جستجوی استاد راهنمای دانشگاهی

Christopher Palمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Computer Vision
• Pattern Recognition
• +۶ مورد دیگر

Christopher Pal is a Full Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montréal. With a Ph.D. from the University of Waterloo, he has held academic positions at the University of Rochester and the University of Toronto, and industry roles at Interval Research and Microsoft Research's Interactive Visual Media Group. Fields of Expertise: Artificial Intelligence, Computer Vision, Pattern Recognition, Machine Learning, and Natural Language Processing Affiliations: CIFAR Chair in Artificial Intelligence, Institute for Data Valorization (IVADO) Member His research focuses on deep learning applications in visual question answering , medical image segmentation , and generative models . Recent work involves multimodal data analysis for climate modeling and vision-language systems for code generation. Key projects include CarbonSense for climate flux modeling and GeoCoder for geometry problem-solving AI. His 15 most recent publications (2023-2025) span topics from diffusion models to multi-agent systems , with emphasis on video generation , 3D animation , and environmental applications . Scientific recognition includes: CIFAR Chair in Artificial Intelligence IVADO Institute Membership Top-2% cited researcher (2021) He has supervised 22 Ph.D. and Master's students, with recent graduates working on generative AI , reinforcement learning , and medical imaging . Current research grants include MITACS-funded projects in software engineering agents and drone imagery analysis for tropical forest conservation.

Ioannis Lambadarisمشاهده پروفایل

استاد

• Network Traffic Modeling
• Quality of Service (QoS) Control
• Cloud Data Center Resource Allocation
• +۸ مورد دیگر

Ioannis Lambadaris is a Full Professor and Chancellor’s Professor at Carleton University's Department of Systems and Computer Engineering, Faculty of Engineering and Design. Holding a Ph.D. from the University of Maryland, he has contributed extensively to network performance analysis over 25+ years. Specializes in stochastic processes, cloud computing, and wireless edge systems Led Ericsson 5G Chair initiatives Supervised over 70 graduate students His research spans QoS control , VNF placement optimization , and IoT indoor localization , with over 170 publications. Recent work focuses on reinforcement learning and deep learning in network resource allocation. Scientific Recognition: Chancellor’s Professor Ericsson 5G Chair Contact: ioannis@sce.carleton.ca | Office: Mackenzie 4448, Ottawa, ON

• Control Systems
• Signal Processing
• Automation Engineering
• +۱ مورد دیگر

Professor Minyue Fu is an Honorary Professor in the School of Engineering at the University of Newcastle, Australia, specializing in Electrical and Computer Engineering. With over 30 years of research experience, he has established himself as a leading expert in control systems and signal processing, having published over 500 research papers with an H-index of 55. His academic journey began with a Bachelor's degree from the University of Science and Technology of China, followed by M.S. and Ph.D. degrees from the University of Wisconsin-Madison. Prof. Fu's research interests span a broad range of topics in control theory and signal processing. His work consistently focuses on fundamental theoretical problems with practical applications in diverse fields including power systems, sensor networks, multi-agent systems, and cyber-physical systems. He has made significant contributions to distributed control algorithms, stochastic systems, quantization effects in control, and networked systems. His recent publications (2021-2024) demonstrate continued productivity and relevance in the field, with research spanning decentralized optimal control, anomaly detection in cyber-physical systems, cart-pole control systems, and mean-field games. These works reflect his ability to bridge theoretical control concepts with practical engineering challenges, particularly in the context of modern networked and distributed systems. Fellow of IEEE (2004) Fellow of IFAC (2022) Fellow of Engineers Australia Fellow of Chinese Association of Automation (2018) Throughout his career, Prof. Fu has held significant editorial positions including Editor of IEEE Transactions on Signal Processing (2010-2014) and Associate Editor for several prestigious journals. His research has been supported by numerous grants, though specific details aren't provided in the current text. His laboratory work has focused on practical implementations of control algorithms in various systems, demonstrating the real-world applicability of his theoretical contributions. Prof. Fu has also supervised numerous students throughout his career, though specific names aren't listed in the available information.

