جستجوی استاد راهنمای دانشگاهی

Bin Huمشاهده پروفایل

استادیار

• Resilient Cyber-Physical Systems (CPS)
• AI-Human Collaboration Safety & Security
• Big Data & Machine Learning-Based Control
• +۵ مورد دیگر

Dr. Bin Hu is an Assistant Professor in the Department of Engineering Technology at the University of Houston (2022–present) and previously held the same position at Old Dominion University (2019–2022). He earned a Ph.D. in Electrical Engineering from the University of Notre Dame (2016), an M.S. in Control Science from Zhejiang University (2010), and a B.S. in Electrical Engineering from Hefei University of Technology (2007). His research focuses on resilient Cyber-Physical Systems (CPS), AI-human collaboration safety, machine learning-driven control, and vehicular networks. Key projects include NASA-funded work on adaptive human-autonomy responsibility allocation (2023–2026) and NSF-supported AI-human collaboration in autonomous vehicles (2020–2023). He has secured over $1.2 million in grants, including a $700k NASA grant (pending) and an ONR Rapid Solutions grant ($42k). Dr. Hu’s work bridges control theory, machine learning, and human factors. Recent contributions include safer leader-follower robotic systems, fault-tolerant UAV control, and studies on driver trust in AI-driven vehicles. His research has been recognized through awards like the 2024–2025 APeX Excellence Speaker Series. Teaching experience includes courses on C++ programming and electrical engineering fundamentals at both the University of Houston and Old Dominion University. He advises multiple undergraduate and graduate students in projects ranging from LiDAR systems to cyber-physical security. Key Labs/Teams : NAIL Lab (Networked Autonomous Intelligence & Learning), part of the University of Houston’s Cybersecurity and Robotics initiatives. Grants : NASA TTT Grant ($700k), NSF CHS Grant ($500k), ONR RSLP Project ($42k).

Paschalis Antonisمشاهده پروفایل

استاد

• Computer Engineering
• Digital Signal Processing
• Space Systems
• +۵ مورد دیگر

Paschalis Antonis is a Professor at the Department of Informatics and Telecommunications, National and Kapodistrian University of Athens. His research focuses on hardware architectures for space systems, embedded systems, and image compression standards such as CCSDS. He specializes in FPGA implementations, radiation-hardened electronics, and biomarker development for immunogenic responses to cancer therapies. Research Interests: High-performance FPGA-based hardware accelerators Space-grade embedded systems and data compression CCSDS standard implementations for aerospace applications Molecular biomarkers for immunotherapy response prediction Recent Trends: His work emphasizes resilient systems against radiation effects (e.g., SEUs in FPGAs), high-throughput image compression cores for space missions, and interdisciplinary research linking computational hardware with medical diagnostics via prothymosin α analysis. Grants & Labs: Leads the ASPIICS coronagraph project for ESA's Proba-3 mission, involving advanced optical instrumentation and formation flying systems. Collaborates on COTS FPGA utilization in extreme environments.

Mohammad Karimمشاهده پروفایل

استاد

• Optical Computing
• Information Processing
• Pattern/Target Recognition
• +۵ مورد دیگر

Mohammad Karim, PhD, is a Professor in the Department of Electrical & Computer Engineering at the University of Massachusetts Dartmouth (UMass Dartmouth), affiliated with the College of Engineering. He previously held leadership roles including Provost, Executive Vice Chancellor for Academic Affairs, and Chief Operating Officer at UMass Dartmouth. His career includes serving as Vice President of Research at Old Dominion University (2004–2013), Dean of Engineering at City College of New York (2000–2004), and Head of Electrical and Computer Engineering at the University of Tennessee (1998–2000). He is an elected fellow of multiple prestigious organizations, including IEEE, OSA, and SPIE. Dr. Karim holds a BS Honors in Physics from the University of Dhaka (1976) and MS in Physics (1978) and MS/PhD in Electrical Engineering (1979/1981) from the University of Alabama. His research focuses on optical computing, pattern recognition, electro-optical systems, and sensors, with funding from agencies like the Office of Naval Research and NASA. He has authored 19 books, over 365 papers, and 13 book chapters, and served as guest editor for 36 journal special issues. His awards include Fellowships from IEEE, OSA, and the Bangladesh Academy of Sciences. He mentors students in MS/PhD programs and advises on research proposals. His work spans academic leadership, technical innovation, and interdisciplinary collaboration in engineering and optics.

