Prithvi Ravi Kantan is a full-time Researcher at Aalborg University's Department of Architecture, Design and Media Technology within The Technical Faculty of IT and Design. His work focuses on developing sound-based and multimodal feedback systems for motor rehabilitation, integrating principles from music technology and biomedical engineering. Education: PhD in Embodied Sonification Design (2021-2023) M.Sc. in Sound and Music Computing (2018-2020) B.E. in Electronics and Telecommunications (2009-2013) Research interests include real-time auditory feedback systems for neurological rehabilitation, user-centered design of clinical technologies, and the application of generative music in data sonification. He actively contributes to projects like HearWalk (2023-2027), exploring sound-facilitated motor learning in cerebral palsy patients. Notable achievements include winning the Danish Sound Day Research Pitch Battle (2023) and receiving the Best Student Paper Award at ICAD 2024. His work aligns with UN SDG 3 (Good Health) and SDG 4 (Quality Education). Teaching responsibilities include coordinating bachelor and master-level courses in PBL-based learning, emphasizing interdisciplinary approaches. He has supervised multiple student projects and contributed to over 39 publications since 2013.
Saleh A. Alshebeili is a Professor in the Department of Electrical Engineering at King Saud University's College of Engineering, Riyadh, Saudi Arabia. With over 139 publications spanning from 1991 to 2024, his research demonstrates significant contributions across multiple engineering disciplines. His academic profile shows consistent collaboration with Saudi research institutions and international partners, particularly in communications and signal processing fields. Dr. Alshebeili's research interests span wireless communications, optical networks, radar systems, and biomedical signal processing. His work bridges theoretical signal processing with practical applications in 5G/6G communications, IoT security systems, and healthcare monitoring. The interdisciplinary nature of his research connects electrical engineering with computer science, particularly through machine learning applications for signal analysis and system optimization. His publications demonstrate expertise in both traditional signal processing techniques and emerging AI-driven approaches to engineering problems. Analysis of his recent publications (2021-2024) reveals a strong focus on next-generation communication technologies including 6G systems, optical wavelength conversion, and OAM-SDM communication. Simultaneously, he maintains active research in biomedical applications, particularly EEG signal processing for seizure detection and biometric authentication using physiological signals. His work consistently appears in top IEEE journals including IEEE Access, IEEE Transactions on Wireless Communications, and IEEE Journal of Biomedical and Health Informatics, reflecting the high quality and relevance of his research. Dr. Alshebeili has established extensive collaborations with researchers across King Saud University, particularly with Fathi E. Abd El-Samie (29 co-authored papers), Turky N. Alotaiby (22 papers), and Amr Ragheb (21 papers). These long-term collaborations suggest leadership in research groups focusing on communications systems and biomedical signal processing. His work spans theoretical development, simulation, and experimental validation, as evidenced by publications with 'Experimental Investigation' and 'Experimental Demonstration' in their titles.
Professor Moses Acquaah is a Professor and Department Head of Management at the Bryan School of Business and Economics, University of North Carolina at Greensboro (UNCG). He serves as Director of the PhD Program in Business Administration. His research focuses on strategic management, emerging economies, family businesses, and sustainability in Africa. He holds a Ph.D. in Strategic Management from the University of Wisconsin-Milwaukee and multiple advanced degrees from institutions like Simon Fraser University and the University of Cambridge. Education: Ph.D. in Strategic Management and International Management, University of Wisconsin-Milwaukee M.B.A. in Accounting & Policy Analysis, Simon Fraser University M.A. in Economics (Monetary and International Economics), Simon Fraser University Graduate Diploma in Development Studies, University of Cambridge B.A. (Honors) in Social Sciences, University of Science and Technology, Ghana Research Interests: Social capital and networking in emerging economies Competitive strategy in sub-Saharan Africa Family business management and entrepreneurship Sustainability and green supply chain practices Leadership in Africa and the diaspora Global strategic alliances and institutional pressures His recent work examines pandemic impacts on African businesses, innovation strategy combinations, and leadership effectiveness. He has published extensively in journals like Journal of Cleaner Production , International Business Review , and Africa Journal of Management . Key Contributions: Pioneered studies on family businesses in sub-Saharan Africa Developed the Leadership Effectiveness in Africa and the Diaspora (LEAD) scale Edited special issues on pandemic management and sustainable development in Africa
Drew R. Gentner is an Associate Professor of Chemical & Environmental Engineering at Yale University, with an additional appointment in the School of the Environment. His research focuses on air quality, atmospheric chemistry, and their intersections with climate, energy, and health. He holds a B.S. from Northwestern University and a Ph.D. from UC Berkeley. Affiliations: Yale School of Engineering & Applied Science, Yale School of the Environment Research Interests: Complex organic mixtures, urban air quality, non-traditional emissions (e.g., volatile chemical products), indoor air pollution, climate impacts of energy systems. Dr. Gentner leads the Gentner Research Group, which employs advanced analytical techniques and sensor networks to study atmospheric processes. Recent work highlights the role of asphalt and commercial cooking emissions in urban pollution. His team collaborates on large-scale field campaigns like AEROMMA and ASCENT. Key findings include identifying gaps in emissions reporting and demonstrating the health risks of aged wildfire smoke. His group develops low-cost sensors and calibration methods for high-spatiotemporal air quality monitoring. Grants & Funding: NSF, NOAA, EPA, and private foundations support his work on energy efficiency, sensor networks, and pollution mitigation. Labs/Teams: SEARCH Center at Yale, Atmospheric Science and Chemistry mEasurement NeTwork (ASCENT), and collaborations with Environment and Climate Change Canada.
