Dr. Yar Muhammad is a Principal Lecturer in Computer Science at the University of Hertfordshire's School of Physics, Engineering & Computer Science. His research develops Brain-Computer Interface applications using AI/ML techniques for healthcare. He holds a PhD in ICT (Tallinn University of Technology) and dual master's degrees. Research Leadership: Supervised PhD students: Nimra Memon (fault-tolerance in web services), Dmytro Zabolotnii (agent behavior prediction), Mahir Gulzar (context-aware modeling) Accepts self-funded PhD candidates in BCI/AI applications Awards: Young Investigator Award (Springer/IFMBE, 2014) Best Paper Award Runner-up (26th ISSC 2015) Professional Recognition: Fellow of Higher Education Academy IEEE Senior Member Editorial board member for multiple journals
Dr. Tatsuya Mori is a Professor at the Department of Computer Science and Communication Engineering , Faculty of Science and Engineering, Waseda University . He also holds visiting researcher positions at RIKEN Center for Advanced Intelligence Project (since 2018) and National Institute of Information and Communications Technology (since 2019). Education: Ph.D. in Information Science (2005), Waseda University Research Interests: Spanning information security and privacy across emerging technologies like autonomous driving , AI , 3D sensing , VR , biometric measurement , and Web3 . His work focuses on offensive security and interdisciplinary research , including physical-layer attacks on sensors and behavioral studies on phishing detection. Scientific Awards: Recipient of multiple prestigious awards, including the Distinguished Paper Award Runners-Up at IEEE EuroS&P 2024 , IPSJ Outstanding Paper Award 2024 , and CSS2024 Concept Research Prize . His research has been recognized in top conferences like USENIX Security , NDSS , and ACM CCS . Professional Leadership: Active in academic governance as Chief Investigator for NISC Working Groups and Committee Member for JST Research Areas . He serves on program committees for NDSS , IMC , and ACM CCS .
Rajesh Krishna BALAN is a Full-Time Professor at the School of Computing and Information Systems (SCIS) at Singapore Management University (SMU) . His research focuses on Human-Machine Collaborative Systems , Pervasive Sensing , and Health & Wellbeing technologies. Based in Singapore, he leverages mobile computing to address urban sustainability and quality-of-life challenges. PhD from Carnegie Mellon University (2006) Specializes in WiFi sensing , VR/AR , and health monitoring Advises PhD students in areas like urban mobility , empathetic design , and cyber-physical systems Beyond academia, BALAN's work bridges ubiquitous computing and public health , with applications in ageing populations , mental health analytics , and smart city optimization . His recent publications highlight cross-disciplinary approaches to sleep analysis , group behavior modeling , and contactless physiological sensing . BALAN actively contributes to educational technology through projects like Technology-Enhanced Learning frameworks. He is also a mentor in collaborative research areas including biomedical informatics and lifestyle monitoring , with a focus on mobile GPU optimization and low-power systems .
Mahadev Satyanarayanan is the Jaime Carbonell University Professor of Computer Science at Carnegie Mellon University. His multi-decade research focuses on performance, scalability, availability, and trust in distributed systems spanning cloud to mobile edge computing. He pioneered foundational concepts in mobile computing and Edge Computing through his seminal work on VM-based cloudlets. His current research explores cloudlet-based Edge Computing for latency-sensitive applications, wearable cognitive assistance systems integrating augmented reality, and edge-based machine learning frameworks for efficient training data discovery. He collaborates with Dan Siewiorek, Martial Hebert, and Bobby Klatzky on transformative applications. Dr. Satyanarayanan received his PhD from Carnegie Mellon University after completing Bachelor's and Master's degrees at the Indian Institute of Technology, Madras. His honors include ACM and IEEE Fellowships recognizing his contributions to distributed systems and mobile computing. ACM Fellow IEEE Fellow
Dr. Timothy H. Murphy is a Professor in the Department of Psychiatry at the University of British Columbia's Faculty of Medicine. He is also an Associate Member of the School for Biomedical Engineering and a Member of the Djavad Mowafaghian Centre for Brain Health. Dr. Murphy leads the Dynamic Brain Circuits in Health and Disease initiative and the Division of Neuroscience and Translational Psychiatry at UBC. Dr. Murphy received his Ph.D. from Johns Hopkins University in 1989 and his B.Sc. from Saint Mary's College Maryland in 1984. His research focuses on understanding brain circuit structure-function relationships in relation to stroke recovery, psychiatric disorders, and neurological diseases. He specializes in mesoscale imaging techniques to study cortical activity patterns and develop automated approaches for brain imaging and stimulation. His laboratory develops innovative tools including open-source hardware