Find Academic Supervisors

Yao-Tai LiView profile

Senior Lecturer

• Race and Ethnicity
• Identity
• Migration
• +5 more

Dr. Yao-Tai Li is a Senior Lecturer in Sociology and Social Policy at UNSW's School of Social Sciences. He holds a PhD from UC San Diego, with prior roles including Assistant Professor at Hong Kong Baptist University (HKBU, 2017–2021). His research focuses on race/ethnicity, migration, contentious politics, and social media analysis, with a particular emphasis on East Asian diasporas and Hong Kong's sociopolitical dynamics. Education: PhD (UC San Diego), MA and BA (National Taiwan University). Awards include the Dean’s Award for Early Career Research (UNSW, 2024) and data journalism accolades for his Hong Kong Lennon Wall documentation. He advises PhD and master’s students on topics ranging from border regimes to queer activism. Key projects include tracking rhetorical shifts in Chinese-Australian community responses to racism since 1973, and analyzing Hong Kong's protest movements through urban sociology and data activism lenses. Active in 45+ journals as a reviewer/editor, and holds leadership roles in migration studies (ISA RC31) and policy initiatives. Grants include UNSW's ADA Seed Funding (2024), National Library of Australia grants (2023), and Hong Kong RGC Early Career support (2020–21). His forthcoming book *Protest Walls* (CUP, 2025) examines physical/digital protest spaces in transnational contexts.

• Remote Sensing
• Environmental Monitoring
• Marine Ecology
• +3 more

Karen Joyce is an Associate Professor at James Cook University (JCU) with expertise in remote sensing and environmental monitoring. She holds a PhD in Geographical Sciences from the University of Queensland (2005). Her work focuses on developing remote sensing tools for applications in marine, coastal, and savanna ecosystems. Notable contributions include advancing drone technology for coral reef mapping, mangrove phenology modeling, and disaster management integration. She co-founded She Maps, a social enterprise promoting women in STEM through drone education, and GeoNadir, emphasizing geospatial innovation. Education: PhD in Geographical Sciences (University of Queensland, 2005) Key Roles: Co-Founder of She Maps and GeoNadir Former Geomatic Engineering Officer in the Australian Army Her research interests center on optimizing remote sensing models to quantify Earth observation data, with applications in coral reef health, mangrove ecosystems, and invasive species management. Recent projects include She Flies Drone Camps to build STEM confidence in girls and hyperspectral drone technology for bathymetric mapping. Her publications emphasize drone-based data acquisition, spectral analysis for coral cover, and automated image processing using tools like Google Earth Engine. Despite no listed academic awards, her work has significant practical impact in conservation and disaster preparedness. Key grants include projects like 'Is satellite technology telling the truth? Perspectives from a coral reef' (2015–2017) and 'Developing hyperspectral drone technology' (2016–2017). She collaborates extensively with institutions like the Australian Army, New Zealand conservation agencies, and Kakadu National Park researchers.

Amelia AckerView profile

Associate Professor

• Digital Preservation
• Information Science
• Mobile Computing Cultures
• +4 more

Amelia Acker is an Associate Professor and Graduate Advisor/Director of Masters Studies at the University of Texas at Austin's School of Information. Her work focuses on the emergence of new information objects in wireless networks, digital preservation, and cultural memory. She holds a PhD with award-winning research on SMS standardization and mobile communication infrastructure. Prior to UT Austin, she served as an Assistant Professor at the University of Pittsburgh's iSchool and worked as an archivist/librarian in Southern California. Her research is funded by NSF and IMLS grants, and has been published in journals like JASIST and Archival Science. She teaches courses on metadata, information studies, and cultural heritage informatics. Her current projects address digital traces in mobile computing and data justice issues. She previously worked with artist John Baldessari as an arts cataloger and has extensive experience in library preservation practices. Key contributions include analyses of Venmo social payments, Palantir's surveillance systems, and API-driven social media archives. She emphasizes interdisciplinary approaches to sociotechnical systems and data ethics in emerging technologies.

• Hyperspectral Imaging
• Computer Vision
• Pattern Recognition
• +3 more

Jun Zhou is Professor and Deputy Head of School (Research) at Griffith University's School of Information and Communication Technology. His research specializes in hyperspectral imaging, computer vision, and pattern recognition with applications in agriculture, environmental monitoring, and remote sensing. Zhou leads significant projects including the ARC Research Hub for Driving Farming Productivity and Disease Prevention. His work develops innovative computer vision systems for agricultural automation, environmental conservation, and industrial quality control. He has received the ARC Discovery Early Career Researcher Award and secured extensive research funding from ARC, CSIRO, and industry partners. Zhou's publications demonstrate consistent contributions to hyperspectral image analysis, object tracking, and deep learning applications. As Deputy Director of the ARC Industrial Transformation Research Hub, he coordinates multi-institutional research teams developing AI-powered solutions for farming productivity and disease prevention.