Danny Poo Chiang Choon is a tenured Associate Professor at the School of Computing (SOC), National University of Singapore (NUS). As Curriculum Chair of the Department of Information Systems and Analytics, he plays a key role in designing and implementing Information Systems and Computer Science curriculum at NUS. Dr. Poo earned his BSc (Honours), MSc and PhD in Computation from the University of Manchester Institute of Science and Technology (UMIST), United Kingdom. His academic journey has established him as a leader in health informatics and information systems at NUS. His research spans multiple domains with strong focus on Healthcare Informatics , where he investigates mobile health interventions, health analytics, and systems for improving patient care. His work in Data Science & Business Analytics explores knowledge management, information sharing, and effective search strategies. In Intelligent Systems , he examines software engineering approaches, object-oriented systems, and knowledge classification frameworks. His recent publications demonstrate a clear trajectory toward mobile health applications, particularly in coronary heart disease prevention and diabetes management. Dr. Poo's work consistently bridges technical computing with practical healthcare applications, focusing on user-centered design and evidence-based interventions. His research shows strong interdisciplinary integration between computer science, healthcare systems, and behavioral science, with emphasis on practical implementation in Singapore's healthcare context. Dr. Poo has served in numerous leadership roles including as the founding Director of the Centre for Health Informatics at NUS (2012-2015) and as a member of the Steering Committee of the Asia Pacific Software Engineering Conference (APSEC) since 1994, serving as Vice-Chairman from 2003-2005. He has been invited to speak at international forums including the Japanese Government's "USA, Kyushu and Asia International Exchange Project" and as a keynote speaker at the 2009 Arabic Scripts Second Symposium in Abu Dhabi. His expertise is recognized through invitations to speak on knowledge management topics at conferences in Singapore. Dr. Poo has authored five books in the Information Technology area: "Enterprise JavaBeans for Students" (2014), "Object-Oriented Programming and Java" (1998, 2007), "Learn to Program Enterprise JavaBeans 3.0" (2009), "Learn to Program Java" (2009), and "Learn to Program Java User Interface".
Professor James Barlow is Co-Director of Imperial College London's Centre for Sectoral Economic Performance and holds a Professorship in the Department of Economics and Public Policy at the Imperial College Business School. He also serves as Academic Director for the MBA programme and Visiting Professor at Halmstad University (Sweden) and Honorary Professor at UCL Bartlett Real Estate Institute. His research focuses on structural challenges in healthcare innovation, housing, and construction sectors, with a particular emphasis on embedding innovations into healthcare systems. Barlow's education includes a background in geography and economics from the London School of Economics. He has held previous roles at the University of Westminster and Policy Studies Institute. His advisory work spans governments, healthcare organizations, and industries including medical technology and pharmaceuticals. He contributes to major initiatives like AGE-WELL (Canada) and the Industry Commons Foundation (Sweden). Research interests include healthcare innovation ecosystems, institutional logics, and frugal innovation. His recent book *Managing Innovation in Healthcare* synthesizes his work. He collaborates across disciplines, addressing challenges in telehealth, AI integration, and regulatory frameworks post-Brexit. Key affiliations include the Centre for Health Economics and Policy Innovation, Policy Innovation Research Unit (PIRU), and the NIHR Health Tech Research Centre. His work bridges academic research with practical policy and industry solutions, emphasizing scalable and sustainable business models.
