Prof. Ramakrishna Gokaraju is a Professor and Graduate Chair in the Department of Electrical and Computer Engineering at the University of Saskatchewan. His academic journey includes roles as Assistant Professor (2003), Associate Professor (2009), and full Professor (2015). He holds a B.E. from NIT Trichy (1992), M.Sc. and Ph.D. from the University of Calgary (1996, 2000). His research focuses on power system protection, smart grids, and sustainable energy systems, including small modular reactors (SMRs) and renewable integration. He has advised 8 PhD and 25+ Master’s students, with over 80 publications in top journals/conferences. Dr. Gokaraju’s honors include the Izaak Walton Killam Memorial Scholarship (1998–2000) and the Professor of the Year Award (2008). He has held visiting roles at the University of Manitoba (2009–2010), IIT Kanpur (2018), and institutions in Australia and India. His work emphasizes high-speed digital relaying, PMU-based solutions, and transient stability protection. Current research includes wind generator modeling, SMR integration, and energy storage systems for remote communities. His technical contributions span fault location algorithms, grid resilience enhancement, and GPU-based optimization for transport systems. Ongoing projects explore hybrid energy systems combining SMRs with renewables. Lab affiliations include the Power Systems Research Group at the University of Saskatchewan, focusing on smart grid innovation and sustainable energy solutions.
Dean Eckles is an Associate Professor of Marketing at MIT Sloan School of Management and serves as an Associate Director of the MIT Institute for Data, Systems, and Society (IDSS). He is also affiliated with the MIT Schwarzman College of Computing through the Institute for Data, Systems & Society and its Statistics and Data Science Center. Additionally, he leads the analytics research area at the Initiative on the Digital Economy and organizes the annual Conference on Digital Experimentation (CODE@MIT). His educational background includes a BA in philosophy, BS and MS in cognitive science, MS in statistics, and PhD in communication, all from Stanford University. Prior to joining MIT, Eckles worked as a scientist at Facebook, where he contributed to areas including News Feed, messaging, advertising, tools for randomized experiments, and survey methods. He previously held research positions at Nokia and Yahoo. Eckles's research primarily focuses on social influence mediated by interactive technologies, examining how communication technologies mediate, amplify, and direct social influence. His work spans multiple specific areas including social interactions, contagion, and interventions in networks; experimental design and inference in networks; and methods for causal inference. His research often combines social science with advanced statistical methods. His notable publications include research on long ties in social networks and their relationship to economic prosperity, how network structure affects social contagions, and algorithmic transparency in social media platforms. His work has appeared in prestigious journals including PNAS and Nature Human Behaviour, and he has provided expert testimony before the US Senate on algorithmic ranking. Long ties, disruptive life events and economic prosperity (PNAS) Long ties accelerate noisy threshold-based contagions (Nature Human Behaviour) Algorithmic transparency and assessing effects of algorithmic ranking (Senate testimony) Eckles actively shares his research through social media platforms including Bluesky, Twitter, and Mastodon, as well as through his blog and contributions to the Gelman et al. blog. His work bridges academic research with practical applications in technology and policy.
Dr Luke Garrod is a Senior Lecturer in Economics at Loughborough University's Loughborough Business School. He holds a PhD, MPhil, and BA from the University of East Anglia. His research focuses on industrial organization, competition policy, consumer policy, and behavioral economics, with a particular emphasis on modeling firm incentives in imperfectly competitive markets. He received the International Journal of Industrial Organization Best Theoretical Paper Award 2019 for his work on collusion mechanisms. His book on hub-and-spoke cartels provides critical insights into antitrust enforcement strategies. Teaching responsibilities include Principles of Microeconomics (ECA002) and Industrial Economics (ECC005). He serves as an Associate Editor for the International Journal of the Economics of Business and contributes to economic consultancy through his role at Economic Insight. His research has explored topics such as cartel damages quantification, digital market regulation, and the interplay between consumer protection and competition policies. Key awards include the 2019 Best Theoretical Paper Award, reflecting his contributions to advancing antitrust and competition policy frameworks. His work bridges theoretical economic modeling with practical regulatory applications, addressing emerging challenges in global competition dynamics and digital economy policies.