for automated mouse brain imaging, synthetic data generation for behavioral analysis, and chronic recording systems that enable simultaneous mesoscale cortical imaging with subcortical or peripheral nerve activity monitoring. Research from the Murphy Lab has significantly advanced our understanding of how brain circuits reorganize after stroke and in models of psychiatric disorders. Dr. Murphy's recent publications reveal trends in mesoscale cortical imaging, development of synthetic data for behavioral analysis, and exploration of circuit-level changes in neurological and psychiatric disease models. His work bridges basic neuroscience with potential clinical applications for stroke recovery and mental health treatments. Dr. Murphy has mentored numerous students and postdoctoral fellows who have gone on to successful careers in neuroscience and related fields. His laboratory has received funding to support innovative approaches to understanding brain circuit function and recovery mechanisms. The Murphy Lab maintains strong collaborative ties across UBC and develops open-source tools that are widely adopted by the neuroscience community. Their work on automated home-cage imaging systems, synthetic behavioral data generation, and chronic recording technologies represents significant methodological advances in the field.
Stuart Reeves is an Associate Professor at the School of Computer Science, University of Nottingham, UK. He is a member of the Mixed Reality Lab, Horizon research institute, Centre for Doctoral Training (CDT), and Social Interaction and Technology (SIT) Special Interest Group. Reeves serves as an elected member of the University of Nottingham Senate with his term extending until 2026. His academic career spans over two decades with significant contributions to human-computer interaction, particularly focusing on social and collaborative technologies in real-world contexts. Reeves' research interests primarily focus on human-computer interaction, collaborative computing, design research, and the application of ethnomethodology and conversation analysis (EMCA) to technology studies. His work examines how people interact with diverse interactive devices and systems in real-world situations and places, with particular attention to public spaces, video gaming contexts, and collaborative work environments. Reeves has developed significant expertise in understanding spectatorship within interactive spaces and the 'work' involved in technological engagements. His publication record demonstrates consistent high-impact contributions to the field, with recent research focusing on robots and AI technologies in action, particularly examining how autonomous robots interact with humans in public streets. Reeves has received multiple prestigious awards including the HRI 2024 Best Paper Award for his work on public robot encounters and previous Best Paper Awards at CHI 2005 and CHI 2008. HRI 2024 Best Paper Award for 'Encountering autonomous robots on public streets' CHI 2015 Honourable Mention Award CHI 2008 Best Paper Award CHI 2005 Best Paper Award CHI 2012 Honourable Mention Award CHI 2020 Best Paper Award Reeves has secured substantial research funding including an EPSRC Early Career Fellowship, multiple EPSRC grants, and international collaborations. His teaching responsibilities include undergraduate and postgraduate supervision across various computer science modules, with a focus on sensor-based systems and software design principles. He maintains an active presence in the research community through publications, conference participation, and his Medium page where he shares insights on research methodology and practice.
Chao Liu is a Research Scientist at CNRS (French National Center for Scientific Research) since 2008, affiliated with the DEXTER team and the Department of Robotics, LIRMM at University of Montpellier, France. He earned his Ph.D. in Electrical & Electronic Engineering from Nanyang Technological University, Singapore (2006). Current research focuses on surgical robotics , haptics , teleoperation , and nonlinear control theory with applications in computer vision. His work addresses challenges in robotic-assisted telesurgery, including: Stable and transparent human-robot interaction through wave variable compensators and passivity filters Physiological motion compensation using spatio-temporal LSTM and dual Kalman filters EMG-based motion recognition for surgical skill assessment 3D soft-tissue reconstruction with stereo-endoscopes and deep learning Dr. Liu leads European and French projects like: TS2RT (CNRS-funded): Safer teleoperation with motion compensation ROBACUS (ANR-funded): Needle positioning with MPC control HaTUMoCo (CNRS-funded): Haptic teleoperation with uncertainty handling ARAKNES (EU-funded): Microrobotic systems for endoluminal surgery Scientific honors include Senior Member of IEEE and Member of Sigma Xi . He supervises Ph.D. and Master's students working on topics such as concentric tube robot optimization, haptic teleoperation, and EMG-based force estimation. Dr. Liu serves on IEEE Technical Committees for Telerobotics and Haptics , and as Technical Editor of IEEE/ASME Transactions on Mechatronics.