Michael OttoView profile

Researcher

• Virtual Technologies for Production Planning
• Immersive Virtual Assembly Assessments
• Markerless Motion Capture Technologies
• +3 more

Dr. Michael Otto is affiliated with the University of Ulm, Department of Computer Science, within the Faculty of Engineering. His research focuses on virtual technologies for production planning, immersive virtual assembly assessments, and markerless motion capture systems. He has contributed to projects like ARVIDA (Cost-efficient motion capture systems) and INTERACT (Human-centered workplaces). His work bridges computer science, manufacturing systems, and human factors. Key contributions include developing frameworks for motion capture, virtual reality benchmarking, and augmented reality applications in industrial contexts. Notable achievements include receiving the Best Industrial Paper award (2015) for his work on ubiquitous tracking using depth cameras. His research addresses challenges in assembly planning, ergonomic assessments, and spatial interaction in manufacturing environments. Education/Background: Former External PhD Candidate at University of Ulm. Research Interests: Dr. Otto’s work emphasizes practical applications of virtual and augmented reality in manufacturing. He explores how technologies like markerless motion capture and immersive environments can optimize assembly processes, enhance worker ergonomics, and improve production verification workflows. His projects often involve interdisciplinary collaboration with industry partners. Articles Overview: His publications (2014–2025) span topics such as augmented reality visualization, motion tracking algorithms, and VR-based simulation tools. These contributions highlight advancements in scalable systems, sensor fusion, and human-motion analysis within industrial contexts.

Kristian AndersenView profile

Professor

• Virology
• Genomics
• Epidemiology
• +3 more

Kristian G. Andersen is a Professor in the Department of Immunology and Microbiology at Scripps Research, with joint appointments in the Department of Integrative Structural and Computational Biology and the Skaggs Graduate School of Chemical and Biological Sciences. He directs the Infectious Disease Genomics program at the Scripps Research Translational Institute. His research focuses on understanding host-pathogen interactions, particularly the emergence, evolution, and spread of viruses like SARS-CoV-2, Ebola, Zika, and Lassa. Andersen earned his PhD in Immunology from the University of Cambridge and completed postdoctoral work at Harvard University and the Broad Institute under Pardis Sabeti. He has pioneered large-scale international collaborations using genomic sequencing, computational biology, and fieldwork to study viral outbreaks. His lab integrates computational methods with experimental biology to track viral evolution and improve outbreak responses. Recent work has included identifying the Wuhan market as the early epicenter of the SARS-CoV-2 pandemic, analyzing mpox outbreaks in West Africa, and developing wastewater surveillance systems for infectious diseases. Andersen has advised on pandemic preparedness initiatives, including the CDC-funded California COVIDNet and SEARCH programs. His team collaborates globally through networks like the Viral Hemorrhagic Fever Consortium and the West African Research Network for Infectious Diseases.

Andrew MartinView profile

Professor

• Systems Security
• Trusted Computing
• Cybersecurity
• +12 more

Professor Andrew Martin is a leading academic in Systems Security at the Department of Computer Science, University of Oxford, and a Governing Body Fellow at Kellogg College. His research focuses on trusted computing, cybersecurity, and secure distributed systems, with applications in cloud computing, IoT, and smart grids. He has been instrumental in advancing secure architectures using hardware-based trust mechanisms such as Intel SGX and Trusted Platform Modules. Research Interests: His work spans Systems Security , Trusted Computing , Confidential Computing , Secure Multi-Party Computation , and Privacy in Distributed Systems . He investigates how hardware-enforced security can mitigate risks in large-scale environments, particularly where privacy and trust are paramount. Publication Trends: His recent publications reveal a strong focus on Trusted Execution Environments (TEEs), remote attestation, and secure cloud architectures. He critically examines the feasibility of using hardware enclaves for both defensive and offensive security, emphasizing architectural soundness and real-world applicability. Scientific Awards: No specific awards mentioned in the provided text. Advising and Grants: Professor Martin has supervised numerous PhD and Master’s students in cybersecurity and systems research. His projects include CRANE , Trustworthy Logging , webinos , TCLOUDS , and Secure Networking by Design (SNbD) . He has secured funding for research in trusted computing and secure distributed systems, contributing to both theoretical foundations and practical implementations. Labs and Teams: He leads a research group focused on systems security and trusted computing, collaborating with industry and academic partners on large-scale security challenges. His team works on developing secure middleware, analyzing vulnerabilities in consumer devices, and designing privacy-preserving protocols for smart infrastructure.

