جستجوی استاد راهنمای دانشگاهی

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.

• Security and Privacy
• Active Cyber Defense
• Security Analytics
• +۶ مورد دیگر

J. Haadi Jafarian is an Assistant Professor in the Department of Computer Science and Engineering at the University of Colorado Denver, where he leads the Active Cyber and Infrastructure Defense (ACID) Lab. He earned his Ph.D. from the University of North Carolina Charlotte in 2017. Research Interests: Active Cyber Defense (Moving Target Defense, Cyber Deception) Big Data Analytics for Cyber Threat Intelligence Security for Cyber-Physical Systems & Critical Infrastructures Cyber Resilience and Automation Recent Publications highlight innovations in traffic obfuscation, adversarial machine learning, and deception-based threat detection. His work spans network security, cybersecurity analytics, and scalable defense frameworks. Teaching includes: CSCI 4743/5743: Cyber and Infrastructure Defense (Fall 2023) CSCI 4742/5742: Cyber Programming and Analysis (Spring 2023) CSCI 4741: Cybersecurity Principles (Spring 2022) CSCI 4800: Web Application Development (Spring 2021) CSCI 3761: Computer Networks (Spring 2020) Labs & Teams: The ACID Lab focuses on developing proactive cyber defense strategies, including moving target defense, deception techniques, and security analytics for critical infrastructure.

Flavio Espositoمشاهده پروفایل

دانشیار

• Cyber-physical Systems
• Networked Systems
• Network Virtualization
• +۵ مورد دیگر

Flavio Esposito is an Associate Professor in the Computer Science Department at Saint Louis University's School of Engineering. He also serves as a Research Institute Fellow and CS Graduate Coordinator. His office is located in ISE 234D at 3450 Lindell Blvd, St. Louis, MO. Dr. Esposito's research focuses on cyber-physical systems and networked systems, including network virtualization, network management, Software-Defined Networks (SDN), network architectures, and wireless networks. He has a strong interest in interdisciplinary applications of these technologies to medicine and agriculture. His work bridges theoretical networking concepts with practical implementations. His publications span key areas in networking research, with recent work focusing on congestion control algorithms, virtual network embedding, recursive network architectures, and edge computing applications. The research trends show a progression from foundational networking protocols toward more sophisticated applications integrating machine learning, edge computing, and cyber-physical systems, with increasing emphasis on real-world applications in diverse domains. Outstanding Graduate Mentoring Faculty Award from the School of Engineering (2021) Finalist for the Undergraduate Mentoring Award in the College of Arts and Sciences Multiple NSF research awards including US Ignite, ICE-T, CNS Core, CC* Integration, CPS:TTP, and ModernCARE projects COMCAST Innovation Fund Award (January 2020) International Center for Responsible Gaming (ICRG) Award ($150K) Dr. Esposito actively mentors PhD and MS students, with numerous current and past students who have gone on to positions at major tech companies, universities, and research institutions. He has been a Principal Investigator on multiple significant research grants totaling millions of dollars. He co-founded Spaghetti Code Labs with former PhD student Alessandro Sangiorgi, whose cybersecurity educational app WeeNet has achieved 5.7M+ downloads. He leads several research labs and teams focused on cyber-physical systems, with current openings for PhD students, visiting researchers, and postdocs working on networks, learning, edge computing, and applications to medicine and agriculture. His teams have developed numerous software systems including Software Mutant, Neighborhood Method Prototype, VINEA, ProtoRINA, and BUtorrent.

Andreas Malikopoulosمشاهده پروفایل

استاد

• Cyber-Physical Systems
• Transportation Systems
• Control Theory
• +۴ مورد دیگر