Dr. Todd D. Murphey is a Professor of Mechanical Engineering at Northwestern University's Robert R. McCormick School of Engineering and Applied Science. He serves as Director of Transformative Research and Director of the Master of Science in Robotics Program at Northwestern, leading initiatives in computational dynamics, control systems, and robotics. His work bridges engineering, neuroscience, and biomedical applications, with a focus on developing systems that interact effectively with humans and their environments. Dr. Murphey received his Ph.D. in Control and Dynamical Systems from the California Institute of Technology in 2002, with a thesis titled "Control of Multiple Model Systems." Prior to that, he earned a B.S. in Mathematics, summa cum laude, from the University of Arizona in 1997. Dr. Murphey's research centers on computational methods in dynamics and control, with applications spanning neuroscience, health science, robotics, and automation. His work in the Interactive & Emergent Autonomy Lab focuses on computational models of embedded control, biomechanical simulation, dynamic exploration, and hybrid control. The group develops mathematical approaches that lead to orders of magnitude improvement in computational efficiency for real-time implementation. Key application areas include assistive exoskeleton control, stabilization of energy networks, bio-inspired active sensing, entertainment robots, robotic exploration, and software-enabled stroke rehabilitation. Analysis of Dr. Murphey's recent publications reveals a strong emphasis on human-swarm interaction, algorithmic matter, and control of cyber-physical systems in uncertain environments. His work increasingly integrates information theory with physical systems, exploring how both autonomous and biological systems interact with environments to learn and improve behaviors. Recent trends show growing applications in rehabilitation technology, with particular focus on human-machine interaction in biomedical devices and embodied intelligence. Dr. Murphey has received numerous honors and awards for his contributions to robotics and engineering: Named Director of Transformative Research at Northwestern University (2025) Appointed IEEE Robotics and Automation Society Vice President of Publication Activities (2022) Co-recipient of Best Paper Award for IEEE Transactions on Robotics (2020) Appointed to Air Force Scientific Advisory Board (2019) Recipient of ABB Best Student Paper Award for CPL-SLAM research (2019) Cole-Higgins Award from Northwestern Engineering (2015) Dr. Murphey has supervised numerous graduate students including Taosha Fan, Giorgos Mamakoukas, and Ian Abraham, with research spanning robotic exploration using electrosense and mechanical contact, human-in-the-loop control, and shared control for rehabilitation devices. His lab has secured significant funding from the National Science Foundation, DARPA, and industry partners including Siemens and Ekso Bionics, supporting research in algorithmic matter, emergent behavior, and human-swarm collaboration. The Interactive & Emergent Autonomy Lab, led by Dr. Murphey, investigates how both autonomous systems and biological systems interact with their environments to learn and improve behaviors. Current projects include active learning and data-driven control, active perception in human-swarm collaboration, algorithmic matter and emergent computation, control for nonlinear and hybrid systems, cyber physical systems in uncertain environments, harmonious navigation in human crowds, information maximizing clinical diagnostics, reactive learning in underwater exploration, robot-assisted rehabilitation, and software-enabled biomedical devices. The lab collaborates with researchers across Northwestern and institutions including Georgia Tech, MIT, and industry partners.
