Find Academic Supervisors

Amir GhalamzanView profile

Associate Professor

• Robot Learning
• Robot Grasping and Manipulation
• Teleoperation
• +3 more

Amir Ghalamzan is an Associate Professor at the University of Surrey's School of Computer Science and Electronic Engineering, leading the Intelligent Manipulation Lab. His research focuses on robot learning, robotic grasping, teleoperation, and agri-food robotics. Previously, he held roles at the University of Lincoln and University of Birmingham. Education: PhD in Robot Learning (Politecnico di Milano, 2015), M.Sc. in Mechanical Engineering (Iran University of Science and Technology, 2009). Research Interests: He addresses real-world challenges like labor shortages in agriculture through robots for extreme conditions, such as strawberry picking. His work integrates advanced perception, AI, and control systems. Notable projects include developing autonomous strawberry-picking robots and haptic-guided teleoperation systems. Key Projects: Led the £310K CERES Agtech project (2020-2021) for autonomous strawberry robots, and contributed to the £1.5M Agri Open-Core project (2023-2027) for open-source harvesting software. Collaborated with institutions like Imperial College London and companies like Saga Robotics. Labs/Teams: Directs the Intelligent Manipulation Lab, focusing on tactile sensors (e.g., AST Skin) and soft robotics innovations.

Sebastian MichelmannView profile

Assistant Professor

• Cognitive Neuroscience
• Memory Processes
• Neurophysiology
• +7 more

Sebastian Michelmann is an Assistant Professor of Psychology at New York University's College of Arts and Science. His research focuses on understanding how temporal dynamic content is neurally represented and processed in episodic memory, with particular emphasis on fast-timescale memory retrieval mechanisms and their interaction with event knowledge. He employs electrophysiological methods (EEG/MEG), computational modeling, and behavioral experiments to study memory formation under naturalistic conditions. Education: PhD in Psychology from the University of Birmingham (2018), thesis awarded the Glushko Dissertation Prize (2020) Master's (Diploma) in Psychology from Julius-Maximilians-Universitaet Wuerzburg (2014) Postdoctoral research at Princeton University (2018–2023) under Professors Ken Norman and Uri Hasson Research interests include neural oscillations, event segmentation, and the role of generalized event knowledge in memory retrieval. His work bridges cognitive neuroscience with computational approaches, exploring how the brain encodes, stores, and retrieves temporally precise information. Key research directions involve studying how memory processes are embedded in continuous experience and developing tools to analyze neural data (e.g., intracranial EEG re-referencing). Recent studies explore event boundary detection using large language models and investigate the neural correlates of natural language comprehension through ECoG datasets. Scientific Awards: Glushko Dissertation Prize (2020) Laboratory activities focus on future projects combining electrophysiology with computational modeling to understand interactive dynamics of episodic memory. Collaborative efforts include developing semi-automatic alignment tools and cloud-based neuroimaging frameworks.

Lambert SchomakerView profile

Professor

• Artificial Intelligence
• Pattern Recognition
• Machine Learning
• +6 more

Prof. dr. Lambert Schomaker is a Full Professor of Artificial Intelligence at the University of Groningen, leading the Artificial Intelligence and Cognitive Engineering (ALICE) institute within the Faculty of Science and Engineering. His work spans perceptual intelligence, machine learning, and neuromorphic computing, with significant contributions to handwriting recognition, robotics, and historical document analysis. Affiliations: Bernoulli Institute, CogniGron (Cognitive Systems & Materials), and Data Science & Systems Complexity (DSSC) centers. Education: M.Sc. (1983) and Ph.D. (1991) in Psychophysiology/Psychology from Nijmegen University. Research Interests: AI, pattern recognition, neural networks, autonomous systems, and applications in cultural heritage (e.g., the MONK system for handwritten archive indexing). He has pioneered handwriting recognition methods used in modern devices like tablets and led the 30MEuro Target project for large-scale data mining. Grants & Projects: Includes NWO-funded initiatives (e.g., Catch, TriGraph) and EU projects (MANTIS, MANIC). Current focus areas include neuromorphic computing with electronic materials and AI-driven analysis of the Dead Sea Scrolls. Awards: IBM Faculty Awards (2011, 2012), IAPR Best Paper Award (2012), Ching Yee Suen Special Award (2012). Advising: Supervised over 20 PhD students in AI, robotics, and document analysis. Active in industry collaborations (e.g., HP, Microsoft). Labs/Teams: Director of ALICE, contributor to CogniGron, and leader of the MONK system team. Current research includes neuromorphic hardware development and AI applications in maintenance systems.

