Find Academic Supervisors

Olaf DimigenView profile

Assistant Professor

• Visual Cognition
• Neuroscience
• Cognitive Psychology
• +3 more

Olaf Dimigen is a tenured Assistant Professor of Experimental Psychology at the University of Groningen, Netherlands. Previously, he held a visiting professorship for Biological Psychology at Humboldt University Berlin (2018-2022) and conducted research at the Max Planck Institute for Human Development. His research focuses on understanding how the brain integrates eye movements with visual perception and cognition, leveraging EEG/eye-tracking co-registration and advanced signal analysis techniques. Key affiliations: Faculty of Behavioural and Social Sciences, Department of Experimental Psychology Education: PhD in Psychology from Humboldt University Berlin (2014) Research interests include: Neural mechanisms of active vision Fixation-related potentials (FRPs) and microsaccade-related activity EEG artifact correction and deconvolution modeling Cross-linguistic reading processes Development of open-source analysis tools (EYE-EEG, UNFOLD, OPTICAT) Selected contributions: Pioneered methods for analyzing temporally overlapping EEG signals using deconvolution (UNFOLD toolbox) Optimized ICA-based ocular artifact removal for free viewing EEG (OPTICAT method) Discovered cognitive modulation of microsaccade-related potentials as attention markers His work bridges cognitive psychology, neuroscience, and computational methods, with applications in language processing, scene perception, and cultural neuroscience.

• Autonomous Underwater Vehicles
• Robotics
• SLAM (Simultaneous Localization and Mapping)
• +3 more

Dr. Gideon Billings is a Research Fellow at the School of Aerospace, Mechanical and Mechatronic Engineering, The University of Sydney. His work focuses on advancing autonomous underwater systems, robotics, and computer vision applications in marine environments. He is affiliated with the ACFR (Australian Centre for Field Robotics) Research Facilities, contributing to cutting-edge technologies like autonomous underwater gliders and shared autonomy systems. His research interests include underwater navigation, SLAM (Simultaneous Localization and Mapping), and precision manipulation in subsea environments. He has developed algorithms for 6D object pose estimation using monocular fisheye imaging and hybrid visual SLAM systems for robotic vehicles. His work bridges robotics engineering with marine science, enhancing unattended oceanographic exploration and subsea operations. Recent projects include a sovereign Autonomous Underwater Vehicle (AUV) capability grant (2024), demonstrating his role in advancing Australia's marine robotics infrastructure. Though no formal awards are listed, his publications in top-tier journals like Science Robotics and IEEE Transactions reflect his impactful contributions to the field. Advising and grants highlight his collaboration with industry partners like Rovver Robotics and academic institutions, focusing on underwater optical systems and navigation technologies. His lab's work is centered at the J18 ACFR facilities, advancing both theoretical and applied aspects of marine robotics.

Kevin D. WilsonView profile

Associate Professor

• Cognitive Neuroscience
• Neuroscience
• Psychology
• +3 more

Dr. Kevin D. Wilson is an Associate Professor of Psychology at Gettysburg College, serving as co-chair of the Neuroscience program. He specializes in cognitive neuroscience, combining non-invasive brain stimulation (tDCS), eye-tracking, and behavioral measures to study attention, memory, and emotional regulation. His academic journey includes a PhD in Experimental Psychology from the University of Pennsylvania (1999), a postdoctoral fellowship at Duke University, and a BA from Swarthmore College (1992). Research Interests: Dr. Wilson’s work focuses on understanding higher-level cognitive and social processes through innovative neuroscientific methods. His lab, the Cognitive Neuroscience Laboratory, explores topics like viewpoint-dependent neural activity, spatial attention mechanisms, and the integration of brain stimulation into undergraduate education. Recent studies highlight interdisciplinary approaches, including linking neuroscience with literature and addressing replication in psychological research. Teaching: Courses taught include PSYCH 238 Cognitive Neuroscience and PSYCH 305 Experimental Methods , emphasizing hands-on experience with advanced techniques like fMRI and tDCS. Labs/Teams: Director of the Cognitive Neuroscience Laboratory , fostering undergraduate research in cognitive processes and neurotechnology integration.

