Find Academic Supervisors

Kshirasagar NaikView profile

Professor

• Mobile and Ad Hoc Networks
• Low Power Software
• Optical Networks
• +15 more

Kshirasagar Naik is a Professor in the Department of Electrical and Computer Engineering at the University of Waterloo, Ontario. He is actively involved in graduate research supervision and has been a member of IEEE since 1994. His academic career spans decades, with a focus on wireless communication, energy efficiency, and cybersecurity. 1992, Doctorate in Computer Engineering from Concordia University, Ontario 1988, Master of Mathematics in Computer Science from University of Waterloo, Ontario 1983, MTech in Computer Engineering from Indian Institute of Technology, Kharagpur, India 1981, BScEng in Electronics and Telecommunication from Sambalpur University, India His research interests include Mobile and Ad Hoc Networks , Cybersecurity , Internet of Things (IoT) , and Intelligent Transportation Systems . He has published extensively on energy optimization in wireless devices, delay-tolerant networks, and security protocols for vehicular systems. Recent publications highlight the integration of Machine Learning and IoT in environmental monitoring, particularly forest fire detection and prediction. Other works focus on cybersecurity , vehicular networks , and energy optimization in data centers and handheld devices. Professor Naik is currently accepting graduate students for research in mobile systems, network protocols, and green computing at the University of Waterloo.

• Numerical Modeling
• Geotechnical Engineering
• Renewable Energy Systems
• +3 more

Dr. Liang Cui is an Associate Professor at the University of Surrey , affiliated with the School of Sustainability, Civil and Environmental Engineering and Institute for Sustainability . With a PhD from University College Dublin (2006) and BE (1st honor) from Tsinghua University (2002) , his career spans geotechnical research and education since joining Surrey in 2009. Key roles: Undergraduate Programme Leader (2020-2022, 2023-on), MSc Programme Leader for Advanced Geotechnical/Civil/Structural Engineering (2022-2023) Professional memberships: Chartered Engineer (CEng), Member of Institution of Civil Engineers (MICE), Fellow of Higher Education Academy (FHEA) His primary research focuses on numerical modeling (DEM/FEM) for geotechnical applications including offshore wind foundations , geothermal energy systems , methane hydrate exploitation , and extra-terrestrial soil mechanics . Secondary interests involve material characterization of polymeric foams , porous media , and biological tissues . Recent 15 publications (2023-2025) demonstrate expertise in soil-structure interaction for renewable energy infrastructure, thermal feedback in groundwater heat pumps, and hypothesis-driven DEM simulations for lunar/martian environments. Collaborative projects span institutions including Tsinghua University , University of Bristol , and Indian Institute of Technology Bhubaneswar . Scientific Awards: Sustainability Fellow (University of Surrey, 2023) Chartered Engineer (CEng) and MICE FHEA for educational contributions Dr. Cui supervises 7 postgraduate researchers and contributes to teaching modules in soil mechanics and energy geotechnics. His work addresses challenges in hybrid marine energy systems , needleless drug delivery , and seismic resilience of critical infrastructure.

• Computer Graphics
• Computer Vision
• Augmented Reality
• +3 more

Aditi Majumder is a Professor of Computer Science at the University of California, Irvine (UCI), affiliated with the School of Engineering and Information Sciences. Her research focuses on multi-projector display systems, augmented reality (AR), and their applications in scientific and medical fields. She holds a Ph.D. from the University of North Carolina, Chapel Hill (2003). Her work addresses challenges in geometric, chromatic, and luminescent corrections for tiled displays, with applications in surgical assistance and deformable surface visualization. Recent projects include precision stencils for surgical sites and dynamic projection mapping on non-rigid surfaces. Notable achievements include the Inaugural Hasso Plattner Endowed Chair in Artificial Intelligence (2025). Her research spans AR in medicine, real-time multi-projector synchronization, and color gamut optimization. Dr. Majumder also engages in public discourse on computer science education, emphasizing its societal importance and foundational skills like programming and discrete mathematics. Her 15 most recent articles (2021–2024) highlight advancements in surgical AR, deformable surface projection systems, and medical visualization. These contributions bridge computer graphics, vision, and biomedical engineering, reflecting her interdisciplinary approach to solving complex display and interaction challenges.