David TerburgView profile

Associate Professor

• Social Neuroscience
• Psychoneuroendocrinology
• Fear Processing
• +2 more

David Terburg is Associate Professor in Social Neuroscience at Utrecht University's Department of Psychology (Faculty of Social and Behavioural Sciences). His research examines neurobiological mechanisms of social behavior using multimodal approaches including hormone administration, fMRI, and lesion studies. His research focuses on: Neural basis of social motivation and aggression Amygdala function in threat processing and escape behaviors Hormonal modulation of social decision-making Cross-species validation of social neuroscience findings Analysis of his publications shows strong emphasis on the basolateral amygdala's role in rapid threat responses, and hormonal influences (testosterone, oxytocin) on social cognition. Recent work develops neurocomputational models of cerebellum-amygdala interactions. Scientific awards include: NWO Veni Award (2013) for research on neuroendocrine mechanisms of defense behaviors He teaches courses in neuropsychology and social neuroscience, employing methods like eye-tracking and psychophysiology. His lab uses pharmacological interventions and neuroimaging to study clinical populations including psychopathy and social anxiety. Research is supported by Dutch Science Foundation grants and involves international collaborations across Europe and South Africa.

Roberto BresinView profile

Professor

• Expressive Music Performance
• Emotion in Sound and Music
• Sound in Human-Robot Interaction
• +3 more

Roberto Bresin is a Professor of Media Technology at KTH Royal Institute of Technology's Division of Media Technology and Interaction Design (MID), part of the School of Electrical Engineering and Computer Science (EECS). He leads the Sound and Music Computing group and serves as Director of Studies for the Media Technology program and Director of NAVET, a center for art, technology, and design research. His work bridges music, robotics, and human interaction. Research focuses include expressive music performance, emotion in sound, robot sound design, and sonification. He holds a PhD in Music Acoustics from KTH (2000) and has extensive experience in sound engineering and interactive systems. Key projects involve designing auditory feedback for robots and exploring light's psychological impacts. His publications span robotics, sonification, and human-centered technology. Recent articles address robot sound aesthetics, daylight effects on behavior, and sonification of computer processes. Bresin collaborates internationally, contributing to EU initiatives like SAME and Nordic SMC networks. His work emphasizes cross-disciplinary innovation, with applications in education, healthcare, and environmental science.

Richard SaveryView profile

Research Fellow

• Artificial Intelligence
• Robotics
• Human-Robot Interaction
• +3 more

Richard Savery is an Honorary Research Fellow at Macquarie University's Faculty of Arts, affiliated with the Performance and Expertise Research Centre and the Centre for Applied Artificial Intelligence. His work bridges artificial intelligence, robotics, and music, focusing on creative interactions and trust-building through robotic musicianship. He holds a PhD in Music Technology from Georgia Institute of Technology (2021) and a Master's from UC Irvine. Key roles include developing the NSF-funded Keirzo rapping/drumming robot and publishing the edited book Sound and Robotics (2023). Research interests include emotional musical prosody, human-robot collaboration, and robotic performance. Notable projects include Shimon the singing robot and IVF sonification. Awards include a GANG Award (2015) for game audio. Active in interdisciplinary collaborations, he has composed music for films, ads, and video games, including Gunman Taco Truck and Gathering Sky . His work spans academic grants ($800k NSF-NRI grant), industry partnerships, and public installations like the Un[contained] Arts Festival's beehive exhibit. Over 50 publications highlight his contributions to robotics, music tech, and AI ethics.

