Find Academic Supervisors

Hamed BadihiView profile

Assistant Professor

• Condition Monitoring
• Fault-Tolerant Control
• Attack-Resilient Control
• +3 more

Hamed Badihi is an Assistant Professor in Automation Technology and Dependable Systems at Tampere University , part of the Faculty of Engineering and Natural Sciences. He leads the Dependability and Automation Research in Cyber-Physical Systems (DARES) Group within the Dependable Systems Cyber Laboratories . His research focuses on critical aspects of condition monitoring, fault-tolerant control, and attack-resilient control to advance sustainable, dependable cyber-physical systems. Research Interests include: Cybersecurity for industrial control systems Fault-tolerant control mechanisms Resilient control strategies for renewable energy systems Condition monitoring of wind turbines and microgrids Recent Contributions emphasize hybrid approaches combining machine learning and control theory for cyber-attack detection and system resilience in wind farms and microgrids. His work addresses challenges like real-time fault diagnosis and adaptive control under adversarial or environmental perturbations. Awards & Roles : Senior Member of IEEE, editor for International Transactions on Electrical Energy Systems , Advances in Fuzzy Systems , and Processes journals. Active in EU projects like StreamSTEP . Labs & Teams : Directs the DARES Group, collaborating on initiatives like the Dependable Systems Cyber Laboratories to pioneer innovations in cyber-physical system dependability.

Nikhil ChopraView profile

Professor

• Nonlinear control
• Robotics
• Control Systems
• +5 more

Dr. Nikhil Chopra is a Professor in the Department of Mechanical Engineering at the University of Maryland, College Park, with affiliate appointments in Electrical and Computer Engineering. He earned his Bachelor of Technology from IIT Kharagpur (2001) and his M.S. and Ph.D. from University of Illinois at Urbana-Champaign (2003, 2006). As Director of Undergraduate Studies, he leads academic programs while advancing research in systems, control, and robotics. His work focuses on robotic system control, soft robotics, teleoperation, and machine learning integration. Research highlights include co-authoring the book *Passivity-Based Control and Estimation in Networked Robotics* (2015), co-chairing the IEEE Technical Committee on Telerobotics, and serving as Associate Editor for *Automatica* and related journals. His lab, the Semi-Autonomous Systems Lab, explores control-theoretic frameworks for robotics and optimization, collaborating with institutions like Sintef and IEEE RAS Technical Committees. Key projects involve underwater robotics navigation, cyber-physical system privacy, and distributed optimization algorithms. His team has exhibited strong presence at ICRA and IROS conferences, including awards for work on 3D water quality mapping and control frameworks. Current initiatives include robotic parasitic arrays for communication enhancement and secure bilateral teleoperation systems. Lab: Semi-Autonomous Systems Lab (SAS Lab) Affiliations: Institute for Systems Research, Maryland Robotics Center Recent Funding: NSF grants, industry partnerships

Brett HarrisView profile

Professor

• Geophysics
• Hydrogeology
• Mineral Exploration
• +4 more

Professor Brett Harris is a faculty member at Curtin University, affiliated with the School of Earth and Planetary Sciences (EPS) within the Faculty of Science and Engineering. He holds a prominent role in the Office of the Provost. His research focuses on subsurface resource technologies, including mineral exploration, CO2 sequestration, and geothermal energy. He has led major initiatives like the DET CRC and MinEx CRC projects, advancing in-hole electromagnetic sensing and distributed acoustic sensing techniques. His expertise spans hydrogeology, geophysics, and environmental geoscience, with notable contributions to aquifer characterization, fault zone dynamics, and CO2 storage monitoring. He coordinates undergraduate courses in electromagnetism, potential fields, and environmental geophysics, while supervising multiple PhD students. Key collaborations include work with government agencies on fractured aquifer detection and geothermal systems. Recent research emphasizes innovative sensor technologies for subsurface imaging, CO2 leakage monitoring, and groundwater sustainability. His work bridges geophysics with applied engineering solutions for resource exploration and environmental stewardship.

Maozhen LiView profile

Professor

• High Performance Computing
• Big Data Analytics
• Artificial Intelligence
• +13 more

Maozhen Li is a Professor in the Department of Electronic and Electrical Engineering at Brunel University of London , within the College of Engineering, Design and Physical Sciences . He serves as the Vice-Dean of the NCUT Transnational Education (TNE) programme, overseeing a joint school with North China University of Technology. He has been at Brunel since 2002, progressing from Lecturer to Professor in 2013. Education: PhD, Institute of Software, Chinese Academy of Sciences (1997) Postdoctoral Research, School of Computer Science and Informatics, Cardiff University (1999–2002) His primary research interests lie in high performance computing, big data analytics, and artificial intelligence, with applications in smart grids, smart manufacturing, and cybersecurity. He focuses on developing interpretable, robust, and lightweight AI models, including work in causal AI, parallel machine learning, and edge computing. His research integrates advanced techniques such as deep learning, reinforcement learning, and blockchain for real-world system optimization. An analysis of his recent publications reveals a strong and consistent research trajectory in AI-driven solutions for environmental monitoring (e.g., PM2.5 prediction), industrial defect detection, IoT security, and intelligent transportation. His work frequently combines deep learning with graph-based modeling and federated or reinforcement learning, emphasizing scalability, efficiency, and robustness in distributed and edge environments. Scientific Awards and Recognition: Fellow of the Institution of Engineering and Technology (IET) Fellow of the British Computer Society (BCS) Shortlisted for the Computing UK BIG DATA EXCELLENCE AWARDS 2018 in the category of Most Innovative Big Data Solution Maozhen Li has successfully supervised 25 PhD students and examined over 30 PhD theses externally. He has secured significant research funding from EPSRC, the European Union (Horizon 2020), Innovate UK, and the Royal Society , with projects including Z-BRE4K, IoRL, and TDX-ASSIST. He serves as an Associate Editor for journals such as the Journal of Cloud Computing and the International Journal of Grid and High Performance Computing . Research Groups and Teams: He is affiliated with the Intelligent Engineering Frameworks (IEF) research group at Brunel, contributing to collaborative efforts in AI, IoT, and smart systems. His leadership in transnational education also fosters international research collaboration between Brunel and Chinese institutions.

