Dr. M.Z. Naser is an Assistant Professor in the Glenn Department of Civil Engineering at Clemson University. His research focuses on causal and explainable machine learning methodologies applied to structural engineering, materials science, and fire safety. He holds a PhD from Michigan State University and an M.S. from the American University of Sharjah. Naser teaches courses such as Machine Learning for Civil Engineers and Structural Fire Engineering, emphasizing interdisciplinary innovation. His work bridges data-driven analysis with domain-specific knowledge to address challenges in resilient infrastructure design, including fire-resistant materials, structural retrofits, and AI-driven decision-making. Education: PhD, Michigan State University; M.S., American University of Sharjah Research Themes: Explainable AI, Fire Engineering, Structural Materials, Causal Inference Key Projects: Developing SPINEX framework, wildfire classification models, and cognitive infrastructure systems Recent publications analyze over 1000 fire tests to uncover spalling mechanisms, explore synthetic fire tests via GANs, and benchmark automated ML platforms. His work on causal diagrams for civil engineers and firefighter algorithms highlights contributions to both theory and practical applications. Naser also advocates for integrating AI into engineering education, emphasizing ethical and transparent model deployment.
Tae Eun Kim is an Associate Professor in Maritime Safety Management at UiT The Arctic University of Norway, working within the Department of Technology and Security. Her research, teaching, and industrial collaboration focus on maritime safety and human factors, with particular expertise in maritime safety management, accident analysis, Maritime Autonomous Surface Ships (MASS), and human factors in maritime operations. Dr. Kim's research spans four interconnected domains: maritime safety management and leadership, maritime accident and casualty analysis, Maritime Autonomous Surface Ships (MASS), and human factors in maritime operations. She has developed assessment instruments like the Safety Leadership Self-Efficacy Scale (SLSES) and conducted STAMP-based causal analyses of maritime accidents. Her work on MASS addresses safety challenges in mixed navigational environments and examines leadership competencies for autonomous shipping operations. Her human factors research explores how technological advancements impact navigators' performance, crew dynamics, and safety outcomes, including gender parity issues in the maritime industry. Dr. Kim's publication record reveals a strong focus on the intersection of maritime safety, technology, and human performance. Her recent work increasingly addresses autonomous shipping technologies, with numerous publications on AI decision transparency, learning analytics in maritime simulator training, and multi-modal data analysis for nautical skill development. She has conducted systematic reviews on simulator training approaches and scenario design, contributing significantly to methodology development in maritime education and training. Her research demonstrates a clear trajectory toward integrating emerging technologies with traditional maritime safety practices as the industry transitions toward greater automation. Dr. Kim is actively involved in several significant research projects, including the i-MASTER EU Horizon Europe Research and Innovation Project, the REFRAME project, and the SPRICE project (Multidisciplinary approach for spray icing modelling). She is a member of both the Advanced Maritime Ship Operations research group and the Maritime Safety Science (MARSCI) Research Group, demonstrating her commitment to collaborative research in maritime safety science. Dr. Kim teaches several specialized courses at UiT, including SVF-3206 Safety Management and Accident Investigation, TEK-3014 Navigation Technology, MFA-2100 Maritime Digitalization, MFA-8010 Maritime HTO (Human-Technology-Organisation) and Innovation, and MFA-2018 Maritime Administration and Leadership. Her teaching portfolio reflects the interdisciplinary nature of her expertise, bridging engineering, safety science, and organizational behavior in maritime contexts.
Erik Scheme is an Associate Professor in the Department of Electrical and Computer Engineering at the University of New Brunswick (UNB), and serves as Associate Director of the Institute of Biomedical Engineering (IBME). He holds a PhD and is a Professional Engineer (PEng). His roles include advising the Dr. J. Herbert Smith Centre for Technology Management and Entrepreneurship, emphasizing innovation in biomedical technologies and healthcare systems. His research focuses on advanced human-machine interaction through biomedical engineering, with a strong emphasis on myoelectric prosthetics, wearable sensors, and machine learning applications. Key areas include improving neuroprosthetic control via incremental learning, gait analysis using underfoot pressure sensors, and developing robust EMG-based gesture recognition systems. His work bridges clinical needs with technological innovation, addressing challenges in rehabilitation, activity monitoring, and user-centric design. Recent publications highlight advancements in adaptive control systems, sensor fusion, and ethical data practices in healthcare. His contributions span both theoretical frameworks (e.g., self-supervised learning models) and applied technologies (e.g., gold-plated 3D-printed electrodes). Dr. Scheme collaborates across disciplines, integrating robotics, signal processing, and clinical validation to create impactful solutions. His lab, affiliated with IBME, actively explores emerging areas like exhaled breath analysis for disease detection and federated learning in healthcare data analytics.