Retsef Levi is the J. Spencer Standish (1945) Professor of Operations Management at the MIT Sloan School of Management, affiliated with the MIT Operations Research Center. He co-directs the Leaders for Global Operations (LGO) Program. His work focuses on data-driven decision models for healthcare systems, supply chain optimization, and risk management. Levi holds a PhD in Operations Research from Cornell University and has led industry collaborations with major hospitals and organizations like the FDA and Walmart Foundation. Education: PhD in Operations Research, Cornell University, 2005 Bachelor’s in Mathematics, Tel-Aviv University, 2001 Research Interests: Levi’s research addresses complex decision-making under uncertainty in healthcare, supply chains, and logistics. Key areas include food safety analytics, risk-based sampling, and predictive modeling for zoonotic diseases. He designs algorithms for inventory control, appointment scheduling, and healthcare resource allocation. Articles Overview: Recent work spans AI-driven epidemiological models, supply chain cybersecurity, and agricultural market interventions. His articles emphasize practical applications of operations research in healthcare and public health. Awards: NSF Career Grant INFORMS Optimization Prize (2008) Wagner Prize (2013) Harold W. Kuhn Award (2016) Advising & Grants: Advised 10 PhD students and 34 master’s students. Led multi-million-dollar projects like the Walmart Foundation initiative for China’s food safety. Active in hospital process optimization and FDA risk management contracts. Labs & Teams: Runs MIT’s Food Supply Chain Analytics and Sensing Initiative, collaborating with global partners on predictive risk tools and healthcare analytics.
Professor Axel Bruns is a Research Professor at Queensland University of Technology’s (QUT) Digital Media Research Centre (DMRC), an institution renowned for its leadership in media and communication studies. His work focuses on the digital transformation of media, the role of social media in public communication, and the dynamics of political polarization in online environments. Bruns is an internationally recognized innovator in computational methods for social media analysis, emphasizing interdisciplinary mixed-methods approaches to study complex societal phenomena. Research Interests: His research addresses critical challenges such as polarization’s threat to democracy, the role of algorithms in shaping public discourse, and the spread of disinformation. Notable areas include filter bubbles, platform governance, and the interplay between social media and political systems. He has pioneered concepts like 'gatewatching' to analyze news curation practices of digital intermediaries. Key Achievements: Bruns leads a prestigious Australian Laureate Fellowship project examining polarization drivers and dynamics. His work combines rigorous methodological innovation with policy relevance, evidenced by submissions to parliamentary committees on social media regulation. He has mentored numerous doctoral students who have become leading methodologists in their fields. Awards and Collaborations: Recipient of the Australian Laureate Fellowship (2023), Bruns collaborates widely with institutions globally, including Algorithm Watch, the Centre for Responsible Technology, and the Alexander von Humboldt Institute for Internet and Society. These partnerships enable cross-border research into digital media’s societal impacts.
Luigi Acerbi is an Associate Professor in the Department of Computer Science at the University of Helsinki, where he leads the Machine and Human Intelligence research group. He is also an active member of the Finnish Center for Artificial Intelligence (FCAI) and ELLIS (European Laboratory for Learning and Intelligent Systems). His research focuses on probabilistic machine learning and computational neuroscience, particularly on developing efficient methods for statistical inference, Bayesian models of perception, and resource-constrained rationality. His work bridges machine learning and cognitive science, with applications in Bayesian optimization, simulation-based inference, and image completion. The recent publications highlight a strong trend toward unifying probabilistic conditioning across diverse tasks using transformer-based meta-learning frameworks like the Amortized Conditioning Engine (ACE). These works emphasize amortized inference, flexible latent variable modeling, and the integration of prior knowledge at runtime, enabling efficient and scalable Bayesian methods for complex problems. Scientific Affiliations: University of Helsinki, Department of Computer Science Finnish Center for Artificial Intelligence (FCAI) ELLIS (European Laboratory for Learning and Intelligent Systems) Education: PhD in Computational Neuroscience, Doctoral Training Centre, Edinburgh, UK Advisor: Sethu Vijayakumar and Daniel Wolpert Visiting work at Computational and Biological Learning Lab, Cambridge Postdoctoral Experience: Alex Pouget’s lab, University of Geneva, Switzerland Wei Ji Ma, New York University, USA Collaboration with the International Brain Laboratory Luigi Acerbi mentors PhD students including Daolang Huang and Nasrulloh Loka, and collaborates widely with researchers such as Samuel Kaski. He has contributed to open-source tools like PyVBMC and is involved in community initiatives such as the EurIPS conference. His work is supported by grants from the Research Council of Finland, Business Finland, and the UKRI Turing AI World-Leading Researcher Fellowship. He leads a research lab focused on amortized probabilistic inference, with ongoing projects including PriorGuide and Stacked VBMC, aiming to make Bayesian methods more practical and accessible for real-world scientific and engineering applications.
