in the American Society of Clinical Investigation (2019) and the Next Big Idea Book Award shortlist (2021). His leadership philosophy prioritizes unlocking potential, fostering community trust, and advancing equitable health solutions. He oversees a college with nearly 2,400 students and $18 million in annual research funding, emphasizing community engagement and innovative scholarship.
Mahzarin R. Banaji is the Richard Clarke Cabot Professor of Social Ethics at Harvard University and a Harvard College Professor. She is affiliated with the Department of Psychology and is a key figure in the Mind, Brain, and Behavior (MBB) Interfaculty Initiative. Her research is centered at the intersection of social cognition, implicit bias, and ethical behavior. Institution: Harvard University School: Harvard College Department: Psychology Email: banaji@fas.harvard.edu Dr. Banaji earned her Ph.D. from Ohio State University and has been a leading scholar in the study of unconscious bias. Her work explores how implicit attitudes shape perception, judgment, and behavior outside conscious awareness. She co-developed the Implicit Association Test (IAT) , a groundbreaking tool for measuring unconscious biases related to race, gender, age, and other social categories. Her research spans social cognition, prejudice, stereotyping, moral psychology, and the neuroscience of social behavior . More recently, she has extended her work into the domain of artificial intelligence, investigating how human-like biases emerge in large language models. The 15 most recent publications reflect a strong trend toward computational social science , combining psychological theory with natural language processing and AI. Her team analyzes bias in digital corpora, studies the transmission of stereotypes in AI systems, and develops tools to measure intersectional and implicit attitudes at scale. These works bridge psychology, ethics, and technology, highlighting the societal implications of implicit cognition. Among her notable scientific honors are: Fellow of the American Academy of Arts and Sciences William James Fellow Guggenheim Fellowship Kurt Lewin Award (SPSSI) Harvard College Professorship Dr. Banaji has advised numerous graduate students, including Tessa Charlesworth and Kerry Morehouse, many of whom are now active researchers in social and cognitive psychology. She has secured major grants through the Mind, Brain, and Behavior Initiative and has led interdisciplinary teams exploring bias in education, law, and technology. She is also the co-creator of OutsmartingHumanMinds.org , a public education platform on implicit bias. Her lab serves as a hub for collaborative research on implicit social cognition, bringing together psychologists, neuroscientists, and computer scientists to understand and mitigate unconscious bias in human and artificial systems.
Jonathan P. Wong is a Senior Policy Researcher at the RAND Corporation and Professor of Policy Analysis at the RAND School of Public Policy. His work bridges academic research and defense policy, focusing on military strategy, acquisition, force planning, and the integration of emerging technologies into military operations. Education: Ph.D. and M.Phil. in Policy Analysis (Pardee RAND Graduate School), M.A. in Security Studies (Georgetown University), B.A. in Political Science (UC San Diego) Professional Experience: U.S. Marine Corps infantry officer (2001–2011), Consultant at Boston Consulting Group, current RAND researcher and professor Wong’s research interests center on defense innovation, military logistics, artificial intelligence in warfare, space capabilities, and the human dimension of military operations. He has led studies on human-machine teaming, non-lethal weapons, defense acquisition reform, and U.S. military posture in the Indo-Pacific. His work emphasizes practical, policy-relevant insights grounded in operational experience. The trends in his recent publications reveal a deep engagement with modern defense challenges: integrating commercial technologies into military systems, improving acquisition agility, enhancing battlefield awareness, and ensuring that defense innovation serves warfighter needs. His research spans strategic, operational, and tactical levels, often focusing on the U.S. Army and Marine Corps. Wong has not received public recognition in the form of listed awards in the provided texts, but his leadership in congressionally mandated studies and high-impact policy research suggests significant influence in defense circles. Advising & Grants: Co-led major projects such as the Long Range Precision Fires study and research on integrating women into Marine Corps infantry. His work is frequently funded by the Department of Defense and other federal entities, though specific grant details are not listed. Wong is affiliated with RAND’s defense and national security research teams, contributing to strategic analysis and policy development. He is not associated with a formal lab but works within RAND’s collaborative research environment, often partnering with other veterans and defense experts to produce actionable insights for military leaders and policymakers.