Professor Andrew Murray is a leading academic in Law with expertise in New Media and Technology Law. He holds the position of Professor of Law at the LSE Law School and directs the LSE Law, Society and Technology Group. His research focuses on digital rights, AI ethics, and regulatory frameworks for emerging technologies. Murray has held roles including Fellow of the Royal Society for the Arts and advisor to the Saudi Arabian government on e-commerce law. He has advised parliamentary committees, including the House of Lords Communications Committee on digital regulation, and delivered the prestigious TMC Asser Lecture on AI and human agency. Education: LL.B. Hons from Edinburgh University (1994), followed by academic roles at Stirling University and LSE since 2000. Professional memberships include the Society of Computers and Law (SCL) and the Higher Education Academy (HEA). He has been a visiting professor at Amsterdam Law and Technology Institute and Sciences Po Paris. Research interests span cyberspace regulation, AI governance, and the intersection of technology with human rights. Key publications include Human Rights in the Digital Age (2004) and The Regulation of Cyberspace (2007). Awards include recognition as an Independent Expert in Nominet UK dispute resolution (2001–2008) and a 2024 Leibniz Prize reviewer. Advocacy includes contributions to EU e-commerce directives and UK surveillance law debates. His work emphasizes balancing innovation with legal accountability in digital spaces.
Dr. Oana Cocarascu is a Senior Lecturer in Artificial Intelligence at the Department of Informatics, Faculty of Natural, Mathematical & Engineering Sciences, King's College London. She holds a PhD and MEng in Computing (Artificial Intelligence) from Imperial College London and conducts applied research focusing on how artificial intelligence can be deployed to support real-world applications, with machine learning and natural language processing as core components of her work. Her research interests span argument mining, explainable AI, machine learning, natural language processing, and symbolic reasoning. She is particularly focused on developing AI systems that can provide transparent, accountable, and ethical decision-making processes. Her work addresses critical challenges in bias mitigation, fairness metrics, fact verification systems, and argumentation-based explanations for complex AI decisions. Analysis of her recent publications (2023-2025) reveals a strong focus on fairness in AI systems, with particular attention to individual fairness metrics and nuanced evaluation frameworks. She has made significant contributions to fact verification systems, especially in multimodal contexts involving charts and tabular data. Her work increasingly integrates argumentation theory with natural language processing to create explainable AI systems that can justify their decisions through structured reasoning. Dr. Cocarascu leads an EPSRC-funded project titled 'A framework for evaluating and explaining the robustness of NLP models' (2024-2027) and is actively involved in the Natural Language Processing Group at KCL. Her research fingerprint shows strong activity in argumentation (100%), decision-making (74%), artificial intelligence (50%), explainable AI (39%), and bias mitigation (35%). She has contributed to numerous high-impact publications in top venues including ACL, EMNLP, AAAI, and the Journal of Artificial Intelligence Research, with a particular focus on making AI systems more transparent, accountable, and aligned with human values. Her work intersects with UN Sustainable Development Goals, particularly those related to reducing inequality and building resilient infrastructure.
Malcolm McCulloch serves as Professor of Energy Systems and Group Leader of the Energy and Power Group within the Department of Engineering Science at the University of Oxford. He also holds the position of Co-Director for the Oxford Martin Programme on Integrating Renewable Energy and maintains affiliation with Christ Church college. His research spans four primary domains: domestic energy systems, electric vehicle technology, renewable generation, and energy solutions for developing regions. McCulloch's research focuses on practical energy transition challenges. His domestic energy work develops user-centric demand side management technologies and behavior change interventions, leading to the spin-out Intelligent Sustainable Energy (now Navetas Energy Management). In transportation, he pioneered the Morgan LifeCar hydrogen sports car project, resulting in high-efficiency motors and the Oxford Yasa Motors spin-out. His renewable generation research includes lightweight tidal turbines through Kepler Energy, while his Energy for Development work creates nano/micro grid solutions for distributed electrification. Analysis of his recent publications reveals a strong emphasis on integrating variable renewables through innovative market mechanisms, grid flexibility solutions, and electric vehicle integration. His work consistently addresses the technical and economic barriers to decarbonization, with increasing focus on peer-to-peer energy trading, thermal storage, and climate-resilient cooling solutions since 2020. McCulloch previously served as Co-Director of the Institute for Carbon and Energy Reduction in Transport (2008-2013) under the Oxford Martin School. His leadership extends to creating the Integrated Transport Network for Oxford and developing practical applications through multiple successful spin-out companies that bridge academic research and commercial implementation.
