جستجوی استاد راهنمای دانشگاهی

John Hastingsمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• Natural Language Processing
• +۵ مورد دیگر

Dr. John Hastings is a Professor in the Department of Computer Science at Dakota State University, part of the Beacom College of Computer & Cyber Sciences. With nearly 35 years of experience, he specializes in teaching and curriculum development in computer science, combining academic rigor with industry insights from his roles as an AI/ML engineer, team leader, and business owner. Education: Ph.D., Computer Science, University of Wyoming M.S., Computer Science, University of Wyoming B.S., Computer Science, University of Wyoming Research interests include machine learning, AI applications in natural language processing (LLMs), generative AI, computer vision, ecological/environmental AI, AI in games, and gamification in education. Recent publications focus on cybersecurity challenges, AI ethics, and insider threat detection. His work has been recognized with awards such as the AAAI’s Innovative Applications of Artificial Intelligence (IAAI) Award and an International IPM Award for Excellence related to the CARMA AI tool. Teaching emphasizes active learning and practical skills, including courses on programming, data structures, AI, and cybersecurity. He advocates for gamification in education to enhance student engagement and success.

Joyoung Leeمشاهده پروفایل

دانشیار

• Connected Vehicle (CV) Systems
• Traffic Management
• Autonomous Vehicle Control
• +۵ مورد دیگر

Dr. Joyoung Lee is an Associate Professor in the Department of Civil and Environmental Engineering at New Jersey Institute of Technology (NJIT). He previously served as Laboratory Manager at the Federal Highway Administration's Saxton Transportation Operations Laboratory. His research focuses on Connected Vehicle (CV) systems, including applications in traffic management, signal control optimization, and autonomous vehicle infrastructure integration. Dr. Lee holds a Ph.D. (2010) and M.S. (2007) in Transportation Engineering from the University of Virginia, and a B.S. (2000) in Transportation Engineering from Hanyang University. His work emphasizes CV-based solutions for real-time traffic systems, cooperative vehicle-infrastructure systems (CVIS), and autonomous vehicle integration. Notable achievements include the 2019 IEEE CAVS Best Paper Award and multiple best paper recognitions from PTV User Group Meetings. His research also addresses traffic safety through innovations like the Virtual Guide Dog system for visually impaired pedestrians and advanced traffic monitoring frameworks using LiDAR and computer vision. Education: Ph.D., Transportation Engineering, University of Virginia (2010) M.S., Transportation Engineering, University of Virginia (2007) B.S., Transportation Engineering, Hanyang University (2000) Dr. Lee's research interests span smart city infrastructure, edge computing for traffic systems, and sustainable transportation solutions. He has pioneered algorithms for cooperative intersection management, automated platooning systems, and federated learning-based traffic optimization. His work bridges theoretical models with real-world implementation through partnerships with FHWA and industry stakeholders. Key contributions include development of the Cumulative Travel-Time Responsive (CTR) traffic signal control system, smart arrival notification systems for paratransit services, and advanced microsimulation calibration techniques. His lab focuses on translating CV data into actionable strategies for safer, more efficient transportation networks. Awards: IEEE CAVS Best Paper Award (2019) ASCE Grand Challenge Innovation Contest Honorable Mention (2017) PTV VISSIM Best Paper Awards (2012, 2008) Excellence in Research Award (University of Virginia, 2011) Ongoing projects include semi-decentralized graph neural networks for traffic forecasting and low-cost LiDAR-based traffic monitoring systems. His work addresses critical challenges in autonomous vehicle integration, incident management, and infrastructure resilience through interdisciplinary collaborations.