Richard HarveyView profile

Professor

• Artificial Intelligence
• Computer Vision
• Computer Science
• +3 more

Richard Harvey is a Professor in the School of Computing Sciences at the University of East Anglia (UEA), holding additional roles as Honorary Professor and Academic Director for Admissions and Internationalisation. His academic background includes a PhD in statistical estimation theory applied to synthetic aperture problems, with early career work in signal processing and acoustics. He transitioned to Computer Vision and AI, pioneering novel image analysis algorithms like 'sieves' and focusing on lip-reading research. His external roles include Former Livery Professor of IT at Gresham College and Fellowships at Gresham College and the British Computer Society. Research interests span computer vision, artificial intelligence, and lip-reading, with contributions to automated systems for security (e.g., baggage scanning) and accessibility (e.g., navigation aids for visually impaired individuals). Key projects include the AgriFoRwArdS CDT and collaborations with industry. He has led initiatives such as the Low Carbon Innovation Fund (LCIF) Investment Committee. His work integrates machine learning, pattern recognition, and multimodal data analysis, with publications in journals like Applied Sciences and Speech Communication. Awards include recognition for his contributions to computing and education.

• Transportation Safety
• Traffic Engineering
• Human Factors in Transportation
• +3 more

Felix Wilhelm Siebert is an Assistant Professor at the Department of Technology, Management and Economics within the DTU Management faculty at the Technical University of Denmark (DTU). His research focuses on transportation safety, human factors in urban mobility, and the application of computer vision and robotics in traffic analysis. Key areas of interest include cycling and e-scooter safety, helmet use compliance, and the psychological and environmental factors influencing risk behaviors. His work spans cross-cultural studies, such as assessing affinity for technology (TAEG Questionnaire), analyzing motorcycle helmet usage in Southeast Asia and Madagascar, and developing models for robot-pedestrian interaction based on proximity theory. He has also contributed to improving assistive technologies like hybrid eye typing interfaces and has explored the impact of substances like nitrous oxide on driving performance. Notable contributions include automated detection systems for helmet use using deep learning, safety perception studies through image comparisons, and behavioral analyses of e-scooter riders in urban settings. His research integrates interdisciplinary methods, combining computer vision, behavioral economics, and urban planning to address real-world transportation challenges. Dr. Siebert has published extensively on topics ranging from traffic conflict techniques to policy implications of shared mobility systems. Despite no listed awards, his work demonstrates significant engagement with global public health and infrastructure safety initiatives.

Robert CookView profile

Professor

• Animal cognition
• Visual perception
• Discrimination learning
• +3 more

Robert Cook is Professor of Psychology at Tufts University School of Arts and Sciences and Interim Chair of Sociology. His NIH-supported research examines animal cognition, visual perception, discrimination learning, and memory mechanisms across species including pigeons, starlings, and humans. Research investigates the perceptual and cognitive processes underlying object recognition, same-different concept learning, action recognition, temporal information processing, and equivalence class formation. Studies explore how animals form perceptual representations to guide learning and behavior. Recent publications advance understanding of visual and auditory processing, sequential learning dynamics, perceptual grouping, and cross-species cognitive strategies. Work integrates computational modeling with behavioral experiments to characterize cognitive architecture. Teaches courses on cognition origins and comparative psychology. Serves as Dean of the Graduate School of Arts and Sciences and publishes Comparative Cognition & Behavior Reviews. Developed online multimedia resources including Avian Visual Cognition and Animal Spatial Cognition cyberbooks.

Martin T. WhiteView profile

Associate Professor

• Thermal Power Systems
• Organic Rankine Cycle (ORC) Technology
• Supercritical Carbon Dioxide (sCO₂) Power Cycles
• +7 more