• Epilepsy
• Consciousness
• Neuroimaging
• +3 more

Hal Blumenfeld, MD, PhD, is a Professor of Neurology, Neuroscience, and Neurosurgery at Yale University's School of Medicine, serving as Director of the Clinical Neuroscience Imaging Center (CNIC). He specializes in epilepsy, consciousness, and neuroimaging. His research focuses on understanding the mechanisms underlying impaired consciousness during seizures and developing innovative diagnostic and treatment approaches. Dr. Blumenfeld holds a PhD from Columbia University and completed neurology residency at Massachusetts General Hospital. Appointments: Neurology (Primary), Neuroscience & Neurosurgery (Secondary) Key Roles: Director, CNIC; Author, Neuroanatomy Through Clinical Cases Research Interests: Epilepsy , Consciousness , Neuroimaging , and Cortical-Subcortical Mechanisms . His work combines human and animal models to study seizure-induced consciousness impairment, with a focus on neurovascular coupling, EEG-fMRI, and wearable technologies for real-time monitoring. Publications highlight advancements in understanding absence epilepsy, focal seizures, and the neural correlates of sensory perception. Recent studies explore cholinergic arousal deficits and predictive models for impaired consciousness. His team has developed the ARTiE Watch for automated responsiveness testing in epilepsy. Awards : Javits Neuroscience Investigator Award (NIH), Francis Gilman Blake Award (Yale), and Whitaker Visiting Professorship (ANA). Labs & Teams : Blumenfeld Lab, CNIC, and collaborations with the Kavli Institute for Neuroscience.

Brandon A. JonesView profile

Associate Professor

• Space Situational Awareness
• Satellite Navigation
• Orbit Uncertainty Propagation
• +5 more

Brandon A. Jones is an Associate Professor in the Department of Aerospace Engineering and Engineering Mechanics at the University of Texas at Austin. He holds the Charles Elmer Rowe Fellowship in Engineering and leads the Texas Spacecraft Laboratory (TSL) and the Controls, Autonomy, Estimation, and Learning for Uncertain Systems (CAELUS) Laboratory. His research focuses on space situational awareness, spacecraft navigation, and uncertainty quantification, with applications to orbital mechanics, multi-target tracking, and autonomous systems. Dr. Jones received his Ph.D. in Aerospace Engineering from the University of Colorado Boulder and has held roles at NASA Johnson Space Center and as a Research Assistant Professor. He is an Associate Fellow of the AIAA and former chair of the American Astronautical Society's Space Surveillance Technical Committee. His work includes NASA-funded projects like the SCOPE-1 CubeSat mission for terrain-relative navigation and the Crater-based Navigation and Timing (CNT) system for lunar missions. Key research areas include: Multi-source information fusion for space object tracking Machine learning for crater detection and autonomous navigation Uncertainty propagation in cislunar and highly perturbed orbits Event-based sensor systems for harsh-lighting environments Recent achievements include the 2023 W. A. 'Tex' Moncrief Grand Challenge Award and leadership in collaborative projects with NASA, JPL, and academia. His labs emphasize student-driven CubeSat missions and cutting-edge algorithms for space domain awareness.

• Biomedical Engineering
• Nanotechnology
• Medical Biotechnology
• +7 more

Dr. Jang Ah Kim is a Lecturer at the Hamlyn Centre, Department of Mechanical Engineering, Imperial College London. She leads the Micro-Nano Innovation Lab and focuses on developing micro/nanostructured biomedical sensors and robotic strategies for diagnostics and minimally invasive therapies. Her work integrates light-matter interaction principles to innovate in areas like localized drug delivery and cellular surgery. Education: BSc (2011) and PhD (2017) in Mechanical Engineering/Nano Engineering from Sungkyunkwan University, South Korea. Prior roles include Research Associate positions at Imperial College London's Department of Computing and Department of Materials, where she specialized in fiber-optic biosensors and SERS-based diagnostics. Research Interests: Biomedical sensing, nanophotonics, medical robotics, diagnostics (biosensors), and nanomaterial applications. Key projects include plasmonic sensors for infection screening, bacterial swarming manipulation, and advanced fabrication techniques like two-photon polymerization. Lab Affiliations: Hamlyn Centre, Institute of Global Health Innovation. Her work bridges engineering and medicine to address unmet clinical needs in precision diagnostics and surgical robotics.