Sabine GrafView profile

Professor

• Educational Technology
• User Adaptive Systems
• Learning Analytics
• +7 more

Dr. Sabine Graf is a Full Professor at the School of Computing and Information Systems, Athabasca University. She holds a PhD in Computing and Information Systems from Vienna University of Technology (2007) and has been a faculty member since 2009. Her research focuses on user adaptive systems, learning/academic analytics, personalization, and game-based learning, with over $2.3M in external funding and 130+ peer-reviewed publications (cited 8,200+ times). She leads the OMEGA+ educational game project and the User Adaptive Systems (UAS) research cluster. Education: PhD in Computing and Information Systems, Vienna University of Technology, 2007 MSc in Computing and Information Systems, University of Vienna, 2003 Research Interests: Dr. Graf specializes in making learning systems more intelligent through adaptive interfaces, AI-driven recommendations, and data analytics. Her work bridges educational technology, artificial intelligence, and collaborative learning. Recent projects include developing OMEGA+, analyzing student behavior in online courses, and enhancing adaptive learning systems with context-aware features. Grants & Funding: NSERC Discovery Grant ($205,000), 2020 CFI John R. Evans Leaders Fund ($164,573), 2020 AU IDEA Lab Grant ($5,000), 2021 Multiple Mitacs Globalink Internships, NSERC awards, and AU-funded projects. Advising & Team: Dr. Graf has mentored over 30 students, including PhD, MSc, and postdoctoral fellows. Notable advisees include Moustafa Mahmoud (NSERC Scholar) and Mohammad Belghis-Zadeh (3MT Competition winner). The research team collaborates globally, with members from Brazil, Taiwan, Spain, and beyond. Labs & Initiatives: The Academic Analytics Tool (AAT) project and the OMEGA+ game platform are central to her work. The UAS cluster connects researchers worldwide to advance adaptive systems research.

David DaneyView profile

Professor

• Robotics
• Cobotics
• Human-Robot Interaction
• +14 more

David Daney is a Senior Researcher (Directeur de recherche) at Inria and HDR-qualified academic, currently serving as Head of Science for the Inria Center at the University of Bordeaux since July 2024. He is the team leader of the Auctus research group, focusing on robotics, cobotics, and human-robot interaction. He is affiliated with Inria and the École Nationale Supérieure de Cognitique (ENSC) at the University of Bordeaux, within the College of Engineering and the Department of Robotics. His research interests include Robotics, Cobotics, Human-Robot Interaction, Human Posture Analysis, Cable-driven Robots, Parameters Identification, Calibration, Interval Analysis, and Haptic Guidance. His work bridges theoretical robotics with industrial applications, particularly in aerospace, automotive, and sustainable agriculture. He has led and participated in numerous industrial collaborations with Airbus, Stellantis, Solvay, AKKA, and Farm3. His recent publications (2023–2025) demonstrate a strong focus on human-robot physical interaction, including real-time capacity estimation (Pycapacity), haptic guidance, model predictive control for dynamic environments, and musculoskeletal modeling for collaborative robotics. These works appear in top-tier journals such as IEEE Transactions on Robotics, Journal of Biomechanical Engineering, and Robotics and Autonomous Systems. HDR (Habilitation à Diriger des Recherches) Principal Investigator of ANR Pacbot Head of Science for Inria Center at University of Bordeaux Erdös number = 3 David Daney supervises multiple PhD students, including Alicia Barsacq, Ahmed-Manaf Dahmani, and Alexis Boulay. He has been principal investigator in several research projects such as LiChIE and ANR Pacbot, focusing on satellite production and human-robot collaboration. He also leads the SHAARE associate team with KAIST’s IRiS lab, advancing shared haptic control. His team develops tools for teleoperation, ergonomic analysis, and robot calibration, with applications in industrial and assistive robotics. He leads the Auctus team at Inria, which develops control and analysis techniques for human-robot physical interaction. The team collaborates with KAIST (SHAARE), ONERA, Pprime Institute, and industrial partners. The MOVER project studies human motor variability for ergonomics, and the Farm3 collaboration explores teleoperated vertical farming robotics.