Professor Elaine Fahey is a leading scholar in EU law and global governance at the City Law School, City St George's, University of London, where she serves as Professor of EU Law and Deputy Head of Department (academic programmes). She is co-convener of the Institute for the Study of European Law (ISEL) and the UACES James Madison Trust EUFUtures initiative (2022–2025). Her academic career includes visiting professorships at Washington College of Law (American University), Keio University, and NYU, as well as fellowships at the European University Institute and the University of Graz. LLB, Trinity College Dublin LLM, Sidney Sussex College, University of Cambridge PhD, Trinity College Dublin Barrister-at-Law, Honorable Society of King’s Inns, Ireland Attorney-at-Law, State of New York Senior Fellowship, Higher Education Authority UK Her research focuses on the intersection of EU law with global governance, digital regulation, transatlantic relations, and the Area of Freedom, Security and Justice. She explores how the EU navigates legal frameworks beyond the nation-state, particularly in digital trade, cybersecurity, and data protection. Her work critically examines the EU’s role as a global regulatory actor and its interactions with international institutions. Her extensive publication record includes the monograph The EU as a Global Digital Actor (Hart, 2022) and numerous articles on digital sovereignty, data transfers, and transatlantic cooperation. Recent research analyzes the EU–US Trade and Technology Council (TTC), the evolution of the Privacy Shield, and strategic litigation in digital rights. Her work reveals a strong trend toward understanding how soft law, institutional design, and judicial decisions shape EU external relations and digital governance. Erasmus+ Jean Monnet Chair in Law & Transatlantic Relations (2019–2022) Emile Noël Fellow, NYU Law School Max Weber Fellow, European University Institute Senior Land Steiermark Fellow, University of Graz Senior Fellowship, Higher Education Authority UK Professor Fahey has supervised multiple PhD students, including Isabella Mancini, Giulio Kowalski, and Christos Karetsos, on topics such as algorithmic collusion, digital markets, and investment law. She has led significant research projects, including the ESRC-funded TRILATTRADE grant and the Marie Curie ITN on EU and Transatlantic Investment and Trade (EUTIP). She previously held leadership roles as Associate Dean (International) and interim Associate Dean (Research) at the City Law School. She is an elected member of the EU Studies Association (EUSA) Executive (2021–2025). She has also contributed to public policy through briefings for the Welsh Parliament and reports on CJEU litigation in Ireland. She is associated with research initiatives such as the Institute for the Study of European Law (ISEL) and has collaborated on interdisciplinary projects on Facebook regulation, transatlantic relations, and EU technological sovereignty. Her work bridges legal scholarship, policy, and international academic collaboration.