Andreas Malikopoulos is a Professor at Cornell University's School of Civil & Environmental Engineering and Director of the Information and Decision Science Lab (IDS Lab). Previously, he held roles as the Terri Connor Kelly and John Kelly Career Development Professor at the University of Delaware (UD) and founding Director of UD's Sociotechnical Systems Center. He also served as the Alvin M. Weinberg Fellow at Oak Ridge National Laboratory (ORNL), Deputy Director of ORNL's Urban Dynamics Institute, and Senior Researcher at General Motors R&D. His research focuses on cyber-physical systems (CPS), stochastic control, and learning-driven approaches for optimizing energy efficiency and sustainable mobility in smart cities and transportation systems. Education: PhD (Mechanical Engineering, University of Michigan, 2008), M.S. (Mechanical Engineering, University of Michigan, 2004), Diploma (National Technical University of Athens, 2000). Research Interests: Analysis and control of CPS, stochastic scheduling, game theory, and mechanism design applied to emerging mobility systems (e.g., autonomous vehicles, electric vehicles). He emphasizes integrating learning and control for socially optimal solutions in transportation networks. Awards: IEEE ITS Young Researcher Award (2019), UD’s Outstanding Junior Faculty Award (2020), Alvin M. Weinberg Fellowship (2010), and recognition as a NAS Kavli Frontiers of Science Scholar (2012). He is an IEEE Senior Member, ASME Fellow, and serves on editorial boards of leading journals. Teaching: Focuses on optimal decision-making, control theory, and emerging mobility systems. Courses include stochastic optimal control and game theory at Cornell. Labs: Leads the IDS Lab, which develops scalable frameworks for CPS and smart city applications. Current projects include coordinated routing for mixed-traffic systems and AI-driven recommendations for autonomous vehicles.

• Construction Safety and Risk Management
• Project Risk Assessment
• Railway and Highway Safety
• +۳ مورد دیگر

Professor Min An is a Professor of Construction and Risk Management at the University of Salford, leading the Infrastructure Research Group within the School of Science, Engineering & Environment. He holds an honorary professorship at two overseas universities (China and Portugal) and serves on the editorial boards of 12 international journals. With over 40 years of experience, his career spans academic roles at Heriot-Watt University, Coventry University, and the University of Birmingham, alongside industry roles as a civil engineer and researcher. His research focuses on safety and risk management in construction, transportation systems, and energy sectors, with over 200 publications. Key areas include railway and highway safety, offshore oil & gas risk assessment, and nuclear reliability management. He has secured funding from EPSRC, EU, DfT, and industry partners, leading 20+ projects. Notable achievements include developing methodologies for infrastructure safety and maintaining collaborations with 30+ industrial partners. Professor An has supervised 30 PhD students and over 280 postgraduate projects, contributing to industry workshops and best practices. Awards include multiple science technology prizes and conference best paper/keynote recognitions. His teaching spans risk management, construction safety, and project management across MSc programs.

Chengzong Pangمشاهده پروفایل

دانشیار

• Power Systems
• Electrical Engineering
• Control Systems
• +۷ مورد دیگر

Chengzong Pang is an Associate Professor and MSECE Graduate Coordinator at the Department of Electrical and Computer Engineering, College of Engineering, Wichita State University. His work focuses on power systems, electrical engineering innovations, and renewable energy integration. He specializes in transient stability analysis, control systems, and smart grid technologies. Research Interests: Dr. Pang's expertise includes advanced control strategies for power electronics (e.g., PMSM, UPQC), machine learning applications for grid stability (LSTM/SVM), and energy storage solutions for renewable integration. His research also addresses challenges in microgrid operation, subsynchronous oscillation mitigation, and battery storage systems. Key Trends in Publications: Over 20 years of publications (2002–2022) emphasize: (1) Machine learning for power system analysis, (2) Control system design for renewable integration, (3) Grid stability enhancement via advanced algorithms, and (4) Smart grid infrastructure optimization. Recent works (2021–2022) highlight transient stability prediction and ANFIS-based power quality solutions. Labs/Teams: Active in energy systems research groups focusing on renewable integration and grid modernization, though specific lab names are not explicitly stated in the provided texts.

