Deva Kannan Ramanan is a Professor at the Robotics Institute of Carnegie Mellon University , focusing on computer vision , machine learning , and human-centered robotics . His work bridges neurorobotics and visual perception , with applications in autonomous driving and 4D reconstruction . Research Topics Computer Vision 3-D Vision and Recognition Visual Servoing Neurorobotics Human-Centered Robotics Graphics & Creative Tools His recent publications in CVPR , ICRA , and ICCV emphasize 4D human reconstruction , neural rendering , and vision-language models for autonomous systems. He serves as General Chair of CVPR 2027 and Program Chair of CVPR 2018 , with IARPA funding for aerial-ground rendering (2023-2027). Current students include PhD candidates Sally Chen, Kangle Deng, and Zhiqiu Lin, while past advisees like Arun Vasudevan and Olga Russakovsky now hold positions at Amazon and Meta respectively.
Dr. José del R. Millán is a Professor and holds the Linda Steen Norris & Lee Norris Endowed Chair in Neuroengineering at The University of Texas at Austin's Chandra Family Department of Electrical and Computer Engineering. He also serves as a Professor in Dell Medical School's Department of Neurology, a courtesy Professor in Biomedical Engineering, and is affiliated with the Mulva Clinic for the Neurosciences, Institute for Neuroscience, Texas Robotics, and the UT CARE Initiative. His work focuses on brain-machine interfaces (BMI), neuroprosthetics, and translating BMI technologies for individuals with motor/cognitive disabilities and able-bodied users. Education: PhD in Computer Science (1992, Technical University of Catalonia). Previous roles include Defitech Foundation Chair in Brain-Machine Interface at EPFL (Switzerland) and visiting scholar positions at Berkeley, Stanford, and the International Computer Science Institute. Research Interests: Neuroengineering, BMI applications in healthcare and assistive robotics, statistical machine learning for neural signals, and neurorehabilitation. Key contributions include EEG-based BMI systems, closed-loop neurostimulation, and wearable neurotechnology. Awards: IEEE Fellow (2017), Norbert Wiener Award (2011), and Fellow of the International Academy of Medical and Biological Engineering (2020). Grants & Labs: Co-director of UT CARE, leader in clinical neuroprosthetics and neurorobotics. Active in developing BMI-driven wheelchairs, VR integration for BCI, and EEG-based speech prosthetics. Research outputs emphasize translational neurotechnology, with projects funded by industry and governmental agencies. Labs/Teams: Clinical Neuroprosthetics & Brain Interaction Lab, Texas Robotics, Wireless Networking and Communications Group (WNCG).
Zhenhong Li is a Lecturer in Robotics and Control at the University of Manchester, holding an EPSRC Fellowship in physical human-robot interaction. He earned his B.Eng. from Huazhong University of Science and Technology (2013), and M.Sc. and Ph.D. in Control Engineering from the University of Manchester (2014 and 2019). Before joining Manchester in 2023, he was a Research Fellow in Rehabilitation Robotics at the University of Leeds (2019–2023). His research focuses on control technologies for human-robot systems, with applications in healthcare and industry. Key areas include physical human-robot interaction for rehabilitation, brain-computer interfaces, and neuromusculoskeletal modeling. He leads the Neurorobotics Lab (NRL) at Manchester and collaborates with healthcare professionals, industries, and designers via EPSRC/STFC/Wellcome Trust funding. Notable achievements include the 2019 Best Paper Award for Unmanned Systems and the 2020 EPS International Academic Pump-priming Award. In 2025, he was elected as a Senior Member of the IEEE. He actively organizes conferences and special issues, including the 2025 IEEE UK Robotics Conference and a Frontiers special issue on intelligent rehabilitation technology. Dr. Li supervises PhD candidates in robotics and control, emphasizing interdisciplinary approaches to human-robot interaction. His lab develops cutting-edge technologies like assistive exoskeletons and adaptive control systems for healthcare and industrial applications.