Lucia Seminaraمشاهده پروفایل

دانشیار

• Tactile Sensing
• Electronic Skin
• Haptic Robotics
• +۵ مورد دیگر

Lucia Seminara serves as an Associate Professor in the Department of Naval, Electrical, Electronic, and Telecommunications Engineering (DITEN) at the University of Genoa's Polytechnic School. She teaches Electronic Devices, Sensors, and Sensing Systems for Master's programs in Electronic Engineering and Engineering for Natural Risk Management, while also contributing to Philosophy of Medicine for Philosophical Methodologies. As a member of the Joint Teacher-Student Commission, she bridges academic governance with pedagogical innovation in engineering education. Her research pioneers tactile sensing systems using piezoelectric polymers (PVDF) and electronic skin for robotics and prosthetics. She investigates indentation mechanics on soft electronic skin, grasping speed sensitivity, and hierarchical sensorimotor control frameworks for human-in-the-loop robotic hands. Key innovations include machine learning-based contact force estimation and electrotactile feedback systems that restore natural touch perception in prosthetic devices, addressing critical gaps in sensory substitution technology. Analysis of her 2021-2025 publications reveals escalating integration of machine learning with tactile sensing, particularly in symmetry detection for efficient haptic exploration and transdisciplinary human-in-the-loop applications. Recent work emphasizes real-world implementations like post-stroke rehabilitation systems and high-bandwidth human-machine interfaces, demonstrating a strategic shift from foundational sensor development toward clinically viable solutions with measurable user impact. Dr. Seminara's research lineage includes significant contributions to the Roboskin project (2013), which established large-area tactile sensor arrays for robotics. Her current work extends this foundation through investigations into viscoelastic properties, stress transmission modeling, and AI-driven tactile perception, positioning her at the forefront of intelligent electronic skin development with active collaborations across engineering, neuroscience, and clinical rehabilitation domains.

Giuseppe FRANZE'مشاهده پروفایل

استاد

• Constrained Predictive Control
• Networked Control Systems
• Cyber-Physical Systems
• +۷ مورد دیگر

Giuseppe FRANZE' is a Full Professor at the Department of Mechanical, Energy and Management Engineering (DIMEG) of the University of Calabria since 2022. He has over 200 publications in archival journals, book chapters, and conference proceedings, with a focus on constrained predictive control, networked control systems, and resilient control for cyber-physical systems. His research includes theoretical and applied projects funded by MIUR/MUR, European Union, and international institutions. IEEE Senior Member (2019) Associate Editor for IEEE/CAA Journal of Automatica Sinica Guest Editor for Special Issue on Resilient Control in Large-Scale Networked Cyber-Physical Systems Organized sessions at CoDIT, ETFA, CASE conferences Collaborations with Carnegie Mellon, Concordia University, Georgia Tech, and others His research spans constrained predictive control, fault-tolerant strategies, obstacle avoidance for autonomous vehicles, and machine learning integration in control systems. Recent articles emphasize resilient control under network attacks, encrypted MPC, and reinforcement learning for multi-agent systems. He received Best Paper and Best Reviewer awards at international conferences. Best Paper - CoDIT’19 Best Reviewer - IEEE ICAS 2021 FRANZE' has taught undergraduate and graduate courses in Automatic Control, Digital Control, and Robotics at the University of Calabria for over 25 years. He has chaired institutional committees, including the Degree Course Council for Automation Engineering and the Research Committee at DIMEG. His scientific partnerships include institutions like Concordia University, Northeastern University, and Université Libre de Bruxelles.

Mohammadhossein Malmirمشاهده پروفایل

پژوهشگر

• Reinforcement Learning
• Robotic Manipulation
• Sim2Real Transfer
• +۳ مورد دیگر

Mohammadhossein Malmir is a Researcher at the Chair of Robotics, Artificial Intelligence and Real-time Systems at Technische Universität München (TUM). He joined the chair in November 2019 and currently contributes to the A-IQ Ready project (successor of AI4DI ), focusing on learning algorithms for industrial manipulators and mobile robots in manufacturing and intralogistics tasks. Education B.Sc. in Electrical Engineering (Control Systems) from Amirkabir University of Technology (Tehran Polytechnic) (2014) M.Sc. in Automation and Control Engineering from Politecnico di Milano (2018) His research addresses Sim2Real Transfer , Reinforcement Learning , Robust Control , and Model Predictive Control for autonomous robotic systems. He has published extensively on sim2real policy transfer, domain randomization, and control algorithms for manipulation and navigation tasks. Recent publications highlight his work in dexterous grasping , continual domain adaptation , and deep reinforcement learning for trajectory optimization . His advising roles include supervising 13 master's students and interdisciplinary projects, with co-advisorship on topics like vision-based robotic grasping and socially compliant path planning . He teaches courses on Cognitive Systems and Cloud-Based/Simulation-Based Machine Learning in Robotics , emphasizing reinforcement learning and sim2real methodologies.