Adriana Tapus is a Full Professor at ENSTA Paris, affiliated with Institut Polytechnique de Paris, leading the Autonomous Systems and Robotics Laboratory (SAR) within the Computer Science and Systems Engineering Unit (U2IS). She holds an HDR (Habilitation) and a PhD from EPFL, Switzerland, with postdoctoral experience at USC. Her research focuses on socially assistive robotics, human-robot interaction (HRI), and personalized therapy for individuals with physical/cognitive impairments. She directs the IP Paris Doctoral School and coordinates national/international projects like the EU-funded ENRICHME and SWEET. Education: PhD in Mobile Robotics, EPFL (2005) Habilitation (HDR), ENSTA Paris (2011) M.S. Computer Science, University Joseph Fourier Engineer, Politehnica University of Bucharest Research Interests: Tapus pioneers socially assistive robotics, integrating machine learning, human modeling, and multimodal communication (verbal/non-verbal/para-verbal). Her work addresses adaptive therapies for vulnerable populations using robotics, physiological data interpretation, and context-aware interaction. Key themes include: Human-robot cooperation and trust Emotion recognition and expression Personalized rehabilitation systems AI ethics and human-centered design Publications: Over 150 articles, with recent work exploring humor in HRI, teleoperation trust models, and cross-cultural intelligent vehicles. Notable 2025 contributions include studies on robot laughter efficacy and multimodal facial expression frameworks. Awards: 2025: 4 IROS papers accepted 2016: 25 Women in Robotics recognition 2010: Romanian Academy Award Multiple conference best paper awards (RO-MAN, ICRA, etc.) Advising & Grants: Supervised over 20 PhD students and led projects like EU Horizon 2020 ENRICHME. Current students focus on teleoperation dynamics, robot humor, and haptic interfaces. Active in editorial roles (IJSR, THRI) and conference organization (HRI General Chair 2019). Labs/Teams: Founder of RoboticsByDesign lab and co-initiator of the Hi! Paris interdisciplinary AI center. The SAR lab develops systems for healthcare, education, and human-robot collaboration.
Associate Professor Kiat Boon, Daniel SENG is a leading academic at the National University of Singapore (NUS), specializing in technology law and infocommunications law. He currently serves as Director of the LLM (Intellectual Property & Technology Law) program and IT Coordinator. Previously, he held roles as Director of Research at the Singapore Academy of Law (2001–2003), partner and head of technology practice at Rajah & Tann, and non-residential fellow at Stanford Law School’s Center for Legal Informatics (CodeX). His education includes a JSD and JSM from Stanford University, BCL (Oxford, Rupert Cross Prize recipient, 1994), and LLB (NUS with first-class honors). His research employs machine learning, NLP, and big data to analyze digital law challenges, particularly in copyright takedown notices and AI governance. Research interests span information technology law, empirical legal studies, quantitative research, and AI’s intersection with legal reasoning. He contributes to global legal reform via advisory roles at the World Intellectual Property Organization (WIPO), focusing on copyright exceptions, music licensing, and intermediary liability. Key awards include the 1994 Rupert Cross Prize. His work bridges law and technology through publications on digital evidence, metaverse legal frameworks, and AI’s impact on private law. He is actively involved in shaping Singapore’s legal infrastructure through government committees and academic initiatives.
Alexis Battle is an Associate Professor at Johns Hopkins University with appointments in Biomedical Engineering , Computer Science , and Genetic Medicine (secondary). She directs the Malone Center for Engineering in Healthcare and serves as Deputy Director of the Data Science and AI Institute . Educated at Stanford University (PhD in Computer Science, 2013), Battle transitioned to academia after leadership roles at Google. Research Focus: Battle’s work bridges genomics and machine learning , emphasizing the impact of genetic variation on human health. Her lab develops tools like Watershed to predict functional effects of rare variants, aiming to enhance rare disease diagnosis. Key themes include non-coding DNA analysis , personalized genomics , and systems biology , with applications in cardiovascular disease and neurodegenerative disorders . Publications & Awards: Over 60 peer-reviewed articles in journals like Nature , Science , and Genome Biology , with recent emphasis on single-cell transcriptomics , multiomics integration , and telomere biology . Recipient of the President’s Frontier Award (2022), Microsoft Investigator Fellowship (2019), and Searle Scholar (2016). Scientific Awards: 2022 President’s Frontier Award 2019 Microsoft Investigator Fellowship 2019 Johns Hopkins Discovery Award 2017 Johns Hopkins Catalyst Award 2016 Searle Scholar Advising & Funding: Mentors 11 PhD students, 3 undergraduates, and postdoctoral fellows. Her research is funded by NIH, Searle Scholars, and institutional grants. The Battle Lab collaborates on projects like the GTEx Consortium , focusing on gene regulation and clinical genomics .
