Find Academic Supervisors

Varadraj GurupurView profile

Associate Professor

• Health Informatics
• Decision Support Systems
• Data Semantics
• +3 more

Varadraj Gurupur is an Associate Professor at the University of Central Florida (UCF) in the School of Global Health Management and Informatics. He holds a Ph.D. and has over 15 years of teaching experience across two countries. His research focuses on software engineering decision support systems for healthcare and education, with a particular emphasis on health informatics, decision support systems, and data semantics. He has received numerous awards, including the AHIMA Triumph Award for Innovation (2021) and the Joseph M. Biedenbach Outstanding Engineering Educator Award (2023). Dr. Gurupur has authored over 100 peer-reviewed publications, including journal articles, conference papers, and book chapters. He has secured research grants and holds three patents in health information management. His work addresses challenges in electronic health records (EHRs), telehealth, and data quality, with applications in diabetes care, dental imaging, and frailty assessment in aging populations. He is active in IEEE, having chaired the Workgroup on Data Quality for EHRs and served as Chair of the IEEE Orlando Section (2021–2023). Key contributions include developing AI-driven decision support systems, improving EHR data completeness through neural network models, and advancing telemedicine frameworks. His interdisciplinary research bridges clinical needs with technological solutions, emphasizing global health equity and patient-centric care.

Hua DongView profile

Professor

• Inclusive Design
• User-Centered Design
• Human-Computer Interaction
• +6 more

Professor Hua Dong is a leading academic in inclusive design at Brunel University London , serving as Full Professor in Design, Director of Brunel Design Research Centre, and Inaugural Dean of Brunel Design School (2020-2024). She was elected Vice-Chair of the Design Research Society (DRS) in 2024, is a Fellow of DRS, and will chair QAA's Art and Design Subject Benchmarking Statement in 2025-26. Research Expertise: Dong pioneers inclusive design theory and application across industrial, engineering, architectural, and service design domains, with a focus on AI-powered products, mHealth for aging populations, and multisensory design. Her work bridges academia and industry through projects like the Design Bugs Out Challenge and collaborations with Ant Financial, Shanghai M&G Stationery, and UK-China initiatives. Scientific Contributions: She has secured major grants including an EPSRC grant and Newton Funds . Her publications span 2007-2024, covering AI-enhanced design ideation, service ontology for aging populations, and sustainable inclusion frameworks. She co-founded the Inclusive Design Research Centre in China and curated a special issue on inclusive design for Design magazine. Scientific Awards: Fellow of Design Research Society (2019) AHRC SEED Fellowship Member of Peer Review College of AHRC Teaching & Leadership: Dong holds a PGCert in Academic Practice and has shaped design education through co-design methodologies. She has supervised 14 PhD and 1 EngD student completions, organized the Cambridge Workshop for Universal Access since 2014, and served as External Examiner at Imperial College. Global Impact: As International Judge for SDGs Design Awards and advisor to UK charities (AgeUK), governments (Nanjing), and corporations (Reckitt Benkiser), she translates design research into tangible societal benefits. Her work has been exhibited at international venues including the Milan Triennale and Zurich Design Museum .

Maitreyee DeyView profile

Research Fellow

• Machine Learning
• Artificial Intelligence
• Low Carbon Technologies
• +9 more

Dr. Maitreyee Dey serves as a Visiting Fellow in Mechanical Engineering and Design and works as a Post-doctoral research fellow at London South Bank University's Department of Electrical and Electronics Engineering. She concurrently holds the position of Data Mining Lead at Neuville Grid Data Management Limited, where she contributes to significant energy research projects. Her research expertise spans machine learning/artificial intelligence and low carbon technologies, with additional interests in pattern recognition, big data analysis, deep learning, image processing, energy optimization in smart buildings, renewable energy technology, and Computer-aided Diagnosis for smart health applications. Her work directly contributes to UN Sustainable Development Goals related to clean energy and sustainable communities. Analysis of her recent publications reveals a strong research trajectory focusing on two primary domains: power grid analysis using machine learning techniques and microwave-based medical imaging for breast cancer detection. Her work demonstrates sophisticated applications of neural networks and data mining methods to solve complex problems in both energy systems and medical diagnostics. Best Paper Award at the CUE conference, Elsevier (2020) Endorsement by the Royal Academy of Engineering Dr. Dey serves as an Editorial board member for MDPI journals and as an Adhoc reviewer for high-impact publications including IEEE transactions and Nature Scientific Data. She is actively involved in the Access to Innovation (A2i) and Low Carbon London (LCLDN) projects funded by the EU commission through its regional development Fund, working in collaboration between London South Bank University and Neuville Grid Data Management Limited. Her professional affiliations include active membership in IEEE, CIGRE NGN, and the Energy Institute, demonstrating her engagement with key professional organizations in her fields of expertise.