Vasos Vassiliouمشاهده پروفایل

دانشیار

• Distributed Network Protocols
• 5G/6G Communication Systems
• Device-to-Device (D2D) Networking
• +۱۲ مورد دیگر

Vasos Vassiliou is an Associate Professor in the Department of Computer Science at the University of Cyprus and Founding Academic Member & Research Group Leader at the Smart Networked Systems (SNS) Multidisciplinary Research Group within the CYENS Research Center. His work focuses on systems and protocols for improving network performance, reliability, and security in next-generation communication systems (5G/6G), with a strong emphasis on distributed AI/ML techniques, device-to-device (D2D) networking, IoT security, programmable metasurfaces, and intelligent network resource management. Department of Computer Science, University of Cyprus CYENS Research Center, Cyprus His research spans multiple subfields including D2D communication (interference management, device discovery), IoT security (blockchain solutions, intrusion detection), network optimization (traffic prediction, power management), and programmable metasurfaces for advanced beam steering. Recent projects like ERMIS (3D Indoor Positioning), ADROIT-6G (DAI-driven architecture), and METACITIES (digital twins/metaverse) demonstrate his leadership in cutting-edge research. His publications reveal a strong focus on distributed intelligence , machine learning applications , and security protocols across wireless systems. He has supervised multiple PhD students to completion and actively contributes to IEEE/ACM as Senior Member. IEEE Senior Member ACM Senior Member Teaching responsibilities include core courses like Computer Networks and specialized postgraduate modules on IoT Networks .

Rubén Martín Garcíaمشاهده پروفایل

مدرس

• Robotics
• Internet of Things (IoT)
• Systems Engineering
• +۵ مورد دیگر

Dr. Rubén Martín García is a Lecturer at the Universidad Politécnica de Salamanca , affiliated with the College of Computer Science and the Department of Systems Engineering and Automation . He is a member of the MARATON research group , focusing on mobile applications, internet of things, data processing, and semantic technologies. He earned his PhD in 2021 from the University of Salamanca with a thesis on anti-pheromone algorithms for urban search-and-rescue robots, supervised by Dr. Gabriel Villarrubia González and Dr. Javier Bajo Pérez. His research spans Robotics , Artificial Intelligence , and Smart Cities , with specific contributions to: Swarm robotics for disaster response Humanoid companions for elderly care Human-robot interaction in healthcare education Entropy-based modeling of shared mobility systems Stochastic navigation in urban environments AI-driven medication management systems Recent publications highlight his interdisciplinary work in medical robotics, swarm intelligence, and technology acceptance studies. His projects emphasize practical applications of IoT, semantic technologies, and open data frameworks.

• Robust Control Systems
• Multi-Agent Robotics
• Machine Learning
• +۳ مورد دیگر

Kunal Garg is an Assistant Professor in the Mechanical and Aerospace Engineering program at Arizona State University's School of Engineering for Matter, Transport and Energy. He holds a PhD and Master of Engineering in Aerospace Engineering from the University of Michigan (2021, 2019). Prior to joining ASU, he was a Postdoctoral Associate at MIT's Laboratory for Information & Decision Systems (LIDS) and Department of Aeronautics and Astronautics. His research focuses on integrating control theory with machine learning for autonomous systems, with emphasis on: Robust control synthesis for multi-agent coordination Finite/fixed-time control under spatiotemporal constraints Deadlock resolution in robotics using foundation models (LLMs/VLMs) Safety-critical control via barrier functions Recent publications demonstrate strong focus on neural control barrier functions, deadlock resolution for multi-robot systems, and failure prediction methods. His work frequently appears in top robotics and control conferences including ICRA, CDC, and TRO. Awards & Honors: 2022 DAAD AInet Fellow (AI and Robotics domain) Pierre T. Kabamba Award for Excellence in Control Systems (2021) Richard and Eleanor Towner Prize for Distinguished Academic Achievement (2021) He advises MS students through programs like ASU's MORE fellowship and teaches MAE 494/598: Design and Analysis of Nonlinear Controls. His research group develops open-source tools like the NeuralFaultDetector framework for model-free fault detection.