Justin Y. Shiمشاهده پروفایل

دانشیار

• Scalable Computing
• Blockchain Protocols
• Software Safety
• +۵ مورد دیگر

Justin Y. Shi is an Associate Professor at Temple University's Computer and Information Science Department. His research focuses on scalable computing, blockchain protocols, software safety, and infinitely scalable systems. He holds a PhD from the University of Pennsylvania and has held roles including Interim Director of the Center for Advanced Computing and Communications (1992-1998) and CIS Department Chair (2007-2009). B.S. Computer Engineering, Shanghai Jiao-tong University (1977) M.S. Software Engineering, University of Pennsylvania (1983) PhD in Concurrent Programming, University of Pennsylvania (1984) His research explores decoupling programs and data from physical devices to achieve fault tolerance and scalability. Key contributions include the Statistic Multiplexed Computing (SMC) paradigm and foundational work on parallel algorithms and distributed systems. He has authored patents on scalable parallel computing and high-performance blockchain systems. Teaching highlights include courses on quantum computing, cybersecurity, and fullstack programming. He has advised over 15 students, many now in industry and academia. Founder & CEO of Parallel Computers Technology Inc. (2000-2017) Co-founder of SMC Labs (2022-present) Active in editorial roles for IEEE Blockchain Technology Briefs and contributor to NSF workshops on cloud computing. His work has been exhibited at Supercomputing Conferences (1991-2018).

Chao Liمشاهده پروفایل

پژوهشگر ارشد

• Artificial Intelligence in Healthcare
• Medical Imaging
• Precision Medicine
• +۳ مورد دیگر

Chao Li is a Principal Research Fellow at the University of Cambridge's Faculty of Mathematics, specializing in AI-driven healthcare solutions. His research focuses on precision medicine through image-based AI and multi-omics integration, with applications in neurological disease modeling, surgical oncology, and clinical AI safety. He leads the Centre for Mathematical Imaging in Healthcare , advancing translational AI for personalized medicine. Research Themes: Image-based AI for precision mental health AI in surgical and interventional oncology Multi-omics approaches for disease characterization Evaluation of AI innovations for clinical translation Publications highlight advancements in multimodal fusion for diagnostics, histology-molecular marker integration, and neuroimaging analytics for mental health. His work bridges computational mathematics with clinical challenges, emphasizing real-world healthcare impact. Labs/Teams: Active member of the Centre for Mathematical Imaging in Healthcare , collaborating across departments to develop AI tools for clinical deployment.

• Systems and Networking
• Computer Architecture
• Machine Learning and Artificial Intelligence
• +۳ مورد دیگر

Andrew W. Moore is a Professor of Networked Systems at the University of Cambridge's Department of Computer Science and Technology. His research focuses on networked systems design, high-performance prototyping (e.g., NetFPGA), and latency measurement across scales from data centers to wide-area networks. He has contributed to SDN architectures, reconfigurable networking, and energy-efficient interconnects. He teaches courses including Computer Networking (Part IB), Scientific Computing (Part IA), and advanced modules on network measurements and system performance. His work emphasizes open-source tools and reproducible research, with publications in top venues like IEEE Transactions and ACM SIGCOMM. Research interests span Systems and Networking, Computer Architecture, Machine Learning applications in networking, and Security. Recent work addresses data center latency optimization, SDN-enabled IXPs, and FPGA-based network prototyping. Collaborations include projects on energy-aware networks and hardware-software co-design. He leads the NetFPGA initiative, a widely used open-source FPGA platform for networking research and education. His lab also explores emerging storage media and applications of software-defined networking in critical infrastructure.