Hong QinView profile

Professor

• Computer Graphics
• Geometric Modeling
• Physics-Based Modeling
• +5 more

Hong Qin is a Full Professor (with tenure) in the Department of Computer Science at Stony Brook University, where he is also a member of the Center for Visual Computing. He holds a B.S. and M.S. from Peking University, and a Ph.D. from the University of Toronto. His research focuses on computer graphics, geometric modeling, physics-based simulation, and scientific visualization. Education: B.S. (1986) and M.S. (1989) in Computer Science from Peking University; Ph.D. (1995) in Computer Science from the University of Toronto. Research interests include geometric modeling, computer-aided design, scientific visualization, medical imaging, and robotics. He has received notable awards like the NSF CAREER Award (1997), Alfred P. Sloan Fellowship (2001-2005), and multiple NSF grants. Qin has organized major conferences such as Computer Graphics International 2005 and chairs editorial boards for IEEE TVCG and The Visual Computer.

Tzu-Chieh Kurt HongView profile

Assistant Professor

• Shape Grammars
• Visual Computing
• Generative Modeling
• +4 more

Dr. Tzu-Chieh Kurt Hong is an Assistant Professor at the Department of Architecture within the School of Architecture and Design at the University of Kansas. He teaches design studios, algorithmic modeling, parametric design, and computer programming in design studies. He founded K9K Research & Design, focusing on innovative computational design methodologies. His research emphasizes shape grammars, visual computing, and generative modeling, particularly through the development of the Shape Machine—a computational tool integrating shape recognition and rewriting into CAD systems. Education: Ph.D. in Architecture (Design Computation), Georgia Institute of Technology (2021) M.S. in Architecture and Design, University of Michigan (2016) Master of Architecture, National Chiao Tung University (2008) M.S. and B.S. in Electronics Engineering, National Chiao Tung University (Taiwan) Research Interests: Shape embedding and rewriting in CAD systems Algorithmic design and generative systems Integration of traditional methods (e.g., Euclidean geometry) with computational tools Applications in architectural education and practice Awards: 2022 ARCC Dissertation Award for contributions to CAD systems through shape recognition research Professional Experience: Research Scientist at Georgia Tech's Shape Computation Lab (2016–2022) Contributions include the Shape Machine framework and the Smart 3D Atlanta visualization platform Labs/Teams: Leads the K9K Research & Design initiative, collaborating with academic and industry partners on computational design tools and generative workflows.

John RasmussenView profile

Professor

• Biomechanics
• Rehabilitation Robotics
• Musculoskeletal Simulation
• +2 more

John Rasmussen is a Professor and Vice Head of the Department of Materials and Production at Aalborg University's Faculty of Engineering and Science. He founded the AnyBody Research Group and served as CEO of AnyBody Technology A/S. His research focuses on biomechanics, rehabilitation robotics, and musculoskeletal simulation, with applications in exoskeleton design and orthopedic interventions. Education: Ph.D. in Computer-Aided Design (Aalborg University, 1989) M.Sc. in Mechanical Engineering (Aalborg University, 1986) Research Interests: Biomechanics, CAD optimization, finite element analysis, and biomedical engineering. His work bridges computational modeling with clinical solutions for mobility disorders. Article Trends: Recent publications emphasize exoskeleton design, spinal biomechanics, and osteoarthritis interventions, utilizing experimental and simulation approaches across robotics and orthopedics. Awards: Wearable Robotics Innovation Prize (2018) Grand Challenge Competition Winner (2014) Steno Prisen (2012) Teacher of the Year (2011) Leadership: Manages the Center for Rehabilitation Robotics and oversees 37 research projects. Advises industry collaborations in assistive technology.

