Find Academic Supervisors

• Nonlinear Control
• Adaptive Control
• Cyber-Physical-Human Systems
• +6 more

Kaiwen Chen is a Research Associate at the Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London. He holds a B.Sc. from the University of Illinois Urbana-Champaign and a B.Eng. from Harbin Institute of Technology, followed by M.Sc. and Ph.D. degrees from Imperial College London. His research focuses on nonlinear and adaptive control theory, particularly in time-varying systems, multi-agent systems, and applications in cyber-physical-human systems and soft robotics. He is affiliated with the Control and Power Research Group and the Hamlyn Centre for Robotic Surgery, contributing to advancements in medical robotics and resilient control systems. Dr. Chen’s work emphasizes adaptive control methodologies for uncertain systems, including robust designs for cyber-physical networks and surgical manipulators. He serves as an Associate Editor on the Conference Editorial Board of the European Control Association since 2022. His notable achievements include the 2023 IET Control and Automation Doctoral Dissertation Prize and the 2018 Hertha Ayrton Centenary Prize for academic excellence. His research portfolio spans theoretical control advancements and practical implementations, such as hybrid manipulators for gastrointestinal interventions and online data-driven adaptive control strategies. He actively explores interdisciplinary applications, integrating experimental robotics into remote teaching through platforms like quadrotor test-beds. Affiliations : Control and Power Research Group, Hamlyn Centre for Robotic Surgery, Mechatronics in Medicine Lab Editorial Role : Conference Editorial Board, European Control Association Key Contributions : Cyber-physical security, resilient control architectures, soft robotic systems

• Distributed Energy Resources
• Electric Power Distribution Systems
• Machine Learning
• +5 more

Daniel Arnold serves as an Adjunct Professor in the Department of Civil and Environmental Engineering within the College of Engineering at the University of California, Berkeley. He maintains a dual affiliation with Lawrence Berkeley National Laboratory (LBNL), where he conducts research within the Energy Storage & Distributed Resources Division's Grid Integration Group. His work bridges academic research with practical applications in power systems engineering. Arnold's educational background includes a Ph.D. in Mechanical Engineering from UC Berkeley (2015), an M.S. in Engineering Science from UC San Diego (2006), and a B.S. in Mechanical Engineering from UC San Diego (2005). This multidisciplinary foundation supports his research at the intersection of electrical engineering, control systems, and data science. His research focuses on developing innovative control strategies for managing distributed energy resources in electric power distribution systems, with particular emphasis on applying machine learning techniques to analyze high-resolution distribution system Phasor Measurement Unit (PMU) data. Arnold is recognized as an emerging leader in using modern data science tools, including artificial intelligence, machine learning, and control theory, to improve the stability and security of energy and power systems. His work addresses critical challenges in grid security, including developing algorithms to mitigate attacks or unintentional outages by enabling real-time control that utilizes non-compromised system components. Analysis of his publication record reveals a consistent focus on extremum seeking control applications for power systems, distributed energy resource management, and cybersecurity in grid operations. His research has evolved from foundational work on smart inverter control (2015) to increasingly sophisticated approaches integrating machine learning with power system operations and addressing cyber-physical security challenges. Arnold actively contributes to the professional community through service as a peer reviewer for leading journals, leadership of conference sessions, and participation in application-oriented workshops aimed at translating research into practical solutions. His work at Lawrence Berkeley National Laboratory complements his academic role, providing a platform for large-scale implementation of his research findings. His laboratory work primarily involves power hardware-in-the-loop testing and simulation of distribution systems, with applications focused on ensuring the security of distributed systems like home batteries and rooftop solar systems to prevent large-scale outages and blackouts. This research has significant implications for grid resilience in the face of increasing distributed energy resource penetration.

Michael BruenigView profile

Professor

• Robotics
• Cybersecurity
• Data Innovation
• +6 more

Professor Michael Bruenig is the Head of School for the School of Electrical Engineering and Computer Science (EECS) at The University of Queensland (UQ), a position he has held since 2016, with an interim role as Head of UQ’s Business School from 2019–2021. He previously led the CSIRO’s $140m National Research Flagship on Digital Productivity and co-founded Data61. With a PhD from RWTH Aachen University, his career spans automotive R&D in Germany, Silicon Valley, and Australia. He holds a Master’s and PhD in Science from RWTH Aachen University, Germany. His research focuses on strategic innovation, entrepreneurship, and translating research into industry impact through ventures like UQ Cyber, the National Industry 4.0 Energy Testlab, and the QLD Government AI Hub. He pioneered UQ’s Bachelor of Computer Science, Master of Cyber Security (based on US NICE Framework), and online Master of Business Analytics. His work spans robotics, sensor networks, and terahertz technology, with recent articles addressing lidar-based navigation, terahertz imaging, and cybersecurity. He advises startups and sits on boards, driving commercialization and spin-offs. Key initiatives include UQ Innovate and UQ Ventures, fostering student and faculty entrepreneurship. Labs and teams include collaborations on AI, Industry 4.0, and energy systems. His leadership emphasizes cross-disciplinary projects and curriculum innovation in tech and data fields.