Sergi Colominas Fuster, PhD , is a Full Professor and Coordinator of the Master’s Degree in Analytical Chemistry at the Department of Analytical and Applied Chemistry, IQS School of Engineering, Universitat Ramon Llull. He has been serving in this leadership role since 2021 and was promoted to Full Professor in 2025. His educational background includes a PhD in Chemistry (2006, URL), a Chemical Engineering degree (2001, IQS), and a Degree in Chemistry (1999, URL). Sergi's research is centered on the design, development, and characterization of electrochemical sensors , with a strong emphasis on applications in nuclear fusion technology and bioanalysis . His work focuses on sensors for molten metals and biosensors, particularly for detecting hydrogen and tritium in fusion reactors. He is an active member of the EQBA – Electrochemistry and Bioanalysis Group , which specializes in analytical, electrochemical, spectrometric, and optical techniques. His recent publications (2023–2025) highlight advancements in 3D-printed perovskite-based high-temperature electrochemical sensors for hydrogen monitoring in fusion environments. These works demonstrate innovation in fabrication techniques such as cold isostatic pressing and 3D printing, contributing to safer and more efficient fusion energy systems. Key research projects he is involved in include: EUTECTIC : Industrial production of Li-6 enriched lead-lithium eutectic for nuclear fusion. ECSINFUS : Development of electrochemical sensors for fusion applications. EUROFUSION : Implementation of fusion roadmap activities under Horizon Europe. He has secured research grants from competitive programs such as AGAUR and the European Commission, reflecting his leadership in fusion-related analytical chemistry. His work bridges materials science, electrochemistry, and energy technology. Sergi contributes to multiple academic programs, including the Master’s in Analytical Chemistry, Materials Science and Engineering, Pharmaceutical Chemistry, and the PhD in Chemistry and Chemical Engineering, indicating his broad academic engagement and mentorship.
Dr.-Ing. Tobias Fiebig is a Senior Researcher at the Max Planck Institute for Informatics (Internet Architecture department) since April 2022. He previously served as a permanent Assistant Professor at TU Delft's Faculty of Technology, Policy and Management from 2017-2022. His work combines network measurement with human factors to improve security practices, focusing on email protocols, DNS infrastructure, and academic cloud migration. PhD in Computer Science from TU Berlin (2017) MSc in System and Network Engineering from University of Amsterdam (2013) BSc in Cognitive Science from University of Osnabrück (2012) His research spans Internet security (DNS, IPv6, email), academic freedom in cloud contexts, and human-centered security challenges. Recent work analyzes MTA-STS deployment, DNS sampling biases, and university cloud migration privacy implications. He has presented at top conferences including USENIX Security , IEEE Symposium on Security and Privacy , and ACM CCS . Teaching roles include lecturing Data Networks (2023-24) and On the Practice of System and Network Engineering (2024), with prior module management in cyber security analytics and sustainable system operations.
Michael Feeley is an Associate Professor in the Department of Computer Science at the University of British Columbia (UBC), affiliated with the Institute for Computing, Information and Cognitive Systems (ICICS). His research focuses on operating systems, distributed systems, and their applications in scalable file systems, cloud storage, and mobile computing. He leads projects such as the Unico file system, Parallax storage system, and Remus virtual machine replication framework. His research interests include peer-to-peer file systems, mobile ad hoc networks, interference mitigation in wireless networks, and system software for workstation clusters. He has supervised numerous graduate students, contributing to advancements in distributed systems and networking. His work often addresses challenges in resource management, fault tolerance, and performance optimization. Publications span topics like interference detection in WiFi networks, dynamic program analysis (Tralfamadore), and distributed storage solutions. Feeley teaches courses such as CPSC 213, emphasizing operating systems fundamentals. His office is located in CISR 393, with contact details available via email and phone.
Adam B. Badawi is a Professor of Law at the University of California, Berkeley - School of Law, where he maintains an active research agenda at the intersection of law, finance, and corporate governance. His scholarly work has established him as a leading expert in contract law, M&A transactions, securities litigation, and ESG compliance. Professor Badawi's research interests span multiple dimensions of corporate law and legal theory. His work on contractual complexity, particularly in debt agreements and M&A transactions, has provided significant insights into how legal drafting affects economic outcomes. He has extensively examined the business judgment rule, board authority, and the role of courts in corporate governance. More recently, his research has expanded into ESG-related topics, analyzing how environmental, social, and governance considerations intersect with traditional corporate law frameworks. His methodological approach often combines legal analysis with empirical techniques, including text analysis of legal documents and event studies of litigation outcomes. Professor Badawi's scholarly output demonstrates consistent high-impact research across multiple domains of corporate law. His early work focused on foundational aspects of contract theory and interpretation, while his more recent publications reflect growing interest in ESG metrics, executive compensation structures tied to sustainability goals, and the evolving regulatory landscape. The trajectory of his research shows a progression from theoretical legal analysis toward increasingly empirical and interdisciplinary approaches that bridge law with finance and data science. Professor Badawi has collaborated with numerous scholars across different institutions, including Duke University, Stanford Law School, and the University of Chicago Law School, reflecting the interdisciplinary nature of his work and its relevance to multiple academic communities.
