جست‌وجوی استاد و پژوهشگر

Yoon Chaeمشاهده پروفایل

استادیار

• Wireless Networking
• Internet of Things (IoT)
• Millimeter Wave (mmWave) Communication
• +۶ مورد دیگر

Yoon Chae is an Assistant Professor in the Department of Computer Science and Engineering at the University of Texas at Arlington (UTA), joining the faculty in January 2025. His work bridges wireless networking and low-power IoT systems, with a focus on millimeter-wave technologies and backscatter communication. Education: PhD in Computer Science, George Mason University, 2024 MS in Computer Science, George Mason University, 2022 MS in Electrical and Computer Engineering, University of Minnesota - Twin Cities, 2012 BS in Electrical Engineering, Yonsei University, 2012 His research centers on enabling reliable and high-speed mmWave backscatter by leveraging the unique properties of millimeter waves, with applications in vehicular networks, IoT, and spectrum efficiency. He has pioneered techniques using commodity WiFi and FMCW radar for backscatter communication, significantly advancing the field of low-power wireless systems. The recent publications highlight a strong trend in utilizing commodity hardware (like WiFi and radar) for novel wireless sensing and communication. His work spans mmWave backscatter, vehicular networking using street view imagery, and interference management between ZigBee and WiFi. The research demonstrates innovation in spectrum reuse, low-power design, and integration of real-world data for network optimization. Scientific Awards: Best Paper Award, ACM MobiSys 2022 SIGMOBILE Research Highlight, 2023 Yoon Chae actively contributes to the academic community as a reviewer for top journals including IEEE Transactions on Mobile Computing, IEEE/ACM Transactions on Networking, and ACM Transactions on IoT, as well as conferences like INFOCOM, MobiCom, and SenSys. He serves on program committees and has held leadership roles such as Registration Co-chair for ICNP'25 and Artifact Evaluation Committee for MobiSys'25. He is currently building a research lab and seeking motivated Ph.D. students and research interns to join his team. He has been involved in collaborative projects with Prof. Parth Pathak (George Mason) and Prof. Song Min Kim (KAIST), and his work has been presented at major venues including NSDI, MobiCom, MobiSys, and SenSys. His lab focuses on experimental systems design, wireless sensing, and next-generation IoT networking.

Roderich Grossمشاهده پروفایل

مدرس ارشد

• Swarm Robotics
• Modular Robotics
• Computational Intelligence
• +۵ مورد دیگر

Roderich Gross is a Senior Lecturer in the Department of Automatic Control and Systems Engineering at the University of Sheffield. He is also a Visiting Scientist at CSAIL, MIT, and leads the Enabling Technologies theme at Sheffield Robotics. His academic journey includes a Ph.D. in engineering science from Université libre de Bruxelles (2007), followed by postdoctoral fellowships as a JSPS Fellow (Tokyo Institute of Technology), Research Associate (University of Bristol), and Marie Curie Fellow (EPFL & Unilever). Research Interests : Swarm robotics, self-reconfigurable robots, multi-robot coordination, robotics software/tools (human-robot interaction interfaces, formal design tools), machine learning for behavior inference (Turing Learning, GANs), autonomous systems, natural computing (swarm intelligence, evolutionary algorithms). Scientific Contributions : Inventor of Turing Learning, a machine learning method for behavior inference. Key work includes swarm coordination, self-assembly, fault-tolerant quadcopters, energy-efficient drone delivery, and infrared-based swarm communication. Scientific Recognition : Held prestigious fellowships including JSPS and Marie Curie, and served as Associate Editor for leading robotics journals (IEEE Robotics and Automation Letters, Swarm Intelligence) and conference roles (General Chair DARS 2016, Program Co-Chair GECCO 2018). Grants : Principal Investigator on Horizon Europe OpenSwarm (£463,699), EPSRC Core Capital (£104,196), DSTL Multi Robot Systems (£98,781), and industry-funded modular robotics projects. Labs : Affiliated with the Natural Robotics Lab at the University of Sheffield.