Bernhard ThomaszewskiView profile

Lecturer

• Computer Graphics
• Robotics
• Computational Mechanics
• +3 more

Bernhard Thomaszewski is a Lecturer at the Department of Computer Science at ETH Zürich. His research focuses on computational mechanics, robotics, and computer graphics, with an emphasis on simulation-based design and material modeling. He explores topics such as deformable contact, flexible materials, and robotic mechanisms. His work bridges theoretical foundations and practical applications, including medical imaging, garment simulation, and biomechanical systems. Notable research interests include the development of novel algorithms for real-time simulation, optimization-driven design of mechanical systems, and integration of machine learning with physical models. He has contributed to advancements in finite element modeling, differentiable simulation, and topology optimization for robotic and biomedical applications. His recent projects highlight interdisciplinary collaboration, addressing challenges in areas like orthodontic treatment prediction, automated pipeline design, and neural network-driven material characterization. While no specific grants or awards are explicitly listed, his prolific publication record underscores his impactful contributions to computational engineering and computer science.

• Earthquake Geology
• Tectonic Geomorphology
• Structural Geology
• +3 more

Ramon Arrowsmith is a Professor at Arizona State University's School of Earth and Space Exploration (SESE). His research focuses on earthquake geology, tectonic geomorphology, and active faulting, with a particular emphasis on leveraging high-resolution topography through initiatives like OpenTopography. He has over 35 years of experience in paleoseismology, geomorphic mapping, and fault zone analysis. Arrowsmith has held administrative roles such as Deputy Director of SESE and associate directorships in graduate studies and geological sciences departments. His work integrates remote sensing, lidar technology, and robotics to address geological hazards and landscape evolution. Key projects include the QUAKES mission for topographic data collection and the development of low-cost seismic tools like ShakeBot. His research spans global regions, including the San Andreas Fault, Pamir-Tien Shan collision zone, and volcanic fields in Arizona and Mexico. Arrowsmith's recent publications highlight advancements in fault slip modeling, seismic hazard assessment, and open-access geospatial data platforms. His contributions to education include courses on field geology and computational methods in earth sciences. Collaborations with international teams and interdisciplinary projects underscore his commitment to advancing geoscience through innovation and accessibility.

Uwe GrünefeldView profile

Visiting Professor

• Human-Computer Interaction
• Virtual Reality
• Augmented Reality
• +5 more

Dr. Uwe Grünefeld is a Visiting Professor at the Faculty of Computer Science , Institute for Computer Science and Business Information Systems (ICB) of the University of Duisburg-Essen. He has been actively contributing to Human-Computer Interaction research through multiple publications in 2025-2022 focusing on Virtual Reality , Augmented Reality , and Robotics . Research Interests span across immersive technology applications for health behavior change (situated artifacts, weight visualization mirrors), haptic feedback systems (EMS for weight perception, vibrotactile directional cues), and behavioral biometrics (hand tracking identification, gaze-based user recognition). His work addresses cross-reality system design , collaborative robotics , and human-in-the-loop simulation methodologies . Key Publications demonstrate significant contributions to VR/AR user engagement, with particular focus on Physical activity promotion through situated artifacts Advanced haptic feedback techniques for immersive environments Behavioral biometric identification systems Robot motion intent communication Cross-reality transition visualization His research often employs mixed-method approaches combining technical implementations with user studies involving quantitative and qualitative data collection.

• Bayesian statistics
• Computational statistics
• Environmental statistics
• +4 more

Roles & Affiliations: Distinguished Research Professor in Statistical Science at Queensland University of Technology (QUT), Director of QUT Centre for Data Science, and Associate Member of University of Oxford's Department of Statistics. Served as Deputy Director of ARC Centre of Excellence in Mathematical and Statistical Frontiers (2015–2021) and ARC Laureate Fellow (2015–2021). Education: BA (Hons) and PhD in Mathematical Statistics from University of New England, Australia. Completed post-doctoral roles at multiple Australian universities. Research Interests: Specializes in Bayesian statistical modelling, computational methods, and their applications in environmental science, genetics, healthcare, and industry. Leads projects on coral reef recovery, cancer epidemiology (Australian Cancer Atlas), and virtual citizen science platforms like Virtual Reef Diver. Her work emphasizes interdisciplinary collaboration, integrating complex data sources with advanced statistical techniques to address real-world challenges. Publications & Grants: Over 350 refereed journal publications and attracted >30 major grants. Recent focus areas include influenza epidemiology, spatial health disparities, and AI-driven early warning systems for climate-sensitive diseases. Active in developing methodologies for spatial statistics, small-area estimation, and federated learning. Awards & Recognition: 2024 Ruby Payne-Scott Medal (Australian Academy of Science), Pitman Medal (2016), first female recipient of this award in 35 years. Elected Fellow of Australian Academy of Science (2018), Academy of Social Sciences (2018), and Queensland Academy of Arts and Sciences (2018). Holds international roles including Vice-President of International Statistical Institute (2021–2025) and Scientific Council Member at Centre International de Rencontres Mathématiques (France). Supervision & Leadership: Supervised over 36 PhD students and leads teams in >50 collaborative projects. Current supervision includes 5 PhD and 4 Masters students at QUT. Founded the QUT Centre for Data Science and previously led the Collaborative Centre for Data Analysis, Modelling and Computation. Labs & Initiatives: Core contributor to the Australian Cancer Atlas 2.0, Virtual Reef Diver project, and Queensland's Learning Potential Fund. Active in global initiatives like the World of Statistics campaign and UN Big Data Task Teams.