Marina Freire-Gormaly is an Assistant Professor in the Mechanical Engineering Department at York University's Lassonde School of Engineering. Her research focuses on renewable energy-powered water treatment systems, machine learning for smart design, advanced manufacturing, and sustainable engineering solutions for remote communities. She holds a PhD and M.A.Sc. from the University of Toronto, specializing in carbon capture and storage technologies. She has worked on nuclear energy projects at Ontario Power Generation and contributed to World Bank sustainability assessments. She currently chairs the Canadian Society of Mechanical Engineers' Student and Young Professional Affairs committee. Education: PhD in Mechanical Engineering, University of Toronto M.A.Sc. in Mechanical Engineering, University of Toronto Research Interests: She pioneers solar-powered reverse osmosis systems, energy recovery mechanisms, and IoT-driven smart systems. Her lab explores nanotechnology applications in environmental sustainability, including carbon capture and aquatic remediation. She integrates machine learning for optimizing energy-water nexus challenges in off-grid regions. Key Contributions: Developed models for membrane fouling in desalination systems, advanced pore network characterization for geologic CO2 storage, and designed automated renewable energy systems. Her work bridges engineering innovation with global sustainability goals. Grants & Collaborations: Engages with industries like Honda Canada and Trane Canada on sustainability initiatives. Supervises graduate students in emerging areas like nanobubble technology and direct air capture systems. Lab Activities: The Freire-Gormaly Lab focuses on clean energy-water systems, with current projects involving nano-technology for space applications (Canadian Space Agency collaboration) and life cycle assessments of carbon storage technologies.
Victor Becerra is a Professor of Power Systems Engineering at the University of Portsmouth, affiliated with the School of Electrical and Mechanical Engineering within the Faculty of Technology. He is also associated with the Centre for Environmental and Renewable Energy Solutions and the Agile Centre For Equitable Sustainability. His research focuses on advanced control systems, renewable energy integration, smart grids, battery management, and nuclear power plant control. He actively supervises PhD students in topics like optimal control of battery systems and microgrid optimization. His academic work spans over 193 publications, with recent contributions emphasizing techno-economic analysis of green hydrogen, modular energy storage solutions, and optimal control strategies for batteries and nuclear reactors. His research often addresses real-world applications such as grid flexibility at ports, peer-to-peer energy trading platforms, and drone-based inspection of offshore wind turbines. Becerra's expertise includes developing control algorithms for marine structures, sodium-cooled reactors, and unmanned aerial vehicles. He has contributed to books on solar energy engineering and applications, highlighting interdisciplinary approaches to sustainability challenges. His work integrates theoretical models with practical implementations, such as energy management systems for compressed air and advanced BMS for drones. Key themes in his research include renewable energy systems optimization, fault-tolerant control mechanisms, and adaptive control strategies for dynamic environments. He collaborates internationally, addressing global energy challenges through innovative control methodologies and sustainable technologies.
Lei Liu, PhD, is a Professor of Biostatistics, Medicine, and Statistics and Data Science at Washington University in St. Louis. He holds positions in the Roy and Diana Vagelos Division of Biology & Biomedical Sciences (DBBS), the Institute for Informatics, Data Science and Biostatistics (I2DB), and the Center for Biostatistics and Data Science (CBDS). His research focuses on biostatistical and data science methods, including survival analysis, longitudinal data modeling, and machine learning applications in healthcare. He collaborates with clinicians across disciplines like cardiology, ophthalmology, and addiction medicine. Dr. Liu’s work emphasizes high-dimensional omics data analysis, medical cost modeling, and joint multi-outcome models. He is an Associate Editor of Biometrics and a former member of the NIH Biostatistical Methods and Research Design Study Section. He mentors underrepresented minority researchers through the NHLBI PRIDE program.