• Control Systems
• Robotics
• Power Systems
• +۲ مورد دیگر

Professor Damiano Varagnolo is affiliated with the Department of Engineering Cybernetics at the Norwegian University of Science and Technology (NTNU), where he conducts research spanning control systems, robotics, power systems, and data-driven modeling. His work bridges theoretical advances with practical applications in underwater vehicles, medical rehabilitation, and energy infrastructure. His research focuses on: Development of formation control algorithms for autonomous underwater vehicles (AUVs) and snake robots Transient stability enhancement for grid-forming converters in renewable energy systems Data-driven modeling of physiological signals for wheelchair propulsion and industrial processes Distributed optimization for underwater communication networks Recent publications (2024-2025) demonstrate strong emphasis on: Underactuated vehicle control using hand position concepts Energy expenditure estimation through physiological signal processing Consensus protocols for JANUS-based underwater networks Educational innovation through control-themed outreach initiatives like the Advent Calendar project He actively collaborates with NTNU colleagues across engineering disciplines and contributes to curriculum development through graph-theoretic approaches for educational coherence.

Giovanni Maria Farinellaمشاهده پروفایل

استاد

• First Person (Egocentric) Vision
• Computer Vision
• Pattern Recognition
• +۱ مورد دیگر

Giovanni Maria Farinella is a Full Professor at the Department of Mathematics and Computer Science, University of Catania, Italy. He is the Founder Member of the IPLAB Research Group at University of Catania since 2005, an Associate Member of the Computer Vision and Robotics Research Group at University of Cambridge since 2006, and an Associate Member of the Italian National Research Council since 2018. He serves as Scientific Advisor of the NVIDIA AI Technology Centre and board member of the CINI Laboratory of Artificial Intelligence and Intelligent Systems. Dr. Farinella obtained his degree in Computer Science (summa cum laude) from the University of Catania in 2004 and was awarded a Doctor of Philosophy (Computer Vision) from the same institution in 2008. He has obtained the National Scientific Qualification to Associate Professor in 2013-2014 and to Full Professor in 2018. His primary research interests focus on First Person (Egocentric) Vision, Computer Vision, Pattern Recognition, and Machine Learning. Dr. Farinella has pioneered research in egocentric video analysis, object interaction detection, activity recognition, and scene understanding from a first-person perspective. His work bridges theoretical computer vision with practical applications in industrial settings, healthcare, and cultural heritage sites. His recent publications demonstrate a clear trajectory toward more sophisticated, real-time egocentric vision systems capable of understanding complex human activities, anticipating actions, and detecting procedural mistakes through integration of visual analysis, gaze tracking, and large language models. Dr. Farinella has published extensively in top-tier computer vision venues, with his most recent work focusing on egocentric action anticipation, mistake detection in procedural tasks, and the integration of multimodal large language models with visual understanding. His research shows strong emphasis on practical industrial applications while advancing fundamental computer vision techniques. PAMI Mark Everingham Prize 2017 Intel's 2022 Outstanding Researcher Award Dr. Farinella has served as Associate Editor for IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition - Elsevier, and International Journal of Computer Vision. He has held leadership roles as Area Chair for CVPR 2020/21/22/23, ICCV 2017/19/21/23, ECCV 2020, and as Program Chair of ECCV 2022. He founded and directs the International Computer Vision Summer School (since 2006) and the Medical Imaging Summer School (since 2014). As PI of the EGO4D project, he helped create one of the largest egocentric video datasets with over 3,670 hours of footage from 923 participants across 74 locations worldwide. His IPLAB research group leads multiple significant projects including VALUE, ENIGMA, and FIPEVIS, with strong industry collaborations.