Tim Baarslagمشاهده پروفایل

استاد

• Automated Negotiation
• Multi-Agent Systems
• Cooperative Artificial Intelligence
• +۵ مورد دیگر

Tim Baarslag is a Senior Researcher and leader of the Intelligent and Autonomous Systems group at CWI (Centrum Wiskunde & Informatica), a Part-Time Professor of Mathematics of Cooperative AI at Eindhoven University of Technology (TU/e), and an Associate Professor at Utrecht University. Additionally, he holds visiting roles as a Scholar at MIT, Associate Professor at Nagoya University of Technology, and Fellow at the University of Southampton. His research focuses on enabling autonomous systems to collaborate through joint decision-making, with applications in smart energy trading, the Internet of Things, and autonomous vehicles. Education: MSc in Mathematics (cum laude), Utrecht University BSc in Computer Science (cum laude), Utrecht University PhD in Automated Negotiation, Delft University of Technology (2014, cum laude) Tim Baarslag investigates foundational theories for cooperative artificial intelligence, particularly in automated negotiation. His work includes developing algorithms for multi-deal coordination, optimizing bidding strategies with reservation values, and creating frameworks like Genius and NegoLog to evaluate automated negotiators. He explores how AI can balance efficiency and fairness in complex, real-world scenarios such as procurement and energy trading. Recent research trends highlight his development of NegoLog, a Python-based negotiation framework with advanced analytics, and his work on multi-deal negotiation protocols. He also investigates preference uncertainty in user-agent interactions and designs optimal concession strategies for risk-seeking agents with high reservation values. Scientific Awards: Cor Baayen Young Researcher Award Academic Pioneer by Elsevier Young Talent by The Financial Daily Science Talent by New Scientist Tim Baarslag leads the Intelligent and Autonomous Systems group at CWI and organizes the International Automated Negotiating Agent Competition. He is involved in the ACM Future of Computing Academy, The Young Academy, and the Netherlands Academy of Engineering. His work is supported by the NWO Vidi grant COMBINE, focusing on coordinating multi-deal bilateral negotiations. Labs & Teams: Intelligent and Autonomous Systems group, CWI EAISI and Combinatorial Optimization groups, TU/e ACM Future of Computing Academy The Young Academy Netherlands Academy of Engineering

Emil Lupuمشاهده پروفایل

استاد

• Computer System Security
• Artificial Intelligence and Image Processing
• Computer Communications Networks
• +۵ مورد دیگر

Professor Emil Lupu is a Professor of Computer Systems at the Department of Computing , Imperial College London. He leads the Resilient Information Systems Security Group and serves as Co-Director of the National Research Institute in Trustworthy Inter-Connected Cyber-Physical Systems (RITICS) . As a Security Science Fellow at Imperial’s Institute for Security Science and Technology, his work bridges academic research with real-world security challenges. Education: PhD in Computing, Imperial College London (1994–1998) His research focuses on security and resilience of cyber-physical systems (CPS) , with emphasis on defending against data spoofing attacks , adversarial machine learning , and IoT vulnerabilities . He pioneered the Ponder policy systems for access control and the Self-Managed Cell framework for autonomic computing, and developed Bayesian Attack Graphs for scalable risk assessment in CPS. Recent publications highlight trends in adversarial robustness (2025–2022), including LIDAR spoofing defense for autonomous vehicles, LLM security , and attack graph analysis for IoT. His work explores the intersection of safety and security , applying model-checking to identify adversarial threats in train control, microgrids, and aviation systems. Scientific Awards: Security Science Fellowship, Imperial College London (2011–present) As co-founder of the PETRAS National Centre of Excellence in IoT Cybersecurity (2016–2021), he advanced security methodologies for interconnected systems. His collaborations with institutions like the Cyber Security Body of Knowledge (CyBoK) demonstrate his leadership in shaping cybersecurity research standards. Current projects include the RITICS Institute , focusing on trustworthy cyber-physical systems, and exploring generative AI for security poisoning with practical defenses against adversarial ML.

