جست‌وجوی استاد و پژوهشگر

Ron C. Chiangمشاهده پروفایل

دانشیار

• Distributed Systems
• Cloud Computing
• High Performance Computer Architectures
• +۴ مورد دیگر

Ron C. Chiang is an Associate Professor at the University of St. Thomas, specializing in software engineering, distributed systems, and cloud computing. His research focuses on optimizing virtualization, resource management, and high-performance architectures. He holds a Ph.D. in Computer Engineering from George Washington University and has contributed to advancements in cloud security, I/O prefetching, and precision agriculture through machine learning. Education: Ph.D. in Computer Engineering (George Washington University). Research Interests: Distributed systems, cloud computing, virtualization systems, and data-intensive applications. He has developed innovative solutions for container placement strategies, interference-aware scheduling, and energy-efficient memory management. Awards include the Best Student Paper Finalist at SC11, a 'Best of HotPower' award, and grants from IBM and Amazon. He teaches courses on cloud computing, database systems, and infrastructure as code. His work integrates theoretical computer science with practical applications, such as sustainable farming through AI and healthcare platforms in cloud environments. Grants: IBM Academic Initiative (2015–2017), Amazon AWS Educator Credits (2015–2016). He has published extensively in journals like IEEE Transactions and at conferences including SC, ICAC, and ICPA.

Amit Chopraمشاهده پروفایل

مدرس ارشد

• Sociotechnical Systems
• Multiagent Systems
• Software Engineering
• +۶ مورد دیگر

Dr. Amit Chopra is a Senior Lecturer at the School of Computing and Communications , Lancaster University , UK. His work bridges multiagent systems and software engineering , focusing on interaction-oriented software engineering (IOSE) to govern sociotechnical systems. Associate Editor, ACM Transactions on Internet Technology (TOIT) Sponsorship Chair, AAMAS 2013 Host of the Dagstuhl Seminar on Normative Multiagent Systems His research explores software abstractions for norms, accountability, and protocols , with applications in ethical AI, blockchain technology, and security . Funded by European grants (e.g., EPSRC, Marie Curie), his work integrates autonomous actors (organizations, people) in decentralized systems. Recent publications emphasize trends in communication protocols , BDI agent programming , and decentralized applications . Themes include compliance, adaptability, and sociotechnical governance across IoT, microservices, and blockchain. Scientific Awards : Marie Curie Intra-European Fellowship Marie Curie Fellowship, Trentino Cofund Grants : PI, Five-year EPSRC grant (£677k, ongoing since 2017) PI, Marie Curie grants (2012–2014, 2010–2012) Research Groups : Lancaster Intelligent, Robotic and Autonomous Systems Centre (LIRA), Software Engineering (SCC), Security Lancaster (Distributed Systems).

• Composite Materials
• Fluid-Structure Interactions
• Hydrodynamics
• +۵ مورد دیگر

Ivan Stenius is a full-time Associate Professor at the Department of Engineering Mechanics, KTH Royal Institute of Technology. He holds a M.Sc. (2003) and Ph.D. (2009) in Lightweight Structures from KTH, with a licentiate degree (2007). His research focuses on composite materials, fluid-structure interactions, hydrodynamics, marine robotics, and model-based systems engineering. He leads the Swedish Maritime Robotics Centre (SMaRC), Sweden’s largest academic initiative in underwater robotics, and co-founded Zparq AB for marine electric propulsion. Education: M.Sc. in Lightweight Structures (KTH, 2003) Technical Licentiate in Lightweight Structures (KTH, 2007) Ph.D. in Hydroelasticity and Fluid-Structure Interactions (KTH, 2009) Research & Collaboration: Stenius develops advanced software tools with FMV and the Swedish Coast Guard. He leads cross-disciplinary projects involving computer vision, electrochemistry, and networked control. His work on hydrofoiling and electric propulsion has spun off Zparq AB. Recent projects include autonomous seaweed farm inspection, bioinspired underwater robots, and reinforcement learning for AUV maneuvering. Labs & Initiatives: PI of SMaRC, which integrates advanced robotics and maritime systems. Active in courses like Underwater Technology (SD2709) and Vehicle Engineering (SD1002).