Frank Stajano is a Full Professor of Security and Privacy at the University of Cambridge, leading the Academic Centre of Excellence in Cyber Security Research. He is a Fellow of Trinity College, where he collaborates with Nobel laureates. His research focuses on security, privacy, and usability in ubiquitous computing, IoT, and digital finance. He holds a PhD from Cambridge and a Laurea in Electronic Engineering from La Sapienza University. Frank's work includes the Pico project (ERC-funded), aiming to replace passwords with secure, usable alternatives. He co-founded Cambridge Cyber, offering cybersecurity consulting. Notable achievements include the Resurrecting Duckling authentication protocol and contributions to location privacy (Mix Zones). He has authored over 50 refereed publications and a research monograph on ubiquitous computing security. His awards include the Toshiba Fellowship (2000) and an ERC Starting Grant (2017). Frank teaches cybersecurity and lectures globally via his YouTube channel. Beyond academia, he is a 5th-dan kendo practitioner and a scholar of Disney comics.
Shujun Li is a Professor of Cyber Security and Head of the Cyber Security Research Group at the School of Computing, University of Kent. He also holds a Visiting Professorship at the Department of Computer Science, University of Surrey. His research focuses on cyber security, privacy, AI applications, and human-centric computing. He leads the Institute of Cyber Security for Society (iCSS), a university-wide interdisciplinary research centre. Education: PhD in Information and Communication Engineering (Xi'an Jiaotong University, 2003), followed by postdoctoral research at City University of Hong Kong, Humboldt Research Fellowship at FernUniversität in Hagen, and a 5-year Zukunftskolleg Research Fellowship at Universität Konstanz. Research interests include cyber security (usable security, digital forensics, misinformation), AI safety, human factors, and socio-technical systems. He has published over 100 papers, with awards including the IEEE Guillemin-Cauer Best Paper Award and EPSRC recognition. Awards: Includes IEEE Transactions Best Paper Awards, EPSRC peer review recognition, and multiple conference best paper awards. Active in interdisciplinary projects like MACRO (cyber risks in mobility systems) and ACCEPT (reducing human-related cyber risks). Labs/Teams: Directs iCSS, co-founded Kent & Medway Cyber Cluster, and leads the Kent Interdisciplinary Research Centre in Cyber Security (KirCCS). Collaborates with industry and government agencies on cyber resilience and AI ethics.
Associate Professor Jason Thompson holds an Associate Professor position in the Department of Psychiatry at the University of Melbourne. He is affiliated with the Faculty of Medicine, Dentistry and Health Sciences and previously served as Co-Director of the Transport, Health and Urban Systems (THUS) Research Laboratory at the Melbourne School of Design. He earned a PhD in Medicine (2015) from Deakin University, a Master's in Clinical Psychology, and a Bachelor of Science with Honours. His research focuses on computational social science applied to injury rehabilitation, compensation systems, and healthcare design. He has attracted over $5M in research funding and published over 100 articles. Key areas include agent-based modeling, systems dynamics, and policy analysis for public health challenges such as pandemic response and urban mobility. Thompson currently leads the NHMRC Centre of Excellence in Compensable Injury after Road Crashes. Grants: ARC Future Fellowship (2022), DECRA (2017) Awards: Best Paper Award (Computational Social Science Society of the Americas, 2017) Labs: THUS Research Lab (until 2024) His work bridges epidemiological modeling (e.g., influencing Victoria's 2020 pandemic exit strategy) and complex systems analysis for injury prevention and health system design.