Bo Han is an Associate Professor in the Department of Computer Science at Hong Kong Baptist University's Faculty of Science, where he leads the Trustworthy Machine Learning and Reasoning (TMLR) Group. He also holds a visiting scientist position at the RIKEN Center for Advanced Intelligence Project (RIKEN AIP) in Japan. His research focuses on developing trustworthy and efficient machine learning systems, particularly under imperfect data conditions such as noisy labels, out-of-distribution data, and weak supervision. Bo Han's research interests span Machine Learning , Deep Learning , Foundation Models , Causal Representation Learning , Weakly and Self-supervised Learning , Robustness and Security in Machine Learning , Federated Learning , and AI for Science . His work aims to build intelligent systems that can reliably learn and reason from complex, imperfect real-world data. His recent publications reveal a strong trend toward trustworthy foundation models , robust reasoning with large language models , out-of-distribution detection , privacy-preserving learning , and causal robustness . His research integrates theoretical foundations with practical applications, often published in top-tier venues like NeurIPS, ICML, ICLR, and TPAMI. Notable Awards and Honors: Outstanding Paper Award, NeurIPS Most Influential Paper, NeurIPS IEEE AI's 10 to Watch Award IJCAI Early Career Spotlight INNS Aharon Katzir Young Investigator Award Dean's Award for Outstanding Achievement RGC Early CAREER Scheme Bo Han has been actively involved in the academic community, serving as a Senior Area Chair and Area Chair for NeurIPS, ICML, and ICLR, and as an Associate Editor for IEEE TPAMI, MLJ, and JAIR. He has advised numerous PhD and research students and leads a globally distributed research group. His work is supported by major grants from RGC, NSFC, GDST, RIKEN, and industry partners including Microsoft, Alibaba, Tencent, and Baidu. He also leads research initiatives in Trustworthy Machine Learning , including projects on federated learning, model unlearning, privacy-preserving AI, and robust foundation models, often in collaboration with industry and international institutions.
Thomas Bäck is a Professor at the Leiden Institute of Advanced Computer Science (LIACS) , Leiden University , Netherlands, and a member of the interdisciplinary programme Society, Artificial Intelligence and Life Sciences (SAILS) . His academic career spans roles at Leiden University (1996–present) and leadership positions at the Center for Applied Systems Analysis in Dortmund (1994–2000). Education : Diplom-Informatiker (Computer Science), Technische Universität Dortmund (1990) Dr. rer. nat. (Computer Science), Technische Universität Dortmund (1994) Research Interests : Dr. Bäck specializes in evolutionary computation , machine learning , and their applications in sustainable smart industry and healthcare . Recent work focuses on integrating large language models (LLMs) and quantum computing into optimization frameworks, with projects like CIMPLO (predictive maintenance), ECOLE (experience-based optimization), and SAPPAO (airline operations optimization). Scientific Contributions : His 526+ publications cover evolutionary algorithms, quantum optimization, and LLM-driven design, with recent trends including: Quantum computing (e.g., quantum approximate optimization, quantum advantage challenges) LLM integration (e.g., hyperparameter tuning, mutation control, code evolution graphs) Healthcare and industry (e.g., predictive maintenance, anomaly detection, melt quality prediction) Algorithm benchmarking (e.g., IOHprofiler, MA-BBOB, explainable benchmarking) Scientific Awards : IEEE Fellow (2022) Royal Netherlands Academy of Arts and Sciences (KNAW) member (2021) Academia Europaea member (2022) IEEE Computational Intelligence Society Evolutionary Computation Pioneer Award (2015) Fellow, International Society of Genetic and Evolutionary Computation (2003) Best Ph.D. thesis award, German Society of Computer Science (GI) (1995) Advising and Grants : He supervises Ph.D. candidates in evolutionary computation and machine learning and has secured 7 major grants from organizations like the Dutch Research Council , European Commission , and The Research Council of Norway . His editorial roles include Editor-in-Chief of the Evolutionary Computation Journal and associate editorships in leading AI journals.