Yuan Tianمشاهده پروفایل

استادیار

• Data Mining
• Software Engineering
• Social Network Analysis
• +۳ مورد دیگر

Yuan Tian is an Assistant Professor in the School of Computing at Queen's University, Faculty of Arts and Science. She holds a PhD in Information Systems from Singapore Management University (2017) and a B.Sc. in Computer Science from Zhejiang University (2012). Her research focuses on integrating heterogeneous data sources to enhance software engineering practices, including data mining, recommender systems, and social network analysis. Prior to Queen's, she was a data scientist at Living Analytics Research Centre (LARC), SMU. She has held visiting positions at Carnegie Mellon University, INRIA Paris, and SAIL Canada. Research Interests: Data Mining Software Engineering Social Network Analysis Information Retrieval Recommender Systems Computer Security Recent Research Trends: Her work emphasizes AI-driven solutions for software bug management, code translation, vulnerability detection, and developer behavior analysis. Notable contributions include leveraging LLMs for technical debt repayment and enhancing code vulnerability detection via Graph Neural Networks. Awards: SMU Presidential Doctoral Fellowship (2015-2016) Best Paper Award at SANER 2017 Grants & Advising: No formal advisees listed, but active in collaborative projects with industry and academic partners. Labs/Teams: Previously associated with SOAR Group at SMU and currently leads research in Queen's School of Computing.

• Computer Network Security
• Mobile Computing
• Cloud Computing
• +۴ مورد دیگر

Dr. Dijiang Huang is an Associate Professor in the School of Computing and Augmented Intelligence at Arizona State University (ASU). He joined ASU in 2005 after completing his Ph.D. in Telecommunications and Computer Networking from the University of Missouri-Kansas City (2004). His research focuses on cybersecurity, mobile computing, and cloud computing, supported by grants from the National Science Foundation (NSF), Office of Naval Research (ONR), and industry partners like HP. He has received prestigious awards, including the ONR Young Investigator Award and HP Innovative Research Award. Education: B.E. in Telecommunications, Beijing University of Posts and Telecommunications (1995) M.S. in Computer Science, University of Missouri-Kansas City (2001) Ph.D. in Telecommunications and Computer Networking, University of Missouri-Kansas City (2004) Research Interests: Huang’s work emphasizes secure communication protocols, privacy-preserving techniques, and resilient network architectures. He has pioneered frameworks like Secure Group Communication (SeGCom) and Attribute-Based Cryptography , addressing challenges in VANETs, SDN, and edge computing. His recent projects include developing Waterfall for SDN security and SmartDefense for DDoS mitigation. Grants & Awards: ONR Young Investigator Award (2008) HP Innovative Research Award (2008) NSF grants for secure mobile cloud frameworks and cyber-physical systems Professional Contributions: Huang has served as a reviewer for journals like IEEE Transactions on Wireless Communications and conferences such as ACM MobiArch. He co-developed the Open Human-Robotic Mobile Networking and Security Testbed (OHReST) and the Virtual Laboratory (VLab) for cybersecurity education.

Pedro Vilaçaمشاهده پروفایل

استاد

• Welding Technology
• Solid-State Manufacturing
• Non-Destructive Testing (NDT)
• +۶ مورد دیگر

Pedro Vilaça is a **Professor and Head of the Department of Energy and Mechanical Engineering** at **Aalto University's School of Engineering**, Finland. Previously, he worked at the Instituto Superior Técnico (Técnico), University of Lisbon, Portugal (1995–2013). His research focuses on **welding technology**, **solid-state manufacturing**, **non-destructive testing (NDT)**, **hydrogen-related materials science**, and **materials safety**, with applications in energy and aeronautics sectors. He leads R&D teams and has collaborated globally, contributing to 142+ publications (h-index 32 via Scopus). **Research Interests**: Advanced welding techniques (e.g., friction stir welding), hydrogen embrittlement in steels, supercapacitor materials, and smart composites. He has pioneered methods for **zero-material-loss welding** and **self-sensing metallic materials**. **Key Projects**: Led initiatives like **THEWFuelCells** (fuel cell welding innovations) and **EARLY/Vilaca** (hydrogen damage assessment). His work aligns with **UN Sustainable Development Goals**, emphasizing renewable energy storage and industrial sustainability. **Awards**: 2011 Eng. Cruz Azevedo Award for outstanding research in Mecânica Experimental. **Collaborations**: Active in international networks, including the International Institute of Welding and European research consortia. He has organized conferences, reviewed patents, and advised doctoral students globally. **Recent Articles**: Focus on corrosion-resistant materials, piezoelectric composites, and hydrogen-induced failure in steels. His 2023–2025 work emphasizes energy storage innovations and advanced joining technologies. **Grants**: Principal investigator for projects funded by Business Finland, EU EIT, and Academy of Finland. **Labs/Teams**: Oversees Aalto’s mechanical engineering research teams and collaborates with institutions like Helmholtz-Zentrum Geesthacht.