Dr. Danial Chitnis is a Chancellor's Fellow and Lecturer in Electronics at the School of Engineering, University of Edinburgh. He holds a DPhil in Engineering Science from the University of Oxford (2013) and has expertise in microelectronics, biomedical engineering, and quantum imaging. His research focuses on SPAD arrays, time-of-flight sensors, and wearable optical systems for biomedical applications. Education: BSc in Electronics Engineering, Chamran University of Ahvaz (2002–2007) MSc in Advanced Microelectronics Systems Engineering, University of Bristol (2007–2008) DPhil in Engineering Science, University of Oxford (2009–2013) Research Interests: Single-Photon Avalanche Diode (SPAD) arrays for optical communications and biomedical imaging Quantum-enhanced imaging via QuantIC Hub Wearable sensors for near-infrared spectroscopy (NIRS) AI-driven automation in test and measurement systems Articles Trends: Recent work emphasizes AI integration in electronics design, photon-counting receivers for 6G networks, and portable biomedical devices. Notable contributions include SYCL-based acceleration of circuit simulations and FPGA-driven time-to-digital converters. Grants & Collaborations: Principal Investigator of multiple grants, including EPSRC-funded projects on AI-enhanced human-machine interfaces and quantum technology applications. Collaborates with UCL, QuantIC, and industry partners like Keysight Technologies. Labs/Teams: Co-investigator at QuantIC, the UK Quantum Technology Hub in Quantum Enhanced Imaging. Leads interdisciplinary research on detector arrays and systems for quantum physics and consumer cameras.
Guojun Chen is an Assistant Professor at the Department of Biomedical Engineering and a member of the Rosalind & Morris Goodman Cancer Institute (GCI) at McGill University . His research focuses on engineering intelligent biomaterials for precision medicine , with emphasis on non-viral genome editing , cold atmospheric plasma (CAP) therapy , and biomaterials-mediated immunotherapy . The lab operates in a multidisciplinary environment , integrating principles from materials science , chemistry , biology , and health sciences . Education : Ph.D. from University of Wisconsin-Madison (2017), Postdoc at UCLA (2020) Research Themes : Genome Editing Delivery : Designing non-viral vectors for efficient CRISPR/Cas9 delivery in vivo. CAP-mediated Immunotherapy : Developing portable cold plasma devices to synergize with immune checkpoint blockade and study CAP’s immunological mechanisms. Biomaterials-based Immunotherapy : Reprogramming tumor microenvironments using bioresponsive materials to enhance immune responses. Publication Trends : Recent work spans responsive nanomaterials , genomic editing systems , and plasma oncology , with a focus on cancer immunotherapy , diabetes diagnostics , and bioinspired medical devices . Scientific Awards : Canada Research Chair (2024, 2025) McGill's President's Prize for Emerging Researchers (2025) FRQS Chercheurs-boursiers (2022) Chinese Association for Biomaterials Young Investigator Award (2022) NSERC Discovery Grant (2021) Advising & Grants : Supervises 14 current graduate and undergraduate students. Secured $5M+ in funding from CIHR , NSERC , CCS , and CFI , including multi-institutional collaborations with Dr. Morag Park , Dr. Réjean Lapointe , and Dr. Ian Watson .
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 .
Dr. Rong-Hao Liang is an Assistant Professor at Eindhoven University of Technology (TU/e), affiliated with both the Future Everyday Group (Department of Industrial Design) and the Signal Processing Systems Group (Department of Electrical Engineering). His research bridges intelligent sensing systems and user interface technology for ubiquitous computing and embodied human-computer interaction . He co-organized international ACM conferences (CHI, UIST, DIS) and has over 70 peer-reviewed publications and 10 patents. PhD in Computer Science (2014) and MSc in Electrical Engineering (2010) from National Taiwan University Founded GaussToys Inc. in 2015, focusing on magnetic-field sensors Cross-appointed to Electrical Engineering in 2021 His research explores intelligent sensing systems , tangible user interfaces , and physiological sensors for real-world challenges. Key trends in his work include ubiquitous health monitoring (e.g., preterm infants), wearable technology , and innovative interaction design . Articles like GaussBits and NFCStack demonstrate his focus on magnetic and RFID-based tangible systems . Scientific awards include the ACM CHI 2013 Best Paper Award , 2014 Honorable Mentions , and the ACM SIGGRAPH Asia 2012 Emerging Technologies Prize . He mentors passion-driven projects in user interface design and embedded systems , emphasizing technical rigor and creativity. His STRAP project (2020–2025) addresses heart disease prevention via big data and AI . Labs and teams include the Future Everyday Group and Signal Processing Systems Group , with collaborations across healthcare , education , and technology startups . His work aligns with UN Sustainable Development Goals , particularly good health and well-being .
