Find Academic Supervisors

Andrew RobbView profile

Assistant Professor

• Virtual Reality
• Human-Computer Interaction
• User Behavior Analysis
• +3 more

Andrew Robb is an Assistant Professor in the School of Computing at Clemson University. His research focuses on the societal impact of consumer virtual reality (VR), including user behavior adaptation, avatar embodiment effects, presence in VR, and perception studies. Prior to Clemson, he earned his PhD in the Virtual Experience Research Group at the University of Florida. He is funded by the NSF CHS Small grant #1717937 and collaborates with researchers like Sabarish Babu and Chris Pagano. His work explores topics such as cybersickness mitigation, pedestrian-AV interactions, and VR's therapeutic applications for social anxiety disorders. Education: PhD in Virtual Experience Research, University of Florida Research Interests: Longitudinal effects of VR exposure on user behavior Avatar embodiment and its real-world behavioral implications Measuring and enhancing presence in VR environments Perception of space and motion in virtual vs. real-world contexts Human-VR interaction design for accessibility and safety Social and ethical considerations of emerging VR technologies Key Research Trends: His recent work emphasizes VR's impact on spatial cognition, cybersickness reduction through interaction design, and leveraging VR for mental health interventions. Over 2023-2024, he has published extensively on avatarization effects, near-field interactions, and pedestrian-AV dynamics in immersive environments. Grants & Lab: Hosts the McAdams Hall 120 lab and has NSF-funded research on longitudinal VR exposure effects. Collaborates with automotive engineering teams on VR-based autonomous vehicle interaction studies.

Michele GermaniView profile

Professor

• Industrial Engineering
• Ergonomics
• Sustainability
• +7 more

Prof. Michele Germani is a Full Professor at the Polytechnic University of Marche, Department of Industrial Engineering and Mathematical Sciences. His research focuses on ergonomics, sustainability, and human-centered design, with particular emphasis on industrial automation, wearable technologies, and circular economy principles. He leads projects on ergonomic risk assessment, environmental impact modeling, and smart manufacturing systems. Academic Background: Holds a position in the Faculty of Engineering, contributing to both teaching and research. His work integrates machine learning, sensor-based systems, and virtual reality to address challenges in manufacturing, healthcare, and sustainable design. Research Interests: Prof. Germani explores topics such as design for disassembly, eco-design tools, and the application of advanced technologies (e.g., exoskeletons, cobots) to enhance workplace safety and efficiency. His studies often bridge engineering and environmental science, aiming to reduce carbon footprints through innovative design methodologies. Key Projects: Development of decision support systems for fall risk detection, sensor-based ergonomic evaluation tools, and frameworks for circular economy implementation. He also investigates the impact of Industry 4.0 technologies on workforce dynamics and operator training via mixed reality simulations. Grants & Collaborations: Engaged in interdisciplinary collaborations focusing on sustainable manufacturing, healthcare technology, and smart systems. His research has led to tools like Durabot for durability analysis and Greenbuild for green building design. Labs & Teams: Oversees labs developing eco-design strategies, human-robot collaboration systems, and ergonomic assessment protocols, with a focus on real-world industrial applications.

Jon SensingerView profile

Professor

• Rehabilitation Engineering
• Prostheses
• Exoskeletons
• +4 more

Jon Sensinger is a Professor in the Department of Electrical and Computer Engineering at the University of New Brunswick and Director of the Institute of Biomedical Engineering (IBME). Based in R.N. Scott Hall 207, Fredericton, his research focuses on rehabilitation technologies. His work spans prosthetics, exoskeletons, computational motor control, and human-centered system optimization. The 'curiosity driven control' research stream explores adaptive interfaces that respond to user intent through novel learning algorithms. As IBME Director, he oversees interdisciplinary research bridging engineering, neuroscience, and clinical practice. This includes neural-machine interfaces, assistive device design, and rehabilitation robotics aimed at enhancing mobility and function.

