Dr. Mohamed Khalifa is a Visiting Fellow at the Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney. He holds a PhD in Health Innovation from Macquarie University (2020) and an MSc in Health Informatics from the University of Edinburgh (2012). His expertise spans health informatics, AI-driven healthcare solutions, and strategic healthcare management. He has led multidisciplinary teams in developing evidence-based frameworks like GRASP for clinical predictive tools. Affiliations: Visiting Fellow, Macquarie University Director of Studies, College of Health Sciences (Education Centre of Australia) Former Digital Health Officer, Australian Digital Health Agency (2020–2021) His research focuses on AI applications in healthcare, clinical decision support systems, and health analytics. Over 20 years, he has published 60+ peer-reviewed papers and holds an innovation patent (2018). He has received awards including the IMIA Best Paper (2020) and ICIMTH Best Paper (2015). Dr. Khalifa’s work emphasizes improving healthcare efficiency through technology, including projects on predictive tools, emergency room performance, and diabetes management. He is a Fellow of the Australasian Institute of Digital Health and certified in healthcare information systems (CPHIMS).
Associate Professor Bruno Schivinski is affiliated with RMIT University's School of Media & Communication. He specializes in online consumer behavior, quantitative research methods, and multivariate data analysis. His work bridges digital media impact, consumer psychology, and health behavior, with a focus on gaming disorder, social media engagement, and brand equity. Education and professional background include roles at Gdansk University of Technology and consulting for institutions like the Polish Ministry of Science. He serves as Associate Editor for the Journal of Management and Business Administration–Central Europe . Research interests span digital phenotyping, behavioral addictions, and sustainable consumption. Notable contributions include studies on gaming disorder measurement, food waste reduction, and influencer marketing effectiveness. His work is published in top-tier journals like Journal of Business Research and Journal of Clinical Medicine . Recognition includes the Vice-Chancellor’s Award for Research Impact (2020), Emerald Literati Outstanding Reviewer (2022), and multiple best paper awards. He supervises research projects on digital behavior, food waste, and social media's role in health. Professional memberships include the Royal Statistical Society, Higher Education Academy, and American Marketing Association. His interdisciplinary approach addresses real-world challenges in digital health, consumer behavior, and sustainability.
Professor Karin Verspoor is the Dean of the School of Computing Technologies at RMIT University in Melbourne, Australia. She previously held roles as Director of Health Technologies and Deputy Head of the School of Computing and Information Systems at the University of Melbourne, and as Scientific Director of Health and Life Sciences at NICTA's Victoria Research Laboratory. Her research focuses on applying artificial intelligence methods to biomedical discovery and clinical decision support, particularly through natural language processing of clinical texts and biomedical literature. Affiliations: RMIT University (STEM College), Australian Alliance for Artificial Intelligence in Health (Victorian Node Lead) Industry Experience: Intelligenesis/Webmind Corp., Applied Semantics, Los Alamos National Laboratory, National ICT Australia Research Interests: Artificial Intelligence in Medicine Biomedical Natural Language Processing Health Informatics Computational Biology Cheminformatics Her work emphasizes cross-modal data integration, EHR analytics, and AI-driven clinical tools to address challenges in healthcare outcomes, musculoskeletal disorders, and infectious disease surveillance. Advising & Grants: Supervises research on AI-based decision-making frameworks, EHR data quality, and chemical knowledge extraction. Leads projects funded by initiatives like CANAIRI (Collaboration for Translational AI in Healthcare). Labs & Collaborations: Co-founder of the Australian Alliance for AI in Health, advancing national AI healthcare policy and translational research.
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.
Nicholas Vincent is an Assistant Professor in the School of Computing Science at Simon Fraser University. His research focuses on Human-Computer Interaction (HCI), Responsible Artificial Intelligence, and Human-Centric Machine Learning. He holds a Ph.D. in Technology and Social Behavior from Northwestern University (2022) and a B.Sc. in Electrical Engineering from UCLA (2016). Education: Ph.D., Northwestern University (2022); B.Sc., UCLA (2016) Affiliations: Simon Fraser University School of Computing Science His work examines the societal implications of AI, including data labor rights, algorithmic governance, and ethical design. Notable contributions include frameworks for measuring attentional agency on digital platforms and studies on collective action in tech contexts. He received the SIGCHI Outstanding Dissertation Award in 2024. Recent publications explore topics like AI ethics, governance of generative models, and Wikipedia's role in content ecosystems. He actively participates in policy discussions through media engagements and conference talks, advocating for public-oriented AI development.