Jeffrey L. Krichmar is a Professor in the Department of Cognitive Sciences and Department of Computer Science at the University of California, Irvine. His academic journey includes a B.S. in Computer Science from the University of Massachusetts Amherst (1983), an M.S. in Computer Science from The George Washington University (1991), and a Ph.D. in Computational Sciences and Informatics from George Mason University (1997). Prior to UCI, he served as Assistant Professor at George Mason University (1997-1999) and Senior Fellow at The Neurosciences Institute (1999-2007). University of California, Irvine (2007-present) George Mason University (1997-1999) The Neurosciences Institute (1999-2007) His research focuses on neurorobotics , exploring how embodied cognition and biologically plausible neural models can enhance robotic systems. Key areas include spiking neural networks , neuromodulation , path planning , and interactive tactile robots for therapeutic applications. His work bridges neuroscience , robotics , and cognitive science , with applications in autonomous vehicles , neuroprosthetics , and AI explainability . Recent publications emphasize spiking neural networks for navigation , neuromodulated attention , and neuromorphic hardware integration. The development of CARLsim, a GPU-accelerated spiking neural network simulator now in version 6.0, represents a major technical contribution. His team's work on socially assistive robots like CARL-SJR targets therapeutic applications for autism and ADHD. Scientific Awards IJCNN 2020 Best Paper Award Finalist for Best Student Paper at IJCNN 2018 Best Paper Award at IEEE IJCNN 2009 Grants include National Science Foundation funding for neural models of decision-making (2009). His lab (Cognitive Anteater Robotics Laboratory) develops systems that use large-scale brain simulations for autonomous behavior , with applications in adaptive robotics , sensorimotor learning , and neuroethology . Current projects explore neuromodulatory influences on attention systems and cognitive flexibility .
Anis Yazidi is a Professor at Oslo Metropolitan University, affiliated with the Faculty of Technology, Art and Design and the Department of Information Technology. His research focuses on Artificial Intelligence, Machine Learning, Medical Technology, and IoT Security, with a particular emphasis on Applications of AI in Healthcare, EEG Signal Processing, and Digital Transformation. Active research projects include AI Mind (dementia diagnostics), Glycopathology in dry eyes, and Pain and mental distress analysis Completed projects: Digital hate speech analysis, AI in reproductive technology, Nano-antibiotics development His recent publications (2023-2025) demonstrate expertise in: Tsetlin Automaton algorithms for concept learning EEG classification using visibility graphs and vision transformers AI ethics frameworks for medical practice Deepfake detection methodologies Collaborative work spans institutions in Norway, Czech Republic, and international AI research communities.
Maria Luce Lupetti is a Fixed-term Assistant Professor at the Department of Architecture and Design (DAD) at Politecnico di Torino . She actively contributes to the College of Architecture and Design and is a member of the College of Mechanical, Aerospace and Automotive Engineering . Her academic role involves teaching Cognitive Ergonomics and HMI in the Automotive Engineering master's program and collaborating on Design and Communication courses. Editorial Roles: Associate Editor for the journal INTERACTIONS since 2024 Conference Leadership: Participating in organizing committee for CHI 2026 Research Projects: Scientific Director of PARJAI (2025-2028) on Participatory Design Justice for Ethical AI Transitions Research Focus : Maria's work bridges Design with Human-Robot Interaction , focusing on Ethical AI , Speculative Design , and Urban Robotics . Her recent publications explore: Speculative design for sustainable digital futures Contextual adaptability challenges in urban robotics Design taxonomies for demystifying AI Trustworthy embodied agents in healthcare Creative applications of AI in HRI Ethical frameworks for energy futures Design Philosophy : She emphasizes participatory approaches, critical design thinking, and transdisciplinary collaboration to address societal challenges at the intersection of technology, ethics, and human factors. Her work appears in leading venues including CHI , HRI , and Frontiers in Neurorobotics , while also contributing to edited volumes and journal special issues.
Mehdi Khamassi is a Research Director at the French National Center for Scientific Research (CNRS), assigned to the Institute of Intelligent Systems and Robotics (ISIR) at Sorbonne University in Paris, France. He holds an engineering background in computer science (specializing in AI and statistical modeling) from the National School of Computer Science for Industry and Business (2003), a Cogmaster in cognitive science from Pierre and Marie Curie University (2003), and a PhD in cognitive neuroscience from UPMC/Collège de France (2007). Recruited by CNRS in 2010, he co-organizes the Symposium of Biology of Decision-Making (SBDM) and co-directs the modeling major for the Cogmaster program. His research integrates computational modeling , neuroscience experiments , and robotic systems to study decision-making and learning mechanisms. Key interests include: Reinforcement learning in biological and artificial systems Role of social/non-social rewards in adaptive behavior Ethical implications of autonomous decision-making in AI Neuro-robotic models of hippocampal-prefrontal interactions Recent publications (2023-2025) demonstrate strong focus on reinforcement learning paradigms, AI alignment with human values, neurorobotics, and computational neuroscience. Work frequently bridges machine learning theory with empirical validation in biological systems or robotic platforms. He leads research within the ACIDE team at ISIR, exploring adaptive coordination of learning strategies in brains and robots. Current collaborations include NTUA (Greece), University of Oxford, and University of Trento.
