Professor John Zeleznikow is an Honorary Associate at La Trobe University's Law School, with a distinguished career spanning 49 years across multiple institutions including the University of Edinburgh and Victoria Business School. His research focuses on AI applications in legal decision-making, dispute resolution, and autonomous vehicle technology. He has secured over $8M in research grants and supervised 20 PhD graduates. Key projects include the Split-Up system (used in high-profile divorce cases like Prince Charles and Lady Di) and Family-Winner software, which won an ABC TV innovation award. His work bridges law, technology, and ethics, with publications in leading journals like the Harvard Negotiation Law Review and Artificial Intelligence and Law . Recent research explores AI-driven online dispute resolution (ODR), autonomous vehicle regulation, and the ethical implications of technology in legal systems. He advocates for transparent, user-centric legal tech solutions to enhance access to justice and improve decision-making processes.
Diana Tamir is a Professor at Princeton University, where she directs the Princeton Social Neuroscience Lab. She earned her Ph.D. from Harvard University and specializes in the intersection of internal mental processes and external social cognition. Her research investigates: How minds predict others' emotions and mental states The cognitive consequences of self-disclosure and social media use Neural mechanisms of social prediction using fMRI and machine learning Effects of fiction reading on theory of mind Dynamics of spontaneous thought and social bonding Her recent publications (2024-2025) demonstrate strong focus on emotion prediction mechanisms, social interaction dynamics, neural signatures of psychological states, and developmental aspects of social cognition. Methodologically, she employs neuroimaging hyperscanning, ecological momentary assessment, and computational modeling across diverse populations. She currently advises graduate students including Faustine Corbani and Yeaju Diana Kim. Her lab focuses on empirical approaches to understanding how individuals navigate between internal experiences and external social environments.
Som G Nanjappa is an Associate Professor in the Department of Pathobiology at the University of Illinois. His academic background includes a Ph.D. in Immunology from the University of Wisconsin-Madison (2009). He specializes in T cell biology, fungal infections, and vaccine development, with a focus on CD8+ T cells, Tc17 cells, and their roles in combating fungal pathogens like Blastomyces dermatitidis and Cryptococcus neoformans. His research explores mechanisms of vaccine-induced immunity, particularly in immunocompromised hosts, and investigates how T cell responses contribute to protection against fungal pneumonia. Recent work highlights the role of GM-CSF+ Tc17 cells in vaccine efficacy and the importance of molecules like sialophorin in CD8+ T cell activation. Collaborations span immunology, oncology, and microbiology, with studies on 27-hydroxycholesterol’s impact on breast cancer progression and T cell dysfunction. Publications emphasize fungal vaccine strategies, immune memory persistence, and the interplay between innate and adaptive immunity. His findings have been featured in journals like Cell Reports, PLoS Pathogens, and Frontiers in Immunology, with impactful contributions to understanding antifungal immunity and T cell plasticity.
Joe Paton is a Professor and Principal Investigator at the Champalimaud Neuroscience Programme, Champalimaud Foundation in Lisbon, Portugal. He leads the Paton Lab which focuses on understanding how animals determine which environmental cues are predictive of behaviorally relevant events, known as the credit assignment problem. His research combines behavioral experiments with neurophysiological recordings in rodents to investigate neural mechanisms of time perception and decision making. Dr. Paton's research interests center on interval timing, temporal processing in the brain, and the neural basis of learning. His work particularly examines how the striatum and dopamine systems contribute to time perception and how animals solve the credit assignment problem through statistical inference in the time domain. His lab employs advanced techniques including optogenetics, neural recordings, and computational modeling to address these questions. Analysis of Dr. Paton's recent publications reveals a strong focus on striatal function in timing processes, with particular attention to how neural populations encode temporal information. His work bridges behavioral neuroscience with computational approaches, demonstrating how timing mechanisms influence decision making and learning processes. The research spans multiple levels from cellular mechanisms to behavioral outputs. Midbrain dopamine neurons control judgment of time (2016) Striatal dynamics explain duration judgments (2015) A Scalable Population Code for Time in the Striatum (2015) The Neural Basis of Timing: Distributed Mechanisms for Diverse Functions (2018) Dr. Paton has mentored numerous PhD students and postdoctoral researchers through the INDP (International Neuroscience Doctoral Program) and supervises a diverse team including research technicians, postdocs, and students. His lab has contributed significantly to understanding the neural basis of time perception and its role in learning and decision making. The Paton Lab also develops experimental tools and frameworks like Bonsai for behavioral neuroscience research.