Kevin LeachView profile

Assistant Professor

• Cybersecurity
• Software Engineering
• Dependable Systems
• +3 more

Kevin Leach is an Assistant Professor of Computer Science at Vanderbilt University's School of Engineering. His research focuses on designing dependable cybersecurity systems and software engineering practices that withstand sophisticated adversarial attacks. He holds a PhD from the University of Virginia (2016), where he received the Louis T Rader Outstanding Research Award. Prior to Vanderbilt, he was a research scientist and lecturer at the University of Michigan. Education: Ph.D. in Computer Engineering, University of Virginia MS in Computer Science, George Mason University BS with Distinction in Computer Engineering and Computer Science, University of Virginia His research investigates two core areas: leveraging hardware capabilities like Trusted Execution Environments for low-overhead security instrumentation, and understanding how developers and operators make decisions in adversarial environments. He has published over 30 refereed articles, 3 of which have received awards. Recent work includes studies on cognitive biases in cybersecurity competitions, AI-driven code assessment, and malware detection techniques. Awards: Louis T Rader Outstanding Research Award (2016) 3 award-winning papers (specific awards unspecified) His research bridges technical security mechanisms with human decision-making processes, emphasizing both system dependability and developer/operator awareness. Current projects include work on federated learning defenses, runtime security optimization for embedded systems, and ethical considerations in crowdsourced data labeling.

Sandeep K NeemaView profile

Professor

• Embedded Systems
• Design-Space Exploration
• Model Integrated Computing
• +3 more

Sandeep K Neema is a Professor of Computer Science and Electrical and Computer Engineering at Vanderbilt University's School of Engineering. He serves as Chair of the Executive Council of the Institute of Software Integrated Systems. His research focuses on embedded systems, design-space exploration, and model integrated computing. He holds a Ph.D. from Vanderbilt University, an M.S. from Utah State University, and a B.Tech. from the Indian Institute of Technology. Dr. Neema's educational background includes: Ph.D., Electrical Engineering & Computer Engineering, Vanderbilt University M.S., Electrical Engineering & Computer Engineering, Utah State University B.Tech., Electrical Engineering, Indian Institute of Technology His research interests encompass embedded systems, design-space exploration, and model integrated computing, with a strong emphasis on cyber-physical systems. He explores formal methods, model-based design, and their applications in automotive systems, smart cities, and reliability engineering. His work integrates theoretical frameworks with practical tools to address challenges in system reliability and adaptive software design. Recent publications highlight advancements in artificial general intelligence evaluation, cybersecurity defense mechanisms, and formal methods applied to neural networks and language models. His work also addresses societal-scale control systems and adaptive software frameworks for resource management. These contributions underscore his interdisciplinary approach to solving complex engineering problems. Scientific Awards include: Best Paper Award (2013) In addition to his academic roles, Dr. Neema leads initiatives in the Institute for Software-Integrated Systems. His work often involves collaborative projects and the development of innovative tools for cyber-physical systems design. He is a key member of the Institute for Software-Integrated Systems, contributing to research in model integration, tool development, and cyber-physical systems engineering.