• Nanophotonics
• Infrared Spectroscopy
• Metamaterials
• +4 more

Prof. Dr. Thomas Taubner serves as a Professor at the Institute of Physics within the Faculty of Mathematics, Computer Science and Natural Sciences at RWTH Aachen University. He leads the IR Nano-Optics and Metamaterials research group, operating from Campus Melaten (Physics Building 26, Room A 104). His team focuses on cutting-edge nanophotonic technologies with applications in infrared optics and reconfigurable optical systems. Taubner's research spans nanophotonics, infrared spectroscopy, metamaterials, and phase-change materials, with particular expertise in plasmonic phase-change materials like In 3 SbTe 2 . His group pioneers techniques for dynamic control of light at the nanoscale through near-field microscopy, beam steering, and thermal emission manipulation. Key areas include 2D material characterization, phonon polariton engineering, and ultrafast optical phenomena in semiconductor heterostructures. Analysis of his recent publications reveals a dominant focus on programmable infrared nanophotonics using plasmonic phase-change materials. His work consistently demonstrates reconfigurable optical devices through direct laser writing, geometric phase metasurfaces, and real-space imaging of confined electromagnetic waves. The research shows strong interdisciplinary connections between condensed matter physics, materials science, and optical engineering, with practical applications in thermal management, sensing, and next-generation optical computing. Prof. Taubner actively supervises doctoral and master's students, regularly advertising thesis positions and doctoral openings through his research group. His team maintains advanced laboratory facilities for nanofabrication, near-field optical characterization, and ultrafast spectroscopy, supporting both fundamental research and technology development in infrared nanooptics.

Shawn LitsterView profile

Professor

• Energy Conversion Technologies
• Fuel Cells
• Batteries
• +15 more

Shawn Litster is a Professor in the Department of Mechanical Engineering at Carnegie Mellon University, where he leads cutting-edge research in sustainable energy conversion technologies. He is affiliated with the Wilton E. Scott Institute for Energy Innovation and serves as a Scott Institute Energy Fellow, contributing to major national initiatives in hydrogen and fuel cell systems. His work is supported by significant funding from the U.S. Department of Energy (DOE), ARPA-E, and the Office of Naval Research. Education: Ph.D. in Mechanical Engineering, Stanford University (2008) Master of Applied Sciences, University of Victoria (2005) Bachelor of Engineering, University of Victoria (2004) His research focuses on micro- and nanoscale transport phenomena in electrochemical energy systems such as fuel cells, batteries, and electrolyzers. Key interests include electrochemistry, multiphase flow in porous media, microfluidics, catalytic gasification, and computational fluid dynamics . He pioneers innovations in ionomer-free electrodes, high-oxygen-permeability materials, and low-iridium anodes to improve efficiency, durability, and cost-effectiveness. His recent publications (2021–2025) reveal a strong trend toward advanced diagnostics, operando characterization, machine learning integration, and multiscale modeling of fuel cell and electrolyzer systems. These works emphasize performance optimization, degradation analysis, and material innovation for heavy-duty and transportation applications. Scientific Awards: George Tallman Ladd Research Award, Carnegie Mellon University National Science Foundation CAREER Award Lieutenant Governor’s Silver Medal, University of Victoria Best Paper/Presentation Award, The Electrochemical Society Best Paper/Presentation Award, American Society of Mechanical Engineers (ASME) Litster has secured over $50 million in research funding as a sub-awardee in DOE hydrogen projects and led a $3.2M ARPA-E OPEN 2021 project on disruptive fuel cell electrodes. He is an inventor on two U.S. patents related to fuel cell design. He advises graduate students and leads the Laboratory for Transport Phenomena in Energy Systems , where his team develops novel materials and diagnostics for next-generation energy technologies.