Professor Richard Bolden is a Professor of Leadership and Management at the Bristol Business School, University of the West of England (UWE), where he also directs the Bristol Leadership and Change Centre. His career includes over a decade at the University of Exeter Business School and experience as a consultant, research psychologist, and software developer. He holds a PhD, MA, and BSc. His research focuses on distributed leadership, leadership development in complex systems, and cross-sector partnerships. Key areas include leadership in higher education, healthcare, and public services, with emphasis on paradoxes, complexity, and inclusion. He has published extensively, including a 2023 second edition of Exploring Leadership (Oxford University Press) and serves as Associate Editor of the Leadership journal. Prof. Bolden leads leadership modules for UWE's EMBA and clinical practitioner programs. His funded projects involve organizations like the NHS Leadership Academy and Singapore Civil Service College. Awards include Fellowship with the International Leadership Association. His work bridges academic theory and practical application, addressing systemic challenges through collaborative, inclusive leadership frameworks. Current interests include post-pandemic academic leadership and the 'great resignation' impact.
Mendel Rosenblum is the Cheriton Family Professor and holds dual appointments as Professor in the Departments of Computer Science and Electrical Engineering at Stanford University. He is a co-founder of VMware Inc. and served as its Chief Scientist for its first decade, playing a pivotal role in designing foundational virtualization technologies. Rosenblum's research focuses on system software, distributed systems, and computer architecture, with notable contributions to virtualization, data center networks, and operating systems. He leads the Platform Lab at Stanford, exploring next-generation data center technologies and high-performance computing systems. Administrative Role: Faculty Director of Stanford Computer Forum (2012–present) Education: PhD (UC Berkeley, 1992), MS (UC Berkeley, 1989), BA (University of Virginia, 1984) His research interests span disk storage management, computer simulation, scalable operating systems, and security. Recent work emphasizes deployable consensus algorithms, programmable smartNICs, and self-programming networks. Rosenblum has authored over 80 publications and holds multiple patents in virtualization and system software. Awards & Recognition: ACM System Software Award (2009) IEEE Computer Entrepreneur Award (2011) ACM Thacker Breakthrough in Computing Award (2018) Member, National Academy of Engineering (2013) He advises PhD and Master's students, including current advisees Sina Jandaghi Semnani and Zixi Liu. Rosenblum teaches advanced courses on web applications, distributed systems, and independent research projects.
Dr. Oscar Meruvia-Pastor is a faculty member in the Department of Computer Science at Memorial University of Newfoundland, within the Faculty of Science. He holds a B.Sc. from ITESM-Monterrey, Mexico, an M.Sc. from the University of Alberta, and a Ph.D. from Otto-von-Guericke Universität Magdeburg, Germany. His research focuses on interactive 3D graphics, non-photorealistic rendering, and biomedical visualization, with applications in telepresence systems, augmented reality (AR), and virtual reality (VR). He has developed tools like OMARC for respiratory condition training and GeNET for gene co-expression network analysis. Dr. Meruvia-Pastor has supervised numerous graduate students and contributed to over 50 publications. His work includes evaluating stereo correspondence methods in AR, robot arm manipulation via depth sensors, and smartphone integration in immersive VR. He has been recognized with awards such as the Best HCI Poster at Graphics Interface 2014 and a semi-finalist poster at SIGGRAPH 2015. He teaches courses in computer science, including computer graphics, multimedia development, and introductory science modules. His research lab focuses on 3D telepresence, medical visualization, and human-centered VR/AR solutions. His academic contributions span software tools for medical imaging analysis, interactive visualization systems, and educational technologies. He actively collaborates with health professionals to advance telemedicine and remote procedural training through AR platforms. His work bridges computer graphics with real-world applications in healthcare, education, and environmental advocacy.
David Churchill is an Associate Professor in the Department of Computer Science at Memorial University of Newfoundland (MUN), specializing in Artificial Intelligence and Real-Time Strategy (RTS) Game AI. He holds a PhD from the University of Alberta and has been actively involved in AI research since 2009. His work focuses on AI for RTS games like StarCraft, emphasizing heuristic search, combat simulation, and build order optimization. He organizes the annual AIIDE StarCraft AI Competition and maintains open-source projects like UAlbertaBot and SparCraft. Education: BSc in Pure Mathematics and Computer Science (MUN) MSc in Computer Science (MUN, 2009) PhD in Computing Science (University of Alberta, 2016) Research Interests: AI in video games, heuristic search algorithms, RTS game strategies, multi-agent systems, and robotics. His work bridges theoretical AI with practical applications in competitive gaming and robotics. Publications & Awards: Notable contributions include Search Ordering for StarCraft Build Order Optimization (2024) and Hierarchical Portfolio Search in Prismata (2017, Best Student Paper Award). His research has advanced combat simulation (SparCraft) and build-order planning (BOSS) in RTS games. Awards: Best Student Paper Award (2017) Best Paper Award (2013, 2022) Advising & Labs: Supervised over 20 graduate and undergraduate theses at MUN. Leads the StarCraft AI Competition and contributes to open-source projects like UAlbertaBot and STARTcraft. Currently not accepting new graduate students due to funding constraints.