• Cybersecurity
• Electronic Identity
• Network Security
• +۷ مورد دیگر

Antonio Lioy is a Full Professor in the Department of Control and Computer Science (DAUIN) at the Polytechnic University of Turin. He serves as the Cyber Security Representative for the university in national and European government collaborations, is a member of the SmartData@PoliTO interdepartmental center, and acts as Scientific Advisor for the DRIVESEC partnership. His research is deeply rooted in cybersecurity, electronic identity, network and web security, and quantum-resistant systems. His research interests focus on cybersecurity , electronic identity , network security , web security , and quantum cryptography . He leads the TORSEC Security Group and conducts research in LAB 7, with a strong emphasis on trusted computing, post-quantum cryptography, IoT security, and secure network infrastructures. His work aligns with ERC sectors in computer systems and cryptology, and supports UN SDGs on innovation and sustainable cities. His recent publications show a strong trend toward post-quantum cryptography , remote attestation , trusted execution environments , and secure network virtualization . These works appear in top venues such as IEEE, ACM, and IFIP conferences, with a focus on securing future digital infrastructures against emerging threats. Themes include integrity management in softwarized networks, standard-based attestation, and quantum-resistant PKI strategies. He has supervised numerous PhD students, including Davide Colaiacomo, Francesco Vaccaro, Flavio Ciravegna, Grazia D'Onghia, Lorenzo Ferro, Francesco Settanni, Enrico Bravi, Silvia Sisinni, Luca Mannella, and Ignazio Pedone, whose research spans cybersecurity, quantum computing, and IoT. He leads multiple high-profile research projects such as Q-FENCE, QUBIP, SERICS, and FISHY, funded by Horizon Europe and national programs, demonstrating significant grant acquisition and leadership. He is actively involved in research labs and teams, primarily the TORSEC - Security Group (DAUIN) and LAB 7 - Research Laboratory (DAUIN) , which focus on applied cybersecurity research. His projects often involve collaboration with industry and government bodies, emphasizing real-world impact in secure digital identity, critical infrastructure protection, and quantum-safe transitions.

Gang (Gary) Tanمشاهده پروفایل

استاد

• Computer Security
• Formal Methods
• Programming Languages
• +۲ مورد دیگر

Gang (Gary) Tan is a Professor at the Pennsylvania State University's College of Engineering, specializing in computer security, formal methods, and programming languages. He co-directs the Institute for Networking and Security Research (INSR) and leads the Security of Software (SOS) Group, focusing on compiler, programming language, and formal method techniques to enhance computer security. Education: B.E. in Computer Science from Tsinghua University Ph.D. in Computer Science from Princeton University His research integrates formal verification with practical security applications, particularly emphasizing: Compiler-based security enforcement Side-channel mitigation in speculative execution Fairness analysis in machine learning systems Formal grammar approaches for software reliability Key article trends show: Security-focused formal methods (15% of publications) ML fairness verification (20% of recent work) Compiler-based security solutions (30% of output) Side-channel defense mechanisms (25% of research) Parser design and formal grammar synthesis (10% of contributions) Scientific achievements include: NSF CAREER Award Google Research Awards (2x) PLDI 2024 Best Paper James F. Will Career Development Professorship Outstanding Research Award at Penn State Ruth and Joel Spira Excellence in Teaching Award Dr. Tan actively contributes to academic communities through: DARPA ISAT study group membership Program committee roles (CGO 2024, ECOOP 2018, etc) Leadership in security research initiatives