Manolis G.H. Katevenisمشاهده پروفایل

استاد

• Computer Architecture
• VLSI Systems
• Interconnection Network Architecture
• +۴ مورد دیگر

Manolis G.H. Katevenis is a Professor at the Department of Computer Science, University of Crete, and Deputy Director and Head of the Computer Architecture and VLSI Systems (CARV) Laboratory at the Institute of Computer Science (ICS), Foundation for Research & Technology - Hellas (FORTH). He co-founded the European Research Center on Computer Architecture (EuReCCA) and is a founding partner of the European Network of Excellence on High-Performance and Embedded Architecture and Compilation (HiPEAC). PhD in Computer Science from University of California, Berkeley (1983) Co-founder of EuReCCA (2011) Contributed to RISC architecture (1980-1983), interconnection networks (1985-2011), and parallel computing (1993-2010) His research spans Scalable Multicore Systems , Interconnection Network Architecture , Packet Switch Design , Computer Architecture , and VLSI Systems . He has made foundational contributions to per-flow queueing, backpressure mechanisms, and wormhole IP over ATM, with applications in internet routers, data centers, and supercomputers. His publications focus on high-radix crossbar switches, flow control algorithms, and explicit interprocessor communication. Notable scientific awards include: ACM Doctoral Dissertation Award (1984) David J. Sakrison Memorial Prize (1983) IBM PhD Fellowship (1981-1983) Greek State Fellowship (1973-1978) He has supervised 40 graduate theses and participated in 22 R&D projects totaling €9M, including HiPEAC (coordinator of interconnection networks), SARC (FPGA prototype design), and ENCORE (cache-optimized remote DMA). His work has received over 2000 citations, with an h-index of 23.

Lisa Yanمشاهده پروفایل

استاد آموزشی

• Computer Science Education
• Computing Ethics
• Teaching Assistant Training
• +۲ مورد دیگر

Lisa Yan serves as a Teaching Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley, appointed in Spring 2022. She teaches core computer science education courses including CS 195 (Social Implications of Computer Technology), CS H195 (Honors variant), CS 294-189 (Teaching Process Design), and CS 375 (Teaching Techniques), holding regular office hours in Soda Hall for student engagement. Her academic credentials include: PhD in Electrical Engineering from Stanford University (2019) MS in Electrical Engineering from Stanford University (2015) BS in Electrical Engineering and Computer Science from UC Berkeley (2013) Dr. Yan's research centers on data-driven analysis of student learning in large-scale computer science courses, with significant contributions to computing ethics pedagogy and teaching assistant development programs. Her work develops innovative methodologies for assessing student earnestness in interactive lectures, creating flexible learning extensions, and designing integrity-focused assessments. Earlier research focused on software-defined networking and network switch performance optimization, demonstrating technical depth before her pivot to educational innovation. Current projects emphasize scalable teaching techniques and mastery learning frameworks that address challenges in modern CS education. Analysis of her 14 publications (2013-2024) reveals a strategic shift from computer networking (pre-2018) to computer science education research (2018-present). Recent work (2020-2024) dominates in venues like SIGCSE, featuring tools such as Otter-Grader for Jupyter notebook grading and the Earnest Insight Toolkit for lecture participation analysis. This evolution highlights her commitment to solving practical educational challenges through data analysis and tool development, particularly for large undergraduate courses. She received recognition through: The Faculty Award for Outstanding Mentorship of GSIs (2024) Lisa actively mentors Graduate Student Instructors and collaborates with educational technology initiatives. Her research team includes dedicated support staff like Taylor Kaserman (taylor.kase@berkeley.edu), reflecting structured collaboration in developing teaching innovations. She contributes to curriculum design committees within EECS, focusing on assessment integrity and scalable pedagogical methods for growing student populations. Her work operates through the EECS department's educational infrastructure, utilizing Soda Hall resources for both teaching coordination and research development, with strong connections to Berkeley's broader computing education ecosystem.

• Distributed control
• Autonomy and Control
• Aerospace Systems
• +۶ مورد دیگر

Dengfeng Sun is a Professor and Associate Head of the Gambaro Graduate Program in the School of Aeronautics and Astronautics at Purdue University. His research focuses on distributed control systems, autonomy, resilient networks, and air traffic management. Sun holds a B.Eng. from Tsinghua University, an M.S. from The Ohio State University, and a Ph.D. from UC Berkeley. His work spans advanced air mobility, UAV trajectory planning, and stochastic optimization for large-scale systems. Key contributions include resilient UAV traffic control, distributed state estimation algorithms, and fault detection methods for navigation systems. Sun's research has been published in top journals like IEEE Transactions on Intelligent Transportation Systems and Transportation Research Part E. Education: B.Eng., Tsinghua University (2000) M.S., Ohio State University (2002) Ph.D., UC Berkeley (2008) He advises on cutting-edge projects integrating robotics, autonomous systems, and cloud-based traffic modeling. His lab develops solutions for urban air mobility, emergency medical UAV networks, and next-generation air traffic control systems. Notable collaborations include work with NASA and industry partners on continuous descent approach procedures and metroplex routing paradigms. Sun's work bridges theoretical control systems with practical applications in aviation and infrastructure optimization.