Dr. Martin T. White is an Associate Professor in Mechanical Engineering at the University of Sussex, part of the School of Engineering and Informatics and the Energy and Materials Engineering Research Centre (EMERC). He holds a PhD from City, University of London (2015) and an MEng in Mechanical Engineering from the University of Southampton (2011). Prior to his current role, he served as Senior Lecturer (2022–2024) and Lecturer in Thermal Power (2019–2022) at City, University of London, and held postdoctoral roles at Imperial College London and City. He is a Fellow of the Higher Education Academy and a member of the Institution of Mechanical Engineers. His research focuses on novel thermal power systems, particularly organic Rankine cycles (ORC), supercritical carbon dioxide (sCO₂) turbines, and waste-heat recovery. He leads the development of experimental test rigs and computational tools like pocketTHERM and pocketORC , which enhance education and design in thermodynamics. Key projects include the EU-funded SCARABEUS initiative, designing axial turbines for concentrated solar power, and optimizing turbine blades for CO₂ blends. Recent work includes advancing wet-to-dry expansion in ORC systems using non-equilibrium CFD simulations and experimental rigs. He has supervised PhD students (e.g., Charlie Westpfel, Pawel Ogrodniczak) and co-supervised Salma Salah, who successfully completed her viva in 2023. His research spans turbine aerodynamics, fluid dynamics, and educational technology, addressing global energy challenges through innovative thermal systems. Key achievements include the Royal Academy of Engineering Research Fellowship (2019–2024), which supported studies on two-phase expansion in ORC turbines. His work integrates academic and industrial collaboration, exemplified by the SCARABEUS turbine design with industrial partners. Future directions include experimental validation of two-phase expansion and exploring CO₂-blend applications in heat pumps and refrigeration systems. Awards and recognition include the IMechE awards for student projects supervised and the University of Sussex’s Brian Roberts Prize for academic excellence. His interdisciplinary approach bridges fundamental research, engineering design, and educational innovation in sustainable energy systems.

Raj SunderramanView profile

Professor

• Databases
• Data Mining
• Big Data
• +6 more

Raj Sunderraman is a Professor of Computer Science at Georgia State University, specializing in databases, data mining, and logic programming. His research focuses on deductive databases, semantic web technologies, bioinformatics, and graph data modeling. He holds a B.E. (Honors) in Electronics Engineering from Birla Institute of Technology and Science, an M.Tech. in Computer Technology from Indian Institute of Technology Delhi, and a Ph.D. in Computer Science from Iowa State University. His research projects include NeuronBank—a tool for cataloging neuronal circuitry—and work on scalable graph storage systems for big data. He has developed a programming environment for protein structure data and contributed to the paraconsistent relational data model. His teaching and research emphasize practical applications in bioinformatics, geoinformatics, and software systems. Key areas of exploration include reasoning with incomplete/inconsistent data, deductive database semantics, and graph query languages. Recent work involves lambda calculus visualization tools and 3D perception benchmarks for UAVs. He has authored over 150 publications and a textbook on Oracle 10g programming.

• Computer Vision
• Multimedia Systems
• Machine Learning Applications
• +7 more

Timothy K. Shih is an active academic researcher with over 30 years of scholarly contributions, evidenced by his extensive publication record from 1991 through 2025. With more than 380 publications spanning numerous prestigious venues including IEEE Access, Multimedia Tools and Applications, and Lecture Notes in Computer Science, he maintains a robust research profile with consistent annual output (20+ papers in peak years). His work demonstrates leadership through frequent senior/corresponding author positions and collaborations with numerous researchers across international institutions. Dr. Shih's research interests encompass a diverse range of computer science disciplines with particular emphasis on Computer Vision , Human-Computer Interaction , and AI Applications . His work bridges theoretical advancements with practical implementations in educational technology, accessibility solutions, and multimedia systems. Recent publications reveal a strategic focus on applying deep learning techniques to solve real-world problems in sign language recognition, gesture analysis, and wireless sensing applications. Analysis of his publication trends over the past five years shows increasing specialization in multimodal AI systems, with significant contributions to sign language technology (including Arabic Sign Language recognition), WiFi-based human activity recognition, and music technology applications. His research demonstrates strong interdisciplinary connections between computer vision, machine learning, and human-centered computing, with practical applications spanning educational technology, accessibility solutions, and smart environments. Through his mentorship, Dr. Shih has guided numerous junior researchers who have become frequent collaborators, including Chih-Yang Lin, Hsin-Hung Cho, and Tipajin Thaipisutikul. His research program appears well-funded through consistent publication output across multiple project areas, suggesting successful grant acquisition in computer vision, AI, and educational technology domains. Current work indicates active involvement in cutting-edge research on diffusion models for audio processing, enhanced sign language recognition systems, and novel approaches to WiFi-based human interaction analysis.