Ziming Zhangمشاهده پروفایل

استادیار

• Computer Vision
• Machine Learning
• Deep Learning
• +۹ مورد دیگر

Ziming Zhang is an Assistant Professor in the Department of Electrical and Computer Engineering at Worcester Polytechnic Institute (WPI) , with additional affiliations in Data Science and Robotics Engineering. He previously held research roles at Mitsubishi Electric Research Laboratories (MERL) and Boston University. PhD in Computing (2013) from Oxford Brookes University , UK MS in Computing Science (2010) from Simon Fraser University , CA BS in Computer Science and Technology (2005) from Northeastern University , China Research interests span computer vision , machine learning , and their applications in point cloud processing , medical imaging , autonomous driving , and IoT . He leads the Vision, Intelligence, and System Laboratory (VISLab) at WPI. Recent publications focus on 3D reconstruction , hyperbolic learning , and robust classifiers . Awards include the R&D100 Award 2018 and NSF funding for data-efficient deep learning. PhD Students: Yecheng Lyu (co-supervised), Guojun Wu (co-supervised), Hangrui Zhang, Xuechu Yu Master's Students: Yun Yue, Yuping Shao Visiting Scholars: Fangzhou Lin His lab partners with industry and academic institutions, focusing on autonomous systems , robotics , and scientific imaging projects.

• Road Safety
• Connected and Automated Vehicles
• Driver Behaviour
• +۵ مورد دیگر

Evita Papazikou serves as a Lecturer in Transport Engineering at the School of Engineering, University of the West of England (UWE Bristol), where she contributes to the Centre for Transport and Society and collaborates with the Bristol Robotics Laboratory's Connected & Autonomous Vehicles Centre. Her academic qualifications include: Civil Engineering (BEng and MEng) from Aristotle University of Thessaloniki MSc in Planning, Organisation, and Management of Transport Systems, Aristotle University of Thessaloniki PhD in Automated Systems and Driver Behaviour (Road Safety) from Loughborough University, sponsored by the Insurance Institute for Highway Safety with access to SHRP2 NDS data Dr. Papazikou's research focuses on road safety, connected and automated vehicles, driver behaviour analysis, and smart infrastructure. She investigates accident causation through statistical modeling, develops driver monitoring systems, and explores human factors in transportation. Her work integrates traffic simulation with mobility data fusion from vehicles, sensors, and infrastructure to enhance safety in future mobility systems, particularly in cooperative, connected, and automated environments. Her recent publications (2023-2025) reveal a concentrated research trajectory examining safety impacts of dedicated lanes for autonomous vehicles, parking policy implications in automated eras, and driver fatigue management. She consistently employs naturalistic driving data and traffic microsimulation to analyze driver-vehicle-environment interactions, with increasing emphasis on real-world intervention effectiveness and environmental sustainability in mobility systems. Scientific Awards: No specific awards were mentioned in the provided information. Dr. Papazikou has secured significant research funding through competitive programs including Horizon 2020, Innovate UK, and the Department for Transport. Her project portfolio demonstrates substantial industry collaboration, particularly with Ford, and includes: LEVITATE: Assessing societal impacts of Connected and Automated Vehicles SafetyCube: Developing an innovative road safety decision support tool i-DREAMS: Creating a smart driver and road environment assessment system DDRST: Building a data-driven road safety tool for hotspot identification TRIP: Developing a driver culpability assignment tool for road injury prevention She actively contributes to interdisciplinary research through her affiliations with the Centre for Transport and Society and the Bristol Robotics Laboratory's Connected & Autonomous Vehicles Centre, where she bridges engineering, human factors, and policy development for next-generation transportation systems.

• Maritime Risk Analysis
• Autonomous Ship Systems
• Safety Engineering
• +۳ مورد دیگر

Børge Rokseth is an Associate Professor at the Department of Engineering Cybernetics , Norwegian University of Science and Technology (NTNU). His work focuses on integrating advanced methodologies for safety and risk control in autonomous maritime systems. He has held academic positions since at least 2014, with a consistent record of research collaboration and publication. Research Areas: Maritime risk analysis, autonomous ship systems, safety engineering, dynamic positioning systems, systems-theoretic process analysis (STPA) Key Publications: 15 most recent articles cover topics like trajectory prediction for autonomous vessels, hybrid power systems safety, machine learning in risk assessment, and dynamic positioning system reliability His publications (2014-2025) emphasize safety-critical systems in marine environments. Common themes include: Application of STPA for hazard analysis in autonomous shipping Development of risk-informed control systems Integration of machine learning with engineering risk assessment Comparative studies of different ship autonomy levels As a supervisor, Rokseth has guided master's students including Ane Joramo Stokke and Ludvig Vik Løite. His work has been presented at international conferences such as the European STAMP Workshop, International Conference on Conceptual Modeling, and the International Seminar on Safety and Security of Autonomous Vessels.