Azalia Mirhoseiniمشاهده پروفایل

استادیار

• AI Systems
• Chip Design Automation
• Deep Reinforcement Learning
• +۳ مورد دیگر

Azalia Mirhoseini is an Assistant Professor of Computer Science at Stanford University and founder of the Scaling Intelligence Lab. She also serves as a Senior Staff Scientist at Google DeepMind. Her research focuses on scalable and self-improving AI systems, including advancements in chip design automation, large language models, and reinforcement learning applications. Prior roles include co-founding the ML for Systems team at Google Brain. Education: BSc in Electrical Engineering from Sharif University of Technology; PhD in Electrical and Computer Engineering from Rice University. Awards include MIT Technology Review’s 35 Under 35 and Best ECE Thesis Award. Research highlights include AlphaChip (deep RL for chip layout optimization), Mixture-of-Experts (MoE) architectures, and Constitutional AI frameworks for alignment. Her work bridges AI and systems, addressing real-world challenges in hardware design and scalable AI. Key contributions span over 50 publications in top venues like Nature , NeurIPS , and ICLR . Media coverage includes MIT Tech Review, IEEE Spectrum, and WIRED. Teaching includes CS229s: Systems for Machine Learning. Labs/Teams: Scaling Intelligence Lab (Stanford), collaborations with Google Research/DeepMind. Advising/Grants: Mentors students through Stanford; her work is funded via industry-academic partnerships.

Xiang Chenمشاهده پروفایل

استاد

• Control Systems
• Autonomous Systems
• Robotics
• +۶ مورد دیگر

Dr. Xiang Chen is a Professor in the Department of Electrical and Computer Engineering (ECE) at the University of Windsor. He holds a PhD from Louisiana State University (1998), an MSc (1996), and a BEng from Huazhong University of Science and Technology (1985). His research focuses on advanced control systems, including multi-objective complementary control (MOCC), autonomous systems, and automotive control. He is also involved in model-guided data-driven optimization and sensor networks. Dr. Chen serves as an Associate Editor for the SIAM Journal on Control and Optimization and a Technical Editor for the IEEE/ASME Transactions on Mechatronics . He is a member of IEEE, ASME, and SAE, and holds P.Eng certification in Ontario. His research interests span control theory, robotics, and systems engineering, with recent work addressing cybersecurity in software systems, telecommunication protocols, and materials science applications. His publications in 2025 include advancements in vulnerability assessment via machine learning, beam management in wireless networks, and studies on epigenetics and psoriasis. Dr. Chen’s contributions bridge theoretical control systems with practical applications in automotive, healthcare, and telecommunications. His work emphasizes interdisciplinary solutions to complex engineering challenges.

• Surgical Robotics
• Medical Robotics
• Autonomous Surgical Systems
• +۴ مورد دیگر

Pierre Berthet-Rayne serves as Chief Technical Officer at Caranx Medical and holds a Chair at the 3IA Institute of Artificial Intelligence, University of the Côte d'Azur. His research pioneers AI-driven autonomous surgical robots to transition from teleoperated systems to clinician-supervised autonomous platforms. Education: Master’s in Electronics and Control, Polytech’Montpellier (France), 2009 MRes in Medical Robotics and Image Guided Intervention (with distinction), Imperial College London (UK), 2015 PhD in Robotics, Hamlyn Centre for Robotic Surgery (development of i²Snake endoscopic robot) His core research spans surgical robotics, tendon-driven mechanisms, snake-like robots, and human-robot collaboration, with emphasis on AI for context-aware surgical planning and execution. Current work integrates image processing, sensor data fusion, and control systems to enable autonomous procedure execution under clinician oversight. Professional trajectory includes two years as an embedded software engineer, postdoctoral research at King’s College London’s Robotics and Vision in Medicine Lab, and visiting scholar roles at UNC Chapel Hill’s Computational Robotics Research Group and University of Arizona’s Model Based Design Lab. He actively collaborates with the Robotics and Vision in Medicine Lab (King’s College), Computational Robotics Research Group (UNC), and Model Based Design Lab (Arizona), driving innovation in surgical robotics through Caranx Medical’s technical leadership.

