Find Academic Supervisors

Mohammad JalayerView profile

Associate Professor

• Transportation Engineering
• Traffic Safety
• Intelligent Transportation Systems (ITS)
• +5 more

Dr. Mohammad Jalayer is an Associate Professor and Graduate Coordinator in the Department of Civil & Environmental Engineering at Rowan University. He also serves as the Associate Director and Manager of the ITS Division at the Center for Research & Education in Advanced Transportation Engineering Systems (CREATES). His research focuses on traffic operations, highway safety, crash modeling, big data analytics, and Intelligent Transportation Systems (ITS). Jalayer’s work is funded by organizations including USDOT, NHTSA, and NJDOT. He holds a Ph.D. from Auburn University (2016), an M.C.E. from Sharif University of Technology, and a B.S. from the University of Mashhad. Research Interests: Highway Safety, Traffic Operations, Crash Modeling, ITS, Connected/Autonomous Vehicles, Data Analytics. Key Projects: Pedestrian Hybrid Beacon Signal, Wrong-Way Driving Crashes, Street-Smart New Jersey Campaign. Recent Grants: Regional UTC Program (2018-2023). Awards: Young Civil Engineer of the Year (2017, ASCE Central Jersey Branch) First Place, ITE Northeastern District Rising Star Program (2017) 2020 AASHTO High Value Research Award Labs/Teams: Leads the CREATES lab, focusing on advanced transportation engineering solutions.

Devavrat ShahView profile

Professor

• Machine Learning
• Artificial Intelligence
• Data Science
• +7 more

Devavrat Shah is a Professor at the Massachusetts Institute of Technology (MIT), affiliated with the Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Laboratory for Information and Decision Systems (LIDS). His research focuses on machine learning, causal inference, and algorithmic fairness, with applications in healthcare outcomes, criminal justice reform, and cryptocurrency analysis. He has contributed to groundbreaking work, such as developing a machine-learning algorithm that nearly doubled Bitcoin investments over 50 days using real-time price data analysis. Shah's academic work integrates statistical methods with real-world challenges, including personalized medicine, policy evaluation, and bias detection in algorithms. His recent projects include global clinical studies on lymphoma treatments and frameworks for auditing racial bias in law enforcement systems. His interdisciplinary approach bridges computer science, statistics, and domain-specific applications. Key areas of his research include causal inference frameworks for data-rich environments, algorithmic fairness in decision-making systems, and predictive modeling for healthcare and public policy. His work often combines theoretical rigor with practical impact, addressing societal challenges through data-driven solutions. Shah's contributions to synthetic interventions and causal simulators have advanced trace-driven simulation methodologies, while his collaboration with global consortia like PETAL highlights his commitment to translational research. His students, including Kang Zhang, have contributed to impactful projects in algorithm design and data science.

• Virtual Reality
• Computer Graphics
• Human-Computer Interaction
• +5 more

Fabrizio Lamberti is a Professor at the Polytechnic University of Turin, Italy. His research focuses on Virtual Reality (VR), Extended Reality (XR), and Human-Computer Interaction (HCI), with applications in medical training, cultural heritage, robotics, and educational technologies. He holds a PhD in Distributed Systems and Information Technologies from the same institution (2005). Key contributions include pioneering work on immersive VR training systems for emergency response, medical procedures, and industrial robotics. He has extensively explored motion capture, real-time rendering, and AI-driven solutions for virtual environments. His work bridges theoretical advancements with practical implementations, such as VR-based surgical simulations and digital twin frameworks for manufacturing. Lamberti's interdisciplinary approach integrates computer vision, machine learning, and semantic technologies. Notable projects include semiotic AI frameworks for facial image analysis and blockchain-based interfaces for autonomous vehicle communication. He frequently collaborates with industry partners like KUKA and IEEE, contributing to standards in consumer electronics and entertainment computing. He has authored over 150 peer-reviewed articles spanning journals like IEEE Transactions on Visualization and Computer Graphics, IEEE Consumer Electronics Magazine, and Medical Image Analysis. His editorial roles include guest editorships for special issues on VR in education and medical imaging. Lamberti's research also addresses ethical and accessibility challenges in emerging technologies, such as cybersickness mitigation in immersive systems.

