Find Academic Supervisors

Sean LarawayView profile

Professor

• Behavior Analysis
• Human Factors
• Motivating Operations
• +3 more

Sean Laraway is Professor of Psychology at San José State University and Director of the SJSU-NASA Human Factors Project at Ames Research Center. His research integrates behavior analysis with human factors engineering to study learning, motivation, and performance in applied settings. Key areas include motivating operations, consumer decision-making, aviation safety, and online education effectiveness. He directs research collaborations with NASA on air traffic control systems, aviation displays, and pilot performance. Educational innovations include studies of Udacity partnerships and self-adapted testing formats. Professional service includes editorial roles for behavior analysis journals and NSF review panels. Honors include the College of Social Sciences Teaching Excellence Award (2014) and Outstanding McNair Scholars Mentor recognition (2009). He holds certification as an Ergonomic Assessment Specialist and affiliations with ABAI, HFES, and APA divisions.

• Autonomous Vehicles
• Educational Technology
• Computational Thinking
• +4 more

Dr. Abdu Arslanyilmaz is a Chair Professor in the Department of Computer Science, Information, & Engineering Technology at Youngstown State University (YSU). His research focuses on autonomous vehicle safety, inclusive computing education for students with autism spectrum disorders (ASD), and game-based learning methodologies. He holds a Ph.D. from Texas A&M University (2007). His work includes groundbreaking studies on driver readiness in autonomous vehicles, hazard perception systems for young drivers, and accessible computing curricula for neurodiverse learners. Notable contributions include the NSF-funded 'ISAC' project (2020-2023) aimed at involving ASD students in computing, and NVIDIA's DRIVE PX 2 GPU platform collaboration for multi-user driving simulations. Dr. Arslanyilmaz has been recognized with YSU's Distinguished Professor awards (2021, 2022) and the 2020 Best Paper Award at the International Traffic and Transportation Simulation Conference. His research spans computational thinking assessment via eye-tracking, online learning effectiveness, and task-based language learning technologies. Grants: NSF STEM+C Partnership ($286,526), NVIDIA DRIVE PX 2 GPU Platform collaboration Awards: 3 YSU Research Professorships (2011-2019), Best Paper (2020) Key Areas: Autonomous vehicle safety systems, inclusive education technologies, multi-user simulation design His lab develops innovative educational tools and safety systems, bridging gaps between technology, education, and human factors.

Mohamad El-HajjView profile

Associate Professor

• Data Mining
• Databases
• Data Warehousing
• +5 more

Dr. Mohamad El-Hajj is an Associate Professor in the Department of Computer Science at MacEwan University. He holds a PhD from the University of Alberta (2006) and a Master's from the Lebanese American University (1998). His research focuses on applying data mining techniques to real-world domains such as healthcare, engineering, education, and sports analytics. His expertise spans databases, data warehousing, AI, parallel programming, and e-learning systems. Educational Background PhD in Computer Science, University of Alberta (2006) M.Sc. in Computer Science, Lebanese American University (1998) Bachelor's in Computer Science, Beirut Arab University (Lebanon) Research Interests Dr. El-Hajj specializes in leveraging data mining for practical applications. His work bridges computational methods with societal challenges, including health informatics (e.g., predicting user behavior in health apps), sports analytics (e.g., NBA performance modeling), and urban data analysis (e.g., traffic patterns and crime prediction). He also explores parallel computing and database optimization for large-scale datasets. Recent Trends in Publications His recent work emphasizes interdisciplinary applications: 2023–2025 articles address smart grid energy profiling, sports strategy optimization, and pandemic policy analysis. Earlier contributions (2003–2017) focus on foundational data mining algorithms, including parallel pattern mining and constraint-based techniques. Professional Engagement He actively participates in conferences like IEEE ICDM and ACS/IEEE AICCSA. His teaching includes courses on database systems and data mining methodologies. Advising & Collaboration Open to supervising senior student research projects, though no current advisees are listed. No grants or lab affiliations explicitly mentioned.