Chao FanView profile

Assistant Professor

• Climate Change Adaptation and AI
• Dynamics of Integrated Socio-Environmental Systems
• Human Networks and Data Science
• +4 more

Dr. Chao Fan is an Assistant Professor in Civil Engineering and Environmental Engineering and Earth Sciences at Clemson University, affiliated with the Glenn Department of Civil Engineering. His research focuses on climate change adaptation, socio-environmental systems dynamics, and urban resilience, leveraging AI and data science. He holds a Ph.D. from Texas A&M University (2020), an M.S. from UC Davis (2017), and a B.S. from China University of Mining and Technology (2016). Dr. Fan's work integrates interdisciplinary approaches to address challenges in disaster management, smart cities, and environmental justice. Key interests include social sensing for infrastructure disruptions, equity in urban mobility networks, and leveraging digital twins for resilience planning. His recent publications explore topics like wildfire impacts, PM2.5 exposure inequity, and carbon market mechanisms for infrastructure adaptation. Professional memberships include ASCE, ACM SIGKDD, AGU, and AAAS. His lab (fanchaolab.com) develops innovative solutions for climate adaptation and equitable urban systems, emphasizing fairness in AI-driven models and network analysis.

Robert JacobView profile

Professor

• Human-Computer Interaction
• Brain-Computer Interfaces
• Implicit Interaction Techniques
• +3 more

Robert Jacob is a Professor of Computer Science at Tufts University's School of Engineering, where he leads research in human-computer interaction with particular focus on implicit brain-computer interfaces. His work bridges computer science, cognitive science, and interface design to create adaptive systems that respond to users' cognitive states without explicit input. His educational background includes a Ph.D. from Johns Hopkins University. Professional milestones include: ACM CHI Academy membership (2007) ACM Fellow designation (2016) Leadership roles as ACM SIGCHI Vice President and conference chair for CHI, UIST, and TEI Professor Jacob's research centers on implicit interaction techniques, particularly using fNIRS brain sensing to create adaptive interfaces. His work has evolved from foundational studies in reality-based interaction and tangible programming to current neuroadaptive systems that measure cognitive workload in real-time. This research spans domains including music learning, museum education, and general user interface adaptation. His publications reveal consistent focus on brain-computer interfaces since 2012, with increasing sophistication in physiological measurement and machine learning techniques. Recent work integrates multiple physiological signals beyond brain data to create comprehensive user state models. Major recognitions include: CHI 2016 Best Paper Award for music learning research CHI 2014 and 2012 Best Paper Honorable Mentions Keynote addresses at major conferences including Neuroadaptive Technology Conference (2017) Extensive media coverage in New Scientist, IEEE Computer, and Boston Globe Professor Jacob has mentored 17 PhD students who now hold faculty positions at institutions including Worcester Polytechnic Institute, Northwestern University, and Carleton University. His HCI Lab, located in the Joyce Cummings Center, receives funding from NSF and other sources supporting neuroadaptive interface research. Current projects focus on broadening implicit interaction to include multiple physiological measurements while maintaining user privacy and system transparency.

Kaitlyn CrawfordView profile

Associate Professor

• Soft Materials
• Flexible Electronics
• Sustainable Polymers
• +1 more

Kaitlyn Crawford is an Associate Professor of Materials Science and Engineering at the University of Central Florida, with a secondary appointment in Chemistry. She directs the Functional Materials and Sensors Lab, focusing on sustainable soft materials for flexible electronics and biomedical applications. Her research integrates polymer science and engineering to develop wearable sensors for health monitoring, biodegradable materials to reduce e-waste, and natural polymer composites. Current projects include a $1.5M DHS-funded wearable for firefighter heat-stress monitoring and NASA-funded space applications. Her recent publications emphasize sustainable polymers, bionic devices, and AI-driven diagnostics. Awards include the 2024 ACS PMSE Early Investigator Award and a Jewish National Fund fellowship. She leads multiple graduate students in biomedical and materials research. Awards: 2024 ACS PMSE Early Investigator Award Faculty Fellowship Program in Israel, Jewish National Fund Faculty Excellence Honoree, Women’s History Month (UCF)