Shuang LiuView profile

Researcher

• Embedded Systems
• Computer Architecture
• Networks-on-Chip (NoC)
• +3 more

Shuang Liu is a Researcher at the Institute of Computer Architecture and Computer Engineering, University of Stuttgart. Their work focuses on embedded systems, networks-on-chip (NoC), and chip design methodologies. They specialize in deadlock-free routing, fault-tolerant computing, and application-specific system synthesis using advanced techniques like integer linear programming. Research interests include optimizing NoC architectures for chiplet-based systems, co-design of floorplanning and routing topologies, and energy-efficient signal processing in medical electronics. Their recent work emphasizes formal verification methods and performance optimization in hardware-software co-design. Publications span topics such as deadlock prevention in NoC, ILP-based routing synthesis, and trade-offs in hearing aid ASIP design. Office hours are Monday 2–3 p.m. in Room 1.001, Pfaffenwaldring 5b, Stuttgart.

Chadi AssiView profile

Professor

• Wireless Networks
• Information Security
• Cybersecurity
• +6 more

Chadi Assi is a Professor and Tier II Concordia Research Chair at the Concordia Institute for Information Systems Engineering, Concordia University. His research focuses on wireless networks, information security, and smart grid systems, with particular emphasis on reconfigurable intelligent surfaces (RIS), integrated sensing and communication (ISAC), cybersecurity for electric vehicles (EVs), and machine learning-driven network optimization. He has pioneered work on mitigating cyber-physical attacks in power grids and IoT ecosystems, while advancing cooperative communication protocols like RSMA and NOMA. His technical contributions span theoretical frameworks for energy efficiency maximization in hybrid SDMA/NOMA schemes, low-complexity RIS element selection algorithms, and adversarial PINN models for grid dynamics. He also investigates vulnerabilities in EV charging infrastructure and O-RAN synchronization protocols, proposing robust detection mechanisms like PEACE and Grid Mirror. His interdisciplinary work bridges communications, power systems, and AI, addressing challenges in 5G/6G security and resilient IoT provisioning. Key Research Areas: RIS-enabled ISAC networks, EV cybersecurity, meta-learning in communications, IoT malware analysis Current Projects: Grid resilience against load-altering attacks, Movable antenna optimization, federated learning for AGC systems Recent publications (2024-2025) emphasize deep reinforcement learning frameworks for RIS-aided networks, cooperative RSMA performance enhancement, and defense mechanisms against dynamic trigger-based attacks. He has also developed novel datasets for advanced persistent threats and frameworks like ChargePrint for EV charging security analysis. His work is published in top venues including IEEE Transactions on Smart Grid, IEEE JSAC, and IEEE ICC, reflecting contributions to both theoretical advancements and practical system implementations.

Thomas WilliamsView profile

Associate Professor

• Human-Robot Interaction
• Natural Language Processing
• Artificial Intelligence
• +3 more

Thomas Williams is an Associate Professor of Computer Science at the Colorado School of Mines, where he directs the MIRRORLab (Mines Interactive Robotics Research Lab). He earned his PhD in Computer Science and Cognitive Science from Tufts University in 2017. His educational background includes: BA in Computer Science, Hamilton College, 2011 MS in Computer Science, Tufts University, 2013 PhD in Computer Science: Cognitive Science, Tufts University, 2017 Williams' research focuses on artificial intelligence for human-robot interaction, especially natural language understanding and generation in uncertain environments. His work integrates cognitive science principles from linguistics and psychology to develop context-aware robotic systems. Key areas include Human-Robot Interaction, Natural Language Processing, Robot Ethics, and Augmented Reality, with emphasis on ethical implications and social dynamics in human-robot communication. Analysis of his publications (2015-2020) reveals a clear trajectory toward context-sensitive dialogue systems that handle ambiguity, social norms, and ethical considerations. His work increasingly explores multimodal interaction through AR/VR and examines how language-capable robots influence human moral frameworks, with growing attention to gender dynamics and noncompliance behaviors in social robotics. His notable awards include: New and Future AI Educator Award, EAAI (2017, 2018) Teaching Fellowship, Tufts Graduate Institute for Teaching (2015) Doctoral Consortia participation at YRRSDS (2014), HRI (2015), and AAAI (2016) Williams teaches Human-Robot Interaction, Robot Ethics, and Computer Vision courses while leading externally funded research. His work receives support from NSF, ONR, ARL, and Early Career awards from NSF, NASA, and AFOSR, focusing on grants that advance context-aware natural language interaction in robotics. As director of the MIRRORLab, he oversees research on human-robot interaction systems that dynamically adapt to environmental, cognitive, social, and moral contexts, with applications in assistive robotics and collaborative workspaces.