Matti Sällberg is a Professor in Biomedical Analysis at Karolinska Institutet's Department of Laboratory Medicine, leading the VIVAC research group focused on vaccines and immunotherapies against viruses and cancer. He earned his DDS and PhD from Karolinska Institutet (1988-1992), followed by postdoctoral research at The Scripps Research Institute (1994-1996). As a leader in infectious disease and hepatology, his research addresses chronic viral hepatitis, cancer prevention, and gene/cell-based therapies (GTMPs/ATMPs). He has directed the Department of Laboratory Medicine (2011-2022) and actively teaches in biomedical laboratory science, dentistry, medicine, and nursing programs. Key research areas include SARS-CoV-2 vaccine development (OPENCORONA consortium), hepatitis B/D/C therapies, and Crimean-Congo hemorrhagic fever vaccines. His work combines basic science with translational efforts at Karolinska's ANA Futura facility. Notable projects include a phase I clinical trial for a broad-acting SARS-CoV vaccine and preclinical testing of hepatitis therapies. Collaborations span academia and industry, with funding from the Swedish Cancer Society, EU, and VINNOVA. He oversees advanced techniques like viral propagation, flow cytometry, and adoptive cell therapy manufacturing. Grants include a 2024 Swedish Cancer Society award for hepatitis-related cancer therapies and a 2022 Swedish Research Council grant for the Doctoral Program in Advanced Therapies. His team maintains an active lab with researchers like Lars Frelin and Gustaf Ahlén. Future work emphasizes expanding vaccine platforms against emerging pathogens and optimizing immuno-therapies for solid tumors.
Laura K. Nelson is an Associate Professor of Sociology at the University of British Columbia , where she also directs the Centre for Computational Social Science . Her work bridges computational methods with sociological inquiry, focusing on gender inequality, social movements, and organizational dynamics. She previously held faculty roles at Northeastern University and affiliated with institutions like the NULab for Texts, Maps, and Networks and the Network Science Institute . Education: PhD in Sociology (2014), University of California, Berkeley MA in Sociology (2009), University of California, Berkeley BA in Sociology (2006), University of Wisconsin-Madison (Phi Beta Kappa) Research Interests span computational sociology, social movement strategy, intersectionality, and STEM equity. She pioneered frameworks like computational grounded theory and radical objectivity , integrating machine learning with qualitative paradigms. Recent publications analyze gender dynamics in emergency medicine, feminist movement histories, and the NSF ADVANCE program’s impact on equity. Her 2024 Social Science Quarterly paper quantifies ADVANCE’s interdisciplinary reach. Awards include the 2020 Best Meta-Reviewer at SocInfo20 and Outstanding Faculty of the Year at Northeastern University. She serves on editorial boards for American Journal of Sociology , Poetics , and Acta Sociologica . She co-PIs a National Science Foundation grant studying gender-equity dissemination in higher education networks and supervises graduate student Jinyang Yu . Her lab, Centre for Computational Social Science , drives open-source methodological innovation.
Ruixiang Tang is an Assistant Professor at Rutgers, The State University of New Jersey. His research focuses on artificial intelligence, machine learning, and natural language processing, with an emphasis on multimodal learning, model security, and ethical AI. He explores topics such as adversarial robustness, bias mitigation, and applications in healthcare and robotics. Key research interests include developing robust algorithms for vision-language models, analyzing model vulnerabilities like backdoors and hallucinations, and designing trustworthy AI systems. His work bridges theoretical advancements and practical applications, addressing challenges in healthcare data augmentation, copyright infringement detection, and cognitive reasoning. His recent publications highlight contributions to multimodal in-context learning, counterfactual reasoning benchmarks, and secure model optimization. Tang's research also intersects with fairness in AI, such as mitigating bias in NLP models and ensuring equitable outcomes in medical applications.
Neelakantan R. Krishnaswami is a Professor of Computer Science at the University of Cambridge's Computer Laboratory , and a Fellow of Trinity College . His research focuses on the intersection of program verification, programming language design, and foundational topics like type theory and semantics. His work spans areas such as refinement types, parser design, separation logic for systems software, and the semantics of reactive programming. Notable contributions include the Datafun language for higher-order Datalog and the λert type theory for explicit refinement types. He has also developed foundational frameworks for verifying imperative programs using advanced type systems and logical relations. Key publications include 'Explicit Refinement Types' (ICFP 2023), 'flap: A Deterministic Parser with Fused Lexing' (PLDI 2023), and 'CN: Verifying Systems C Code' (POPL 2023). His work frequently addresses challenges in efficiency, correctness, and modularity for both functional and imperative systems. His awards include Distinguished Paper Awards at PLDI 2019 and POPL 2020. His research integrates theoretical rigor with practical tooling, exemplified by contributions to languages like Coq, Lean, and Haskell.