Professor Chin Hoong Chor is a Professor in the Department of Civil Engineering at the National University of Singapore (NUS), affiliated with the Faculty of Engineering. He specializes in transportation systems modeling, safety assessment, and congestion management. As a registered professional engineer and road safety auditor, he has contributed to numerous projects with Singapore’s land authorities and private companies. He holds leadership roles including Vice Chairman of the Chartered Institute of Logistics and Transport and Editorial Board membership for the International Journal of Transport Management. Qualifications include a BEng and MEng from NUS and a PhD in Transportation Engineering from the University of Southampton. His research interests span vehicle detection using image processing, traffic conflict analysis, and public transport optimization. Notable awards include the NUS Faculty Innovative Teaching (Gold) Award (2001/2002) and the UK Institution of Civil Engineers Webb Prize (2003). Education: BEng in Civil Engineering, National University of Singapore MEng in Civil Engineering, National University of Singapore PhD in Transportation Engineering, University of Southampton His research focuses on quantitative safety analysis, traffic flow modeling, and smart city initiatives. Recent work explores maritime collision risk modeling and sentiment analysis for transportation planning. He actively contributes to government committees and has authored over 40 peer-reviewed papers on traffic management and safety. Awards: Faculty Innovative Teaching (Gold) Award, 2001/2002 UK Institution of Civil Engineers Webb Prize 2003 Prof Chin has undertaken traffic impact studies and road safety reviews in Singapore, collaborating with public and private sectors. His work bridges academic research and practical policy implementation, emphasizing sustainable urban mobility solutions.
Pablo Durango-Cohen is an Associate Professor of Civil and Environmental Engineering at Northwestern University, located in Evanston, IL. He holds a Ph.D. in Industrial Engineering and Operations Research from UC Berkeley, following an M.S. from the same program and a B.S. in Industrial and Systems Engineering from the University of Southern California. His research focuses on developing and analyzing optimization and econometric models for transportation infrastructure systems, integrating environmental design, life-cycle assessment, and policy analysis to address decarbonization challenges in freight systems. He also explores dynamic segmentation models for nonprofit fundraising strategies. Education: Ph.D. Industrial Engineering and Operations Research, University of California, Berkeley (2006) M.S. Industrial Engineering and Operations Research, University of California, Berkeley B.S. Industrial and Systems Engineering, University of Southern California Research Interests: Prof. Durango-Cohen’s work bridges transportation engineering, environmental science, and operations research. He emphasizes infrastructure management through data-driven frameworks, including statistical process control for condition monitoring and predictive maintenance. His recent projects address decarbonization of freight rail systems, electric vehicle impacts on road infrastructure, and optimal auction designs for road concessions. He also applies mathematical models to analyze donor behavior and fundraising efficiency in universities, aiming to improve nonprofit resource allocation strategies. Awards: NSF Faculty Early CAREER Development Award (2006) Young Author Prize, 2007 World Congress on Transport Research Matthew G. Karlaftis Best Paper Awards (2020–2025) Advising & Grants: He advises current PhD candidates including Jing Yu, Adrian Hernandez, and Callahan Skiles, while mentoring former students across sustainability, infrastructure, and fundraising analytics. His research is supported by agencies like the National Science Foundation, Department of Energy (through ARPA-E), and Department of Transportation. He co-leads the LOCOMOTIVES project with ANL researchers, focusing on decarbonizing rail networks, and founded the Virtual Inter-university Symposium on Infrastructure Management (VISIM) to foster academic collaboration. Labs & Teams: As Principal Investigator (PI) on major initiatives like LOCOMOTIVES and VISIM, he collaborates with multidisciplinary teams at Northwestern and Argonne National Laboratory. His group develops tools such as the Locomotives interactive dashboard and a computational framework for input-output lifecycle assessments, accessible via repositories like CivEnv304 .
Dae-Jin Lee is an Assistant Professor at IE University’s School of Science and Technology, specializing in statistical modeling and data science. Previously, he served as a Research Line Leader at the Basque Centre for Applied Mathematics (BCAM) and coordinated the Knowledge Transfer Unit in Data Science/AI. His academic background includes a Ph.D. in Mathematical Engineering (2010) from Universidad Carlos III de Madrid and postdoctoral research at CSIRO (Australia). His research focuses on statistical methods for complex data, including penalized splines, tensor product smooths, and applications in biomedicine, epidemiology, environmental science, and sports analytics. He has led multidisciplinary projects funded by public and industry grants, collaborating globally with experts across fields like engineering, medicine, and biology. Key research themes include predictive modeling for health outcomes (e.g., SARS-CoV-2 pneumonia severity), sports injury prevention, and AI in healthcare. His work integrates machine learning with traditional statistical techniques, addressing real-world challenges like pedestrian dynamics simulations and automated medical diagnostics. He is actively involved in scientific organizations, including the Spanish Biostatistics Society and the Statistical Modelling Society. His recent publications highlight innovations in growth curve modeling, AI ethics, and spatiotemporal data analysis, reflecting his commitment to advancing both theoretical and applied statistics.