Mei HongView profile

Professor

• Software architecture
• Program analysis and testing
• Software System for Cloud Computing and Big Data
• +5 more

Mei Hong is a Professor and Vice President for HR and International Collaboration at Beijing Institute of Technology. Previously held roles include Professor and Vice President at Shanghai Jiao Tong University (2013-2016), Director of key national research centers at Peking University, and leadership positions in software engineering education and research. Holds dual academic leadership and technical expertise in software engineering. Education: BSc/MSc (Nanjing University of Aeronautics & Astronautics, 1984/1987); PhD (Shanghai Jiao Tong University, 1992). Research focuses on software architecture, cloud computing systems, component-based engineering, and software testing. Has pioneered the 'Internetware' paradigm and contributed to national standards for software development. Publications span software engineering methodologies and tools, with recent work emphasizing mobile computing optimization and automated testing techniques. Over 20 awards including IEEE Fellow (2014), Member of Chinese Academy of Sciences (2011), and multiple best paper awards. Advisory roles include Alibaba DAMO Academy's Academic Board, China's National Key R&D Program, and leadership in 863 High-Tech Program committees. PI of 40+ grants totaling over 200 million CNY. Editorial leadership includes SCIENCE CHINA-Information Sciences (Editor-in-Chief since 2018), ACM Computing Surveys, and top-tier journals/conferences. Active in conference organization (General Chair for ICSME 2017, SPLC 2016).

Annie LiangView profile

Senior Lecturer

• Air Traffic Management
• Trajectory-Based Operations
• Machine Learning
• +7 more

Dr. Annie Liang is a Senior Lecturer in the School of Engineering at RMIT University, specializing in Air Traffic Management (ATM), Trajectory-Based Operations (TBO), machine learning, and big data analytics with a focus on autonomous systems and Advanced Air Mobility (AAM). Her work addresses challenges in urban air mobility, sustainable aviation, and airspace optimization. She holds licenses in air traffic control and is an active member of professional societies like the Royal Aeronautical Society and AIAA/IEEE. Research interests include intelligent air traffic systems, unmanned traffic management, and safety-centered AAM. Her UN Sustainable Development Goals alignment includes Industry, Innovation and Infrastructure; Sustainable Cities and Communities; and Climate Action. Teaching focuses on aviation law, avionics, and sustainable aviation practices. Key projects involve trajectory prediction, wind disturbance analysis for Urban Air Mobility, and drone fleet management for agriculture. She supervises Master’s and PhD students in topics like air traffic flow optimization and autonomous systems. Collaborates with labs such as Intelligent Automation & Autonomy for Aerospace and Information in Society.

• Computer Networks
• Internet Video Distribution
• Network Synthesis
• +6 more

Sanjay Rao is a Professor in the School of Electrical and Computer Engineering at Purdue University, leading the Internet Systems Laboratory. His research focuses on network synthesis/design/verification and Internet video distribution. He holds a B.Tech from IIT Madras and a Ph.D from Carnegie Mellon University. He has held visiting roles at Google, AT&T Research, and Princeton University. Research & Awards: His work includes groundbreaking contributions like End System Multicast (winner of the ACM SIGMETRICS Test of Time Award), Oboe (ABR auto-tuning), and Veritas (causal video streaming analysis). He received the NSF CAREER Award (2010) and is an ACM Distinguished Member (2021). Teaching: Courses include Computer Networking (ECE 463), Object-Oriented Programming (ECE 39595), and Computer Network Systems (ECE 595). Service: Chair, ACM Sigcomm Doctoral Dissertation Award Committee (2022); Associate Editor, IEEE/ACM Transactions on Networking (2016–2020). Labs & Teams: Directs the Internet Systems Lab (ISL) with active projects on video streaming, network resilience, and intent-based design. Graduate students collaborate on these initiatives.

• Distributed Systems
• High-Performance Computing
• Fault Tolerance
• +5 more

Ozalp Babaoglu is a Full Professor at the Department of Computer Science and Engineering, University of Bologna. He has held this position since 1987, following a PhD in Computer Science from the University of California, Berkeley in 1981. His research focuses on distributed systems, High-Performance Computing (HPC), fault tolerance, self-organization, and machine learning applications in data-driven autonomics. He has led numerous European research projects like BROADCAST, CABERNET, ADAPT, BISON, and DELIS, contributing to foundational work in biology-inspired distributed algorithms and gossip-based systems. He co-founded the Bertinoro International Center for Informatics (BiCi) in 2001 and the IEEE SASO conference series in 2007. Babaoglu is a Fellow of the ACM (2002) and has received prestigious awards, including the Sakrison Memorial Award (1982) and the USENIX Lifetime Achievement Award (1993). His contributions to BSD Unix and open standards are seminal, including virtual memory extensions during his PhD. Babaoglu has served on editorial boards for ACM Transactions on Autonomous and Adaptive Systems, and previously for ACM Transactions on Computer Systems and Distributed Computing. His recent work addresses HPC fault classification, data-driven resource allocation, and energy-efficient computing in hybrid systems. He actively advises on European projects and explores cognitive paradigms in distributed systems.