Monica LiljeströmView profile

Associate Professor

• Online Learning
• Digitalization in Education
• Special Education
• +2 more

Monica Liljeström serves as an Associate Professor in the Department of Education at Umeå University, Sweden, where she is affiliated with the Learning and ICT (LIKT) research area. Her primary teaching responsibilities span online-based education programs, including the fully online Education A-C curriculum, special education courses, and HR management instruction. Appointed as assistant professor in 2001, she completed her doctoral degree in 2010 and has since been instrumental in developing the institution's online pedagogical frameworks. Her educational trajectory culminated in a doctorate in 2010 after seven years as assistant professor, reflecting deep institutional commitment and scholarly development. Liljeström's research centers on digital transformation in education, specifically examining online learning methodologies, special education adaptations, and innovative assessment practices. She investigates how collaborative learning and peer assessment function in digital environments, with particular focus on video-based tasks and text-based discussion forums. Her work bridges theoretical frameworks with practical course development, emphasizing student-centered evaluation approaches that foster meaningful engagement in virtual classrooms. Analysis of her publication history reveals a sustained 20-year commitment to advancing online education, evolving from foundational studies on text-based collaboration (2004-2010) to contemporary explorations of video-mediated learning (2017-2023). Her research consistently addresses peer assessment mechanisms, student perception dynamics, and the integration of process evaluation in digital pedagogy, demonstrating methodological rigor across diverse online educational contexts. Scientific Recognition: Distinguished University Teacher award for exceptional pedagogical contributions As an active academic leader, Liljeström has supervised students in special education and pedagogy programs while directing significant research initiatives including the "Collaborative Mixed Reality Aid" project (2019-2020) and foundational work on "Peer assessment in online courses" (2007-2009). These projects secured institutional funding and directly shaped Umeå University's online course development standards. She remains a core contributor to the Learning and ICT (LIKT) research group, driving collaborative investigations into how digital tools transform teaching practices and learning outcomes across educational levels.

• Music Education
• Choral Music
• Music Technology
• +3 more

Seth Pendergast is an Assistant Professor of Music in the School of Music, Theatre, and Dance at Colorado State University, part of the College of Liberal Arts. His research focuses on adolescent music participation, technology integration in music education, and choral pedagogy. He holds a Ph.D. in Music Education from the University of Utah, an M.M. from Florida State University, and a B.S. from Southeastern University. Dr. Pendergast's scholarship explores how formal and informal music education contexts influence student engagement. He has published book chapters on technology-based music courses and presented at national conferences like the Music Research and Teacher Education National Conference. Active in professional development, he leads clinics, festivals, and honor choirs, and serves as an adjudicator. He is affiliated with organizations such as the American Choral Directors Association and the Society for Music Teacher Education. His recent articles address curricular change in modern band programs, motivation frameworks for choral participation, and creative music-making with digital tools. While no formal awards are listed, his work emphasizes innovative approaches to music education accessibility and youth engagement.

Greg L. RohrauerView profile

Associate Professor

• Advanced Composite Materials
• Composite Pressure Vessels
• Materials Testing
• +4 more

Dr. Greg L. Rohrauer is the Department Chair and Associate Professor at the Department of Automotive and Mechatronics Engineering, Ontario Tech University. He holds a PhD in Mechanical Engineering from Concordia University (1999), alongside earlier degrees from Concordia and Dawson College. His research focuses on advanced composite materials, vehicle dynamics, and manufacturing technology, with notable contributions to composite pressure vessel design and hybrid vehicle development. Education: PhD (Mechanical Engineering, Concordia, 1999); BEng (Mechanical Engineering, Concordia, 1985); DEC (Mechanical Engineering Technology, Dawson College, 1981). Research interests include materials testing, alternate-fueled vehicles, and manufacturing applications. He has authored over a dozen peer-reviewed publications, including work on trailer dynamics control and composite elasticity solutions. Awardees of multiple scholarships and honors, including the Governor General’s medal nomination (1999), SAE Doctoral Scholarships, and academic excellence awards. He has held academic roles at Concordia University and the University of Windsor, alongside industrial experience in motorsports engineering. Teaching responsibilities include courses on automotive fundamentals, capstone design, and materials science. His professional activities include SAE faculty advising (2003–2005) and senate membership at the University of Windsor.