Ji LiuView profile

Associate Professor

• Distributed Control
• Multi-Agent Systems
• Distributed Optimization
• +4 more

Ji Liu is an Associate Professor in the Department of Electrical and Computer Engineering at Stony Brook University. He is affiliated with the Department of Applied Mathematics and Statistics, the Institute for AI-Driven Discovery and Innovation, and the Institute for Engineering-Driven Medicine. He holds a Ph.D. from Yale University and completed postdoctoral research at the University of Illinois at Urbana-Champaign and Arizona State University. His research focuses on distributed control, multi-agent systems, distributed optimization, and cyber-physical systems, with applications to social networks, epidemic models, and quantum networks. Key areas of investigation include consensus algorithms, network topology design, and resilient reinforcement learning. Recent work explores topics like entanglement routing in quantum networks, decentralized multi-armed bandits, and bi-virus disease dynamics. His contributions span theoretical frameworks and practical implementations in domains such as smart grids, medical prosthetics, and secure microgrid control. Education: Ph.D. in Electrical Engineering, Yale University (201X) Postdoctoral Research: UIUC (Coordinated Science Lab), ASU (School of ECEE) Labs: Active in distributed systems, quantum control, and networked epidemic modeling

Christos NicolaidesView profile

Assistant Professor

• Data Science
• Machine Learning
• Social Networks
• +5 more

Christos Nicolaides is an Assistant Professor at the Department of Business and Public Administration within the School of Economics and Management at the University of Cyprus (UCY), holding a secondary appointment as a Digital Fellow at MIT's Initiative on the Digital Economy. Previously, he spent three years as a James McDonnell Foundation-funded Postdoctoral Fellow at MIT Sloan School of Management. His educational background includes a PhD in Engineering from Massachusetts Institute of Technology (2014), SM from MIT (2011), MSc in Applied Mathematics from Imperial College London (2009), and BSc in Physics from University of Thessaloniki (2008). Nicolaides' research applies mathematical, statistical, and computational tools to large-scale empirical questions in social influence mediated by digital technologies. His work spans Data Science , Machine Learning , Social Networks , and Computational Social Science , with significant contributions to understanding human mobility patterns, disease transmission dynamics, and social contagion effects. His research has established novel methodologies for analyzing complex network structures in mobility data and social interactions. Analysis of his 15 most recent publications reveals a consistent focus on applying network science to real-world problems, particularly in pandemic response (12 publications), human mobility analytics (9 publications), and social contagion dynamics (7 publications). His work demonstrates increasing interdisciplinary integration, combining computer science, epidemiology, and organizational behavior since 2020. Marie S. Curie Fellow Two Highly Cited Papers by Web of Science (2017, 2020) Best Paper Award by Risk Analysis Society (2019) Professor of The Week by Poets & Quants (2020) As principal institutional investigator, Nicolaides has secured over €1 million in research funding from the European Commission, industry partners, Cyprus Innovation and Research Foundation, and Cyprus Ministry of Health. His current teaching includes Social Networks and Entrepreneurship, Introduction to Operations Management, and Quantitative Methods in Management. Media coverage of his work spans major outlets including The New York Times, CNN, Nature, and Science, with significant impact on public health policy discussions during the COVID-19 pandemic.

Sudhakar GantiView profile

Associate Professor

• Cloud Computing Resource Management
• Software Defined Networking (SDN)
• Traffic Management and Quality-of-Service
• +3 more

Sudhakar Ganti is an Associate Professor in the Department of Computer Science at the University of Victoria, part of the Faculty of Engineering and Computer Science. He holds a PhD from the University of Ottawa. His research focuses on cloud computing resource management, software-defined networking (SDN), traffic management, quality-of-service optimization, and performance evaluation through queueing theory. His work bridges theoretical frameworks with practical applications in network efficiency and distributed systems. Dr. Ganti’s expertise includes optimizing resource allocation in fog-cloud systems, enhancing telehealth IoT energy efficiency, and developing dynamic defense frameworks for SDN security. His contributions span network traffic prediction, large file transport protocols, and formal verification of networking systems. He has published extensively in top-tier conferences and journals, addressing challenges in distributed computing, cyber security, and edge computing. His research trends emphasize leveraging reinforcement learning for fog-cloud resource allocation, multi-objective optimization in IoT, and SDN-driven network security. Earlier work includes foundational studies on optical router bypass, cloud workload characterization, and conversational agents for smart environments. Despite his prolific output, no academic awards or grants are explicitly mentioned in his profile.