Theophilus BensonView profile

Professor

• Cloud computing
• Distributed systems
• Networking
• +5 more

Theophilus Benson is a Professor of Electrical and Computer Engineering at Carnegie Mellon University's College of Engineering. He holds a B.S. from Tufts University, M.S. and Ph.D. from the University of Wisconsin-Madison, and a post-doctorate from Princeton University. His research focuses on democratizing digital infrastructure access, particularly in the global south, through projects like the 'Democratizing Mobile Web Performance' initiative and KubeKlone/Nimble frameworks. He leads efforts at Carnegie Mellon University Africa to bridge the digital divide via collaborations with Internet Society and local IXPs. Research Interests: Cloud computing and distributed systems Programmable infrastructures (eBPF) Global network equity and policy impacts Mobile web optimization under memory constraints Sustainable development goals (SDG 9) Key Achievements: SIGCOMM Test of Time Award NSF CAREER Award Google/Facebook Faculty Awards Lead DARPA ISAT study group member Recent work includes analyzing subsea cable vulnerabilities in Africa, presenting at ACM Internet Measurement Conference 2024, and developing frameworks like KubeKlone for cloud-native simulations. His research bridges technical innovation with societal impact, addressing both performance and accessibility challenges in global networks.

Bill EllisView profile

Research Fellow

• Koala Ecology
• Wildlife Conservation
• Genetics
• +3 more

Dr Bill Ellis is a Research Fellow at the School of the Environment, The University of Queensland. He holds a BSc (Zoology) and Master of Environmental Law from ANU, and a PhD in Zoology from UQ (1998). His postdoctoral work included a fellowship at San Diego Zoo's Centre for Research on Endangered Species (2011). His research focuses on koala ecology, conservation, and management, integrating applied and theoretical approaches to address ecological challenges such as habitat use, climate impacts, and disease dynamics. Education: BSc Zoology (Honours), Australian National University Master of Environmental Law, Australian National University PhD Zoology, University of Queensland (1998) Research Interests: Ellis studies koala behavior, population dynamics, and conservation strategies. Key areas include: Habitat use and spatial dynamics Climate variability and heat load adaptation Disease transmission (e.g., chlamydia, koala retrovirus) Ecological impacts of urbanization and land use Application of bioacoustic and GPS technologies Grants & Collaborations: Supported by San Diego Zoo, Brisbane City Council, and Queensland government projects Focus on applied conservation, such as reducing roadkill and managing fragmented populations Key Contributions: Ellis has advanced understanding of koala vocal communication, thermal physiology, and disease ecology. His work directly informs land management and policy decisions to ensure sustainable ecosystems for koalas.

• Physics-Informed Machine Learning
• Structural Health Monitoring
• Computer Vision Applications
• +5 more

Zhilu Lai is an Assistant Professor at The Hong Kong University of Science and Technology (Guangzhou). He previously worked as a Postdoctoral Researcher at ETH Zurich's Chair of Structural Mechanics and Monitoring (2018-2020) and as a Senior Assistant with the Dynamic Mobile Sensing Platform team at the Singapore-ETH Centre (2020-2022). His research bridges physics-based modeling and machine learning. Research Interests Physics-informed machine learning for dynamical systems Computer vision in structural monitoring Variational inference with physical constraints Hybrid frameworks for structural health monitoring (SHM) Energy-preserving neural architectures Applications in bridge monitoring and wind turbine dynamics Scientific Contributions Developed symplectic encoder frameworks for nonlinear dynamics modeling Proposed physics-guided Deep Markov Models (PgDMM) for hysteretic systems Integrated neural ODEs with physics-based eigenmodes for high-dimensional SHM Created robust algorithms for bridge weigh-in-motion and influence surface identification

• Sustainable Transport Systems
• Energy Economics
• Environmental Economics
• +3 more