• Robotics and Autonomous Systems
• Computer Vision
• Machine Learning
• +7 more

Dr. Sen Wang is an Associate Professor in Robotics and Autonomous Systems at Imperial College London's Department of Electrical and Electronic Engineering, affiliated with I-X (Imperial's AI initiative), the Grantham Institute, and the Robotics Forum. He directs the Sense Robotics Lab and founded the MSc in Artificial Intelligence Applications and Innovation. His research focuses on advancing robotic autonomy through probabilistic and machine learning methods, addressing challenges in unstructured environments such as underwater infrastructure inspection and climate change solutions. Key projects include leading the £18M UKRI ORCA Hub, developing underwater robotics for offshore energy infrastructure inspection, and achieving the first autonomous wind farm foundation inspection at EDF's Blyth site. He holds editorial roles at IEEE Transactions on Robotics and other journals. Research interests span robotics, computer vision, SLAM, and AI applications, with recent work emphasizing underwater systems, sensor fusion, and safety-critical autonomy. His publications bridge theoretical advancements with real-world deployments in marine robotics and environmental monitoring. Awards: 2024 AI Most Influential Scholar Award Honourable Mention Grants: £18M ORCA Hub funding (UKRI) Labs: Sense Robotics Lab, I-X AI Initiative

• Artificial Intelligence and Data Science
• Decision Making & Optimization
• Machine Learning & Intelligence
• +8 more

Min Lee is a Full-time Assistant Professor of Computer Science at Singapore Management University's School of Computing and Information Systems (SCIS). Holding a PhD from Carnegie Mellon University (2021), Lee specializes in Artificial Intelligence with a focus on Human-AI Collaborative Systems and their applications in healthcare. Their research bridges technical innovation with human-centric design, emphasizing trustworthiness, explainability, and accessibility in AI systems. Research interests include decision-making optimization, human-machine collaboration, and AI-driven solutions for healthcare challenges such as stroke rehabilitation, elderly care monitoring, and clinical decision support. Lee has pioneered low-cost AI/robotic solutions for post-stroke rehabilitation exercises, integrating socially assistive robotics with real-time feedback mechanisms. Recent work highlights AI's role in enabling trustworthy clinical decision-making through explainable AI (XAI) techniques like counterfactual explanations and gradient-based methods. Their systems address ethical concerns in predictive healthcare and advocate for stakeholder-inclusive design processes. Awards and grants: No specific awards mentioned in the profile, though research has been supported through collaborative projects with clinical partners and iterative user evaluations involving therapists and patients. Advising focuses on multidisciplinary projects spanning AI, healthcare, and human-computer interaction. Current advisees include BHOSALE Rimmon Saloman, TRAN Truong Thuy, and YANG Xinlin. Lee collaborates closely with clinical stakeholders to translate technical advancements into practical healthcare solutions, emphasizing iterative design and real-world applicability. Labs/teams: Active in SCIS's AI and Data Science initiatives, leading projects on intelligent decision support systems, socially assistive robotics for rehabilitation, and human-centered AI ethics frameworks.

Hanan SametView profile

Professor

• Spatial Databases
• Data Structures
• Geographic Information Systems (GIS)
• +5 more

Hanan Samet is a Distinguished University Professor at the University of Maryland's Computer Science Department, affiliated with the Institute for Advanced Computer Studies (UMIACS) and the Center for Automation Research. He holds a Ph.D. from Stanford University (1975) and specializes in spatial databases, data structures, and geographic information systems. His research bridges computer science and geospatial analytics, with applications in image databases, computer vision, and spatio-temporal data management. Education: Ph.D., Computer Science, Stanford University, 1975 Research Interests: Focuses on spatial data structures, GIS, spatio-textual systems like NewsStand and CoronaViz, trajectory analysis, and metric indexing. His work emphasizes scalable algorithms for spatial networks and multimedia databases. Notable Projects: CoronaViz : Tracks disease spread via spatio-temporal data visualization NewsStand : Maps news articles geospatially SAND: Spatial browser for digital government Awards: ACM Paris Kanellakis Award (2014), IEEE McDowell Award (2015), UCGIS Research Award, and Fellowships in ACM/IEEE/AAAS. Recognized for advancing spatial database theory and practice. Grants/Advising: Leads NSF-funded projects on spatio-textual extraction and similarity search. Advises graduate students (e.g., Nicole Schneider, Montana Hoover) and undergraduate researchers. Labs/Teams: Active in UMIACS and the Center for Automation Research, collaborating on projects like VASCO (spatial visualization tools) and MARCO (image database systems).