Seth PolsleyView profile

Assistant Professor

• Human-Computer Interaction
• Intelligent Systems
• Educational Technology
• +4 more

Seth Polsley is an Assistant Professor in the Jeffrey S. Raikes School of Computer Science and Management at the University of Nebraska-Lincoln. His academic home resides in the School of Computing, where he bridges intelligent systems design with human-computer interaction to enhance educational and universal computing experiences. BS in Computer Engineering (2014) - University of Kansas MS (2017) & PhD (2023) in Computer Engineering - Texas A&M University His research explores: Intelligent tutoring systems Brain-computer interfaces Accessible educational technologies Machine learning for child development assessment Sketch recognition in STEM learning Recent publications demonstrate expertise in tactile learning interfaces, sketch-based developmental assessment, and equitable AI systems. Key disciplines span Human-Computer Interaction, Machine Learning, and Educational Technology. Scientific recognition includes: James Blackiston Memorial Graduate Fellowship Sigma Xi Research Award With professional experience at Lexmark International and MIT Lincoln Lab, Polsley combines practical engineering with educational innovation. His work on sketch-based tools and wearable systems addresses both technical and societal challenges in computing.

Eleonora OreggiaView profile

Lecturer

• Electronic Music
• Media Art
• Human-Computer Interaction
• +4 more

Eleonora Oreggia is a Lecturer in Electronic Music, Computing and Technology at Goldsmiths, University of London. She holds a PhD in Media & Arts Technology from Queen Mary University of London (2020), an MPhil in Cultural Studies from Goldsmiths (2013), and a Laurea (Summa Cum Laude) in Semiotics of Art, Drama, Art and Music Studies (DAMS) from the University of Bologna (2003). Her interdisciplinary work bridges science, humanities, and creative arts, focusing on electromagnetic sensing systems, expressive interaction in electronic music, and the intersection of identity with technology. Teaching roles include convening the BMus/BSc in Electronic Music, Computing and Technology, and courses like Music Computing 1, 2, and Advanced Audiovisual Processing. Her research explores invisible interfaces and electromagnetic fields as artistic tools, blending performance, installation, and live electronic music. She has exhibited globally in museums, festivals, and digital platforms, with notable projects like REBUS - Electromagnetic Interactions and Bamboo Ring Live . Key themes in her work include human-machine relations, perception of reality, and technomagical interfaces. She has collaborated with institutions such as BBC R&D, Jan van Eyck Academie, and founded Nebularosa Records to support experimental music. Her articles and books address topics like instrument design, digital creativity, and the philosophical implications of technology.

Paul NuyujukianView profile

Assistant Professor

• Motor Systems Neuroscience
• Neuroengineering
• Brain-Machine Interfaces
• +4 more

Paul Nuyujukian serves as an Assistant Professor of Bioengineering and Neurosurgery, with courtesy appointment in Electrical Engineering at Stanford University. He is a Faculty Scholar of the Wu Tsai Neurosciences Institute, directing the Brain Interfacing Laboratory where his team develops neural interface technologies for clinical applications in stroke and epilepsy. Education: MD, Stanford University (2014) PhD in Bioengineering, Stanford University (2012) BS, UCLA (2006) Dr. Nuyujukian's research integrates motor systems neuroscience with neuroengineering to decode brain activity during movement and recovery from injury. His laboratory pioneers brain-machine interface (BMI) platforms that translate neural signals into communication and control systems, with particular emphasis on intracranial EEG recording and real-time neural decoding. Current work focuses on developing clinically viable BMI solutions for neurological conditions through both preclinical models and human trials, advancing our understanding of neural population dynamics in health and disease. Recent publications reveal strong trends in intracranial EEG acquisition systems, seizure detection algorithms using information theory, and closed-loop BMI applications for ambulatory neuroscience. His work bridges fundamental neuroscience with clinical translation, particularly in epilepsy monitoring, chronic pain management, and neural prosthetics for paralysis. A notable emphasis exists on creating scalable, minimally invasive recording platforms that reduce clinical burden while maintaining high-fidelity neural data. Scientific Awards: No specific awards listed in provided materials As director of the Brain Interfacing Laboratory, Dr. Nuyujukian mentors students and collaborators in neural engineering research while securing grant funding for BMI development. His group maintains active collaborations with Stanford's Department of Neurosurgery and Neurology for clinical translation, with current projects including real-time decision-state decoding and personalized network mapping for pain management. The laboratory operates advanced facilities for both animal and human neural recording, emphasizing seamless integration of engineering innovation with clinical neuroscience. The Brain Interfacing Laboratory comprises multidisciplinary scientists and engineers developing next-generation neural interfaces. Current initiatives include the LiCoRICE platform for ambulatory neuroscience, seizure detection systems using compression-enabled entropy estimation, and ketamine's effects on hippocampal connectivity. The team actively participates in clinical trials for BMI applications in stroke rehabilitation and epilepsy, with strong partnerships across Stanford's medical and engineering schools to accelerate technology translation.