Daniel Wigdorمشاهده پروفایل

استاد

• Human-Computer Interaction
• Computer Science
• Artificial Intelligence
• +۷ مورد دیگر

Professor Daniel Wigdor is a prominent academic and entrepreneur in Human-Computer Interaction (HCI), holding the rank of Professor at the University of Toronto’s Department of Computer Science. He also serves as Associate Chair for Industrial Partnerships and has held roles at Meta’s Reality Labs Research and Facebook Reality Labs. His research focuses on inventing technologies that enhance human capabilities through novel sensing systems, AI, and haptic interfaces. Key projects include VibraForge, AeroHaptix, and Nabokov’s Cards, emphasizing tactile feedback and creative AI tools. Wigdor has published over 130 peer-reviewed papers, holds 60+ patents, and received awards like the Alfred P. Sloan Fellowship and Ontario Early Researcher Award. Education & Affiliations: PhD in Computer Science (implied, though specific details not provided) Alumnus of the University of Toronto’s Department of Computer Science Former positions at Cornell Tech, Microsoft Research, and Harvard Research Interests: Wigdor’s work spans haptics, VR/AR interfaces, AI-assisted creativity, and multimodal interaction systems. His lab develops tools like TactileNet (digital touch systems) and Fidgets (predictive UI components), reflecting a focus on practical, user-centric innovations. Recent Work Trends: His publications emphasize scalable vibrotactile systems (e.g., VibraForge), UAV teleoperation safety (AeroHaptix), and AI-driven creative writing tools (Nabokov’s Cards). These projects highlight a blend of technical depth and societal impact. Awards: Alfred P. Sloan Foundation Research Fellowship (2015) Ontario Early Researcher Award (2014) Multiple Best Paper Awards at CHI Advising & Grants: Wigdor has mentored over 50 students and postdocs, many advancing to academic and industry roles. Notable advisees include Zhicong Lu (CityU Hong Kong) and Haijun Xia (UC San Diego). His grants support projects like the Symphony of Devices and cross-device software tools. Labs & Teams: Leads the University of Toronto’s HCI research group and co-founded Tactual Labs (2013) and Chatham Labs (2019). Current projects include predictive UI toolkits and AI-assisted creative systems.

• Computer Vision
• Machine Learning
• Action Recognition
• +۶ مورد دیگر

Prof. Juergen Gall is a Professor at the University of Bonn, affiliated with the TRA Mathematics, Modelling and Simulation of Complex Systems and the Department of Information Systems and Artificial Intelligence. He leads the Computer Vision Group at the Lamarr Institute for Machine Learning and Artificial Intelligence. His research focuses on action recognition, video understanding, anticipation, human pose estimation, and applications in plant science, earth science, and neuroscience. He has contributed to numerous projects and conferences, including organizing workshops on machine learning for Earth systems and holistic video understanding. His work spans over 200 publications in top venues like CVPR, ICCV, and NeurIPS. He oversees software tools like MANTA and STING-BEE, and has developed datasets such as Humans in Kitchens and PoseTrack21. Research interests emphasize advancing computer vision for real-world challenges, with a focus on multi-modal learning and deep learning applications. Recent articles explore parameter-efficient models, diffusion-based anticipation, and multi-view matching for plant analysis. His contributions bridge academia and industry, addressing agricultural and environmental monitoring needs.

• Urological Epidemiology
• Biostatistics
• Public Health
• +۳ مورد دیگر

Sample is a Professor in the Departments of Epidemiology and Urology at the University of Michigan. Their research interests focus on urological epidemiology, biostatistics, public health, and innovative medical technologies. They lead a lab at the University Hospital in Ann Arbor, Michigan, and have mentored students like Paul Grant, MD. Their work integrates advanced technologies such as virtual reality (VR), sensor systems, and artificial intelligence (AI) to address challenges in healthcare delivery, patient adherence, and medical training. Research highlights include developing VR-based simulations for team training in acute care, passive magnetic sensing systems for object recognition, and privacy-preserving activity monitoring. Their lab’s interdisciplinary approach spans medical informatics, wearable devices, and robotics. Notably, Sample has pioneered sensor systems for eye drop instillation success in glaucoma patients and magnetic-based navigation for mobile robots. Their contributions bridge clinical practice and engineering, emphasizing real-world applications in healthcare.