• Swarm Robotics
• Bio-inspired Swarms
• Multi-agent Systems
• +4 more

Farshad Arvin is a Professor of Robotics in the Department of Computer Science at Durham University. Prior to this, he held academic positions at The University of Manchester (2018-2022) and worked as a Research Assistant at the University of Lincoln (2012-2015). He holds a BSc in Computer Engineering (2004), an MSc in Computer Systems Engineering (2010), and a PhD in Computer Science (2015). His research focuses on Swarm Robotics , Bio-inspired Swarms , and Autonomous Multi-agent Systems . He pioneered the Swarm & Computation Intelligence Laboratory (SwaCIL) at Durham, leading projects like H2020-FET RoboRoyale (€3.27M), Horizon Europe Sensorbees (€3.2M), and BioDiMoBot (€8M), with total funding exceeding £4M. Recent publications highlight advancements in swarm trajectory optimization (T-STAR), collision-free multi-robot coordination, and bio-hybrid environmental monitoring. His work integrates bio-inspired algorithms with practical applications in autonomous vehicles, aerial drones, and hazardous environments. Scientific Awards: Marie Skłodowska-Curie fellowship Notable Projects: EU H2020-FET RoboRoyale (2021-2026) Horizon Europe Sensorbees (2024-2029) Horizon Europe BioDiMoBot (2025-2030) H2020-FET Robocoenosis (2020-2025) Supervision: Mentors 8 postgraduate students at Durham, including Hanadi Alhamdan, Hang Wang, and Honghao Pan.

Abolfazl HashemiView profile

Assistant Professor

• Large-Scale Optimization
• Machine Learning
• Artificial Intelligence
• +6 more

Abolfazl Hashemi is an Assistant Professor in the Elmore Family School of Electrical and Computer Engineering at Purdue University, directing the MINDS Group. He holds a B.Sc. from Sharif University of Technology (2014), and M.S.E. and Ph.D. degrees from The University of Texas at Austin (2016, 2020). His research focuses on Large-Scale Optimization for AI/ML, Learning at the Edge, and Decision-Making under Uncertainty, with applications in Federated Learning, Medical Image Analysis, and Cyber-Physical Systems. He leads the MINDS Group and collaborates with EnCORE and ICON centers. Key research areas include optimizing algorithms for machine learning, robustness in distributed systems, and adversarial learning. He has developed algorithms with mathematical guarantees for efficient deployment under resource constraints. Teaching includes Optimization for Deep Learning (graduate) and undergraduate courses like ECE 20001. He advises the Purdue RoboMaster robotics team and has mentored students through programs like SURF and Summer Stay Scholars. Outreach activities include fostering diversity through robotics competitions and research fellowships. His work bridges theoretical optimization with practical AI applications, emphasizing equitable and robust solutions in federated and decentralized learning.

Mihran TuceryanView profile

Professor

• Computer Vision
• Image Processing
• Pattern Recognition
• +3 more

Professor Mihran Tuceryan is a Professor of Computer Science at Purdue University Indianapolis, affiliated with the Department of Computer Science within the College of Science. He holds a PhD from the University of Illinois at Urbana-Champaign (1986) and a BS from MIT (1978). His expertise spans Computer Vision, Image Processing, Pattern Recognition, and Augmented Reality. Recent research focuses on crime prediction via video analysis, forensic imaging, and distributed tracking systems. He is a Senior Member of IEEE and ACM. Key research interests include augmented reality integration for industrial training, real-time illumination modeling, and monocular SLAM algorithms. His work addresses challenges in photorealistic AR, dynamic object labeling, and medical imaging applications such as hepatic fibrosis detection. He has contributed to projects like the e-DOTS indoor tracking system and forensic 3D impression acquisition. His publications span over three decades, emphasizing real-world applications in security, healthcare, and robotics. Education: Bachelor of Science in Computer Science and Engineering, MIT, 1978 PhD in Computer Science, University of Illinois at Urbana-Champaign, 1986 Awards: Senior Member, IEEE Senior Member, ACM Labs/Teams: Focus on AR, SLAM, and medical imaging applications Collaborative frameworks for distributed visual SLAM