• Power Systems
• Renewable Energy
• Control Systems
• +7 more

Dr. Jianli Gao is a Researcher in the Control and Power (CAP) Research Group at Imperial College London’s Department of Electrical and Electronic Engineering, within the Faculty of Engineering. His work focuses on modeling and control of future power grids dominated by renewable energy sources, supported by a National Grid ESO-funded project. He is affiliated with the Electric Power Innovation for a Carbon-free Society (EPICS) Center and the KIOS Research and Innovation Center of Excellence. Dr. Gao holds a PhD in Electrical and Electronic Engineering from Imperial College London (2024), with a thesis on power systems stability under Prof. Alessandro Astolfi and Dr. Balarko Chaudhuri. He also earned a First Class B.Eng. from the University of Manchester (2016–2018) and a B.Eng. from North China Electric Power University (2014–2016), alongside an M.Sc. in Control Systems (Distinction) from Imperial (2018–2019). His research interests span power systems stability, control theory, renewable energy integration, dynamical systems, and machine learning applications. His recent work includes developing graph neural networks for stock market prediction and multi-scale analysis, alongside contributions to neuroscience data repositories like the developing Human Connectome Project (dHCP). Dr. Gao’s publications reflect a blend of foundational engineering and cross-disciplinary innovation, including projects on prosthetic interface optimization and cloud-based metabolomics tools. His work bridges theoretical advancements in control systems with practical applications in energy, finance, and healthcare.

Kenneth M. HopkinsonView profile

Professor

• Cybersecurity
• Networking
• Smart Grid Protection
• +12 more

Dr. Kenneth M. Hopkinson is a Professor of Computer Science and Head of the Department of Electrical and Computer Engineering at the Air Force Institute of Technology (AFIT) in Dayton, Ohio. He holds a Ph.D. and M.S. from Cornell University and a B.S. from Rensselaer Polytechnic Institute, all in Computer Science. He is a Senior Member of IEEE and ACM, reflecting his active engagement in the academic and professional communities. Ph.D., Computer Science, Cornell University, 2004 M.S., Computer Science, Cornell University, 2002 B.S., Computer Science, Rensselaer Polytechnic Institute, 1997 Dr. Hopkinson's research focuses on cybersecurity, networking, smart grid protection, critical infrastructure, and sensor fusion. His work integrates formal methods, machine learning, and distributed systems to enhance the reliability and security of cyber-physical systems. He has pioneered research in trust management, agent-based protection systems, and formal verification of safety-critical software. His recent publications highlight a strong trend in applying machine learning to hardware security, formal verification of algorithms, and resilience in critical infrastructure using social sensing. These works span domains from FPGA Trojan detection to SPARK-based verification of sorting algorithms, indicating a multidisciplinary approach that bridges theory and practical defense applications. Best Student Paper Award Winner, 15th International Command and Control Research and Technology Symposium (ICCRTS), 2010 Dr. Hopkinson has secured significant research funding and leads projects involving simulation, wargaming, and critical infrastructure protection. He has mentored numerous students through collaborative research, though formal advisee lists are not provided. He is actively involved in major research initiatives, including the EPOCHS simulation platform for power and communication systems. He has also contributed to book chapters and edited volumes on avionics cybersecurity and cyber-physical systems. He leads or contributes to research teams focused on cognitive radio networks, secure SCADA systems, and space applications. His work often involves interdisciplinary collaboration with electrical engineers, computer scientists, and defense analysts. Labs under his oversight likely include those in cybersecurity, network simulation, and hardware security, supporting both academic and military applications.