Sanjeev Dewan is a Professor of Information Systems and Associate Dean of Masters Programs at the Paul Merage School of Business, University of California, Irvine. He also serves as Faculty Director of the Master of Science in Business Analytics program. Prior to joining UCI in 2001, he held faculty positions at the University of Washington and George Mason University. PhD, University of Rochester MS, University of Rochester Bachelor of Technology, Indian Institute of Technology, Delhi His research focuses on the economics of digital platforms , social and mobile analytics , and the valuation of technology investments . He investigates how information technology creates business value, impacts consumer behavior, and influences firm performance. His work spans electronic markets, Web 2.0 technologies, IT productivity, and the digital divide. The most recent publications reveal a strong emphasis on empirical analysis of digital platforms , including studies on gender bias in open source communities, quality certification in the sharing economy (e.g., Airbnb), personalized ranking in app stores, and mobile health applications. His research frequently uses large-scale datasets to examine behavioral patterns, market dynamics, and the economic implications of IT innovations. Faculty Service Award for 2023-24, UCI Paul Merage School of Business Best Paper Award, INFORMS 2019 e-Business Cluster Faculty Service Award for 2016-17, UCI Paul Merage School of Business Best Paper Award, INFORMS Conference on Information Systems and Technology (2009) INFORMS Service Award (2009) INFORMS Certificate of Appreciation (2008) Beta Gamma Sigma Honor Society (1991) University of Rochester Fellowship (1985–1990) Sanjeev Dewan has advised numerous PhD students who have secured faculty positions at leading institutions such as the University of Wisconsin-Madison, HKUST, Penn State, and the University of Hong Kong. His editorial service includes senior editor roles at Information Systems Research and associate editor at Management Science . He has also chaired tracks at ICIS and served as program co-chair for PACIS. There is no indication of external grant funding in the provided text, but his sustained publication record and leadership roles suggest significant research activity and institutional support. He is actively involved in academic leadership and research dissemination, contributing to major conferences and editorial boards. His work bridges theory and practice, particularly in digital platform ecosystems and analytics-driven decision-making.
Brent Doberstein is an Associate Professor in the Department of Geography and Environmental Management at the University of Waterloo, Faculty of Environment. His research and teaching focus on disaster risk reduction, climate change adaptation, and sustainable resource management, particularly in developing countries across Asia and in Canada. His research interests include: Hazards and disaster risk reduction Climate change adaptation and managed retreat Post-disaster reconstruction and institutional capacity building Sustainable resource and environmental management Parks and protected areas Over the next five years, he is particularly interested in supervising graduate students in themes related to disaster risk reduction, climate adaptation, and managed retreat. His recent publications reflect a strong emphasis on community resilience, policy evaluation, and cross-national comparisons, especially in Southeast Asia and Canada. Key trends in his work include the integration of local knowledge, social equity in disaster recovery, and innovative frameworks like the PARA model for flood risk management. His scientific contributions are recognized through publications in leading journals such as International Journal of Disaster Risk Reduction , Climate and Development , and Disasters . Dr. Doberstein actively supervises graduate students, many of whom are co-authors on his recent publications. He has taught courses including GEOG101, GEOG306, GEOG356, and led field research in Indonesia. He has also been involved in research projects related to flood recovery in Canada and post-disaster adaptations in countries like the Philippines, Bangladesh, and Thailand. He leads research initiatives centered on post-disaster adaptations at individual, community, and national levels, often working with interdisciplinary teams and international collaborators. His work contributes significantly to policy development and community resilience planning in vulnerable regions.