Martin T. Wells is the Charles A. Alexander Professor of Statistical Sciences at Cornell University, with joint appointments in the Department of Statistical Science, Department of Biological Statistics and Computational Biology, Department of Social Statistics, and as Professor of Clinical Epidemiology and Health Services Research at Weill Medical School. He serves as Editor-in-Chief of the ASA-SIAM Book Series and Co-Editor of the Journal of Empirical Legal Studies. Cornell University, Ithaca, NY Weill Cornell Medical College Research Interests span applied and theoretical statistics, Bayesian methods, biostatistics, clinical epidemiology, and computational biology. His work bridges disciplines like finance, legal studies, and health services research. Article Trends highlight advancements in Bayesian modeling, quantum cognition machine learning, tensor analysis, and misclassification correction, with applications in genomics, finance, and public health. Fellow of the American Statistical Association Fellow of the Royal Statistical Society Contributions include developing statistical software (e.g., rTensor), methodological innovations in clinical trials, and empirical legal studies on civil rights and the death penalty.
Charles M. Jones is a Professor of Finance at Columbia Business School, Columbia University, with an extensive publication record spanning several decades. His research focuses on market microstructure, high-frequency trading, short selling, retail investor behavior, and stock market liquidity. His work has appeared in top finance journals including the Journal of Finance, with his most recent publication "Nonstandard Errors" appearing in the June 2024 issue. Professor Jones's research interests center on understanding how financial markets function at a granular level. His work on market microstructure examines the mechanics of price formation, liquidity provision, and the impact of trading technologies on market quality. His research on short selling has been particularly influential, investigating when short sellers trade, what information they possess, and how regulatory interventions like short sale bans affect market functioning. His more recent work has explored the rise of retail trading through platforms like Reddit and its implications for price discovery, particularly during events like the GameStop phenomenon and the COVID-19 pandemic. Analysis of his publication trends reveals a consistent focus on market efficiency and price discovery mechanisms, with increasing attention to retail investor behavior in recent years. His work spans both theoretical modeling and empirical analysis of market data, often utilizing high-frequency datasets to examine intraday trading patterns. The interdisciplinary nature of his research bridges finance, economics, and information science, contributing to both academic understanding and practical market regulation. Professor Jones has collaborated extensively with researchers across the globe, as evidenced by his numerous co-authored papers with scholars from institutions worldwide. His work has significant implications for market regulators seeking to understand the impact of technological changes and regulatory interventions on market quality and efficiency.
Jyh-An Lee is a Professor and founding Executive Director of the Centre for Legal Innovation and Digital Society (CLINDS) at The Chinese University of Hong Kong (CUHK) Faculty of Law. He leads the New Ventures Legal Team (NVLT) and holds advisory roles at institutions like the European Center for E-Commerce & Internet Law and National University of Singapore. Education : JSD (Stanford), LLM (Harvard), MBA & LLB (National Taiwan University) Admissions : Practicing lawyer in Taiwan His research interests focus on Intellectual Property , AI and the Law , Law & Digital Technology , and Asian Law . He has contributed to landmark studies on NFTs, metaverse legal frameworks, cybersecurity, and IP litigation in Asia. The scientific awards he has received include: CUHK PhD IMPAC Award (2024-25) CUHK Vice-Chancellor’s Exemplary Teaching Award (2023, 2019) CUHK Outstanding Research Impact Award (2022-23) Numerous other university and faculty-level honors His work has been cited by major international courts and agencies. He is also a TRAIL Academic Fellow and active in policy advisory roles for Creative Commons and IP offices in Taiwan and Hong Kong.