• Embodied AI
• Robotics
• Computer Vision
• +۵ مورد دیگر

Roozbeh Mottaghi is a Senior AI Research Scientist Manager at Meta's Fundamental AI Research (FAIR) group and an Affiliate Associate Professor at the Paul G. Allen School of Computer Science & Engineering at the University of Washington. His work bridges academic research and industrial AI development, focusing on embodied artificial intelligence, robotics, and computer vision. Dr. Mottaghi received his Ph.D. in Computer Science from UCLA under the supervision of Alan Yuille. He completed his Master's degrees at Simon Fraser University and Georgia Institute of Technology, and earned his Bachelor's degree from Sharif University of Technology. Prior to his current positions, he was a Postdoctoral Researcher at Stanford University and Research Manager of the PRIOR team at the Allen Institute for AI. Dr. Mottaghi's research focuses on embodied AI , where agents learn to interact with and understand their physical environments. His work spans robotics , computer vision , and human-robot interaction , with particular emphasis on 3D scene understanding, visual reasoning, and language-vision integration. His research addresses fundamental challenges in how AI systems can perceive, navigate, and manipulate the physical world through embodied experiences. His recent publications demonstrate a strong trend toward increasingly sophisticated embodied AI systems capable of complex multi-agent collaboration, open-vocabulary understanding, and human-like reasoning about physical environments. His work bridges simulation and real-world robotics, with significant contributions to benchmark creation and standardized evaluation frameworks for embodied AI. Dr. Mottaghi's work has been recognized with several prestigious honors including: Outstanding Paper Award at NeurIPS 2022 Multiple oral presentations at top-tier conferences (CVPR, ICCV) Spotlight presentations at major computer vision conferences Dr. Mottaghi has mentored numerous students and researchers, including PhD students and Pre-doctoral Young Investigators. His advising style emphasizes both theoretical rigor and practical implementation, preparing students for successful careers in both academia and industry. His work has been supported by significant research funding from Meta and previously from the Allen Institute for AI. Dr. Mottaghi has been instrumental in developing AI2-THOR, RoboTHOR, and Habitat simulation platforms, which have become standard tools in the embodied AI research community. His leadership in the PRIOR team at AI2 and currently at Meta's FAIR has driven significant advances in how AI systems understand and interact with the physical world.

• Collective behaviour
• Theoretical and Computational Biology
• Decision theory
• +۷ مورد دیگر

Professor James A.R. Marshall is a Professor of Theoretical and Computational Biology at the University of Sheffield's School of Computer Science, where he also serves as Director of the Centre for Machine Intelligence. He leads the Behavioural and Evolutionary Theory Lab (BET Lab), an interdisciplinary research group focused on understanding behavior through mathematical and computational approaches. His academic journey includes previous positions at the University of Bristol before joining Sheffield in 2010. Marshall's research spans collective social insect behavior, evolutionary theory, decision theory, robotics, and theoretical neuroscience. He applies mathematical and computational approaches to understand how and why behaviors evolve, with particular interest in social insect colonies, swarm intelligence, and biomimetic applications for robotics. His work often bridges biology and computer science, developing algorithms inspired by natural systems. He has made significant contributions to understanding confidence-weighted decision-making, quorum sensing in swarms, and magnitude-sensitive reaction times in multi-alternative choices. His recent publications reveal a strong trend toward applying insights from biological systems to robotics and AI, particularly through projects like Brains on Board and Opteran Technologies. His work increasingly focuses on neuromorphic control systems that mimic insect brains for autonomous navigation, demonstrating how constraints in biological systems can lead to robust engineering solutions. The interdisciplinary nature of his research is evident in publications spanning computational neuroscience, robotics, animal behavior, and theoretical biology. EPSRC Peer Review College Member (2010-present) Member of the UKRI Future Leaders Fellowship Panel College (2019-present) Editorial Board, Swarm Intelligence (2017-present) Associate Editor, PLoS Computational Biology (2020-present) Marshall has successfully mentored numerous researchers including HaDi MaBouDi, Andreagiovanni Reina, and Alexander Cope, while securing substantial research funding including EPSRC grants totaling over £4 million. His lab has produced the spinout company Opteran Technologies, which has secured over £12 million in funding to develop natural intelligence technology for autonomous systems. The BET Lab maintains strong connections with Sheffield Robotics and focuses on testing theoretical models in physical robotic systems while developing computational models of biological processes.