Atrisha Sarkarمشاهده پروفایل

استادیار

• Human-centric multiagent systems
• Human-AI interaction
• Human-robot interaction
• +۴ مورد دیگر

Atrisha Sarkar is an Assistant Professor in the Department of Electrical and Computer Engineering at Western University , Canada, and heads the Humans and Autonomous Agents Lab . She is also a faculty member of the Rotman Institute of Philosophy and a Faculty Affiliate at the Schwartz Reisman Institute for Technology and Society . Her research integrates empirical and behavioral game theory with software engineering to design human-centric AI systems that prioritize safety and societal well-being. Education: Atrisha holds a PhD and has previously served as a postdoctoral fellow at the Schwartz Reisman Institute for Technology and Society at the University of Toronto under the supervision of Prof. Gillian Hadfield. Research Focus: Her work centers on human-centric multiagent systems , combining methods from: Behavioral and empirical game theory Software engineering Human-AI and human-robot interaction AI safety and reliability She applies these to domains such as autonomous driving, cooperative AI, and social media dynamics, aiming to ensure AI systems align with human values and societal norms. Publications and Impact: Atrisha has published extensively in top-tier venues including AAAI , AAMAS , ICRA , NeurIPS , and EC . Her work spans from theoretical models of strategic behavior to practical frameworks for validating autonomous systems, with a strong emphasis on real-world applicability. Labs and Teams: She leads the Humans and Autonomous Agents Lab at Western University, where her team focuses on designing AI agents that can cooperate effectively with humans in complex, dynamic environments.

Nakul Gopalanمشاهده پروفایل

استادیار

• Language Grounding
• Robot Learning
• Human-Robot Interaction
• +۳ مورد دیگر

Nakul Gopalan serves as an Assistant Professor at Arizona State University's School of Computing and Augmented Intelligence (SCAI) in Tempe, where he founded and leads the Logos Robotics Lab since joining in August 2022. His academic foundation was established through a PhD in Computer Science from Brown University completed in 2019. Education: PhD in Computer Science, Brown University (2019) Research Focus: Dr. Gopalan pioneers work at the critical intersection of language grounding and robot learning, developing algorithms that enable robots to interpret natural language instructions and learn from human demonstrations. His research directly addresses real-world usability challenges by focusing on hierarchical reinforcement learning, task planning, and human-robot collaboration frameworks that empower non-expert users to train robots for home and office environments. Key innovations include plannable representations for natural language instruction following and transfer learning techniques for robotic task execution. Publication Evolution: Recent publications (2023-2025) demonstrate accelerating specialization in language-conditioned robot learning, with 80% of his latest work exploring compositional instruction following, novice-user teaching interfaces, and explainable AI for robotics. His research trajectory shows a deliberate shift from foundational language grounding (2017-2020) toward practical human-robot collaboration systems, evidenced by increased focus on hardware-software co-design, cross-embodiment transfer, and clinical applications of explainable AI in neurology support systems. Scientific Recognition: Best Paper Award at RoboNLP workshop (Association for Computational Linguistics) 2017 RSS 2023 Best Student Paper Finalist Mentorship & Service: As lab director, Dr. Gopalan actively mentors graduate researchers while teaching core courses including Data Structures and Algorithms (CSE 310) and specialized seminars on robot learning. His significant service contributions include organizing the RSS 2021 "Robotics for People" workshop, serving as Action Editor for ICRA 2023/2024, and extensive reviewing for top-tier robotics conferences (RSS, ICRA, CORL) and AI venues (NeurIPS, AAAI). Research Infrastructure: The Logos Robotics Lab operates as his primary research vehicle, focusing on natural language interfaces for robot training, hierarchical task decomposition, and real-world deployment of language-grounded learning systems. Current projects integrate large language models with robotic control frameworks to enable zero-shot task generalization across different robot embodiments.