Andrea CavallaroView profile

Professor

• Machine Learning
• Artificial Intelligence
• Computer Vision
• +3 more

Andrea Cavallaro is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL), serving as Director of the Idiap Research Institute. His roles span academia and leadership, including directing the Centre for Intelligent Sensing and holding editorial positions in top journals. He specializes in machine learning for multimodal perception, privacy-preserving AI, and autonomous systems. Cavallaro leads projects like CORSMAL (multimodal object recognition) and GraphNEx (explainable AI). Education: PhD in Electrical Engineering from EPFL (2002). Notable awards include the Royal Academy of Engineering Teaching Prize (2007) and IEEE AVSS Best Paper Award (2009). He is a Fellow of the Higher Education Academy, International Association for Pattern Recognition, and ELLIS. Research focuses on aligning AI with societal values, particularly privacy and trustworthiness. Recent work explores adversarial attacks, privacy personas, and robotic manipulation. His 2025 publications address 3D reconstruction, privacy-aware models, and human-robot interaction. PhD students: 11 advisees in deep learning and robotics. Grants/Projects: AlignAI (trustworthy LLMs), GraphNEx (GNNs for XAI), CORSMAL (multimodal sensing). Labs/Teams: Idiap Lab (EPFL), leading CORSMAL consortium, and Turing Institute collaboration.

Heike TrautmannView profile

Professor

• Multi-criteria optimization
• Evolutionary optimization
• Automated algorithm selection and configuration
• +6 more

Prof. Dr. Heike Trautmann is a leading researcher in statistics and optimization at the University of Twente (2021-2026) and former Professor at WWU Münster (2013-2016). Her work bridges computational statistics, evolutionary optimization, and social media analytics. She has held visiting positions at TU Dortmund, Leiden University, and RWTH Aachen. Current affiliation: University of Twente (Data Science: Statistics and Optimization) Previous roles: WWU Münster (Professor for Information Systems and Statistics), TU Dortmund (Postdoctoral researcher) Research Focus: Multi-criteria optimization, automated algorithm selection, data stream mining, and disinformation detection in social media. Her methodological innovations in exploratory landscape analysis and evolutionary computation have transformed algorithm configuration practices. Developed COSEAL consortium for algorithm selection Co-founder of Benchmarking Network (2019) Principal investigator in projects like PropStop and MODERAT! Academic Contributions: Over 150 publications in top venues like GECCO, PPSN, and Evolutionary Computation journal. Pioneered feature-based landscape analysis tools (flacco, pflacco) and stream clustering frameworks.

Antonella PalmeseView profile

Assistant Professor

• Observational Cosmology
• Gravitational Wave Astronomy
• Galaxy Evolution
• +5 more

Antonella Palmese is an Assistant Professor in the Department of Physics at Carnegie Mellon University's Mellon College of Science. She specializes in observational cosmology, gravitational wave astronomy, and galaxy evolution, with affiliations to the Dark Energy Survey (DES), Dark Energy Spectroscopic Instrument (DESI), Laser Interferometer Space Antenna (LISA), Rubin Observatory Legacy Survey of Space and Time (LSST), and the Cosmic Explorer Consortium. Her research leverages galaxy surveys and gravitational wave data to study cosmic dynamics, dark energy, and the formation of compact object binaries. Ph.D., University College London (2018) M.Sc. and B.Sc., La Sapienza University of Rome (2013, 2011) Previous roles: NASA Einstein Fellow at UC Berkeley (2021–2022), Postdoctoral Research Associate at Fermilab (2018–2021), Associate Fellow at the University of Chicago (2019–2021) Her research lies at the intersection of gravitational wave experiments , large galaxy surveys , and time domain astronomy . Key projects include standard siren cosmology, GW follow-up with DECam, and galaxy cluster studies. She leads or co-leads initiatives like the DESI Transients and Low-redshift Cosmology Working Group, the GW-MMADS survey, and the DESIRT project. Recent publications focus on gravitational wave cosmology (e.g., Hubble constant measurements), binary black hole mass distributions , AGN flare correlations , and dust attenuation in galaxies . Her work integrates data from LIGO/Virgo runs, DES, DESI, and LSST to address fundamental cosmological questions. 2022 : Leonardo Da Vinci Award for Physics, Math, and Engineering 2021 : NASA Einstein Fellowship 2020 : Fermilab Exceptional Performance Recognition Award 2019 : Royal Astronomical Society Michael Penston Prize runner-up 2014 : Enrico Persico award Antonella uses facilities like the Dark Energy Camera (DECam) and contributes to multi-messenger astronomy by linking gravitational waves to electromagnetic transients. Her extracurricular interests include beach volleyball, crossfit, and visual arts.