Mervi Paulasto-Kröckelمشاهده پروفایل

استاد

• Electronics Integration
• Reliability Engineering
• Microelectromechanical Systems (MEMS)
• +۸ مورد دیگر

Mervi Paulasto-Kröckel is a Professor in the Department of Electrical Engineering and Automation at Aalto University, specializing in Electronics Integration and Reliability. With a doctoral degree in Engineering and Technology from Helsinki University of Technology (1995) and a Master's degree from the same institution (1990), her work focuses on microelectronics packaging, MEMS, and sustainable electronic manufacturing. Doctoral Degree: Engineering and Technology, Helsinki University of Technology (1995) Master's Degree: Engineering and Technology, Helsinki University of Technology (1990) Her research explores advanced packaging techniques like SLID bonding, reliability of microbumps, and thermally conductive materials. Recent work includes buried aluminum nitride for silicon-on-insulator and fatigue crack analysis in IGBT modules. Her publications emphasize low-temperature processes, interdiffusion, and MEMS reliability. Awards include the JVST A Best ALD Paper Award (2021) and a Best paper award (2000). She leads projects like PowerizeD and 3DPiezoMems, focusing on digitalization and 3D MEMS development. Best paper award (2000) JVST A Best ALD Paper Award (2021)

• Control Systems
• Robotics
• Machine Learning
• +۳ مورد دیگر

Professor Bing Chu is an academic at the University of Southampton, actively contributing to research in control systems, robotics, and machine learning. They are a member of the Vision, Learning and Control Centre for Internet of Things and Pervasive Systems and the Centre for Robotics, focusing on interdisciplinary approaches that combine control theory with data-driven methodologies. Current research interests include: Iterative learning control Human-robot interaction Wind farm power optimization Robot behavior modeling Control system architectures Collaborative learning systems Recent publications highlight trends in data-driven control systems, human-robot interaction datasets, and optimization techniques for both continuous-time systems and wind energy applications. Professor Chu supervises multiple PhD students across robotics and electronic engineering, including Balint Gucsi, Haonan Shen, and Aleksander Wolski, while leading projects funded by Zhengzhou University and the Royal Society.

• Database Technology
• Database Management Systems
• Distributed Systems
• +۴ مورد دیگر

Michael Stonebraker is a renowned computer scientist and Adjunct Professor of Computer Science at MIT's CSAIL. He is a pioneer in database technology, having developed foundational systems like INGRES and POSTGRES at UC Berkeley. His work spans database management, distributed systems, and data integration. He has founded multiple startups to commercialize his research and holds numerous awards, including the ACM Turing Award (2014) and IEEE John von Neumann Medal (2005). He earned his Ph.D. from the University of Michigan and undergraduate degrees from Princeton and Michigan. His research focuses on advancing database systems, operating systems, and big data analytics. Recent work includes contributions to video data management, cloud computing optimization, and data discovery systems. Education: Ph.D., Computer, Information and Control Engineering, University of Michigan (1971) M.S.E., Electrical Engineering, University of Michigan (1966) B.S.E., Electrical Engineering, Princeton University (1965) Research Interests: Database Technology, Distributed Systems, Data Integration, and Big Data Analytics. His work bridges theory and practice, emphasizing scalable architectures and real-world applications. Awards & Recognition: ACM Turing Award (2014) ACM SIGMOD Systems Award (2015) MIT Tech Review TR7 (2016) C&C Prize (2020) Grants & Labs: His research is supported by grants from NSF, DARPA, and industry collaborations. He leads MIT's efforts in database systems and is affiliated with CSAIL labs focused on data management and high-performance computing.