Ahmad BarariView profile

Professor

• Advanced Manufacturing Technologies
• Digital Manufacturing
• Precision Manufacturing
• +7 more

Dr. Ahmad Barari is a Professor in the Department of Mechanical and Manufacturing Engineering at the University of Ontario Institute of Technology. He holds a PhD in Mechanical Engineering from Western University (2006), MSc from Sharif University of Technology (1997), and BSc from Amirkabir University of Technology (1995). His research focuses on advanced manufacturing technologies, additive manufacturing, coordinate metrology, surface integrity, and design optimization. He has authored numerous publications and serves on multiple international conference committees. Education highlights include: PhD, Mechanical Engineering, Western University, 2006 MSc, Mechanical Engineering, Sharif University of Technology, 1997 BSc, Mechanical Engineering, Amirkabir University of Technology, 1995 Research interests span Advanced Manufacturing Technologies, Digital Manufacturing, Precision Manufacturing, and FEA-Based Design Optimization. He has contributed to innovations in additive manufacturing processes, surface quality analysis, and computational metrology. His work addresses challenges like measurement uncertainty, surface tribology, and topology optimization. Notable awards include the Best Paper Award at IMS2016 and multiple recognitions as academic advisor for student projects. He actively participates in professional activities such as organizing conference sessions and serving on review panels for NSERC, CFI, and OCE. His professional roles include organizing tracks at ASME, CAD Conferences, and IMECE events, reflecting his leadership in advancing manufacturing research. He also contributes to academic governance through roles like Design Chair for capstone projects.

Alan HuView profile

Professor

• Formal Verification
• Algorithms
• Computer Architecture
• +3 more

Alan Hu is a Professor in the Department of Computer Science at the University of British Columbia (UBC), part of the Faculty of Science. His research focuses on formal verification, algorithms, computer architecture, and electronic design automation. He teaches courses such as Intermediate Algorithm Design and Analysis (CPSC 320) and Introduction to Formal Verification and Analysis (CPSC 513). Dr. Hu has received notable awards, including the IEEE Council on Electronic Design Automation Outstanding Service Award and the IBM Faculty Award. His work emphasizes scalable verification techniques, SAT-based algorithms, and optimization in cloud computing and hardware systems. His research spans formal methods for hardware/software systems, including verification of embedded software, cache coherence, and network function virtualization. Notable contributions include advancements in SAT modulo theories, data race detection in heterogeneous systems, and cloud resource allocation frameworks like Cospot. Dr. Hu has been actively involved in teaching and curriculum development, consistently offering courses on algorithms, formal verification, and software design since 2000. His publications reflect a blend of theoretical foundations and practical applications in electronic design, cloud infrastructure, and verification tools. His scientific achievements include innovations in post-silicon validation, emulation-based coverage reduction, and formal analysis for debug trace optimization. He also contributes to the academic community through conference organization and editorial roles in formal verification and computer-aided design.

• Transport Planning
• Traffic Simulation
• Intelligent Transport Systems (ITS)
• +3 more

Dr. Mark Raadsen is a Postdoctoral Research Fellow at the University of Sydney's Institute of Transport and Logistics Studies (ITLS) within the Business School. His research focuses on the supply side of transport, particularly dynamic/static traffic assignment methods, traffic flow theory, and algorithm design. He co-founded the open-source transport planning tool PLANit . Mark holds an MSc from Twente University (Netherlands) and a PhD from the University of Sydney. **Education:** MSc in Computer Science, Twente University, Netherlands PhD in Transport Planning, University of Sydney **Research Interests:** Combines academic rigor with practical applications, emphasizing aggregation/decomposition methods in multi-scale/multi-modal transport contexts. His work integrates sustainability aspects into transport models to aid policy-making. Key areas include variable speed limits, traffic simulation, and intelligent transport systems. **Teaching:** Contributes to courses such as Strategic Transport Planning, Traffic and Mobility Management, and Quantitative Methods in Transport. His teaching bridges theoretical frameworks with real-world applications. **Awards & Recognition:** While no explicit awards were listed, his work has led to commercial adoption and tangible impacts in transport systems globally. **Labs/Projects:** Co-lead of the PLANit project, an open-source platform for transport planning. His research has influenced both academic discourse and industry practices through models like the link transmission framework.