George PanoutsosView profile

Professor

• Computational Intelligence
• Explainable Machine Learning
• Data-Driven Modeling
• +7 more

Professor George Panoutsos is a faculty member at the University of Sheffield , affiliated with the School of Electrical and Electronic Engineering and the Department of Automatic Control and Systems Engineering (ACSE) . He was promoted to Professor of Computational Intelligence in 2019 after joining as a Lecturer in 2010. Research focus on Computational Intelligence with applications in advanced manufacturing , healthcare , energy , and infrastructure Secured over £3M in grants from EPSRC , Innovate UK , DSTL , EU Horizon 2020 , and industry partners Over 100 publications in machine learning , optimization , and decision support systems Recent research trends include: Explainable AI for neural networks and optimization algorithms Physics-informed ML in additive manufacturing and fuel cells Multi-objective optimization frameworks for industrial processes Autonomous systems in manufacturing and biomedical imaging Reinforcement learning for process control and stability Granular computing for data compression and modeling Scientific contributions : Co-PI for EPSRC MAPP Hub (£6.7M 2016-2023) Lead PI for VULCAN (Innovate UK, £334k 2019-2022) International patent in Granular Computing from PhD work Fellow of the Higher Education Academy (FHEA) Teaching activities include module leadership for ACS6402: Industry Training Programme in Advanced Manufacturing and ACS6403: Computational Intelligence . His Computational Intelligence Systems Laboratory includes researchers working on projects like NanoMan , Responsive Manufacturing , and INTEGRADDE .

• Computer Science
• Cybersecurity
• Edge and Cloud Computing
• +4 more

Luca Ferretti is an Associate Professor at the University of Modena and Reggio Emilia , affiliated with the Department of Physical, Computer and Mathematical Sciences . His research focuses on cybersecurity, edge/cloud computing, and machine learning applications in security. Office located in the former Mathematics campus (Building MO18, third floor), Modena, Italy Scientific disciplinary sector: INFO-01/A Computer Science Research areas include: Edge and Fog Computing Automotive Cyber Security Security for Industry 4.0 Security for Machine Learning and Machine Learning for Security Applied Cryptography for Network and Information Security Luca is a core member of the SECloud (Security Edge and Cloud Lab) , which operates within the Department of Engineering 'Enzo Ferrari' and collaborates with the Interdepartmental Research Center on Security and Risk Prevention (CRIS). His recent publications highlight applications of adversarial AI, decentralized systems, and secure automotive communication protocols.

Mario BaldiView profile

Associate Professor

• Programmable data planes
• Software-defined networking
• Network security
• +5 more

Mario Baldi is an Associate Professor (on leave) of Information Processing Systems at the Department of Control and Computer Engineering , Politecnico di Torino , and concurrently a Fellow in the Office of the CTO, Adaptive and Embedded Computing Group, at AMD, San Jose, CA. His career blends deep academic research with extensive industry R&D leadership. Education M.Sc. (Summa Cum Laude) in Electrical Engineering, Politecnico di Torino, 1993 Ph.D. in Computer and System Engineering, Politecnico di Torino, 1998 Research Focus Baldi’s research spans programmable data planes, software-defined networking, big-data analytics for network management, network security, high-performance switching architectures, optical networking, QoS mechanisms, and multimedia/voice-over-IP systems . He is especially known for pioneering work on P4 -based programmable networks and SmartNIC architectures. Publication & Patent Impact Across 150+ refereed papers and 35+ US patents (plus European filings), his recent output concentrates on machine-learning-driven network data-plane functions , disaggregated stateful network services , and cloud-grade DPUs . The 2021–2024 articles emphasize real-time inference directly in the network data plane and modular SDN programming. Awards & Honors Best Paper Award, IEEE ICC 2007 Best Paper Award, IEEE ISCC 2008 Best Paper Award, IEEE GreenComm 2009 Best Paper Award, ACM/IEEE WI/IAT 2014 Grants & Projects Baldi has served as Principal Investigator or Scientific Coordinator on numerous EU Framework and Italian national projects (PRIN, FAR), leading consortia on energy-efficient packet networks, trusted software execution, wireless mesh architectures, and streaming media delivery. Teaching & Mentoring He has taught graduate courses on Enterprise Network Technologies, Computer Network Technologies and Services, Networks/Cloud/Application Security at Politecnico di Torino since 2003. He has also supervised PhD collegi for the Computer and Systems Engineering doctoral program (cycles 19–23) and held visiting/adjunct positions across four continents. Labs & Teams Previously headed the NetGroup (Computer Networks Group) at Politecnico di Torino (2001–2007) and co-chairs the p4.org Architecture Workgroup , driving open standards for programmable networking.