Qiushi Fu is an Associate Professor in the Department of Mechanical and Aerospace Engineering at the University of Central Florida, focusing on neuromuscular control, human-robot interaction, and biomechanics. His work leverages assistive and rehabilitation technologies to improve motor function and performance. Ph.D. in Biomedical Engineering – Arizona State University M.S. in Mechanical Engineering – State University of New York at Buffalo B.S. in Automation – Tsinghua University Research interests include sensorimotor learning, bioinspired robotics, and rehabilitation prosthetics, integrating neuroscience, robotics, and machine learning. His recent publications emphasize adaptive control in dexterous manipulation, haptic communication, and wearable rehabilitation devices. Fu leads a multidisciplinary lab advancing human movement through technology, with applications in stroke recovery and prosthetic design. His work demonstrates trends in machine learning integration for neural decoding, bioinspired exoskeletons, and collaborative human-robot systems. Though no specific awards are listed, his research has been published in high-impact journals like Frontiers in Neurorobotics and Journal of Neuroscience .
Lisa Miracchi Titus is an Assistant Professor of Philosophy at the University of Denver, previously serving as an Associate Professor with tenure at the University of Pennsylvania. She is an IEEE Tech Ethics Ambassador and member of the IEEE SA Working Group on the Ethics of LAWS. Her research focuses on the nature of intelligence, AI ethics, and the integration of ethical considerations into AI development. She holds a Ph.D. in Philosophy (with a Cognitive Science certificate) from Rutgers University and an AB in Philosophy from Harvard. Her work bridges philosophy, cognitive science, robotics, and ethics, addressing questions about intelligent systems, agency, and ethical AI applications. She received an NEH grant for her book project on effective and ethical intelligence research, emphasizing feminist and social justice perspectives. Education: Ph.D. in Philosophy (Rutgers, 2014), A.B. in Philosophy (Harvard, 2009). Previous positions include Bersoff Assistant Professor at NYU and tenure-track roles at Penn. She is committed to academic diversity, having led wellness initiatives for graduate students and participated in LGBTQ+ advocacy. Her research also explores the ethical implications of AI’s feminization and the future of human-AI collaboration. Research Interests: Philosophy of AI, ethics of robotics, embodied cognition, and feminist approaches to technology. She advocates for interdisciplinary collaboration to ensure AI systems align with ethical, social, and cognitive science principles. Her current projects include the integration of ethical frameworks into AI design and the societal impacts of AI labor. Awards and Fellowships: National Endowment for the Humanities Grant (2022), NEH Fellowship (2021). Her work appears in journals like Journal of Philosophy , Philosophical Studies , and Frontiers in Neurorobotics . Labs and Collaborations: Affiliated with the GRASP Lab (Robotics) and MindCORE (Cognitive Science) at Penn, and now contributes to Denver’s interdisciplinary initiatives. She balances academic rigor with personal advocacy for mental health, wellness programs, and LGBTQ+ inclusion in academia.
Maria Letizia Marchegiani is an Assistant Professor at the University of Parma , affiliated with the Department of Engineering and Architecture . Previously, she held academic positions at Aalborg University (2019) and Oxford Robotics Institute (2014-2018). Education: PhD in Computer Science and Engineering from Sapienza - University of Rome , MSc/BEng in Computer Engineering Her research interests span signal processing , machine learning , and their applications to robotics , autonomous systems , intelligent transportation , and intelligent healthcare . She explores intersections between auditory perception , cognitive modeling , and energy-efficient wearable systems . Recent publications demonstrate expertise in acoustic event localization , ML-SDWSN architectures , thermal camera integration for vehicles, and privacy-preserving wearable systems . Her work addresses challenges in network reliability , urban soundscapes , and human-robot collaboration .