• Internet of Things (IoT)
• Cyberphysical systems
• Sensors and digital hardware
• +۳ مورد دیگر

Martin De Jode is a Lecturer in Connected Environments (Hardware) at the Centre for Advanced Spatial Analysis (CASA), University College London. His academic journey includes a PhD in nonlinear optics from the University of Essex (1990), an MSc in Object Oriented Software Systems from City University (2000), and a BSc (Honours) in Physics from the University of York (1983). He also holds a PGCert in Higher Education from the University of Greenwich (2018). His research focuses on IoT, cyberphysical systems, sensors, and digital hardware, with notable projects like the Tales of Things platform (2010–2013) enabling object tagging via QR/RFID, and the EPSRC-funded 'Internet of Second-Hand Things' project. He contributed to the CEDE project exploring digital empathy and led development of mobile apps for cultural heritage and environmental monitoring. Recent work emphasizes IoT applications in urban environments, environmental sensing, and human-centered technologies. His publications span 1989–2024, covering photodynamic therapy innovations, mobile development methodologies, and IoT-driven solutions in retail, art, and ecology. He has held academic roles including Senior Lecturer at the University of Greenwich (2016–2018) and Research Associate at CASA (2009–2016). Current teaching includes the MSc Connected Environments program at UCL East, integrating hardware development with spatial analysis.

Christopher Alexanderمشاهده پروفایل

دانشیار

• Artificial Intelligence
• AI-enhanced Learning
• Technology Enhanced Learning (TEL)
• +۳ مورد دیگر

Dr. Christopher Alexander is an Associate Professor in Technology Enhanced Learning, Applied Linguistics, and TESOL at the University of Nicosia. He currently serves as Head of the AI Learning Centre (AI-LC), leading initiatives to integrate AI into educational practices. Previously, he led the Technology Enhanced Learning (TEL) Centre and the Distance Learning IT Unit, driving innovations like the NEPTON Test and e-learning strategies since 2004. His research focuses on AI-driven learning, learning design, and data analytics, with over 80 single-authored papers and 150+ AI/TEL-related publications. He co-edits the Journal of Teaching English with Technology (Scopus-indexed). As AI-LC director, he develops the Accelerate/PowerFlow platform to enhance teaching and learning via AI, collaborating across academic and IT teams. His work emphasizes AI-infused learning spaces, data-informed education, and pedagogical innovation. He has led five applications and numerous IT projects, ensuring the university remains a leader in AI-driven education. Research contributions span AI applications in education, learning analytics, and language technology. His recent studies address AI-generated writing detection in higher education and safety-critical AI systems in aviation. Collaborations include projects on UAV compliance and neural network-based image restoration. Dr. Alexander holds editorial leadership roles and has shaped UNIC's distance learning and blended learning strategies. His interdisciplinary approach bridges applied linguistics, computer science, and educational technology, contributing to UN Sustainable Development Goals through innovation in learning systems.

• Autonomous Vehicles
• Software Engineering
• Cybersecurity
• +۳ مورد دیگر

Pavle Dakić is a researcher at Singidunum University, affiliated with the Faculty of Informatics and Computing and the Department of Electrical Engineering and Computing. He holds a doctoral degree in Applied Informatics from the Slovak University of Technology (2020-2024) and another doctoral degree in Electrical Engineering and Computing from Singidunum University (2015-2024). His research focuses on autonomous vehicles, cybersecurity, IoT/IIoT systems, and software compliance in automotive and healthcare sectors. He is actively involved in publishing peer-reviewed articles and conference papers, with recent work exploring AI-driven solutions for parking systems, cybersecurity in IoT environments, and the economic impacts of global market changes on automotive manufacturing. Pavle has collaborated on projects addressing standards compliance, fake news mitigation in online communities, and energy efficiency in autonomous vehicles. Education: Doctoral studies in Applied Informatics: Slovak University of Technology (2020-2024) Doctoral studies in Electrical Engineering and Computing: Singidunum University (2015-2024) Master’s in Contemporary Information Technologies: Singidunum University (2014-2015) His research interests span advanced topics such as intrusion detection systems for autonomous vehicles, software quality control using black-box testing, and the intersection of artificial intelligence with call-center optimization in automotive retail. Pavle has contributed to interdisciplinary projects, including analyses of agro-food production potential in Serbia and wage stability in the Republic of Srpska. His work emphasizes practical applications of technology in compliance, sustainability, and industry standards.