Meeyoung Cha is a Professor at KAIST and Scientific Director of the Max Planck Institute for Security and Privacy (MPI-SP) in Bochum, Germany. Her research focuses on Data Science for Humanity, encompassing computational social science, misinformation dynamics, and human-machine interaction. She holds a PhD in Computer Science from KAIST (2008) and previously served as Chief Investigator at the Institute for Basic Science and Visiting Professor at Facebook. Her work addresses societal challenges such as poverty mapping, fraud detection, and AI ethics. Key achievements include best paper awards and recognition like the Hong Jin-Ki Creator Award (2024) and Test-of-Time Awards (ACM IMC 2022, AAAI ICWSM 2020). Research interests span AI ethics, social media analysis, and interdisciplinary applications of machine learning. Notable projects include modeling climate risks via satellite imagery and analyzing chatbot interactions' societal impacts. She leads the MPI-SP's Data Science for Humanity Group, mentoring over 20 students across PhD and postdoc programs. Education: PhD in Computer Science (KAIST, 2008) Affiliations: MPI-SP (Germany), KAIST Key Awards: Hong Jin-Ki Creator Award, Korean Young Information Scientist Award, Test-of-Time Awards Her publications bridge computational methods with societal issues, including climate modeling, protein engineering, and algorithmic fairness. Current projects explore geospatial AI for economic development and ethical AI design frameworks.
Kristian J. Hammond is the Bill and Cathy Osborn Professor of Computer Science at Northwestern University's McCormick School of Engineering. He directs both the Master of Science in Artificial Intelligence Program and the Center for Advancing Safety of Machine Intelligence (CASMI). His research focuses on artificial intelligence, natural language generation, narrative generation, conversational interfaces, and ethical AI applications across domains like law, education, and journalism. Hammond co-founded Narrative Science, leveraging AI for automated journalism from data. Education: PhD, MS, and BA in Philosophy (all from Yale University). His work spans technical innovation and societal impact, with notable contributions to AI transparency, bias mitigation, and machine learning ethics. Hammond has authored influential articles on AI governance, conversational systems, and the future of work in an automated economy. His leadership roles emphasize interdisciplinary collaboration between computer science, business, and humanities. Research highlights include developing AI systems that enhance human capabilities, exploring ethical frameworks for machine intelligence, and advancing AI safety through initiatives like CASMI. He frequently engages in public discourse via TEDx talks and commentaries on AI's societal implications, emphasizing the need for human-centered technology design.
Levi J Hargrove is an Associate Professor at Northwestern University, holding dual appointments in the Department of Physical Medicine and Rehabilitation at the Feinberg School of Medicine and the Department of Biomedical Engineering at the McCormick School of Engineering. He is also a Research Scientist at the Center for Bionic Medicine at Shirley Ryan AbilityLab. His work focuses on developing neural control systems for prosthetic limbs, particularly in myoelectric control and pattern recognition, aiming to create clinically viable solutions for amputees. Education: BScE in Electrical Engineering, University of New Brunswick, 2003 MScE in Electrical Engineering, University of New Brunswick, 2005 PhD in Electrical Engineering, University of New Brunswick, 2008 Research Interests: Signal processing, pattern recognition, myoelectric control of powered prostheses, and neural interfaces for bionic limbs. His lab translates research into clinical applications, such as the first thought-controlled bionic leg and Coapt LLC's pattern recognition systems for upper-limb prosthetics. Awards: 2017 American Academy of Orthotists and Prosthetists Research Award 2014 Department of Defense Outstanding Research Team Award 2015 Collaboration Award from Chicago Innovation Grants: Manages a $25 million portfolio from federal, military, and philanthropic sources. Key projects include NSF-funded research on human-robot interaction and DoD grants for prosthetic innovation. Labs: Leads the Regenstein Foundation Center for Bionic Medicine and collaborates with the Neurorehabilitation and Neural Engineering Lab. His work emphasizes translational research, bridging engineering and clinical practice.
Dr. Debraj Roy is a Visiting Professor at the University of Amsterdam (UvA), affiliated with the Faculty of Science, Mathematics and Computer Science and the Informatics Institute. His research focuses on agent-based modeling, socio-economic dynamics, environmental resilience, and blockchain technology. He investigates complex systems such as urban slums, disaster recovery, and climate adaptation using computational methods like remote sensing and machine learning. His work bridges theory and practice, offering insights into policy design for sustainable development and social equity. Key research interests include slum dynamics, poverty traps, and the application of blockchain oracles for decentralized systems. He employs advanced techniques such as global sensitivity analysis and manifold learning to explore multi-scale socio-environmental challenges. His recent articles highlight trends in carbon pricing, flood risk valuation, and multi-agent systems. Earlier work concentrated on urban inequality in cities like Bangalore and Mexico City, leveraging geospatial and statistical tools. No scientific awards or grants are explicitly listed. His advising and team collaborations are unspecified in the provided text.