Robin A. Murphy is a Professor of Experimental Psychology at the University of Oxford and a Fellow and Tutor for Admissions at Corpus Christi College. He holds a PhD from McGill University (Canada) and has contributed over 50 scientific publications on associative learning mechanisms, their role in mental disorders like depression and psychopathy, and translational neuroscientific applications. His research bridges animal and human learning, with a focus on computational psychopathology and neurochemical modulation (e.g., serotonin). Education: Undergraduate degree, Queen's University MA and PhD in Psychology, McGill University Research Interests: Dr. Murphy investigates how associative learning processes underpin mental disorders, particularly through neurochemical systems like serotonin. His work explores causal reasoning biases in depression, psychopathy's learning deficits, and translational models linking animal studies to human cognition. Key themes include agency perception, contingency judgment, and the neural substrates of prejudice. Recent projects involve peptide research in aging and computational modeling of multi-agent systems in depression. Grants and Funding: Supported by MRC, BBSRC, Wellcome Trust, and Japan Society for the Promotion of Science. He has advised UK Research Councils and NSERC (Canada). Labs and Teams: Leads a lab focusing on associative learning mechanisms, collaborating with institutions globally on computational psychopathology and translational neuroscience.
Samuel W.K. Wong is an Associate Professor in the Department of Statistics and Actuarial Science at the University of Waterloo. He holds a Ph.D. in Statistics from Harvard University (2013) under Prof. Samuel Kou. His research focuses on statistical methodology for complex data science challenges in protein structure modeling, dynamic systems inference, and reliability engineering of wood-based products. He has held academic positions at the University of Florida (2013–2018) and has been at Waterloo since 2018. His research interests include Bayesian computation, statistical inference for dynamic systems, and spatial-temporal data analysis. Notable contributions include the development of manifold-constrained Gaussian processes (MAGI package) and sequential Monte Carlo methods for protein folding studies. He has advised over 15 graduate students and researchers, many of whom are now in academic or industry roles worldwide. Wong has received teaching distinctions at Harvard and holds awards including the Nash Medal (2008) for academic excellence. His work bridges computational statistics with applications in bioinformatics, structural engineering, and environmental science. He has published extensively in top-tier journals like Journal of Computational and Graphical Statistics and Biometrics , and collaborates with wood scientists to improve real-time lumber quality assessment using laser imaging data. His teaching portfolio includes courses on probability theory, statistical inference, and spatial data analysis at both undergraduate and graduate levels. Beyond academia, he maintains an active passion for classical piano performance, having performed recitals combining music with his statistical research interests.
Stephanie Rogers is an Assistant Professor of Geosciences at Auburn University's College of Sciences and Mathematics, specializing in geospatial technologies and environmental applications. She leads the GeoIDEA Lab, focusing on GIScience, water quality modeling, and environmental impacts on honey bee colonies. Her research integrates emerging technologies like drones for ecological monitoring and addresses interdisciplinary challenges such as groundwater management and pollution tracking. Education: PhD in Geosciences from the University of Fribourg, Switzerland. Research Interests: Rogers' work bridges geospatial innovation with real-world problem-solving. Key areas include: GIS-driven environmental monitoring and modeling Drone-based assessment of water quality and algal blooms Groundwater contamination dynamics and public health implications Honey bee colony health through spatial analysis Advising & Grants: Currently mentors two trainees (Bethany Foust and Mallory Jordan) and collaborates on projects funded by environmental agencies. Her grants focus on geospatial data integration for ecological decision-making. Labs/Teams: GeoIDEA Lab coordinates multidisciplinary efforts in environmental geoscience, with active projects in Alabama's Black Belt region and international glacial archaeology initiatives.
Professor Albert Cheng is a faculty member in the Department of Computer Science at the University of Houston. His research focuses on real-time systems, cyber-physical systems, smart cities, and embedded systems with societal impacts. He has authored over 270 publications and a textbook on real-time systems. Cheng holds roles as an Associate Editor for the IEEE Transactions on Knowledge and Data Engineering and ACM Computing Surveys. His research interests span real-time scheduling, machine learning applications, and systems optimization. Recent work includes vehicular traffic modeling for epidemiological risk reduction, quantum computing response time analysis, and satellite mission planning. Awards include Fulbright Specialist, Distinguished ACM membership, and IEEE Senior Member status. Cheng’s articles demonstrate expertise in real-time scheduling algorithms, cyber-physical systems development, and smart city infrastructure. His contributions bridge theoretical computer science with practical implementations in transportation, healthcare, and aerospace domains. Ongoing efforts include fault-tolerant systems, energy-efficient scheduling, and CPS education initiatives. Awards: Fulbright Specialist, ACM Distinguished Member, IEEE Senior Member, Institute of Physics Fellow Labs/Teams: Hewlett Packard Enterprise Data Science Institute (HPE DSI), Research Computing Data Core (RCDC)