• Visual Media Compression
• Machine Learning
• End-to-End Optimization
• +5 more

Jona Ballé is an Associate Professor in the Department of Electrical and Computer Engineering at New York University Tandon School of Engineering. His research focuses on visual media compression, leveraging machine learning and end-to-end optimization to advance compression techniques for traditional and emerging modalities (e.g., AR, plenoptic imaging). He holds a PhD in signal processing from RWTH Aachen University (2012), followed by postdoctoral work at NYU’s Center for Neural Science and a Research Scientist role at Google (2017–2024). His contributions include foundational work on JPEG AI and leadership in conferences such as CLIC and DCC. Education: PhD in Signal Processing, RWTH Aachen University (2012) Master’s in Signal Processing, RWTH Aachen University (2007) Research: Ballé bridges machine learning and perceptual science to improve compression efficiency. Key areas include perceptual metrics, end-to-end optimization, and distributed coding. His work on Wasserstein distortion and Fourier basis models reflects cutting-edge advancements in compression theory. Impact: As co-organizer of the Challenge on Learned Image Compression (CLIC) and program committee member of the Data Compression Conference (DCC), he drives community progress. His industry collaborations and leadership in the JPEG AI standard highlight his translational research.

Rick GrushView profile

Professor

• Philosophy of Mind
• Cognitive Science
• Perception
• +4 more

Rick Grush is a Professor of Philosophy at the University of California, San Diego (UCSD). His primary affiliation is with the Department of Philosophy, though his research intersects with cognitive science, neuroscience, and interdisciplinary studies. His research focuses on perception, temporal experience, representation theory, enactivism, and neurophilosophical questions. Notable themes include crossmodal perception, agency theory, and the philosophical analysis of sensory integration. He critiques and synthesizes theories from both analytic philosophy and cognitive science, often engaging with empirical research in neuroscience. Grush’s recent work explores the temporal structure of perceptual experience, agency’s role in perception, and the philosophical implications of enactivist frameworks. His publications consistently bridge gaps between abstract philosophical concepts and concrete scientific methodologies, emphasizing interdisciplinary dialogue. Though no academic awards or grants are explicitly noted in the provided materials, his prolific output from 2016 to 2023 demonstrates sustained engagement with cutting-edge debates in philosophy of mind and cognitive science.

Pamela Carreno-MedranoView profile

Lecturer

• Human-Robot Interaction
• Robot Learning
• Socially Assistive Robotics
• +4 more

Dr. Pamela Carreno-Medrano is a Lecturer and Early Career Research Representative in the Department of Electrical and Computer Systems Engineering at Monash University. Her research focuses on Human-Robot Interaction (HRI), robot learning, and socially assistive robotics. She holds a PhD in Information & Communication Sciences (Université de Bretagne-Sud), Master's in Computer Science (École Nationale d’Ingénieurs de Brest), and a Bachelor's in Computer Systems Engineering (Universidad EAFIT). Her work emphasizes human-centered design for intelligent systems, including adaptive navigation algorithms, human-robot collaboration models, and affective computing applications. She leads projects on long-term human-robot interaction and has contributed to interdisciplinary studies on robot ethics and public space integration. Dr. Carreno-Medrano also serves as an Adjunct Lecturer at Universidad EAFIT and collaborates internationally on sustainable aging technologies through the ARC Training Centre for Optimal Ageing. Current research themes include aligning task representations between humans and robots, modeling non-goal-driven human behaviors, and socially aware navigation strategies. She actively supervises postgraduate students in HRI, offering projects on interactive robot learning and embodied AI systems.