Jules WhiteView profile

Professor

• Cybersecurity
• Mobile/Cloud Computing
• Cyber-physical Systems
• +3 more

Jules White is a Professor of Computer Science and Senior Advisor to the Chancellor for Generative AI in Education at Vanderbilt University's School of Engineering. He also holds an appointment as Associate Professor of Biomedical Informatics. His research focuses on cybersecurity, mobile/cloud computing, and cyber-physical systems. White has led the online MS in Computer Science program to #1 ranking by Fortune and commercialized research into industry products like PAR Works. Education: Ph.D./M.S. in Computer Science (Vanderbilt University), B.A. in Computer Science (Brown University). Research Interests: Cybersecurity, mobile computing, cyber-physical systems, healthcare informatics, and AI applications. His MAGNUM Group explores these areas with over 160 publications and industry collaborations. Articles Overview: Recent work spans AI-driven prompt engineering, healthcare transparency via NLP, and UAV design optimization. Themes include LLM applications, cybersecurity frameworks, and medical technology integration. Awards: NSF CAREER Award, CES Innovation Award (2013), and multiple best paper awards. Recognized for entrepreneurship with $12M venture funding for startups. Advising & Grants: Directed over 100 students in MOOCs and research. Secured grants totaling ~$1.5M annually, including NSF, AFRL, and industry partnerships. Focus areas include secure IoT systems and blockchain in healthcare. Labs & Teams: Directs the Mobile Application computinG, optimizatoN, and secUrity Methods (MAGNUM) Group. Collaborates with industry (e.g., Siemens, Cloudpoint/PAR Works) and government agencies (NSF, ARO).

Martin HochwallnerView profile

Associate Professor

• Industrial Automation
• Remanufacturing Processes
• Hydraulic Systems
• +3 more

Martin Hochwallner is an Associate Professor at Linköping University (LiU), affiliated with the Department of Management and Engineering (IEI) and the Division of Product Realisation (PROD) . His work focuses on advancing industrial automation, remanufacturing processes, and hydraulic systems through interdisciplinary research. Education & Affiliations: PhD in Mechatronics (assumed based on role) Member of Product Realisation division within IEI Active collaborator with industry through Vinnova-funded projects Research Interests: Dr. Hochwallner explores: - Automation in remanufacturing and repair processes - Advanced control systems for hydraulic actuators - Cyber-physical production systems integration - Process data analysis for industry optimization His work bridges theoretical models with practical industrial applications. Key Projects (2020-2023): HiValueMill : Extracting hidden values from paper mill process data MiKoVa 2022/2021 : Reducing process variations via thermal imaging fusion ARR : Automation for repair and remanufacturing (2018-2021) Advising & Grants: Supervises PhD student Anan Ashrabi Ananno Secured funding from Vinnova, LiU SEED programs Principal investigator in multiple industry-academia collaborations Labs & Teams: Active in PROD division labs focusing on: - Automation prototyping facilities - Hydraulic actuator testing environments - Cyber-physical systems integration platforms

Timothy Christian LethbridgeView profile

Professor

• Software Engineering
• Artificial Intelligence
• Machine Learning
• +3 more

Timothy Christian Lethbridge is a Professor of Software Engineering and Computer Science at the University of Ottawa, where he has held roles including Vice-Dean (Governance) and Acting Associate Dean. His research focuses on software engineering tools, model-driven development (notably the Umple project), and education. He earned his PhD in Computer Science from the University of Ottawa (1994) and earlier degrees from the University of New Brunswick. Research Interests: Complexity Reduction in Software Engineering Modeling Tools (e.g., Umple for state machines and class diagrams) Enterprise Architecture in Education Software Engineering Education Usability and Human-Computer Interaction in Software Tools Large Language Models in Assurance Cases Awards and Memberships: Fellow of the Canadian Information Processing Society (CIPS) Professional Engineer (P.Eng) Senior Member of IEEE and ACM Teaching and Students: Supervised over 30 graduate students, currently advising Abdulaziz Algablan, Aliaa Alghamdi, and Emmanuel Celestine Ayeleso. Teaches courses like Software Engineering Capstone (SEG4910/11) and Software Usability (CSI5122). Labs: Leads the CRuiSE Lab, focusing on software engineering and usability research.

• Cryptology
• Intrusion Detection Systems
• Wireless Communication Security

Slobodan Petrovic is a Professor at the Norwegian University of Science and Technology (NTNU) in the Department of Information Security and Communication Technology (IIK), part of the Faculty of Information Technology and Electrical Engineering. His research focuses on Cryptology, Intrusion Detection Systems, and Wireless Communication Security. He teaches Cryptology and Intrusion Detection and Prevention in NTNU's Master in Information Security (MIS) and PhD programs. He is a member of the Cryptology Research Group (Norwegian Applied Crypto Lab - NaCl Lab). His research interests span cryptographic algorithm design, cybersecurity threats in autonomous systems and 5G networks, and secure communication protocols. Recent work includes frameworks for nonlinear combiners in ternary logic, dynamic LFSR analysis, and physical-layer security in MIMO OFDM systems. Publications highlight trends in cybersecurity applications of computational intelligence, intrusion detection systems, and cryptographic analysis. Notable contributions include countermeasures for unmanned vehicles and secure guidance systems. He has been actively involved in developing algorithms for efficient data analysis in digital forensics and cybersecurity analytics. His lab, the NaCl Lab at NTNU, focuses on applied cryptographic solutions. He collaborates on projects related to secure network communication, biometric security, and true random number generation.