Anna Gautier is an Assistant Professor in the Department of Computer Science at Chalmers University of Technology, affiliated with the Division of Data Science and AI. Previously, she was a Digital Futures Postdoctoral Fellow at KTH Royal Institute of Technology (2023–2025), focusing on mechanism design for multi-robot systems. Her research emphasizes planning under uncertainty, multi-agent systems, and human-robot interaction. She holds a PhD from the University of Oxford (2023), an MSc from the London School of Economics, and dual undergraduate degrees from Washington University in St. Louis. Education Background: PhD in Computer Science, University of Oxford (2023) MSc in Applied Mathematics, London School of Economics BA in Mathematics and BS in Computer Science, Washington University in St. Louis Research Interests: Dr. Gautier explores planning algorithms for multi-agent systems, particularly in uncertain environments. She designs mechanisms to coordinate robots and humans, leveraging game theory and formal methods. Her work addresses challenges like resource allocation, risk-aware decision-making, and trust in autonomous systems. Recent projects include contingency planning for autonomous vehicles and auction-based resource distribution. Professional Activities: She co-chairs the ECAI 2025 Demonstration Track and teaches the course Safe Robot Planning and Control at KTH. Her projects include collaborations with WASP-Nest (PerCorSo) and TECoSA on trustworthy autonomy. She actively publishes in top venues like AAMAS and AAAI. Labs and Teams: Affiliated with Chalmers' Data Science and AI division, she leads research in multi-agent systems and human-AI collaboration.
Siddharth Garg is the Institute Associate Professor of Electrical and Computer Engineering at NYU Tandon School of Engineering, leading the EnSuRe Research Group. He holds a Ph.D. from Carnegie Mellon University (2009) and a B.Tech. from IIT Madras. His research focuses on secure and energy-efficient computing systems, integrating machine learning, cybersecurity, and hardware design. He previously held roles as Assistant Professor at NYU Tandon (2014-2020) and the University of Waterloo (2010-2014). Key affiliations include NYU Center for Cybersecurity (CCS), NYU Wireless, and the Center for Advanced Technology in Telecommunications. His work has been recognized with prestigious awards like the NSF CAREER Award (2015) and inclusion in Popular Science’s 'Brilliant 10' (2016). Notable research includes private inference optimization, secure hardware IP protection, and adversarial machine learning defenses. Publications highlight advancements in zero-knowledge proofs, AI-driven chip design, and mitigating backdoor attacks in neural networks. His grants include funding from NYU Wireless and NSF initiatives like the Chips4All project. The EnSuRe group emphasizes bridging software and hardware design gaps using AI and fostering cybersecurity education.
Dr. Céline Castets-Renard is a Full Professor in the Civil Law Section of the Faculty of Law at the University of Ottawa and holds the Canada Research Chair in International and Comparative Law of Artificial Intelligence. She also serves as the University Research Chair on Accountable AI in a Global Context (2020-2024) and is an affiliated researcher at ANITI (Toulouse) and Yale Law School's Internet Society Project. She previously held senior academic roles at Université Toulouse Capitole and was a visiting scholar at institutions including Fordham Law School and Osaka University. Her research focuses on digital technology and AI governance from an international and comparative law perspective, emphasizing EU, Canadian, and US frameworks. Key areas include AI law, data protection, digital copyright, platform regulation, and the intersection of technology with human rights, equity, and gender issues. She has authored over 100 articles, 2 monographs, and edited 4 books. Dr. Castets-Renard advises on EU initiatives such as the AI Office’s General-Purpose AI Code of Practice and the Digital Markets Act. Her work bridges legal scholarship with practical challenges in AI accountability, privacy, and transnational governance. Awards include the Honorary Junior Membership of the Institut Universitaire de France (2015-2019).
Gabe Kaptchuk is an Assistant Professor in the Computer Science Department at the University of Maryland, College Park (UMD), focusing on cryptography, privacy, and their social implications. He is affiliated with UMD's MC² (Maryland Cybersecurity Center) and UMIACS (Institute for Advanced Computer Studies). Previously, he was research faculty at Boston University and earned his PhD from Johns Hopkins University under advisors Avi Rubin and Matt Green. Research Interests: Kaptchuk's work bridges theoretical cryptography and social applications, emphasizing secure multiparty computation (MPC), zero-knowledge proofs, and steganography. He also explores the intersection of cryptography with law, policy, and human-centered design. Notable projects include Meteor (secure steganography using generative models) and Pulsar (MPC for dynamic participants). Teaching: Courses include Governing Algorithms (UMD) and Law and Algorithms (BU), focusing on algorithmic governance, privacy, and legal implications of technology. He has taught computer security and networks at Johns Hopkins and BU. Grants & Funding: Recent NSF awards include Collaborative Research: ReDDDoT Phase 2 (2024) for participatory privacy protections in AI training data. Active in deploying MPC for social good, such as analyses for Boston Women’s Workforce Council. Labs/Teams: Collaborates with researchers at Georgetown, Columbia, and institutions like the Wikimedia Foundation. Co-authors include Rachel Cummings, Elissa Redmiles, and Matthew Green on privacy and usability topics.