• Artificial Intelligence
• Image Processing
• Computer Vision
• +3 more

Stamatia Giannarou is an Associate Professor in Surgical Cancer Technology and Imaging at the Department of Surgery & Cancer, Faculty of Medicine, Imperial College London. She is affiliated with the Hamlyn Centre for Robotic Surgery, CRUK Convergence Science Centre, and other institutes. Her research focuses on artificial intelligence, image processing, computer vision, and surgical robotics. Giannarou holds a Royal Society University Research Fellowship and has contributed to advancements in intraoperative imaging, surgical instrument tracking, and machine learning applications in healthcare. Education: MEng in Electrical and Computer Engineering (Democritus University of Thrace, Greece, 2003) MSc in Communications and Signal Processing (Imperial College London, 2004) PhD in Object Recognition (Imperial College London, 2008) Research Interests: Her work bridges AI and surgical technology, including visual recognition in surgery, robotic navigation, and real-time tissue characterization. Key themes include: Autonomous robotic ultrasound systems for neurosurgery Deep learning for tumor segmentation and image analysis LiDAR and hyperspectral imaging for intraoperative guidance Markerless surgical tool tracking and pose estimation Awards: Royal Society University Research Fellow Grants & Labs: Leads projects on AI-driven surgical data science and collaborates on initiatives like the SurgRIPE challenge for robotic instrument pose estimation. Active in the Hamlyn Centre’s multidisciplinary research teams. Future Work: Expanding real-time surgical imaging modalities and ethical AI integration in surgical training systems.

Sandip DuttaView profile

Lecturer

• Thermal Systems Engineering
• Image Processing and Cognition
• Software Quality Assurance
• +3 more

Dr. Sandip Dutta is a Lecturer in the Department of Mechanical Engineering at Clemson University. He holds a Ph.D. from Texas A&M University, an MS from Louisiana State University, and a BS from the Indian Institute of Technology, Kharagpur. He is certified in ASQ Software Quality and Six Sigma Green Belt. His research focuses on Thermal Systems, Turbulence modeling, Software Quality Assurance, Image Processing and Cognition, and Business Analytics. He has contributed to 33 international patents in Gas Turbine Technology, 3D Metal Printing, and Thermal Systems engineering. His work bridges mechanical engineering with healthcare technology through innovations in medical imaging analysis using deep learning. Notable contributions include automated medical image alignment, CT image segmentation, and low-dose calcium scoring techniques. Dr. Dutta’s research also extends to fusion energy physics through studies on the ADITYA-U tokamak and additive manufacturing applications in turbine components. His publications highlight advancements in domain adaptation for medical imaging, hybrid 3D-2D localization systems, and artifact detection in CT scans. While no specific grants or advising roles are listed, his patents and collaborations indicate active engagement in industry-research partnerships.

Lester LoschkyView profile

Professor

• Visual Cognition
• Attention and Eye Movement Tracking
• Cognitive Psychology
• +6 more

Lester Loschky is a full Professor in the Department of Psychological Sciences at Kansas State University's College of Arts and Sciences. His Visual Cognition Laboratory conducts interdisciplinary research combining visual perception studies with machine learning applications, supported by National Science Foundation and Office of Naval Research grants. Current NSF-funded focus on attention measurement in online learning Pioneering work in Scene Perception & Event Comprehension Theory (SPECT) Global collaborations with psychologists, computer scientists, and STEM educators Active graduate student mentorship with 5-year funding packages available His research explores how attention shapes awareness through eye movement tracking in natural scenes, integrating AI methodologies for attention modeling. Key subfields include scene gist recognition, event segmentation, and cognitive load theory applications in educational contexts. Students gain comprehensive research experience from experimental design to publication, with former students holding positions at Washington University, University of Colorado Denver, and U.S. Coast Guard Research. His lab offers both basic science and applied research opportunities with real-world implications in education and human factors.