• Computational Methods
• High Performance Computing
• Cloud Computing
• +۳ مورد دیگر

Professor Simon Cox is a Professor of Computational Methods and Director of the Microsoft Institute for High Performance Computing within the Faculty of Engineering and Physical Sciences at the University of Southampton. He holds a doctorate in Electronics and Computer Science, complemented by first-class degrees in Mathematics and Physics. His research focuses on computational tools and platforms, particularly in high-performance computing, cloud computing, and interdisciplinary applications in engineering and science. He has secured over £30 million in research and enterprise funding, published over 250 papers, and is a Microsoft Most Valuable Professional since 2003. Research interests include computational electromagnetics, meshless methods, and data management. His team, the Computational Engineering and Design Group, develops high-performance computing systems and commercial distributed computing solutions. Notable projects include a Raspberry Pi and Lego-based supercomputer and a spin-off company from computational electromagnetics research. He actively supervises PhD students in Engineering and Environmental Science. Key awards include the Microsoft MVP title. His work spans environmental monitoring (e.g., methane sensors, IoT-based peatland tracking), cybersecurity for IoT devices, and biomedical applications like 3D X-ray histology. He leads outreach initiatives, including the 'Supercomputing in Engineering Course' since 2005.

Kyle Konisمشاهده پروفایل

دانشیار

• Building Science
• Sustainable Architecture
• Occupant-Centric Design
• +۴ مورد دیگر

Kyle Konis is an Associate Professor of Architecture and Director of the Chase L. Leavitt Master of Building Science Program at the University of Southern California's School of Architecture. He holds a Ph.D. in Architecture (Building Science) from UC Berkeley, an M.Arch from Yale University, and a B.A. in Architectural Studies from the University of Washington. His research focuses on aligning building performance with human needs through participatory evaluation techniques, data-driven design tools, and evidence-based practices in sustainability and healthcare environments. Prof. Konis has led six externally funded research projects, including grants from the AIA Upjohn Initiative and California Energy Commission. His work emphasizes occupant-centric design, with notable contributions to daylighting strategies, circadian lighting in dementia care facilities, and energy-efficient building systems. He is a licensed architect in Washington and California. Education: B.A. Architectural Studies, University of Washington M.Arch, Yale University Ph.D., Architecture (Building Science), UC Berkeley His research interests include sustainable building practices, occupant well-being, and the application of technology to improve design outcomes. Notable projects include studies on thermal comfort databases, participatory sensing frameworks (TrojanSense), and circadian design tools. He has authored or co-authored over 30 peer-reviewed articles and a Springer-published book on daylighting. Awards: 2016 ARCC New Researcher Award 2015 ACSA New Faculty Teaching Award 2015 ACSA Housing Design Education Award 2015 BTES Emerging Faculty Award Prof. Konis teaches courses on architectural sustainability, environmental systems, and interactive computing in design. His lab integrates real-world data collection with computational modeling to bridge gaps between design intent and building performance. Ongoing work explores climate-responsive interventions for at-risk communities and the role of lighting in mental health contexts.

Arthur F Witulskiمشاهده پروفایل

استاد پژوهش

• Radiation Effects on Electronic Devices
• Power Semiconductor Reliability
• Space System Radiation Hardening
• +۳ مورد دیگر

Arthur F Witulski is a Research Professor of Electrical Engineering at Vanderbilt University's School of Engineering. He specializes in radiation effects on electronic power semiconductor devices and systems, focusing on radiation reliability in aerospace and nuclear environments. His research addresses challenges in satellites, robotics, and high-reliability power electronics. Education: PhD, MS, and BS in Electrical Engineering from the University of Colorado. Research Interests include radiation hardening of power electronics, semiconductor reliability under ionizing environments, and system-level modeling of radiation effects. His work spans energy systems, nano-materials, and risk mitigation strategies for complex engineering projects. Key contributions include developing models for SiC power device failures, Bayesian assurance frameworks for space systems, and methodologies linking component-level testing to system reliability. His recent articles emphasize single-event effects in advanced semiconductors and radiation tolerance in commercial-off-the-shelf (COTS) components. Witulski has pioneered radiation assurance tools for small satellites and robotic systems, emphasizing probabilistic modeling and fault-tolerant designs. His work integrates theoretical physics with practical engineering solutions for harsh radiation environments.