Nilanjan SarkarView profile

Professor

• Human-Robot Interaction
• Human-Computer Interaction
• Robotics
• +6 more

Nilanjan Sarkar is the Vice Dean and Senior Associate Dean for Faculty Affairs at Vanderbilt University's School of Engineering, holding the David K. Wilson Professorship in Engineering. He is a Professor in Mechanical Engineering, Computer Engineering, and Computer Science. His research focuses on intelligent systems for human interaction, including robotics, virtual/augmented reality, and assistive technologies for neurodevelopmental disorders and aging populations. Education: PhD (Mechanical Engineering, University of Pennsylvania), ME (Indian Institute of Science), BE (Indian Institute of Engineering Science and Technology, Shibpur). Research interests span human-robot interaction, sensor fusion, and rehabilitation engineering. His lab develops systems for autism intervention, stroke rehabilitation, and elderly engagement through socially assistive robotics and VR/AR. Notable projects include robot-mediated therapy for children and AR telepresence systems for long-term care facilities. Labs/Teams: Robotics and Autonomous Systems Laboratory. Key contributions include CoMove, RASSLE, and the Career Interview Readiness in VR platform. His work emphasizes participatory design with end-users for ethical and inclusive technology.

David J ReinkensmeyerView profile

Professor

• Neuroengineering
• Rehabilitation Robotics
• Motor Control
• +3 more

David J. Reinkensmeyer is a Professor at the University of California, Irvine (UCI), holding appointments in the Department of Mechanical & Aerospace Engineering (The Henry Samueli School of Engineering), Anatomy & Neurobiology (School of Medicine), and Biomedical Engineering. His research focuses on neurorehabilitation engineering, developing robotic and sensor-based technologies to enhance motor recovery after neurological injuries such as stroke and spinal cord injury. He leads interdisciplinary efforts in robotic therapy, sensor design for movement assessment, and computational models of motor learning. Key areas include: Design of robotic devices for upper/lower extremity rehabilitation Development of wearable sensors to monitor home exercise programs Studying motor adaptation and proprioception in clinical populations Optimizing neurorehabilitation interventions through computational modeling His work integrates biomechanics, machine learning, and clinical neuroscience to create practical solutions for disabling movement disorders. Recent projects explore scalable mRehab systems, data-driven diagnostics, and real-time feedback technologies. Funding sources include NIH grants (e.g., R01 HD062744) and industry collaborations. Over 200 peer-reviewed publications and numerous patents reflect his impact in translating engineering innovations into clinical practice.

James BellinghamView profile

Professor

• Autonomous Underwater Vehicles (AUVs)
• Marine Robotics
• Ocean Observing Systems
• +3 more

James Bellingham is the Bloomberg Distinguished Professor of exploration robotics at Johns Hopkins University, holding primary appointments in the Department of Mechanical Engineering and the Applied Physics Laboratory's Asymmetric Operations Sector. He serves as executive director of the Johns Hopkins Institute for Assured Autonomy and is a member of the Data Science and AI Institute. With over 30 years of expertise, Bellingham pioneered small, high-performance autonomous underwater vehicles (AUVs), leading global expeditions across polar and oceanic regions. His work bridges robotics innovation with environmental monitoring, including oil spill response, Arctic exploration, and NASA collaborations for extraterrestrial oceanic exploration. Bellingham's educational background includes BS, MS, and PhD in physics from MIT. He previously led Woods Hole Oceanographic Institution's Marine Robotics Consortium, creating advanced prototyping facilities and fostering entrepreneurship in robotics. His leadership roles span institutional boards such as the Naval Studies Board and OceanX. His research focuses on advancing AUV capabilities for adaptive sampling, fault detection, and interdisciplinary oceanography. Over 50 publications demonstrate his technical contributions, including AUV design, environmental hazard mapping, and collaborative robotic systems. Awards include National Academy of Engineering induction and military honors for public service.