Hugo MoraisView profile

Research Fellow

• Renewable Energy
• Smart Grids
• Electric Vehicles
• +3 more

Hugo Morais is a Research Fellow at INESC-ID in Portugal, specializing in Smart Grids , Electric Vehicles , and Renewable Energy Systems . He leads major projects like InnoCyPES , nexIK , and EV4EU , focusing on cyber-physical energy systems, industrial kitchen energy optimization, and vehicle-to-grid (V2X) technologies. Supervises 7 PhD students in Electrical/Informatics Engineering Active in European energy conferences (CIRED, IEEE PES) Co-author of 15+ high-impact journal papers (2021-2025) Research Trends: Recent work emphasizes clustering for flexibility characterization , explainable AI in solar PV , digital substation security , and peer-to-peer energy markets with electric vehicles. His 2025 publications analyze grid investments, urban multi-energy systems, and industrial kitchen consumption patterns. Scientific Recognition: Ranked among Portugal's top Computer Science researchers (H-index >40, 2021) Organizer of Horizon Europe EV4EU project (2022) Advising: Supervises PhD candidates on topics including blockchain for energy flexibility, V2X business models, and AI-driven demand response. Formerly mentored Tiago Soares (DTU, 2017) and Paul Javal (EDF/ParisTech, 2021).

• Cybersecurity
• Cryptography
• Blockchain
• +3 more

Willy Susilo is a Professor and Australian Laureate Fellow at the School of Computing and Information Technology, University of Wollongong (UOW). As Head of School since 2015, he leads academic and research initiatives while maintaining active roles as Editor-in-Chief of Computers Standards and Interface and associate editor for IEEE journals. A Fellow of IEEE, IET, ACS, AAIA, and AIIA, he has received numerous accolades including the 2024 Premier's Prizes, 2023 ARC Laureate Fellowship, and UOW's Researcher of the Year (2016) and Supervisor of the Year (2019). Education : Ph.D. and M.Sc. in Computer Science (University of Wollongong, 2001), B.Sc. in Computer Engineering (University of Surabaya, 1994) His research focuses on cybersecurity and cryptography , particularly post-quantum cryptography, blockchain security, and privacy-preserving systems. Recent publications explore lattice-based encryption, federated learning privacy, and blockchain authentication mechanisms, reflecting trends in quantum-resistant algorithms and secure decentralized systems. Scientific Awards : ARC Laureate Fellowship (2023) Researcher of the Year (2016) Supervisor of the Year (2019) Vice Chancellor's Award for Global Strategy (2020) Premier's Prizes (2024) UOW Alumni Award (2024) He supervises multiple higher-degree research projects in areas like lattice reduction algorithms , deepfake detection , and blockchain regulation , and leads significant grants including the ARC-funded Secure Cloud Computing (2024-2029) and Enabling Anonymity for Blockchain (2020-2024). As director of the Institute of Cybersecurity and Cryptology (iC2), he oversees cutting-edge research infrastructure and collaborates across disciplines in AI security and satellite imaging applications.

Yingjie ChenView profile

Professor

• Virtual Reality
• Human-Computer Interaction
• AI in Computer Graphics
• +3 more

Yingjie Chen is a Professor at Purdue University's Purdue Polytechnic Institute, Department of Computer Graphics Technology. He holds a Ph.D. in Human-Computer Interaction from Simon Fraser University (2011), a Master of Science in Information Technology (2007), and a Bachelor of Engineering from Tsinghua University (1992). His research focuses on interdisciplinary domains including Virtual Reality, AI in Computer Graphics, Human-Computer Interaction, and Information Visualization. He has led multiple grants, including projects on VR training systems for Cryo-EM and precision medicine using Graph AI. Education: Ph.D., Human-Computer Interaction, Simon Fraser University (2011) M.Sc., Information Technology, Simon Fraser University (2007) B.Eng., Thermal Engineering, Tsinghua University (1992) Dr. Chen’s research emphasizes practical implementation and evaluation, blending theory with real-world applications. His work spans VR training systems, autonomous driving perception, and clinical decision support systems. Recent grants include funding for VR-based Cryo-EM training and AI in precision medicine. Research Interests: Virtual Reality (VR) System Design AI-Driven Computer Graphics Visual Analytics for Healthcare Human Factors in Autonomous Systems Grants & Awards: "Virtual Reality Augmented Hands-on Cryo-EM Training" (2020–2023) "Graph AI for Precision Medicine" (2021–2023) VAST Challenge Awards (2017, 2019) His lab, VA.Tech , develops innovative visual systems for interdisciplinary challenges. Collaborations span healthcare, transportation, and environmental science.