• Distributed Computing
• Distributed Algorithms
• Fault-Tolerance
• +۸ مورد دیگر

Marina Papatriantafilou is an Associate Professor in the Department of Computer Science and Engineering at Chalmers University of Technology and University of Gothenburg. Her research focuses on distributed computing, fault-tolerance, parallel algorithms, and concurrency control. She has contributed to methods for fault-tolerant distributed systems, visualization tools for distributed algorithms, and scalable overlay networks. Her academic roles include teaching advanced courses on distributed systems, computer communication, and operating systems. She advises graduate students in areas like distributed algorithms and parallel computing. Key research interests include lock-free synchronization, memory reclamation, and self-stabilizing systems. She has authored over 100 publications in top-tier conferences and journals, with recent work on data streaming frameworks, energy-sharing optimization, and vehicular network processing. Professional involvement includes roles in program committees for conferences like OPODIS, SWAT, and SSS, plus membership in research evaluation boards for Swedish and European funding agencies. She pioneered educational tools like the Lydian environment for distributed algorithm visualization.

• Distributed Systems
• Cloud Computing
• Fault Tolerance
• +۳ مورد دیگر

Rodrigo Miragaia Rodrigues is a full professor at the Instituto Superior Técnico (ULisboa) and a researcher at INESC-ID since 2015. He previously held roles as an associate professor at Universidade Nova de Lisboa, tenure-track faculty at MPI-SWS, and completed his PhD at MIT in 2005 under Barbara Liskov. Education: PhD in Computer Science, MIT, 2005 Research Interests: Focuses on distributed systems, fault-tolerant computing, cloud infrastructure, and consistency models. His work bridges theoretical foundations and practical implementations, addressing challenges in geo-replication, secure analytics, and resource allocation in serverless environments. He emphasizes scalable systems and resilient data management. Awards: Best Paper Award at SOSP ERC Starting Grant Google Faculty Research Award Advising & Grants: Has advised 7 PhD students as main advisor, with graduates in top institutions like Purdue, TU Munich, and USTC. Secured funding from the European Research Council (ERC) and Google, focusing on projects like DependableCloud (ERC Grant 307732). Labs & Teams: Leads research at INESC-ID and previously directed the Dependable Systems Group at MPI-SWS. Active in academic leadership roles, including President of the Scientific Council at IST.

Peter Jansenمشاهده پروفایل

دانشیار

• Natural Language Processing
• Artificial Intelligence
• Cognitive Science
• +۵ مورد دیگر

Peter Jansen is an Associate Professor at the University of Arizona's College of Information Science with a joint appointment at the Allen Institute for Artificial Intelligence (Ai2). He specializes in natural language processing (NLP), cognitive artificial intelligence, and automated scientific discovery. His research focuses on virtual environments for scientific reasoning, such as ScienceWorld and DiscoveryWorld, and methods for explainable AI through projects like the Explanation Bank. Education: PhD in Psychology and Neuroscience from McMaster University, and a Bachelor of Independent Studies from the University of Waterloo. His interdisciplinary background combines NLP, computer science, physics, and electrical engineering. Key projects include open-source hardware initiatives like the science tricorder (featured in over 50 media outlets and exhibited at the German Museum of Technology in Berlin) and TextWorldExpress, a text-game simulator. His work emphasizes grounding science education through sensing and developing AI systems capable of systematic reasoning and explanation generation. Current roles include advising students in automated scientific discovery and contributing to cross-listed courses in Computer Science and Linguistics. He maintains an active presence in academic outreach through teaching, conferences, and publications.

Pablo Serrano Yáñez-Mingotمشاهده پروفایل

دانشیار

• Wireless Networks
• Network Protocols
• 5G/6G Communication Systems
• +۳ مورد دیگر