• Ophthalmology
• Vitreoretinal Diseases & Surgery
• Optical Coherence Tomography
• +۵ مورد دیگر

Cynthia Ann Toth is the Joseph A.C. Wadsworth Distinguished Professor of Ophthalmology at Duke University, with additional appointments as Professor of Ophthalmology and Professor of Biomedical Engineering. Her extensive career has positioned her as a leading authority in vitreoretinal diseases and surgery, particularly in the development and application of optical coherence tomography (OCT) technologies for both adult and pediatric patients. She has made significant contributions to retinal imaging, with a special focus on retinopathy of prematurity and age-related macular degeneration. Joseph A.C. Wadsworth Distinguished Professor of Ophthalmology Professor of Biomedical Engineering Specialist in Vitreoretinal Diseases & Surgery Director of advanced imaging research programs Dr. Toth received her M.D. from Drexel University in 1983, followed by ophthalmology training at Geisinger Medical Center (1984-1987) and the University of California, Davis, School of Medicine (1989-1991). Her educational background provided the foundation for her pioneering work in retinal imaging technologies. Dr. Toth's research primarily focuses on advancing optical coherence tomography for clinical and surgical applications. Her work spans several critical areas including: development of handheld OCT devices for infant and pediatric imaging; intraoperative OCT for vitreoretinal surgery; OCT angiography for microvascular assessment; and application of OCT in retinopathy of prematurity and age-related macular degeneration. She has been instrumental in translating OCT technology from research settings to clinical practice, particularly for vulnerable patient populations like premature infants who require bedside imaging. Her publication record demonstrates a clear trajectory from foundational OCT technology development to sophisticated clinical applications. Recent work shows increasing integration of artificial intelligence, robotics, and novel optical clearing techniques with OCT systems. The research consistently bridges engineering innovation with immediate clinical needs, particularly in pediatric ophthalmology and retinal surgery. ARVO/Alcon Keynote (2022) Gertrude Pyron Award from American Society of Retina Specialists (2021) Scientific Achievement Award from Women in Ophthalmology (2019) Wacker Prize from Club Jules Gonin (2018) Paul Henkind Award and Lecture from Macula Society (2018) Rockefeller Foundation Academic Writing Residency (2017) As a mentor, Dr. Toth has guided numerous students and junior faculty in ophthalmic research, with particular emphasis on imaging technology development. Her research has been supported by significant grant funding from NIH and other organizations, enabling her team to develop innovative imaging approaches that have transformed clinical practice in retinal diseases. She has been particularly active in collaborative research efforts, often leading multi-center studies that establish standards for retinal imaging and diagnosis. Dr. Toth leads a multidisciplinary research team that includes ophthalmologists, biomedical engineers, computer scientists, and clinical researchers. Her laboratory focuses on developing next-generation imaging technologies that can be deployed at the bedside for infants and during surgery for precise guidance. The team has pioneered several handheld OCT systems specifically designed for pediatric use and has developed novel image processing techniques that extract maximum diagnostic information from OCT scans.

• Reinforcement Learning
• Internet of Things (IoT)
• Cognitive Robotics
• +۴ مورد دیگر

Iñaki Vazquez Gomez is a Lecturer and Researcher at the University of Deusto , affiliated with the College of Engineering and Department of Computing, Electronics and Communication Technologies . He holds a PhD in Computer Science and Artificial Intelligence (University of Deusto and Lancaster University) and served as Director of Deusto Institute of Technology (2020-2023). His research focuses on Reinforcement Learning , Internet of Things , and Cognitive Robotics , with applications in human-robot interaction and ambient intelligence. Member of European Internet of Things Council Founder of technology startups Editorial board member of International Journal of Ambient Computing and Intelligence His 15 most recent publications (2005-2024) span themes of Autonomous Systems , Context-Aware Computing , and Smart Environments , with subtopics including semantic device communication, adaptive positioning algorithms, and collaborative robotics architectures. 2024: Adaptive Robot Behavior via Reinforcement Learning 2021: Gesture Recognition for Resource-Constrained Devices 2015: Context-Aware Service Matching in AAL Scientific honors include: X Premio UD-Banco Santander de Investigación (2015) Sexenio de Investigación (2018-2025) Profesor Doctor de Universidad Privada (2009-2025) He supervised PhD students like Asier Gonzalez Santocildes and Ignacio Fidalgo Astorquia, while leading grants such as AI-Driven Cognitive Robotics (2021-2024) and Quantum Technologies (2021-2022). His work includes developing middleware for smart spaces and founding the Sentient Things project for self-adapting environmental systems.