Elizabeth CondliffeView profile

Assistant Professor

• Neurorehabilitation
• Exercise
• Movement Impairment
• +4 more

Dr. Elizabeth Condliffe is an Assistant Professor at the University of Calgary's Cumming School of Medicine, Department of Clinical Neurosciences, specializing in Physical Medicine and Rehabilitation. She holds adjunct roles in the Faculty of Kinesiology and is a Full Member of the Hotchkiss Brain Institute. Her clinical and research work focuses on neurorehabilitation strategies for children and adults with cerebral palsy and neurodisabilities, emphasizing robotic technologies, neurophysiological tools, and exercise interventions to enhance motor function and quality of life. Education: PhD in Biomedical Engineering, University of Alberta (2021) MD, University of Toronto (2008) MS in Biomedical Engineering, Boston University (2004) BSE in Mechanical & Aerospace Engineering, Princeton University (2002) Research Interests: Dr. Condliffe leads the Pediatric Onset Neuromotor Impairment (PONI) Lab, exploring robotic walking aids, neurostimulation, and clinical tools to address movement impairments. Key areas include: Robotic exoskeletons for bone/muscle health Neuroplasticity mechanisms in cerebral palsy Brain stimulation for motor recovery Adapted physical activity impacts on family dynamics Labs & Networks: She co-leads the Movement Impairment team in the RESTORE Network, participates in the NonInvasive Neurostimulation Network (N3), and is part of the Vi Riddell Pediatric Pain & Rehabilitation Centre.

• Language Acquisition
• Music Cognition
• Comparative Cognition
• +3 more

Juan Manuel Toro Soto is an ICREA Research Professor at the Department of Information and Communication Technologies, Pompeu Fabra University (UPF), Spain. He holds a BSc in Psychology from Universidad Nacional de Colombia and a PhD in Psychology from Universitat de Barcelona. His postdoctoral research included work at SISSA (Trieste, Italy) under Jacques Mehler, Harvard University (Primate Cognitive Neuroscience Lab), University of Rochester (Center for Language Sciences), and University College London (Institute of Cognitive Neuroscience). His research focuses on language and music processing in humans and non-human animals. Key interests include how infants and animals extract linguistic and musical patterns, comparative cognition, and the biological foundations of language acquisition. Notable findings include demonstrating that rats can perceive prosodic speech cues similarly to human infants (earning an Ig Nobel Prize) and showing that non-human species outperform humans in certain rule-learning tasks. Research Grants : European Research Council (ERC) Starting Grant Ministerio de Ciencia e Innovación (Spain) Bial Foundation (Portugal) AGAUR (Generalitat de Catalunya) Awards : Ig Nobel Prize in Linguistics (2023, for the rat speech study) Premio Extraordinario de Doctorado (Universitat de Barcelona) Cambio magazine '50 personajes de Colombia' (2020) His work bridges cognitive science and neuroscience, employing behavioral, neuroimaging, and computational approaches. Current projects explore cross-species auditory processing mechanisms and their implications for artificial language learning systems.

Avniel Singh GhumanView profile

Associate Professor

• Visual Cognition
• Magnetoencephalography (MEG)
• Intracranial EEG (iEEG)
• +4 more

Avniel Singh Ghuman, PhD, is an Associate Professor in the Department of Neurological Surgery at the University of Pittsburgh School of Medicine. He leads the Cognitive Neurodynamics Lab and serves as director of MEG Research. His work focuses on understanding visual perception mechanisms using advanced neuroimaging techniques like MEG and intracranial EEG. Dr. Ghuman holds a BA in Math/Physics from Johns Hopkins University (1998) and a PhD in Biophysics from Harvard University (2007), followed by postdoctoral training at the National Institute of Mental Health. Research Interests: Investigates how the brain processes visual information (objects, faces, words), social/affective perception, and neural dynamics underlying cognition. Uses MEG, iEEG, and machine learning to study spatiotemporal neural activity patterns and network interactions. Recent work explores real-world face perception coding and chaotic brain state transitions during natural behavior. Awards: Young Investigator Award (NARSAD, 2012) Award for Innovative New Scientists (NIMH, 2015) Lab & Collaborations: Directs the Cognitive Neurodynamics Lab, collaborating with neurosurgeons Drs. Taylor Abel and Jorge González-Martínez. Research emphasizes translational applications of MEG and neural stimulation to understand perception and cognition in real-world contexts.