Dr. Ting Hu is an Associate Professor in the School of Computing at Queen's University, affiliated with the Faculty of Arts and Science. She leads the Machine Intelligence & Biocomputing (MIB) Laboratory, focusing on bio-inspired AI and bioinformatics. Her research bridges evolutionary computing, machine learning, and biomedical data analysis. Dr. Hu holds a PhD in Computer Science from Memorial University and completed postdoctoral training at Dartmouth College. She teaches courses with strong student evaluations, winning the Howard Staveley Teaching Award (2019-2020) and recognition as a Mental Health Champion (2023). Education: B.Sc. in Computational Mathematics, Wuhan University M.Sc. in Computer Science, Wuhan University PhD in Computer Science, Memorial University Postdoctoral Fellowship, Geisel School of Medicine, Dartmouth College Research Interests: Evolutionary algorithms and genetic programming Interpretable and explainable AI Biomedical data mining (metabolomics, genomics) Complex network analysis Applications in precision medicine and disease prediction Awards & Recognition: Queen's AMS Undergraduate Mentorship Award (2025) IEEE CIBCB Best Student Award (2022) Howard Staveley Teaching Award (2019-2020) NSERC Discovery Grant Reviewer (2019) Memorial University's Best Professor Award (2016) Lab & Collaborations: MIB Lab develops tools like geneDRAGNN (graph neural networks for gene-disease prioritization) Active roles in IEEE Computational Intelligence Society and EuroGP Advances include vaccination strategies via graph-RL and interpretable clustering methods
Regina Fabry is a Lecturer in the Department of Philosophy at Macquarie University, Australia, affiliated with the School of Humanities Ethics and Agency Research Centre. Previously, she held positions at Ruhr University Bochum (Lecturer, 2018–2021) and Justus Liebig University Giessen (Postdoctoral Researcher, 2016–2018). Her research focuses on situated cognition, affectivity, and the socio-cultural influences on self-narration and grief, particularly in the context of emerging technologies like deathbots. She holds a PhD in Philosophy (summa cum laude) from Johannes Gutenberg University Mainz (2015), awarded the Barbara Wengeler Prize for her work on enculturated predictive processing. Fabry’s research is funded by grants including an ARC DECRA (2021–2024) and explores interdisciplinary themes in AI ethics, cognitive science, and literary studies. **Education**: PhD in Philosophy, Johannes Gutenberg University Mainz (2012–2015) MA in Comparative Literary Studies, Philosophy, and Theatre Studies, Johannes Gutenberg University Mainz (2007–2012) **Research Interests**: Combines empirical cognitive science with feminist theory to study narrative practices, grief, and AI ethics. Current projects include analyzing deathbots’ impact on grief dynamics and the socio-cultural situatedness of self-narration as tools of oppression or resistance. Her work bridges philosophy, psychology, and technology studies. **Articles Trends**: Recent publications address grief in digital contexts (deathbots), narrative ethics (e.g., gaslighting), and cognitive frameworks like predictive processing. Her work frequently intersects with technology’s role in shaping human experiences. **Awards**: Barbara Wengeler Prize 2016 for doctoral dissertation on enculturated cognition. **Teaching & Grants**: Teaches courses on AI ethics, including PHIL8400 (Rights, Responsibilities, and AI). Supervises postgraduate research in philosophy of mind and AI. Leads projects like “Living to tell, telling to live” (2021–present) and co-leads “A lone or lonely life?” (2025–2028) on autism and loneliness. **Labs/Teams**: Engaged in interdisciplinary collaborations on grief, narrative theory, and AI ethics, leveraging her background in philosophy, psychology, and literary studies.
Yonghwi Kwon is a Visiting Assistant Professor in the Department of Computer Science at the University of Virginia. His research focuses on software systems security, cyber forensics, and software engineering. He received the CAREER Award for developing dynamic defenses against cyber threats. His work emphasizes securing software from cyber attacks, recovering forensic evidence, and improving software testing and reverse engineering techniques. Key research areas include memory safety mechanisms, automated vulnerability detection in web applications and mobile systems, and forensic analysis of phishing campaigns. He has pioneered frameworks like CMASan for memory allocator-aware sanitization and Racedb for detecting race conditions in database-backed systems. His contributions span cloud security automation, kernel exploitation analysis, and embedded system fuzzing. Notable achievements include the 2025 CAREER Award supporting his dynamic defense research, and impactful publications in areas like Android information leakage detection (DryJIN), Bluetooth protocol fuzzing (BTFuzzer), and autonomous driving bug discovery (Drivefuzz). His work bridges theoretical computer science with practical cybersecurity solutions.