• Networking and Operating Systems
• Information Security and Assurance
• Network Architecture and Protocols
• +۳ مورد دیگر

Sonia A. Fahmy is a Professor of Computer Science and Associate Department Head at Purdue University's Department of Computer Science (College of Science). She holds a PhD from The Ohio State University (1999). Her research focuses on network architectures, protocols, and security, with over 100 refereed publications. Key areas include virtual reality networking, cellular network optimization, and network experimentation tools like NFV-VITAL and ENVI. Her work is supported by NSF, DHS, industry partners, and she leads Purdue's CERIAS cybersecurity initiatives. Education: PhD in Computer and Information Science from The Ohio State University (1999). Research Interests: Network security, distributed systems, wireless sensor networks, and network function virtualization. Notable contributions include the HEED clustering algorithm and Contain-ed latency management system. Awards: NSF CAREER Award (2003), IEEE Fellow. Grants: NSF, DHS, AT&T, Cisco, Juniper, and Meta-funded projects. Professional service includes leadership roles in IEEE ICNP, INFOCOM, and editorial roles in top journals. Advising: Mentored over 20 PhD students and postdocs. Current advisees include Umakant Kulkarni and Yufeng Chen. Research teams collaborate with industry partners like Hewlett-Packard and Sandia National Labs. Labs/Teams: Active in Purdue's CERIAS, leading projects on secure network protocols and experimentation frameworks. Tools developed include EMIST, Testbed Mapping, and iHEED for sensor networks.

• Ultra-low power systems
• Microelectronics
• Integrated Circuits
• +۱۱ مورد دیگر

Professor Aniruddha Desai is a Research Professor and Director of the Centre for Technology Infusion (CTI) at La Trobe University. He holds a Bachelor’s in Industrial Electronics, a Master’s in Micro-electronics, and a PhD in Computer Science. His expertise spans microelectronics, AI, IoT, and sensor networks, with a focus on socially impactful applications like transportation, healthcare, and precision agriculture. Research Interests: Ultra-low power systems Micro-nano electronics AI/ML and edge computing IoT and sensor networks Transportation and logistics Major Projects: Led multi-million-dollar R&D programs in areas such as smart cities, energy management, and smart farming. Notable collaborations include the IIT Kanpur - La Trobe University Research Academy and the Asian Smart Cities Research and Innovation Network. Awards: Recipient of the 2016 Vice-Chancellor’s Award for Research Excellence and the 2020 Victorian Tall Poppy Award for Science. Served on advisory panels for the Australian Research Council and provided expert testimony in parliamentary inquiries. Labs/Teams: Directs the CTI, which delivers technology-based innovations to industry and government. Co-founded the Asian Smart Cities network to advance urban technology solutions.

Shahrokh Valaeeمشاهده پروفایل

استاد

• Wireless Networks
• Signal Processing
• Vehicular Networks
• +۴ مورد دیگر

Shahrokh Valaee is a Professor and Associate Chair for Undergraduate Studies in the Edward S. Rogers Sr. Department of Electrical and Computer Engineering at the University of Toronto, part of the Faculty of Applied Science and Engineering. He founded and directs the Wireless and Internet Research Laboratory (WIRLab). Education: BSc and MSc in Electrical Engineering from University of Tehran PhD in Electrical Engineering from McGill University Research Interests: Focuses on wireless networks (vehicular/sensor networks, B5G/6G), signal processing (indoor localization, machine learning for medical imaging), and integrated sensing/communication. His work spans: Localization in GPS-denied environments Machine learning for healthcare with limited/imbalanced data Reconfigurable Intelligent Surfaces (RIS) and drone networks Publications: Recent articles (2014-2016) show strong focus on indoor localization techniques, vehicular network protocols, and network coding, with emerging trends in machine learning applications for wireless systems and healthcare. Awards: Connaught Award (2012, 2013) NSERC Discovery Accelerator Award (2010) MaRS Innovations cPOP Award (2012) IEEE Fellow (FIEEE) Engineering Institute of Canada Fellow (FEIC) Leadership: Advises graduate students at WIRLab, where research combines theory with practical implementation (GPU-based ML, Android localization). Manages projects in integrated sensing/communication, ML for health, and B5G networks. Labs/Teams: Directs WIRLab with focus on wireless signal processing, networking, and ML implementations. Current team includes postdocs and PhD students working on localization, B5G networks, and medical ML applications.