Keith LeGrandمشاهده پروفایل

استادیار

• Multi-sensor Multi-object Tracking
• Spacecraft Navigation
• Space Domain Awareness
• +۵ مورد دیگر

Keith LeGrand is an Assistant Professor in the School of Aeronautics and Astronautics at Purdue University, part of the Cislunar Space Initiative. He holds a Ph.D. in Aerospace Engineering from Cornell University (2022), an M.S. (2015), and a B.S. (2014) in Aerospace Engineering from Missouri University of Science and Technology. His research focuses on multi-object tracking, spacecraft navigation, space domain awareness, and intelligent sensor control. Key projects include developing probabilistic filters for cislunar space object tracking and information-driven autonomy systems. LeGrand leads the Sensing, Controls, and Probabilistic Estimation (SCOPE) Group, which advances space surveillance and autonomous systems. Notable awards include the 2025 AFOSR and ISIF Young Investigator Awards, 2023 AMOS Best Paper Award, and the E.F. Bruhn Teaching Award for excellence in undergraduate instruction. LeGrand advises a diverse group of graduate and undergraduate students in astrodynamics and space applications. His work is supported by grants from AFOSR, ISIF, and partnerships with institutions like Sandia National Laboratories and Draper Labs. The SCOPE lab collaborates on projects such as lunar landing navigation, satellite proximity operations, and multi-sensor fusion for space surveillance.

• Intelligent Transportation Systems
• Automated Vehicles
• Control Systems
• +۶ مورد دیگر

Lingxi Li is a Professor at the Elmore Family School of Electrical and Computer Engineering at Purdue University's Indianapolis campus. His research focuses on modeling complex systems, connected and automated vehicles, intelligent transportation systems, and parallel intelligence. He holds a Ph.D. from the University of Illinois at Urbana-Champaign (2008), and master's and bachelor's degrees from the Chinese Academy of Sciences (2003) and Tsinghua University (2000). Research Interests: Dr. Li's work bridges control systems, transportation engineering, and AI, with emphasis on human-machine interaction, autonomous vehicle systems, and scenario-based traffic modeling. His projects include developing frameworks for Industry 5.0 collaboration, enhancing traffic flow prediction through parallel learning, and advancing safety in micro-mobility systems like e-scooters. Recent Publications: Over 15+ articles (2023-2025) explore topics such as game-theoretic vehicle interaction modeling, vision-language systems for autonomous driving, and acoustic SLAM technologies. These studies reflect a focus on real-world validation and system integration in smart transportation. Labs & Initiatives: Leads research in autonomous mining systems and scenario engineering for intelligent vehicles, leveraging parallel intelligence concepts. Collaborates on projects like ParallelWorkforce (Industry 5.0 frameworks) and SceNDD++ (naturalistic driving datasets).

Andrew Zhangمشاهده پروفایل

استاد

• Wireless Communications
• Sensing Technologies
• Signal Processing
• +۳ مورد دیگر

Prof. Andrew Zhang is a Professor at the School of Electrical and Data Engineering, University of Technology Sydney (UTS). He leads the UTS Radio Sensing and Pattern Analysis (RaSPA) Lab and serves as Technical Director of the UTS-TPG Network Sensing Lab. His research focuses on integrated sensing and communications (ISAC), wireless signal processing, and autonomous vehicular networks. He holds a PhD from the Australian National University and has over 15 years of industry experience, including roles at CSIRO and ZTE Corp. Education: B.S. (Xi’an Jiaotong University), M.Sc. (Nanjing University of Posts and Telecommunications), Ph.D. (Australian National University). Research Interests: ISAC, radio sensing, machine learning for communications, and 6G waveform design. Key projects include developing perceptive mobile networks and flood/storm sensing via ISAC. Publications: Over 290 papers, 5 patents, and notable works on ISAC frameworks, joint communication-sensing systems, and mmWave technologies. Recent trends emphasize ISAC, 6G waveforms, and IoT integration with federated learning. Awards: CSIRO Chairman’s Medal, Australian Engineering Innovation Award, and multiple best paper awards. Active in IEEE leadership roles, including Editor-in-Chief of ISAC-Focus. Grants: ~$8M in research funding. Advises on ISAC-ETI initiatives and collaborates with industry partners like TPG Telecom. Labs: RaSPA Lab (radio sensing analytics) and UTS-TPG Lab (ISAC industrial solutions).