Weiwen JiangView profile

Assistant Professor

• Quantum Computing
• AI Accelerators
• Hardware-Software Co-Design
• +3 more

Weiwen Jiang is a tenure-track Assistant Professor in the Department of Electrical and Computer Engineering at George Mason University (GMU), affiliated with the College of Engineering and Computing (CEC). He leads the JQub lab, focusing on hardware/software co-design for computing systems, spanning classical (FPGAs, ASICs) and quantum computing applications in AI-driven fields like medical imaging and geophysics. Prior to GMU, he held a postdoctoral position at the University of Notre Dame and earned his PhD in Computer Science from Chongqing University with a joint PhD in Electrical and Computer Engineering from the University of Pittsburgh. His research emphasizes quantum computing, AI accelerators, and domain-specific computing. Notable achievements include the 2025 NSF CAREER Award, ACM Sigda Meritorious Service Award (2024), and IEEE QuantumWeek Best Paper Award (2023). His work is funded by NSF, DoE, ARO, Meta, and Leidos. He co-chaired IEEE QuantumWeek (2023–2025) and created workshops like StableQ at ESWEEK 2023. Key contributions include developing frameworks like QuPAD for quantum learning and JQub's AI-driven geophysical and medical imaging tools. His lab graduated Dr. Yi Sheng (now at University of South Florida) and Dr. Zhepeng Wang (Amazon Applied Scientist). Current research explores quantum machine learning, noise mitigation, and fairness in AI for edge devices.

Kyle B. ReedView profile

Associate Professor

• Rehabilitation engineering
• Haptics
• Human-robot interaction
• +4 more

Kyle B. Reed serves as an Associate Professor in the Department of Mechanical Engineering at the University of South Florida's College of Engineering. His academic career at USF has progressed from Assistant Professor (2009-2016) to his current position as Associate Professor (2016-present), following postdoctoral research at Johns Hopkins University. He teaches specialized courses including Haptics (EML 4593/6594), Mechanical Controls, and Advanced Engineering Mathematics. Dr. Reed earned his Ph.D. (2007) and M.S. (2004) in Mechanical Engineering from Northwestern University, and his B.S. in Mechanical Engineering from the University of Tennessee-Knoxville (2001). Prior to his faculty position, he completed postdoctoral research at Johns Hopkins University's Laboratory for Computational Sensing and Robotics (2007-2009) and worked as a researcher at Los Alamos National Laboratory (1998-2001). His research focuses on rehabilitation engineering, haptics, human-robot interaction, and medical robotics, with applications in medical devices and rehabilitation technologies. The REED Lab (Rehabilitation Engineering and Electromechanical Design Lab), which he directs, develops innovative solutions for human motion analysis and assistive technologies. His work bridges fundamental engineering principles with clinical applications, particularly in stroke rehabilitation and assistive device development. Analysis of his publication record shows consistent contributions to haptics research, human-robot interaction, and rehabilitation engineering. His work spans theoretical investigations of human motor control to practical applications in medical devices, with publications appearing in venues like IEEE Transactions on Haptics, EMBC, and Haptics Symposium. Recent work emphasizes wearable haptic devices, rehabilitation robotics, and human factors in medical technology. Developed the Gait Enhancing Mobile Shoe (GEMS) prototype during postdoctoral work Created minimally invasive steerable needle system for biopsies at Johns Hopkins Established REED Lab focusing on rehabilitation engineering and haptic technologies Developed innovative haptic devices for communication, rehabilitation, and education Dr. Reed actively mentors students through the REED Lab, supervising both graduate and undergraduate researchers. His teaching philosophy emphasizes building intuition while providing frameworks for logical problem-solving. He incorporates substantial project components into his courses, with students regularly developing haptic devices and robotics applications that sometimes lead to publications. The lab maintains strong outreach connections, working with K-12 students to promote engineering education. The REED Lab, located in the Interdisciplinary Research Building Room 114 on USF's Tampa campus, serves as the hub for his research activities. Current projects include wearable haptic devices for communication, diagnostic tools for Parkinson's disease, and rehabilitation technologies for gait analysis. The lab maintains strong connections with both clinical partners and industry, facilitating translational research from concept to application.

Timothy DuffView profile

Assistant Professor

• Algebraic Geometry
• Computer Vision
• Numerical Analysis
• +1 more

Timothy Duff is an Assistant Professor in the Mathematics Department at the University of Missouri's College of Arts and Science. He co-organizes the Math & Data Seminar and specializes in applied computational algebraic geometry for 3D reconstruction in computer vision. Research integrates algebraic geometry with machine learning and numerical analysis to solve geometric problems in imaging systems. Core interests include multi-view geometry, minimal solvers, and certified numerical methods. Recent publications emphasize efficient algorithms for camera calibration, 3D reconstruction, and polynomial system solving. Work frequently develops tools in Macaulay2 and addresses theoretical challenges in computer vision through algebraic frameworks.