Pablo Serrano Yáñez-Mingot is an Associate Professor at the Telematics Department of Universidad Carlos III de Madrid (UC3M), where he has been since 2002. He holds a Telecommunication Engineering degree and PhD from UC3M (2002 and 2006, respectively). Currently, he serves as Deputy Director of Infrastructure, Sustainability, and Digitalization at the Higher Polytechnic School (EPS). His research focuses on wireless networks, network protocols, and experimental performance evaluation, with over 100 peer-reviewed publications in top journals/conferences like IEEE/ACM Transactions on Networking and IEEE INFOCOM. He has led major projects such as the Hexa-X 6G flagship and Flex5Gware. He is an IEEE Senior Member and has received awards like the UC3M Excellence Award (2021) and Distinguished Member of the INFOCOM TPC (2022). Education: Telecommunication Engineering (UC3M, 2002), PhD in Telematics (UC3M, 2006). Research Interests: Wireless networks, 5G/6G systems, network protocols, energy efficiency, and experimental evaluation of communication systems. Recent Articles Trends : Focus on 5G/6G architectures, network automation, serverless computing, and energy-efficient solutions. Publications highlight advancements in NFV scaling, network slicing, and AI-driven orchestration. Awards : UC3M Excellence Award 2021 (Young Research Excellence) ACM WiNTECH 2016 Best Paper Award Elevated to IEEE Senior Member (2015) Advising & Grants : Supervised over 30 PhD/MSc students. Principal Investigator of projects like AMAZING-6G and iTrust6G. Actively involved in editorial and organizational roles in IEEE conferences (e.g., INFOCOM, WCNC). Labs & Teams : Leads research groups in network protocols, 5G/6G systems, and experimental evaluation. Collaborates with institutions like the University of Rome Tor Vergata and Trinity College Dublin through visiting positions.

• IoT Security
• Network Measurement
• Privacy Engineering
• +۳ مورد دیگر

Dr. Anna Maria Mandalari is an Assistant Professor at University College London (UCL), affiliated with the Electronic and Electrical Engineering Department. She serves as Director of the SafeNetIoT laboratory and the Internet Engineering/Telecommunications MSc/MRes Programme at UCL. She holds an Honorary Research Fellow position at the Institute for Security Science and Technology at Imperial College London. Her research focuses on IoT security, privacy engineering, and network measurement techniques, particularly analyzing information exposure from consumer devices and developing adaptive network security strategies. Her work has led to significant contributions such as the IMC'19 Community Contribution Award-winning study on multidimensional IoT device exposure and the Telekom Challenge-winning IoTrim prototype for blocking non-essential IoT traffic. She has secured funding through InnovateUK’s CyberASAP program and participated in high-impact projects like NATwatcher and the European roaming analysis initiative. Key Awards: Community Contribution Award (IMC'19), Best Paper Award (C2B(I)D 2015) Grants: InnovateUK CyberASAP Phase 2 funding, Telekom Challenge Development Stream Top 5 prize Labs/Teams: Director of SafeNetIoT Lab, Leading M2M and IoT security teams at UCL Her recent work addresses IoT device misactivation risks (e.g., smart speakers), scalable detection of IoT devices in the wild, and protocol design informed by crowdsourced data. She actively collaborates with industry partners like Telekom and academic institutions on network infrastructure security and performance optimization.

Tomer Galantiمشاهده پروفایل

استادیار

• Machine Learning
• Deep Learning
• Large Language Models
• +۵ مورد دیگر

Tomer Galanti is an Assistant Professor in the Department of Computer Science & Engineering at Texas A&M University, affiliated with the College of Engineering. His research focuses on machine learning, deep learning, large language models, and artificial intelligence. He holds a B.S., M.S., and Ph.D. in Computer Science and Mathematics from Tel Aviv University (2015–2021), followed by a postdoctoral position at MIT (2021–2024). His work spans theoretical foundations of neural networks, optimization, generalization bounds, and practical applications in language modeling and self-supervised learning. Education: Postdoctoral Associate, Massachusetts Institute of Technology (MIT), 2021–2024 Ph.D., Computer Science, Tel Aviv University, 2021 M.S., Computer Science, Tel Aviv University, 2017 B.S., Mathematics and Computer Science, Tel Aviv University, 2015 Research Interests: Machine and deep learning, large language models, artificial intelligence, generalization bounds, neural collapse phenomena, and self-supervised learning. His recent work explores optimization techniques (e.g., SGD with weight decay), distributed inference systems, and theoretical guarantees for neural network performance. Articles Trends: His publications emphasize theoretical advancements in neural network dynamics, generalization, and optimization. Notable themes include sparse neural networks, speculative inference acceleration, and fairness in language models. He also investigates representation learning and decision tree integration in language modeling frameworks. Advising & Grants: No advising or grant details are explicitly listed in the provided materials. His research is supported through institutional and collaborative efforts in computational and theoretical machine learning.