Cathy Wuمشاهده پروفایل

دانشیار

• Reinforcement Learning
• Machine Learning
• Large-scale Optimization
• +۶ مورد دیگر

Cathy Wu is the Class of 1954 Career Development Associate Professor in Civil and Environmental Engineering at MIT, affiliated with the Institute for Data, Systems, and Society (IDSS). Her research bridges machine learning, optimization, and urban systems, with a focus on mixed autonomy systems in mobility. She holds degrees from MIT (B.S., M.Eng in EECS) and a Ph.D. from UC Berkeley (EECS). Education: B.S. and M.Eng in Electrical Engineering and Computer Science, MIT (2012-2013) Ph.D. in Electrical Engineering and Computer Science, UC Berkeley (2018) Research Interests: Reinforcement Learning and Machine Learning Large-scale Optimization and Control Theory Mobility Systems and Urban Infrastructure Implications of AI and Automation Her work emphasizes interdisciplinary collaboration, involving transportation, computer science, and public policy. She founded the Interdisciplinary Research Initiative within the ACM Future of Computing Academy to advance cross-disciplinary computing research. Key Projects: Includes Flow (open-source RL framework for traffic control), eco-driving incentive mechanisms, and mixed autonomy traffic optimization. Her articles address congestion mitigation, autonomous vehicle integration, and scalable supervision strategies. Awards: Recipient of fellowships, best paper awards, and teaching honors (specific names unlisted). Engagement: Collaborations with institutions like Microsoft Research, OpenAI, and Caltrans. Active in policy-oriented initiatives and education through IDSS programs.

Xinya Duمشاهده پروفایل

استادیار

• Natural Language Processing (NLP)
• Large Language Models (LLMs)
• Multimodal Models (VLMs)
• +۷ مورد دیگر

Xinya Du is an Assistant Professor in the Department of Computer Science at the University of Texas at Dallas (UT Dallas), affiliated with the Erik Jonsson School of Engineering and Computer Science. She holds a Ph.D. in Computer Science from Cornell University and completed a postdoctoral fellowship at the University of Illinois at Urbana-Champaign. Her research focuses on advancing trustworthy and impactful AI systems, particularly in Natural Language Processing (NLP), Large Language Models (LLMs), and Vision-Language Models (VLMs). Key research areas include Document understanding and knowledge acquisition Trustworthy reasoning and hallucination detection in LLMs Applications of NLP in scientific research and multimodal systems Alignment of AI systems with human values Dr. Du has received notable awards such as the NSF CAREER Award (2024), Amazon Research Award (2023), and recognition as a Spotlight Rising Star in Data Science. She has authored over 30 papers in top venues like ACL, EMNLP, NeurIPS, and CVPR, contributing to foundational work in multimodal reasoning, LLM evaluation, and automated scientific hypothesis generation. She teaches advanced courses including CS 6301: Special Topics in Computer Science - Deep Learning for NLP and actively mentors students in research projects. Her work has been highlighted in major media and led to impactful open-source contributions, including repositories for event extraction and LLM benchmarking.

Julie A. Adamsمشاهده پروفایل

استاد

• Human-Machine Teaming
• Robotics
• Unmanned Systems
• +۵ مورد دیگر

Julie A. Adams is a Professor of Computer Science at Oregon State University's School of Electrical Engineering and Computer Science, with a courtesy appointment in Mechanical and Industrial Engineering. She serves as the CoRIS Associate Director for Research in the Collaborative Robotics and Intelligent Systems Institute. Her research focuses on human-machine teaming, unmanned systems, and swarm robotics, with over 25 years of experience in the field. Education: Ph.D., Computer and Information Systems, University of Pennsylvania (1995) M.S.E., Computer and Information Systems, University of Pennsylvania (1993) B.S., Computer Science & B.B.A., Accounting, Siena College (1989-1990) Research Interests: Human interaction with unmanned systems, swarm robotics, drone technology, and human-AI collaboration. Her work has been highlighted in National Geographic, Scientific American Podcast, and BBC Online. She leads the Human-Machine Teaming Laboratory and is the principal investigator for the FAA Center of Excellence (ASSURE). Awards: 2007 NSF CAREER Award, DARPA Computer Science Study Panel member, contributor to National Academies reports on UUVs and UAV countermeasures. Grants & Labs: Primary investigator for ASSURE (FAA-funded). Her lab explores adaptive systems for human-robot interaction, including swarm supervision and unmanned aerial system safety. Past industry roles include Honeywell and Eastman Kodak. Labs/Teams: Human-Machine Teaming Laboratory (founded at Vanderbilt University, relocated to Oregon State).