University of California , Santa Barbara (UCSB)United States
Isabelle Mejean serves as Professor in the Department of Economics at Sciences Po, specializing in international macroeconomics and international trade. Her prior academic appointments include Ecole Polytechnique, CEPII (Centre d'Etudes Prospectives et d'Informations Internationales), and the IMF Research Department. Education: PhD in Economics, University of Paris 1-Panthéon-Sorbonne (2006) Mejean's research explores micro-foundations of global trade systems, emphasizing firm-level adaptations to geopolitical shifts, environmental regulations, and supply chain disruptions. Her work bridges macroeconomic phenomena with granular trade data, investigating how carbon taxes reshape supply networks, how trade fragmentation affects economic security, and how labor market structures influence volatility resilience. This approach reveals critical mechanisms behind inflation transmission and policy spillovers across borders. Analysis of her 2022-2025 publications shows consistent focus on empirical trade dynamics using French manufacturing datasets and global firm networks. Key trends include quantifying carbon leakage through supply chains, mapping shock propagation in firm-to-firm trade, and evaluating de-risking strategies amid geopolitical tensions. Her research directly informs contemporary debates on climate-trade policy coherence and energy security. Scientific Awards: No awards documented in source material. Advising and Grants: Doctoral supervision activities and research funding sources remain unspecified in available records. Labs and Teams: Affiliation with specific research collectives or laboratories is not referenced in current institutional profiles.
Alex Lombardi is an Assistant Professor of Computer Science at Princeton University, specializing in cryptography and theoretical computer science. His work explores cryptographic proof systems, post-quantum security, and quantum cryptography. Princeton University (Current) Simons-Berkeley Postdoctoral Fellow (Former) MIT (Graduate Training) Visiting Scientist, Cryptography 10 Years Later Program (2025) Education: PhD in Computer Science from MIT (advised by Vinod Vaikuntanathan) Master's Thesis on Provable Instantiations of Correlation Intractability and the Fiat-Shamir Heuristic Dr. Lombardi's research spans foundational cryptography, with a focus on indistinguishability obfuscation, worst-case assumptions, and quantum cryptographic protocols. His work on SNARGs and PPAD hardness has advanced cryptographic proof systems, while his recent projects address quantum verification and post-quantum security. He encourages prospective cryptography students to apply to Princeton's PhD program. His publications highlight advancements in LWE-based cryptography, quantum protocols, and complexity-theoretic foundations. Key themes include secure computation, hash function design, and cryptographic reductions under quantum assumptions. Scientific Awards: Simons-Berkeley Postdoctoral Fellowship Dr. Lombardi serves on program committees for STOC 2025, EUROCRYPT 2025, and other conferences. He has taught courses like COS 433/533 (Cryptography) and COS 533 (Advanced Cryptography) at Princeton.
Rick Hoyle is a Professor of Psychology and Neuroscience at Duke University, where he serves as Associate Chair of the Department of Psychology and Neuroscience. He is also a Faculty Network Member of the Duke Institute for Brain Sciences. His academic career spans decades, with significant contributions to understanding self-regulation and adolescent development. Dr. Hoyle earned his B.A. from Appalachian State University (1983), followed by an M.A. (1986) and Ph.D. (1988) from the University of North Carolina, Chapel Hill. He progressed from Assistant to Associate to Full Professor at the University of Kentucky from 1989 to 2003 before joining Duke University. His research focuses on how adolescents and emerging adults manage goal pursuit through self-regulation, taking a broad view that accounts for personality, environment, cognition, emotion, and social influences. He employs longitudinal methods with repeated assessments, sometimes spanning years with data collection multiple times per year, or intensive studies with assessments several times daily. His lab develops innovative measurement tools including self-report measures of self-control and grit, as well as unobtrusive approaches using mobile phones and wearable devices to track goal pursuit in natural settings. His recent publications reveal a strong focus on self-regulation in digital contexts, adolescent substance use, socioeconomic influences on development, and innovative measurement approaches. His work increasingly integrates technology (social media analysis, wearable devices) with traditional psychological research methods to understand real-world behavior. Fellow, Association for Psychological Science (2013) Dr. Hoyle has secured numerous research grants totaling millions of dollars, including the current Real-Time and Randomized Tests of Social Media and Mental Health Links in Early Adolescence (2024-2029), NCCU Duke - Substance Use Research & Education (2024-2029), and Mid-Life Health Inequalities in the Rural South: Risk and Resilience (2023-2028). His grant portfolio demonstrates sustained funding for research on adolescent development, substance use, self-regulation, and health disparities. He teaches advanced courses including Applied Structural Equation Modeling and Psychology and Neuroscience Grant Writing, mentoring the next generation of researchers in quantitative methods and research design. His work through the Center for the Study of Adolescent Risk and Resilience (2008-2025) has established a significant research infrastructure for longitudinal studies of adolescent development. Current projects examine social media effects on mental health, substance use patterns, and the impact of environmental factors on adolescent well-being using innovative digital tracking methods.