Tridas Mukhopadhyay is the Deloitte Consulting Professor of e-Business at Carnegie Mellon University's Tepper School of Business, where he has served on the faculty since 1986. His academic journey at CMU progressed from Instructor of Information Systems (1986-1987) to Assistant Professor (1987-1993), Associate Professor (1993-1997), Professor (1998-present), and Deloitte Consulting Professor of e-Business (2000-present). He also served as Director of the MS in Electronic Commerce program from 1999-2004. Ph.D. in Computer and Information Systems, University of Michigan–Ann Arbor, 1987 M.B.A. in Computer and Information Systems, Indian Institute of Management Calcutta, 1981 B. Tech. in Electrical Engineering, Indian Institute of Technology Kharagpur, 1978 Professor Mukhopadhyay's research spans multiple critical areas in information systems and technology management. His work on strategic IT use examines how organizations derive business value from information technology investments. He has conducted extensive research on business-to-business commerce, particularly focusing on e-procurement systems, web-based marketplaces, and electronic intermediation models. His cybersecurity research investigates the economic aspects of cyber security, including liability mechanisms and patch release strategies. In software engineering, he has studied productivity, quality metrics, and offshore software development contracts. His most recent publications reveal several key trends in his research trajectory. There's a growing focus on digital platform economics, examining advertising models, virtual currency systems in gaming, and sharing economy dynamics. His work increasingly incorporates behavioral aspects, studying how users respond to personalized content and how backers exert control in crowdfunded projects. Methodologically, his research employs sophisticated analytical approaches including hierarchical Bayesian models, structural equation modeling, and natural experiment designs. CART Research Frontier Award, Carnegie Mellon, 2005 Distinguished Ph.D. Alum, Michigan Business School, 2004 Best Paper, International Conference on Information Systems, 2001 Best Paper, MIS Quarterly, 1995 Xerox Research Chair, Tepper School of Business, 1988-1989 Information Systems Society Distinguished Fellow, 2012 Professor Mukhopadhyay has served on numerous editorial boards including Information Systems Research (1994-2003), Management Science (1999-2003), and MIS Quarterly (1997-1999), demonstrating his significant contributions to the field. His consulting work with major organizations including Alcoa, Chrysler, Ford, General Motors, IBM, and governmental agencies like the United States Post Office and Pennsylvania Turnpike has provided practical insights that inform his academic research. He has been actively involved in university governance through committee service including the Business Technology Faculty Search Committee and the CMU Faculty Senate. His research has been supported through various industry partnerships and academic grants, though specific grant details aren't provided in the source material. His teaching focuses on Business Computing and Strategic IT courses, reflecting his expertise in both foundational information systems concepts and strategic applications of technology in business contexts.
Professor Damian Damianov holds the Chair in Finance at Durham University Business School. His research examines asset pricing anomalies, housing market dynamics, and household financial behavior, with particular focus on boom-bust cycles in real estate and cryptocurrency markets. Methodologies combine econometric analysis with behavioral experiments to study price formation mechanisms. Recent work investigates housing affordability policies, wealth accumulation pathways, and cross-market contagion effects. His laboratory develops novel experimental designs to test auction mechanisms and fundraising strategies for charitable organizations. Current projects analyze: (1) Property tax compliance in shared occupancy arrangements; (2) Uncertainty transmission across cryptocurrency markets; (3) Lifecycle models of household wealth management.
Dr. Jingyun Wang is an Assistant Professor in the Department of Computer Science at Durham University. Previously, she held an Assistant Professor position at Kyushu University, Japan. Her primary affiliations include the Centre for Neurodiversity & Development and the Artificial Intelligence and Human Systems Group (AIHS), as well as the Pedagogical Innovation in Computer Science Group (PICS). She is a Fellow of the Higher Education Academy and has led or contributed to research projects funded by JSPS, JST, NICT, Innovate UK, and industry partners. Her research focuses on AI-driven educational technologies, including AI-based feedback systems, computational thinking education, game-based learning, and ontology techniques. She actively contributes to editorial boards (e.g., Computers & Education: Artificial Intelligence ) and serves as a conference chair for AIED, ICCE, and LTLE. Current research includes adaptive learning systems for mathematics education, serious games for cybersecurity training, and visualization tools for e-learning. Her scientific contributions span over 50 peer-reviewed publications, with recent work emphasizing learning analytics, multimodal systems, and digital health interventions. She advises multiple PhD students and mentors in professional recognition pathways. Key projects include developing the BETTER speech training system, the MEMORABLE cybersecurity game framework, and ontology-based language learning platforms.