Dr. Truong Truong is an Honorary Professor of Sustainable Transport Systems at the University of Sydney’s Institute of Transport and Logistics Studies. He holds degrees in electrical engineering, economics, law, and a PhD in economics. His career spans academia and industry, including roles as a Visiting Associate Professor at Purdue University and a Marie Curie Fellow at the German Institute for Economic Research (DIW). He has also been a Fellow at the Hanse Wissenschaftskolleg Institute for Advanced Study in Germany. Research interests include sustainable transport systems, energy-economy-environment modeling, computable general equilibrium analysis, climate change mitigation strategies, and transport infrastructure policy. His work bridges theoretical economic frameworks with applied policy analysis, particularly in the context of global trade and environmental sustainability. Key achievements include contributions to congestion modeling, electricity sector technology substitution, and the integration of discrete choice models into spatial economic analysis. His publications span journals like Energy Economics and Journal of Transport Geography , alongside conference proceedings and book chapters. He has received prestigious fellowships, including the Marie Curie International Incoming Fellowship and a residency at the Hanse Wissenschaftskolleg. His research has informed policy debates on transport infrastructure, climate change adaptation, and sustainable energy systems.

Kajsa WeibullView profile

Researcher

• Traffic Psychology
• Human-Computer Interaction
• Cognitive Science
• +1 more

Kajsa Weibull is a researcher at the Department of Computer and Information Science at Linköping University , affiliated with the Human-Centered Systems division. Her work focuses on driver behavior , emergency vehicle interactions , and intelligent transport systems . Her research emphasizes traffic psychology and human-computer interaction in road safety contexts, particularly through studies on driver gaze behavior, geofencing, and warning system design. Recent publications highlight cooperative ITS, emergency vehicle visibility, and lighting effects on traffic dynamics. Key trends in her work include collision avoidance , cognitive load analysis , and driver alert optimization , aligning with broader themes in transportation safety and human factors.

Monicque LoristView profile

Professor

• Cognitive Neuroscience
• Healthy Ageing
• Mental Fatigue
• +6 more

Monicque Lorist is a Full Professor of Psychology at the University of Groningen's Faculty of Behavioural and Social Sciences, affiliated with the Department of Experimental Psychology. She leads research on cognitive and neural dynamics underlying human performance variability, with a focus on healthy ageing, mental fatigue, and caffeine's cognitive effects. Her work combines behavioral measures and neuroimaging (EEG, fMRI) to study attention, memory, and reward processing. Education: Bachelor's and Master's in Psychology at University of Groningen PhD from University of Amsterdam Postdoctoral research at University of Groningen's Medical Physiology Department Research Interests: Healthy ageing, mental fatigue, attention mechanisms, caffeine effects, gender differences in stress response, sensory perception of food, and reward processing. She explores how brain dynamics adapt to cognitive demands across ages using multi-method approaches. Key Contributions: Pioneered studies on object-based attention variability, neural feedback during probabilistic learning, and the impact of mental fatigue on typewriting performance. Her work bridges cognitive neuroscience and applied research in ageing populations. Awards: Heymans Collaboration Fund (2018) ERI-HSF Travel Award (2012) Best Poster Awards (2012, 2011) Teaching & Supervision: Leads courses in Biopsychology, Cognitive Neuroscience, and EEG methods. Supervises BA, MA, and PhD students in Psychology and Neurosciences programs, including Research Master’s in BCN. Lab Affiliations: Member of the School for Behavioural and Cognitive Neurosciences (BCN), contributing to interdisciplinary projects on brain-cognition interactions.