Professor Gordon Cheng is a faculty member at the Technical University of Munich (TUM), affiliated with the School of Computation, Information and Technology (CIT). He serves as the Director of the Chair of Cognitive Systems at the Institute for Cognitive Systems (ICS), where he focuses on advancing cognitive systems, robotics, and their intersections. His research addresses fundamental challenges in creating intelligent systems capable of understanding and interacting with complex environments. Research Interests: His work spans Neuroengineering , Robotics , and Cognitive Systems , emphasizing the integration of biological principles into artificial systems. Key projects include robot skin development , EEG-based prosthetic control , and human-robot co-adaptation . Selected Publications: Recent articles highlight advancements in real-time tactile sensing , neuroprosthetics , and BCI-driven rehabilitation , reflecting his interdisciplinary approach bridging robotics and neuroscience. Supervision: He supervises PhD students from the Graduate School of Neuroscience (GSN), including Jasmin Kajopoulos and Nikolas Berberich. Contact: Email: gordon@tum.de | Website
Nashra Ahmad is a Research Fellow at Durham University, affiliated with the Department of Music and the Institute for Medical Humanities. She is a PhD candidate supported by the Durham Doctoral Studentship and holds a Master's in Cognitive Science from IIT Gandhinagar (2021) and a BA in Psychology (First Class Honours) from Aligarh Muslim University (2018). Her research focuses on rhythm perception, consonance/dissonance dynamics, and music cognition, combining neuroscience and interdisciplinary approaches. She is an active member of the Music and Science Lab and an editorial assistant for DURMS . Additionally, she teaches Psychology at the Durham Centre for Academic Development (DCAD). Key research interests include: rhythmic entrainment in North Indian classical music, sensorimotor synchronization, and neural correlates of musical perception. Her work bridges cognitive science, musicology, and technology, with publications in Data in Brief , Frontiers in Neurorobotics , and Music & Science . Awards include the Sabarmati Bridge Fellowship (2021) for pre-doctoral research and the Durham Doctoral Studentship (2022). Education: Bachelor of Arts in Psychology (First Class Honours), Aligarh Muslim University, 2018 Masters in Cognitive Science, Indian Institute of Technology Gandhinagar, 2021 Her publications analyze EEG responses to music, resonance strategies in AI design, and beat prediction from neural data. She has presented at international conferences such as the International Conference of Students of Systematic Musicology (2023) and the Max-Planck-Institut für empirische Ästhetik (2022). Awards: 2022: Durham Doctoral Studentship 2021: Sabarmati Bridge Fellowship Teaching and Outreach: She teaches Psychology to foundation-year students at DCAD and has prior experience teaching guitar and music theory in India. Her creative interests include landscape painting and sculpting, reflecting her interdisciplinary engagement with art and science.
Athanasios Vourvopoulos is an Assistant Professor at the Department of Bioengineering, Instituto Superior Técnico (University of Lisbon). He leads research in Brain-Computer Interfaces (BCI), Virtual Reality (VR), and neurorehabilitation, focusing on applications for stroke recovery and neurological disorders. His work integrates EEG neurofeedback, neuromodulation, and embodied VR to enhance clinical outcomes. He teaches courses such as Fundamentals of Bioinstrumentation and Introduction to Biomedical Engineering. Research Interests Brain-Computer Interfaces Neurorehabilitation EEG Neurofeedback Neuromodulation techniques Human-Machine Interaction Assistive technologies His research emphasizes translating neurotechnologies into clinical settings, with studies on BCI-VR systems for motor recovery in stroke patients and EEG-based action anticipation in robotics. Recent work includes multimodal neuroimaging (EEG-fMRI) and open-source tools like NeuXus for real-time artifact reduction. Awards Early Career Investigator Award , International Society for Virtual Rehabilitation (ISVR, 2022) Diploma of Excellence in Teaching , Instituto Superior Técnico (IST, 2023) He collaborates with the Institute of Systems and Robotics (ISR-Lisbon) and has published extensively on BCI-VR integration, neuromodulation, and neurorehabilitation outcomes. His labs focus on developing embodied VR systems and BCI-driven therapies for motor impairment recovery.
Tossapon Boongoen is a Professor in the Department of Computer Science at Aberystwyth University, with over a decade of experience in artificial intelligence and machine learning. Previously, he served as Associate Professor at Mae Fah Luang University (2017-2022) and Royal Thai Air Force Academy (2011-2017), where he also directed the MFU Research and Innovation Institute. His research spans ensemble clustering for privacy-preserving data fusion deep learning in remote sensing and sky survey data network security applications for ransomware and intrusion detection forest fire risk modeling using spatial-temporal data Recent publications focus on convolutional neural networks, adversarial attack classification, and collaborative filtering algorithms. He leads international projects funded by the British Council, FCDO, and Academy of Medical Sciences, including collaborations with institutions in Thailand, Korea, Vietnam, France, and Czech Republic. Professional engagements include editorial roles in journals like Knowledge-Based Systems Frontiers in Neurorobotics PeerJ Computer Science ICT Express and partnerships with GISTDA, GOTO Observatory, and Imperial College London.
Oliver Lomp is a researcher at the Institute for Neuroinformatics (INI) within the Faculty of Computer Science at Ruhr University Bochum. His work focuses on integrating perception and object recognition into dynamic field theory frameworks for robotic systems. He actively contributes to publication and teaching in neurorobotics and cognitive systems. Contact details: Email: oliver.lomp@ini.rub.de Office: NB 02/77, Ruhr University Bochum Campus Research trends include: Dynamic Field Theory applications in robotics Neurodynamic architectures for autonomous systems Object recognition with concurrent pose estimation Development of cognitive frameworks like CEDAR