Bei Wu is Dean’s Professor in Global Health and Vice Dean for Research at the NYU Rory Meyers College of Nursing, where she also serves as Co-Director of the NYU Aging Incubator. She holds an additional appointment as Affiliated Professor in the Ashman Department of Periodontology & Implant Dentistry at NYU, reflecting her interdisciplinary expertise. She previously held the Pauline Gratz Professorship at Duke University School of Nursing, underscoring her national prominence in gerontology and nursing science. Her educational background includes a PhD and MS from the Gerontology Center at the University of Massachusetts, Boston, and a BS from Shanghai University. These foundational qualifications have supported her extensive research career focused on aging, global health, and oral-systemic health linkages. Dr. Wu’s research is centered on gerontology and global health, with a strong emphasis on oral health, dementia, cognitive decline, caregiving, and health disparities among minority populations, particularly older Asian Americans. She is a pioneer in studying the connections between oral health and cognitive outcomes in older adults. Her work integrates interdisciplinary approaches across nursing, dentistry, public health, and social sciences, often with a focus on vulnerable and underserved communities. Her recent publications reveal a consistent focus on the biological and social determinants of cognitive aging, oral frailty, caregiving burden, and mental health in older populations. Themes include the role of toothbrushing in preventing dementia, the impact of social capital on mental health, and the development of culturally tailored interventions for dementia caregivers. Her work often employs mixed methods, including systematic reviews, cohort studies, and qualitative inquiry. Distinguished Scientist Award for Geriatric Oral Research, IADR (2017) Pauline Gratz Professorship, Duke University (2014) J. Morita Junior Investigator Award (2007) Fellow, Gerontological Society of America Fellow, New York Academy of Medicine 2022 Wei Hu Inspiration Award Honorary Member, Sigma Theta Tau International Dr. Wu has successfully mentored hundreds of early-career scientists and has secured substantial funding from the NIH, CDC, and private foundations. She currently leads multiple NIH-funded projects, including a clinical trial on oral health in dementia and a large data analysis on diabetes and cognitive decline. She co-leads the Rutgers-NYU Center for Asian Health Promotion and Equity and directs the Research and Education Core for the NIA-funded Asian Resource Center for Minority Aging Research (RCMAR), which focuses on building research capacity and addressing health inequities. Her work is conducted through key labs and initiatives including the NYU Aging Incubator, the Rutgers-NYU Center for Asian Health Promotion and Equity, and the Asian Resource Center for Minority Aging Research (RCMAR). These centers support interdisciplinary collaboration, innovation in aging research, and the development of culturally appropriate health interventions.
Prof. Christoph Lütge holds the Peter Löscher Endowed Chair for Business Ethics at the TUM School of Social Sciences and Technology and directs the Institute of Ethics in Artificial Intelligence . He earned a PhD from TU Braunschweig (1999) and habilitation from LMU Munich (2005). Notable roles include a Heisenberg Fellowship (2007) and Distinguished Visiting Professorship at the University of Tokyo (2020–) . His research focuses on AI ethics, business ethics, and ethical challenges in autonomous systems. Education : Doctorate: TU Braunschweig (1999) Postdoctoral Qualification (Habilitation): LMU Munich (2005) Research interests span AI ethics , autonomous driving , and business ethics . He explores ethical frameworks for emerging technologies, regulatory governance, and societal impacts of AI. Recent work includes AI in healthcare, surveillance technologies, and hybrid work models. Awards : Heisenberg Fellowship (2007) Best Scientific Article Award (2020) Academic Membership at Tsinghua University (2021–) His advising and grant activities are not detailed here, but he collaborates with global institutions like AI4People and the German Ethics Commission for Automated Driving. His lab, the Institute of Ethics in AI, drives interdisciplinary research on ethical AI integration.