Kuo-Ting HuangView profile

Assistant Professor

• Digital Inequalities
• Health Inequalities
• Community-Based Technology Interventions
• +3 more

Dr. Kuo-Ting (Tim) Huang is an Assistant Professor at the University of Pittsburgh’s School of Computing and Information. His research focuses on digital/health inequalities and community-based technology interventions targeting marginalized groups, with a focus on immersive technologies like VR/AR to address health disparities. He holds a PhD in Media and Information from Michigan State University. Dr. Huang’s work examines how emerging digital divides exacerbate health literacy gaps and explores solutions using technologies such as virtual reality. He emphasizes designing interventions to improve health outcomes for vulnerable populations, including older adults and racial minorities. His contact information includes timhuang@pitt.edu and an office at Room 616 in the Information Sciences Building. His research portfolio spans topics like telehealth adoption, AI literacy, and social media’s role in mental health. While no formal awards are listed, his work consistently addresses critical issues in health equity and technology access. Dr. Huang’s advising and grants are not explicitly detailed here, though his projects likely involve collaborations with healthcare and community organizations. He is affiliated with the School of Computing and Information’s broader initiatives in technology for social good.

• Machine Learning
• Computer Vision
• Robotics
• +4 more

Stéphane Lathuilière is currently a postdoctoral researcher at the University of Trento, having completed his PhD at INRIA under the supervision of Dr. Radu Horaud within the PERCEPTION team. His educational background includes: Engineering degree in Applied Mathematics and Computer Science from Ensimag, Institut polytechnique de Grenoble, France (2014) Master thesis conducted at the International Research Institute MICA, Hanoi, Vietnam His research spans machine learning for activity recognition and tracking, deep regression models, and reinforcement learning for audio-visual fusion in robotics, with primary applications in human-robot interaction and computer vision systems. Analysis of his 2014-2017 publications reveals consistent focus on multimodal machine learning approaches across computer vision domains, including head-pose estimation, group activity recognition, UAV imagery analysis, and mental health assessment through depression severity estimation. No scientific awards were documented in the source material. Information regarding student supervision or research grants is not provided in the available text. During his doctoral studies, he contributed to the PERCEPTION team at INRIA, specializing in perception systems for robotics and computer vision.

Nejc GeržiničView profile

Researcher

• Travel behaviour
• Public transport
• Micromobility
• +7 more

Nejc Geržinič is a PostDoc researcher at Delft University of Technology in the Transport, Mobility and Logistics department within the Civil Engineering & Geosciences school. His research focuses on travel behavior, particularly examining the integration of new mobility services with traditional public transport systems and investigating sustainable mobility solutions through innovative approaches like tradeable mobility credits. Dr. Geržinič completed his PhD at TU Delft between 2019 and 2023, with research focusing on the impact of on-demand mobility and its interaction with public transport, as well as long-distance international travel behaviour. His doctoral work contributed significantly to the CriticalMaaS project, which developed comprehensive frameworks for Mobility as a Service systems. Geržinič's research spans several critical areas in contemporary transportation studies. His work primarily investigates travel behaviour with a focus on how new mobility options like on-demand services and micromobility integrate with traditional public transport systems. He employs advanced choice modelling techniques to understand passenger decisions, particularly regarding access/egress trips in train travel chains and the potential of tradeable mobility credits systems. His research contributes significantly to the fields of sustainable transport and modal shift , aiming to develop more efficient and environmentally friendly urban mobility solutions. His expertise aligns with UN Sustainable Development Goals related to sustainable cities and communities. Analysis of Geržinič's publication record reveals a strong progression from foundational work on on-demand mobility services toward more sophisticated modeling of travel behavior and innovative mobility concepts. His recent 2025 publications indicate an expanding research agenda that now includes examining barriers to micromobility adoption through latent class analysis and exploring the potential of microtransit for regional commuting patterns. His work consistently examines how new mobility services can serve as effective first/last mile connectors for train stations, potentially increasing overall public transport usage while reducing private vehicle dependency. Dr. Geržinič has been actively engaged in disseminating his research through multiple media channels, with documented media contributions each year from 2019 to 2023. His presentations at workshops and conferences have addressed critical topics including the role of on-demand services in urban mobility mixes and the market potential of pooled mobility services. As part of the CriticalMaaS project (2019-2023), Geržinič collaborated with a multidisciplinary team including O. Cats, N. van Oort, and S.P. Hoogendoorn. His current postdoctoral research continues to explore innovative mobility concepts, particularly focusing on access/egress trips in train travel chains and travel behaviour in systems with tradeable mobility credits. His research outputs include 16 publications, 7 datasets, and numerous academic activities, demonstrating consistent productivity and contribution to the transportation research community.