• Wireless Networks
• Signal Processing
• 5G/6G Communications
• +۳ مورد دیگر

Dr. Wibowo Hardjawana is a Senior Lecturer in Telecommunications Engineering at the School of Electrical & Computer Engineering , University of Sydney. He holds a PhD from the University of Sydney and serves as an ARC DECRA Research Fellow. His research focuses on wireless network softwarisation, enabling programmable radio interfaces to address traffic elasticity in 5G/6G systems. Education : PhD (University of Sydney) Grants : ARC DP210100744 (2021), ARC DECRA DE140101114 (2014) His work spans 5G/6G network architectures , machine learning for wireless systems , and open radio interfaces . Key contributions include graph representation learning for interference management, Bayesian neural network detectors for OTFS modulation, and NOMA decoding techniques . Recent publications analyze ultra-reliable low-latency communications , UAV-enabled networks , and stochastic geometry in wireless systems . He has collaborated with institutions in China, Indonesia, and UAE, and engaged with industry partners like Telstra and Ausgrid.

Xiaolei Guoمشاهده پروفایل

استاد

• Transportation
• Supply Chain Management
• Congestion Pricing
• +۳ مورد دیگر

Xiaolei Guo is a Professor of Management Science at the Odette School of Business, University of Windsor. His expertise spans transportation systems, supply chain optimization, and infrastructure pricing strategies. He holds a Ph.D. in Transportation from the Hong Kong University of Science and Technology (2008) and a B.A. in Hydraulic Engineering from Tsinghua University (2004). His research focuses on congestion pricing mechanisms, transportation network modeling, and toll road economics. Notable areas include optimizing toll designs under uncertainty, analyzing autonomous vehicle impacts on ridesharing, and evaluating strategic distribution channel decisions under environmental regulations. Dr. Guo has contributed to over 30 peer-reviewed articles since 2005, exploring topics such as Braess paradox under bounded rationality, Pareto-improving congestion schemes, and profit maximization for private toll roads. His work bridges theoretical optimization with practical policy applications. He is an active member of the Canadian Transportation Research Forum (CTRF) since 2011 and the Institute for Operations Research and the Management Sciences (INFORMS) since 2009.

Soufiene Djahelمشاهده پروفایل

استاد

• Connected and Autonomous Vehicles (CAVs)
• Unmanned Aerial Vehicles (UAVs)
• Cyber Security
• +۷ مورد دیگر

Soufiene Djahel is a Professor at the Centre for Future Transport and Cities (CFTC) at Coventry University, UK. His research focuses on connected and autonomous vehicles (CAVs), unmanned aerial vehicles (UAVs), cyber security, and smart cities. He holds a PhD in Secure Routing and Medium Access Protocols from Université des Sciences et Technologies de Lille (2010), and has held academic positions including Senior Lecturer at the University of Huddersfield and Manchester Metropolitan University. His research interests include CAV coordination protocols, cyber-physical security solutions, and intelligent transportation systems. Djahel leads projects such as the £1.2M AeroPharma Logistics initiative and has secured funding from the Newton Fund and JSPS. He is a recipient of the 2021 JSPS Invitational Fellowship and has published extensively in IEEE journals and conferences. Current projects explore UAVs-as-a-service, digital twins for CAVs, and B5G/6G for smart infrastructure. He advises PhD students on topics like AI-based threat mitigation and transport electrification. Djahel also serves as an external examiner and editorial board member for journals like IEEE Transactions on Intelligent Transportation Systems.