• Applied Microeconomics
• Economics of Education
• Labour Economics
• +1 more

Jeffrey Penney, PhD, is an Associate Professor in the Department of Economics at the University of Alberta, Faculty of Arts. His research focuses on Applied Microeconomics, Economics of Education, Labour Economics, and Law and Economics. He teaches courses such as ECON 378 (Law and Economics) and ECON 399 (Introductory Econometrics). Penney’s work explores topics like educational interventions, sentencing policies, and labor market dynamics. He is affiliated with the Laboratorio de Economía de la Educación and can be reached via penney1@ualberta.ca or dr.jeffrey.penney@gmail.com. His research interests emphasize empirical analysis of education systems, labor markets, and legal frameworks. Notable studies include investigations into teacher diversity impacts, scholarship efficacy, and migration effects on earnings. Penney’s methodologies often involve econometric analysis and experimental designs to evaluate policy outcomes. His recent work addresses issues like test score normalization challenges and the long-term effects of cramming on academic performance. Publications span topics from criminal sentencing distributions to the socioeconomic implications of educational programs, reflecting his interdisciplinary approach to microeconomic research. He maintains an active scholarly profile with ongoing contributions to peer-reviewed journals and policy-relevant studies.

• Marine Cybernetics
• Autonomous Systems
• Underwater Robotics
• +5 more

Asgeir Johan Sørensen is a Professor of Marine Control Systems at NTNU's Department of Marine Technology, Faculty of Engineering. He also serves as an adjunct professor at UiT the Arctic University of Norway. His roles include Director of NTNU VISTA CAROS and former Director of NTNU AMOS (2013-2023). Sørensen holds an MSc (1988) and PhD (1993) in Marine Technology and Engineering Cybernetics from NTNU. He has extensive industry experience, co-founding companies like Marine Cybernetics AS, Eelume AS, and Zeabuz AS. His research focuses on marine robotics, autonomous systems, and hybrid power systems. He leads labs such as the Marine Cybernetics Laboratory (MC-Lab) and Applied Underwater Robotics Laboratory (AUR-Lab), emphasizing innovation and entrepreneurship. Over 280 publications and 153 students (41 PhDs) reflect his scholarly impact. Current projects include Oppdrag Mjøsa, aiming to map freshwater ecosystems via autonomous systems. Education: MSc (Marine Technology, NTNU, 1988), PhD (Engineering Cybernetics, NTNU, 1993) Research: Autonomous marine operations, underwater robotics, marine cybernetics, and zero-emission propulsion systems Labs: MC-Lab, AUR-Lab, NTNU AMOS His work bridges fundamental research with practical applications, driving advancements in marine autonomy and sustainability.

• High Performance Computing
• Cloud Computing
• Interconnection Networks
• +3 more

Ernst Gunnar Gran is an Associate Professor at the Department of Information Security and Communication Technology at the Norwegian University of Science and Technology (NTNU), where he leads the communication technology discipline. He also holds an adjunct research scientist position at Simula Research Laboratory, focusing on High Performance Computing (HPC) and cloud computing. Education: M.Sc. and Ph.D. in Computer Science from the University of Oslo (2007, 2014) Research: Intersections of HPC, interconnection networks, enterprise data centers, cloud computing, and data-intensive multi-cloud processing His recent work addresses real-time anomaly detection in IoT systems, traffic speed prediction for transportation networks, and adaptive routing in HPC environments. Articles span machine learning, network security, and distributed computing, with a focus on lightweight, self-adaptive algorithms. Current projects include leadership of the RCN-funded eX3 infrastructure project and contributions to the EU H2020 Melodic initiative. He has designed the NorNet Core testbed and holds patents in network reconfiguration and cloud architecture.