Deepak Kumarمشاهده پروفایل

استاد

• Artificial Intelligence
• BDI Architectures
• Robotics
• +۵ مورد دیگر

Deepak Kumar is a Professor of Computer Science at Bryn Mawr College , with adjunct appointments in the Department of Philosophy and as faculty in the Neural & Behavioral Sciences . He serves as Associate Director for Education & Diversity at the Center for Science of Information and co-founded the Foundations of Data Science Institute . Research Interests: Artificial Intelligence, BDI Architectures, Robotics, Cognitive Science, Computational Linguistics, Science of Information, Data Analysis & Visualization, AI Education. Projects: Institute for Personal Robots in Education , Pyro (Python Robotics) , Serendip educational platforms. Publications: Co-authored Processing: Creative Coding & Generative Art in Processing 2 and Learning Computing with Robots: A CS1 Text . Affiliations: Member of AAAI , ACM , and committees for ACM SIGCSE and ACM SIGART . Email: dkumar@brynmawr.edu | dkumar@cs.brynmawr.edu

• Artificial Intelligence
• Symbolic Artificial Intelligence
• User Experience
• +۱۲ مورد دیگر

Isabel Machado Alexandre is an Assistant Professor in the Department of Information Science and Technology at Iscte – Instituto Universitário de Lisboa, where she also serves as Coordinator of the Information Technology Group and as an Integrated Researcher at the Institute of Telecommunications - IUL. Her academic journey includes a PhD in Computing from the University of Leeds and a Bachelor’s degree in Computer and Informatics Engineering from the Higher Technical Institute - UTL. Her research spans artificial intelligence, user experience, information visualization, and digital inclusion, with a strong focus on ethical AI, dementia care, and educational technologies. She teaches courses such as Symbolic Artificial Intelligence for Data Science, User Experience and Information Visualization, and Knowledge and Reasoning in Artificial Intelligence. Her recent publications and student projects reflect a growing trend in AI-driven educational tools, serious games for social and health challenges, and inclusive digital platforms. These works emphasize human-centered design, ethical considerations, and practical applications in healthcare and education. She has supervised numerous Master's and PhD students, many of whose research focuses on AI applications in cognitive support, gamification, and digital literacy. Her leadership in EU-funded projects like PIONEER, KidLe, and EDEM underscores her commitment to interdisciplinary and socially impactful research. Scientific Awards: No scientific awards explicitly mentioned. She is actively involved in guiding doctoral and master’s research, securing research funding through European projects such as COST Actions and Horizon Europe initiatives. Her work integrates academic rigor with real-world applications in digital inclusion, dementia care, and sustainable urban development. She leads and participates in research labs and teams including the Information Technology Group at ISTA and the Institute of Telecommunications - IUL, fostering collaboration across disciplines and institutions.

Eric Jacksonمشاهده پروفایل

عضو هیئت علمی

• Transportation Data Systems
• Web-Based Data Collection
• Safety Data Integration and Analysis
• +۳ مورد دیگر

Eric Jackson, Ph.D., serves as the Executive Director of the Connecticut Transportation Institute (CTI) and Director of the Connecticut Transportation Safety Research Center (CTSRC) at the University of Connecticut. He holds an Associate Research Professor position. Dr. Jackson earned his B.S. in Civil Engineering from the University of Kentucky (2002), followed by a Master's (2004) and Ph.D. (2008) from UConn. His research focuses on transportation data systems, web-based data analysis, safety data integration, and remote sensing. He has led initiatives like the modernization of Connecticut’s crash data repository (CTCDR) and the Connecticut Roadway Safety Management System (CRSMS). His work emphasizes accessible crash data tools and systemic safety improvements. Dr. Jackson’s recent publications (2021–2025) address topics such as autonomous vehicle-pedestrian interaction, telematics data for crash analysis, and ADAS driver reactions. His research bridges technological advancements with practical road safety solutions. He has collaborated on state-wide infrastructure projects, including asphalt material studies and pavement marking evaluations. Despite no listed awards, his leadership in CT transportation initiatives underscores his impact in the field. Dr. Jackson oversees the CTSRC Safety Analysis Team, driving software development for safety tools like the Highway Safety Manual integration. His work ensures timely, accurate data access for transportation planners and policymakers. He maintains a laboratory focused on data-driven safety analytics and has contributed to over 100 publications, reflecting his commitment to advancing transportation safety through innovation.