Ali H. Sayed is the Dean of the School of Engineering (Faculté des sciences et techniques de l'ingénieur - STI) at École Polytechnique Fédérale de Lausanne (EPFL), Switzerland, where he also directs the Adaptive Systems Laboratory (Laboratoire de systèmes adaptatifs). Previously, he served as an emeritus professor and chair of the Electrical Engineering Department at UCLA. He is a highly cited researcher and a member of the US National Academy of Engineering and the World Academy of Sciences. Sayed served as president of the IEEE Signal Processing Society in 2018 and 2019. Professor Sayed's research focuses on adaptation and learning theories, data and network sciences, statistical inference, multi-agent systems, adaptive networks, and optimization. His work bridges theoretical foundations with practical applications in signal processing, machine learning, and network science. He has made significant contributions to distributed learning algorithms, social learning over networks, and adaptive signal processing techniques that have influenced both academic research and practical implementations. His recent publications demonstrate a strong focus on multi-agent systems, distributed learning, privacy-preserving techniques, and social learning over networks. The research trends show increasing emphasis on federated learning with privacy guarantees, graph-based learning approaches, and the intersection of social dynamics with information processing. His work consistently addresses fundamental theoretical questions while maintaining relevance to practical applications in communication networks, social media analysis, and distributed artificial intelligence systems. Professor Sayed has received numerous prestigious awards throughout his career, including: IEEE Fourier Award (2022) Norbert Wiener Society Award (2020) IEEE Signal Processing Society Education Award (2015) Papoulis Award from the European Association for Signal Processing (2014) Technical Achievement Award from IEEE Signal Processing Society (2012) Terman Award from the American Society for Engineering Education (2005) IEEE Donald G. Fink Prize (1996) Multiple Best Paper Awards from IEEE and EURASIP Sayed has authored or co-authored over 570 publications and six monographs. He has mentored numerous PhD students and researchers in the fields of signal processing and adaptive systems. His editorial leadership includes serving as Editor-in-Chief of IEEE Transactions on Signal Processing (2003-2005) and EURASIP Journal on Advances in Signal Processing (2006-2007), as well as Founding Editor-in-Chief of the Open Access Book Series on Information and Learning Sciences. At EPFL, Professor Sayed leads the Adaptive Systems Laboratory, which focuses on developing theoretical frameworks and practical algorithms for adaptive systems, networked learning, and distributed signal processing. The lab's research encompasses both fundamental theoretical investigations and applications to real-world problems in communications, social networks, and computational biology.
Tim G. J. Rudner is an Assistant Professor in the Department of Statistical Sciences at the University of Toronto, a Faculty Member at the Vector Institute, and a Title A Fellow at Trinity College, University of Cambridge. He was previously an Assistant Professor and Faculty Fellow at New York University. University: University of Toronto School: Faculty of Arts and Science Department: Department of Statistical Sciences Affiliation: Vector Institute, Trinity College (Cambridge) He holds a PhD in Computer Science and an MSc in Statistics from the University of Oxford, where he was advised by Yee Whye Teh and Yarin Gal, and a BS in Applied Mathematics and Economics from Yale University. PhD: Computer Science, University of Oxford MSc: Statistics, University of Oxford BS: Applied Mathematics and Economics, Yale University His research focuses on building robust, transparent, and trustworthy machine learning systems, particularly for high-stakes applications. He develops probabilistic models that improve generalization under distribution shifts, provide reliable uncertainty estimates, and enable fair and interpretable predictions. His work spans generative models, large language models, healthcare, and biomedical discovery. The recent publications highlight a strong trend toward function-space modeling, Bayesian regularization, and AI safety. Tim's work emphasizes principled uncertainty quantification, robustness to subpopulation and semantic shifts, and the development of frameworks for AI governance and specification. His research bridges theoretical advances with real-world applications, especially in safety-critical domains like medicine and defense. Tim has received numerous accolades including being named a Rhodes Scholar, Qualcomm Innovation Fellow, and 2024 Rising Star in Generative AI. He was awarded a $700,000 Foundational Research Grant and a $30,000 Apple Seed Grant for improving LLM trustworthiness. Rhodes Scholar Qualcomm Innovation Fellow AISTATS Notable Paper Award (2024) Outstanding Paper Award, ICLR GenAI4DM Workshop (2024) Apple Seed Grant ($30,000) Foundational Research Grant ($700,000) NeurIPS Spotlight Talk 2024 Rising Star in Generative AI He actively mentors students, particularly first-generation and low-income scholars, and has contributed to major policy frameworks including the OECD AI Classification Framework and a series of CSET issue briefs on AI safety. His work demonstrates a strong commitment to responsible AI development, combining technical rigor with societal impact. Tim leads research efforts at the intersection of machine learning theory and practical deployment, with ongoing projects in generative modeling, reliable LLMs, and AI governance. His lab produces high-impact work regularly published at top-tier conferences such as NeurIPS, ICML, and AISTATS.