Stavros KalafatisView profile

Professor

• Datacenter System Optimization
• SDN/SDS/SDI Technologies
• Robotics in Manufacturing
• +4 more

Stavros Kalafatis is an Associate Department Head and Professor of Practice in the Department of Electrical and Computer Engineering at Texas A&M University, part of the College of Engineering. He holds an M.S.E.E. from the University of Arizona (1991) and a B.S.E.E. from the University of Surrey (1989). His research focuses on datacenter system optimization, SDI/SDN/SDS improvements for server efficiency, robotics in manufacturing, and sensor systems for agricultural applications. He has received multiple awards, including the Intel Achievement Award (2005) and repeated Intel Divisional Recognition Awards (1993, 2000–2010). His work spans cutting-edge technologies like precision agriculture robotics, network performance optimization, and machine learning-driven systems for hydroponics and wildfire prediction. Recent publications emphasize interdisciplinary solutions in agriculture, networking, and environmental modeling. Kalafatis is affiliated with the Computer Engineering and Systems Group at Texas A&M and contributes to advancing practical applications of engineering and computing. Education: M.S.E.E., University of Arizona, 1991 B.S.E.E., University of Surrey, 1989 Awards: Intel Achievement Award (Lynnfield Team), 2005 Intel Divisional Recognition Award (multiple years) His research trends highlight innovations in smart systems, including digital twins for manufacturing, AI-driven crop monitoring, and network optimization for data centers. While no grants or advising records are explicitly listed, his publications reflect active collaboration with industry and academic partners.

Jing FengView profile

Professor

• Human Factors Engineering
• Cognitive Psychology
• Driving Safety
• +3 more

Jing Feng is a Professor of Psychology at North Carolina State University within the College of Humanities and Social Sciences, specializing in the Human Factors and Applied Cognition Program. Her research integrates cognitive theories of attention with practical applications in transportation safety and interface design. She holds a Ph.D. in Cognitive Psychology from the University of Toronto (2011), with postdoctoral training at Baycrest's Rotman Research Institute and the University of Toronto's Mechanical and Industrial Engineering department. Her multidisciplinary work focuses on aging drivers' visual attention, driver-automation interaction, and cognitive training. She directs the Applied Cognitive Psychology Lab, which develops tools like the SWAVF task to assess visuospatial attention during walking and evaluates robotic prosthesis user preferences. Her research also explores the impact of in-vehicle displays and non-safety messages on driver behavior. Key career milestones include the Earl Alluisi Award (2021) and APA Fellow designation (2023). She has mentored students in human factors engineering and cognitive science, with notable contributions to driver distraction mitigation and interface design for aging populations. Current projects investigate automated vehicle monitoring systems and virtual reality applications in spatial skill training. Notable Awards: 2023 APA Fellow, 2021 Earl Alluisi Award, 2023 Undergraduate Mentorship Award Labs: Applied Cognitive Psychology Lab (http://www.jfenglab.com/) Key Research Themes: Driver Safety, Human-Machine Interaction, Aging Cognition

Yu FuView profile

Researcher

• Neuroscience
• Metabolic Regulation
• Feeding Behavior
• +3 more

Yu Fu is a Group Leader at the Singapore Bioimaging Consortium (SBC), part of A*STAR. He holds a PhD in Neuroscience from Stony Brook University and conducted postdoctoral research at the University of California San Francisco, focusing on neuroimaging techniques in behaving mice. In 2014, he was awarded the A*STAR Investigatorship and established his lab at SBC in 2015. His primary research investigates neural mechanisms of metabolic regulation, particularly feeding behavior. Additionally, his work spans structural engineering and civil infrastructure, leveraging machine learning for predictive modeling and real-time monitoring systems. Education: PhD in Neuroscience, Stony Brook University Postdoctoral Training, University of California San Francisco Research interests include interdisciplinary applications of AI in bioimaging, structural health monitoring, and extraterrestrial habitat simulations. Key contributions include edge intelligence systems for infrastructure assessment and modular virtual testbeds for space habitats. His work bridges neuroscience and engineering through innovative data-driven methodologies. Notable Achievements: A*STAR Investigatorship (2014) Pioneered GABAergic neuron imaging techniques in mouse visual cortex Developed xImpact and xShake systems for infrastructure monitoring His lab’s research integrates neural mechanisms with advanced engineering solutions, addressing challenges in both biological systems and built environments. Current projects focus on metabolic regulation pathways and AI-driven infrastructure resilience strategies.