• Automotive Cybersecurity
• Formal Verification
• Autonomous Systems
• +2 more

Hoang Nguyen is an Associate Professor in Cyber Security at Swansea University with research focus on automotive and autonomous systems security. Research Focus: Specializes in model-based verification methods and simulation techniques for security validation of cyber-physical systems. Current projects include VRBMAS, ACID, Ditto, QRNG for CAV, Secure CAV, and AutoCHERI funded by EPSRC, RSSB, InnovateUK, and Digital Catapult. Publication Trends: Recent work centers on automotive cybersecurity frameworks, threat modeling for connected vehicles, and formal verification techniques. Contributions include simulation-based risk assessment, attack-defense tree generation, and secure communication protocols for vehicular platoons.

Hsieh, Sheng-JenView profile

Professor

• Automation and Robotics
• Infrared Imaging
• Non-destructive Testing and Evaluation
• +6 more

Professor Hsieh, Sheng-Jen holds a faculty position at Texas A&M University in the Department of Engineering Technology & Industrial Distribution, with affiliated roles in Electrical & Computer Engineering. He specializes in automation, robotics, infrared imaging, and smart system design. His research bridges engineering education and advanced manufacturing technologies, emphasizing Industry 4.0 applications and cyber-physical systems. Education includes a Ph.D. in Industrial Engineering from Texas Tech University (1995), M.S. from St. Mary's University (1989), and B.S. from National Taipei Institute of Technology (1982). He has received numerous accolades including the NSF CAREER Award, Halliburton Foundation Professorship, and multiple teaching awards. His research interests span additive manufacturing optimization, thermal stress prevention in 3D printing, and remote-access lab development for education. Key achievements include developing AI-driven systems for anomaly detection in motors and smart traffic light control algorithms. He actively contributes to educational outreach through low-cost automation kits and PLC training modules. Scientific contributions include over 100 publications, with recent work focusing on machine learning applications in manufacturing processes and educational technology innovations. He has advised multiple undergraduate research projects in mechatronics and robotic systems. Labs and collaborations involve experimental setups for thermal imaging analysis, automated material handling systems, and IoT-enabled HVAC control strategies. His work integrates cognitive task analysis to improve engineering education practices.

Zheng O'NeillView profile

Professor

• Building/HVAC&R Energy Efficiency
• Intelligent Building Controls
• Grid-Interactive Efficient Buildings
• +3 more

Dr. Zheng O'Neill is a Professor in the Department of Mechanical Engineering at Texas A&M University, holding the J. Mike Walker ’66 Professor II title. His research focuses on building energy efficiency, intelligent controls, and grid-interactive systems. He leads the Texas A&M Building Energy and HVAC&R Research Group, advancing sustainable building technologies. Education: Ph.D. in Mechanical Engineering from Oklahoma State University (2004), M.S. in Thermal Engineering from Tongji University (2000). Research Interests: Building/HVAC&R energy efficiency Intelligent building controls and optimization Grid-interactive efficient buildings Heat pump technologies Uncertainty quantification in building energy systems Well-being in the built environment Publications reflect a focus on cutting-edge topics like cyber-physical security, occupancy-centric controls, and AI-driven energy systems. Recent work emphasizes resilience, fault detection, and testbed development for smart buildings. Awards: Recognized as an IBPSA and ASHRAE Fellow (2021), recipient of multiple grants including Texas A&M’s Engineering Genesis Award (2020) and DOE-funded projects. His work bridges academia and industry, addressing global energy challenges. Grants and Collaborations: Active in NSF and DOE-funded initiatives, including the IN2WIBE network for well-being in buildings and the CYDRES project on cyber defense for grid systems. Collaborates with institutions like Pacific Northwest National Laboratory and Daikin. Labs/Teams: Maintains advanced facilities like the Smart and Connected Homes Testbed and the Water Source Heat Pump Testbed, enabling hardware-in-the-loop experiments and field demonstrations.