ChanMin Kimمشاهده پروفایل

استاد

• Educational Technology
• Computer Science Education
• Science Writing
• +۳ مورد دیگر

ChanMin Kim is a Professor in the Learning and Performance Systems department at Penn State College of Education. With over 80 publications and 2553 citations, their work focuses on integrating artificial intelligence , robotics , and educational technology into science and computer science education. Research interests: Science writing, AI-human partnerships, robotics in education, equity-focused technology design Key methodologies: Natural Language Processing, learning analytics, scaffolding strategies Recent work explores large language models in education, debugging processes in pre-service teacher training, and automated assessment systems for science explanations. While the provided data doesn't show specific scientific awards or student advisees, their publications in venues like British Journal of Educational Technology and Journal of Science Education and Technology demonstrate significant contributions to learning sciences. Kim collaborates extensively with researchers in AI, educational technology, and equity-focused domains.

Lorenzo Cavallaroمشاهده پروفایل

استاد

• Trustworthy AI for Systems Security
• Adversarial Machine Learning
• Malware Detection
• +۶ مورد دیگر

Lorenzo Cavallaro is a Full Professor of Computer Science at University College London (UCL), specializing in Trustworthy AI for Systems Security. His research focuses on developing learning-based methods that are robust against adversaries by understanding the interplay between program analysis, representations, and machine learning models. His research interests span multiple critical areas in cybersecurity, including adversarial machine learning, malware detection, program analysis, and security evaluation. Cavallaro's work particularly emphasizes the challenges of concept drift in security systems and the development of robust defenses against evolving threats. His research has significant implications for Android security, binary analysis, and memory safety in embedded systems. Analysis of his recent publications (2024-2025) reveals a strong focus on addressing fundamental challenges in ML-based security systems. His work spans malware detection systems that maintain reliability under distribution shifts, adversarial attacks in the problem space, context-driven approaches using LLMs for security applications, and temporal invariance in malware detection. A recurring theme is the critical examination of whether ML-based security systems are truly robust and reliable in real-world scenarios. Cavallaro serves in significant editorial and advisory roles including the NDSS Steering Group (2023-2026), Associate Editor for Computer & Security and ACM TOPS, and Scientific Advisory Board for SERICS. He has been actively involved in program committees for top security conferences including IEEE S&P, USENIX Security, CCS, and NDSS from 2021-2025. He teaches Malware (COMP0060; 2022—ongoing), Research in Information Security (COMP0057; 2021—23), and Computer Security 2 (COMP0055; 2021—ongoing) at UCL, contributing to the next generation of security researchers and practitioners.

Andrew Colesمشاهده پروفایل

دانشگاهی

• Artificial Intelligence
• Temporal Planning
• Numeric Planning
• +۱۰ مورد دیگر

Dr Andrew Coles is a Reader in Artificial Intelligence at the Department of Informatics, King's College London, within the Faculty of Natural, Mathematical & Engineering Sciences. His research focuses on temporal and numeric planning, explainable planning, and human-robot collaboration. He leads and co-investigates multiple research projects funded by EPSRC, the Royal Academy of Engineering, and the European Commission. His research interests include Artificial Intelligence, Temporal and Numeric Planning, Planning with Rich Domain Models, Explainable Planning, Human-Robot Interaction, Autonomous Systems, Heuristic Search, and Decision-Making. He has published extensively in top-tier AI and robotics conferences such as ICAPS, IROS, HRI, AAAI, and IJCAI. His recent publications demonstrate a strong trend toward explainable AI in human-robot collaboration, with a focus on multimodal sensing (e.g., eye tracking), user needs for explanation, and adaptive planning. His work integrates planning algorithms with human-centered evaluation and real-world applications in robotics. Scientific Awards: International award for PhD thesis on assistive robots (2020) Advising and Grants: Dr Coles has supervised multiple students, including Lara Wachowiak, Guillem Canal, and Petra Tisnikar. He has led or co-investigated several major research projects, including: COHERENT (EPSRC): Collaborative Hierarchical Robotic Explanations Plan and Goal Reasoning for Explainable Autonomous Robots (Royal Academy of Engineering) ADE (European Commission): Autonomous Decision Making in Very Long Traverses ERGO (European Commission): European Robotic Goal-Oriented autonomous controller Labs and Teams: He is affiliated with the Reasoning and Planning research group and the Trusted Autonomous Systems Hub at King's College London, focusing on developing trustable autonomous systems through robust planning and human-centered AI.