Xiaowen Zhang is a Professor of Computer Science at the College of Staten Island (CSI), City University of New York (CUNY), and a Doctoral Faculty Member at the CUNY Graduate Center. His academic work bridges theoretical and applied research in cybersecurity, information systems, and network technologies. Dr. Zhang holds a Ph.D. in Computer Science from the CUNY Graduate Center (2007) and a Ph.D. in Electrical Engineering from Northern Jiaotong University (1999), along with an M.A. from CUNY Queens College, an M.S. from Northern Jiaotong University, and a B.S. from Shanxi University. His research focuses on Cryptography, Information Security, Cybersecurity, Secure Biometrics, RFID Security & Privacy, Information Retrieval, and Wireless Sensor Networks . He explores both foundational cryptographic methods—such as secret sharing schemes and hash functions—and their practical implementations in secure systems, including RFID authentication protocols and data visualization platforms for sensor networks. The analysis of his recent publications reveals a consistent focus on security mechanisms in distributed and wireless environments . His work frequently combines cryptographic theory with system-level implementations, particularly in RFID and sensor networks. There is a strong trend toward privacy-preserving protocols, efficient data retrieval, and secure information sharing , often leveraging mathematical structures like Latin squares and Bloom filters. Dr. Zhang has been actively involved in mentoring students, as evidenced by numerous co-authored publications with graduate and undergraduate researchers. His contributions span journals such as Security and Communication Networks , Journal of Applied Security Research , and International Journal of Security and Networks , as well as major conferences including IEEE LISAT, ACM CODASPY, and IEEE Sarnoff Symposium.
Dr.-Ing. Thomas Wild serves as an Academic Director at the Technical University of Munich (TUM), working within the TUM School of Computation, Information and Technology at the Chair of Integrated Systems. He maintains an active research and teaching role at the institution, with his office located in Building N1 (Theresienstr. 90), Room N2136 in Munich, Germany. Dr. Wild's research focuses on advanced computing architectures, with particular emphasis on manycore system on chip (SoC) architectures, network processor (NPU) architectures, on-chip communication architectures including networks on chip (NoC), and system level design methodologies. His work bridges theoretical research with practical implementation, often exploring design space exploration techniques to optimize system performance. The evolution of his research over two decades demonstrates a consistent focus on improving communication architectures and system-level design for embedded and high-performance computing platforms. His recent publications (2023-2025) reveal a growing integration of machine learning techniques with traditional hardware design, particularly in optimizing power-performance tradeoffs in embedded systems. There's a clear trend toward hardware-software co-design approaches, with significant work on SmartNICs, Linux system optimization, and network processing acceleration. His research shows strong interdisciplinary connections between computer architecture, networking, and machine learning. EUROPRACTICE representative for TUM city campus, facilitating access to commercial EDA tools for academic purposes Active collaborator with Professor Andreas Herkersdorf and other researchers at TUM Focus on practical implementations with FPGA-based prototyping and real system modifications Dr. Wild teaches several hardware design courses including VHDL Lab, SystemC Lab, and HW/SW Codesign, contributing to the education of next-generation computer engineers. His teaching directly complements his research in system design and hardware acceleration, providing students with hands-on experience in cutting-edge technologies.
Pere-Pau Vázquez is an Assistant Professor in AI for Visual Computing at the Computer Vision Lab, TU Wien, Austria . Previously, he held academic positions at the ViRVIG Group and Facultat d'Informàtica de Barcelona (UPC) , where he taught courses in Programming, Computer Graphics, and Visualization for over 20 years. His research focuses on Information Visualization, Scientific Visualization, Medical Data Visualization, Molecular Visualization, and AI applications to Visual Computing . Current Teaching : Data Visualization, Fast Realistic Rendering, Information Visualization, Medical Images, Scientific Visualization, Virtual Reality, and 3D Medical Visualization. Former PhD Students : Elena Molina, Alexandra Cortez, Jesús Díaz, Pedro Hermosilla, Eva Monclús. His scientific awards include the Best PhD Thesis Award (UPC, 2003), Best Student Paper Award (SPIE, 2012), and Best Paper Award (International Conference on Computer Graphics Theory and Applications, 2013). Recent publications explore AI integration in biomedical visualization, molecular data analysis, and interactive techniques for volume rendering. He serves on the EuroGraphics Executive Board as Secretary and is active in steering committees for EuroVis and Visual Computing for Biology and Medicine . His work bridges Computer Graphics, Artificial Intelligence, and Human-Computer Interaction , with applications in medical and molecular data analysis.