Alex SprintsonView profile

Professor

• Networking
• Network Coding
• Security and Privacy
• +4 more

Prof. Alex Sprintson is a Professor in the Department of Electrical and Computer Engineering at Texas A&M University, affiliated with the College of Engineering. He currently serves as a rotating Program Director at the NSF, managing networking research programs such as NeTS, SaTC, RINGS, and MLWiNS. His research focuses on algorithmic and information-theoretic aspects of networking, network coding, security, privacy, distributed storage systems, wireless communication, and software-defined networking. Sprintson holds a Ph.D., M.S., and B.S. in Electrical Engineering from Technion-Israel Institute of Technology (2003, 2001, 1995). His academic accolades include the Wolf Award, Viterbi Fellowship, TAMU Outstanding Contribution Award, and NSF CAREER Award. He has served on editorial boards (e.g., IEEE Transactions on Wireless Communications) and conference committees (e.g., IEEE Infocom). His work spans theoretical frameworks for secure communication, privacy-preserving protocols, and efficient distributed systems. Research highlights include pioneering contributions to private information retrieval, network coding applications, and coded computing. He leads projects on securing next-generation wireless networks and optimizing distributed storage systems. His NSF roles involve advancing research in machine learning for wireless systems and resilient cyber-physical infrastructure.

Moshe Y. VardiView profile

Professor

• Automated Reasoning
• Artificial Intelligence
• Computational Complexity Theory
• +4 more

Moshe Y. Vardi is a University Professor and the Karen Ostrum George Distinguished Service Professor in Computational Engineering at Rice University. He holds dual appointments in the Computer Science Department, the Ken Kennedy Institute for Information Technology, and is a Fellow for Science and Technology Policy at the Baker Institute. His research spans automated reasoning, computational complexity, formal verification, and the societal impact of technology. Education: PhD in Computer Science, Hebrew University of Jerusalem (1981) MSc in Computer Science, Weizmann Institute of Science (1980) BSc in Physics and Computer Science, Bar-Ilan University (1974) Research Interests: Moshe's work integrates theoretical foundations with practical applications. He pioneered advancements in automated reasoning, database theory, and formal verification. His recent focus includes the ethical implications of AI, technology governance, and the societal consequences of automation. He authored influential books like Reasoning About Knowledge and Finite Model Theory and Its Applications . Notable Achievements: Recipient of the Knuth Prize, ACM Allen Newell Award, and IEEE Norbert Wiener Award Member of the US National Academies of Sciences and Engineering Fellow of the ACM, AAAS, and numerous scientific societies Editor-in-Chief Emeritus of Communications of the ACM Lead the Rice Initiative on Technology, Culture, and Society Grants & Leadership: He directed Rice's Computer Science Department (1994–2002) and the Ken Kennedy Institute (2001–2019). His leadership spans interdisciplinary projects on AI ethics, tech policy, and resilience engineering. Current initiatives include postdoctoral programs in sociotechnical systems and global tech governance. Labs & Teams: He collaborates with the Ken Kennedy Institute, Baker Institute Policy Program, and leads the Technology Ethics Research Group at Rice. His lab focuses on formal methods, AI ethics, and societal impact analysis.

• Sensor Technologies
• Nanotechnology
• Nanomaterials
• +9 more

Dr. Ata Khalid is a Senior Lecturer in Sensors and Sensor Systems at Cranfield Defence and Security, part of Cranfield University and the Defence Academy of the UK. He leads the Electro-Optic and Autonomy Group and teaches the Electro-Optic & Infrared Systems module in the MSc Military Electronic Systems Engineering program. Research Interests: His expertise spans Sensor Technologies, Nanotechnology, Nanomaterials, Energy and the Environment, and advanced semiconductor devices for THz, mm-wave, and mid-IR applications. His work focuses on compound semiconductors, nanofabrication, and photonic systems with defense and security applications. Publication Trends: His recent publications (2015–2024) show a strong focus on planar Gunn diodes, resonant tunneling diodes, InSb-based infrared detectors, and monolithic integration for THz and mid-IR systems. Key themes include device modeling, thermal management, antenna integration, and miniaturized sensor development for imaging and detection. Scientific Leadership: He has been a Co-I on major projects including the EPSRC EP/H011862/1 and the €4M Horizon 2020 TeraApps project, demonstrating significant research funding and collaboration. Advising and Grants: He has supervised numerous MSc projects and currently mentors research students Reece Dillon and Noor Mohammadd. His leadership in the TeraApps and EPSRC projects highlights his role in securing and managing research grants. Labs and Teams: He leads the Electro-Optic and Autonomy Group at Cranfield Defence and Security, focusing on advanced electronic warfare, information, and cyber systems with experimental work in nanofabrication and device testing.