Matt Rattoمشاهده پروفایل

استاد

• Artificial Intelligence
• Human-Computer Interaction
• Critical Making
• +۷ مورد دیگر

Matt Ratto is a full Professor in the Faculty of Information at the University of Toronto , where he also serves as Associate Dean, Research . He is a faculty affiliate of the Climate Positive Energy Institute , the Schwartz Reisman Institute for Technology and Society , and an SDG Fellow with the Sustainable Development Goals Institute . His work bridges critical theory and digital innovation , focusing on the social production of knowledge through emerging technologies. His research explores critical making and socio-technical systems , with applications in 3D-printed prosthetics (deployed in Cambodia, Tanzania, and Uganda), AI-driven healthcare solutions , and climate justice in computing . He has received over $6 million in funding, including two Canada Grand Challenge grants , and founded organizations advancing equitable technology access. Ontario Minister of College and Universities’ Award of Excellence (2020) Bell Canada Usability Labs Chair in Human-Computer Interaction (2018–2023) He supervises students such as Olivia Doggett and Sarah Gram , with past advisees including Brian Sutherland and Dan Southwick . His Critical Making Lab fosters interdisciplinary collaboration, and he teaches courses like INF2241: Critical Making and INF351: Information Design Studio .

Metin Sittiمشاهده پروفایل

استاد

• Medical Microrobotics
• Bio-inspired Robotics
• Physical Intelligence
• +۷ مورد دیگر

Prof. Dr. Metin Sitti is a leading academic and researcher currently serving as Director at the Max Planck Institute for Intelligent Systems and affiliated faculty at Carnegie Mellon University's Robotics Institute and Koç University's Schools of Medicine and Engineering. His interdisciplinary work bridges robotics, materials science, and biomedicine. His research interests center on medical microrobotics , bio-inspired robotics , and physical intelligence , exploring how intelligent behaviors can emerge from material properties and system design. He leads the Physical Intelligence Research Group , pioneering novel approaches in soft and micro-robotic systems. The scientific publications attributed to Prof. Sitti span diverse areas including micro-robotic locomotion, stimuli-responsive materials, and collective behavior in synthetic systems. Though specific titles are not listed, his body of work consistently contributes to robotics, nanotechnology, and biomedical engineering. Rahmi M. Koç Science Award ERC Advanced Grant IEEE Fellow National Science Foundation CAREER Award SPIE Nanoengineering Pioneer Award IEEE/ASME Best Mechatronics Paper Award Robotics: Science and Systems Conference Best Paper Award IEEE/RSJ Intelligent Robot Systems Conference Best Paper and Video Awards IEEE Robotics and Automation Conference Best Paper and Video Awards IEEE Robotics and Biomimetics Conference Best Paper and Video Awards Prof. Sitti has secured major grants including the ERC Advanced Grant and NSF CAREER Award, supporting high-impact research in intelligent materials and robotic systems. He has mentored numerous researchers and students across institutions, though specific advisees are not listed. His entrepreneurial initiative led to the founding of nanoGriptech Inc. in 2009, commercializing gecko-inspired microfiber adhesives. He leads the Physical Intelligence Department at the Max Planck Institute, where his team develops novel robotic materials and microsystems that exhibit intelligence through physical design rather than computation alone.