Srishti BanerjiView profile

Assistant Professor

• Construction Materials
• Structural Fire Engineering
• Sustainable Infrastructure
• +4 more

Dr. Srishti Banerji is an Assistant Professor in the Department of Civil and Environmental Engineering at Utah State University and Director of the Systems, Materials, and Structural Health (SMASH) Lab. She leads research on advanced construction materials, structural resilience under extreme loads (particularly fire), sustainable infrastructure, and structural health monitoring. Her group focuses on experimental testing, numerical simulations, and developing design solutions for civil infrastructure. Education: PhD in Civil (Structural) Engineering, Michigan State University (2021) MS in Civil (Structural) Engineering, Concordia University (2016) BS in Civil Engineering, National Institute of Technology Silchar (2013) Research Focus: Her work spans: 1) Characterization of high-performance/sustainable materials (e.g., UHPC, recycled glass pozzolan), 2) Structural behavior under fire exposure, 3) Integration of electric charging systems in concrete pavements, 4) Non-destructive testing and structural health monitoring, and 5) Retrofitting techniques for infrastructure strengthening. She employs machine learning, thermo-mechanical modeling, and full-scale experimentation. Publication Trends: Her 13+ journal articles primarily analyze fire resistance of concrete/timber structures, UHPC material properties at high temperatures, sensor-based infrastructure monitoring, and sustainable material development. Recent works increasingly incorporate machine learning and electrification concepts. Awards & Honors: Teacher of the Year (USU, 2025) ASCE ExCEEd Faculty Teaching Fellowship (2023) Top Cited Article Award, Fire and Materials Journal (2023) SHMII-11 Early Career Grant (2022) NSERC Scholarship (2015) Best Conference Paper (SEC 2016) Current Projects & Teams: She leads 5+ funded projects including fire performance of polymer concrete, self-healing concrete for bridges, and Utah-sourced UHPC development. Mentees include 3 PhD students (Abdullah Al Sarfin, Mehrnoosh Nazari, Mahmoud Ali) and alumni working on sustainable materials and additive manufacturing.

• Cybersecurity
• Networking
• Wireless Security
• +6 more

Thaier Hayajneh , Ph.D., is a University Professor at Fordham University's Department of Computer and Information Sciences. He serves as Founder Director of the Fordham Center for Cybersecurity and Program Director for the MS in Cybersecurity program. Previously, he held academic roles at New York Institute of Technology and Hashemite University in Jordan. Specializes in cybersecurity, networking, and applied cryptography Focus areas include blockchain, IoT security, and wireless network vulnerabilities Active in NSF cybersecurity review panels and as a CAE reviewer for NSA Recipient of peer-review awards from Publons His research spans secure protocols for medical IoT systems, lightweight cryptographic algorithms, and smart contract implementations in healthcare. Publications in IEEE IoT Journal, IEEE Systems Journal, and Journals like Future Generation Computer Systems demonstrate his expertise in securing emerging technologies. Dr. Hayajneh has received research funding from federal agencies including NSA, Department of Defense, and NSF. He has published over 80 papers and maintains active editorial roles in prestigious journals. Scientific Awards: Peer-review awards from Publons

• Internet of Things
• Edge Computing
• Artificial Intelligence
• +6 more

Professor Xiaodong Liu is a faculty member at Edinburgh Napier University, affiliated with the School of Computing, Engineering and the Built Environment . His research spans Internet of Things , Edge Computing , Artificial Intelligence , and Cybersecurity , with a focus on decentralized systems and data-driven decision-making. Research Themes : IoT orchestration, federated learning, smart city infrastructure, building maintenance optimization, and automotive cybersecurity. Current Projects : Leading Swarmchestrate (EU-funded), Long-range Perceptive Autonomous Vehicles (Royal Society), and Met-Bot for Disaster Surveillance (Royal Society). His recent publications emphasize privacy-preserving edge learning , semantic IoT data validation , and deep learning for weather prediction . As a supervisor, he has guided PhD students in areas like federated learning, smart building systems, and IoT security. Collaborations include partnerships with institutions in Scotland, China, and Italy, alongside funding from European Commission , Royal Society , and Scottish Funding Council . He contributes to international conferences and journals, with notable work in IEEE Transactions , ACM TAAS , and MDPI publications.

David C MohrView profile

Professor

• Digital Mental Health
• Behavioral Intervention Technologies
• User-Centered Design
• +3 more

Dr. David C Mohr is a Professor at Northwestern University Feinberg School of Medicine, holding joint appointments in Preventive Medicine, Medical Social Sciences, and Psychiatry. He serves as Director of the Center for Behavioral Intervention Technologies (CBITs) and Chief of Behavioral Medicine in the Department of Preventive Medicine. With a PhD in Clinical Psychology from the University of Arizona (1991), he transitioned from UCSF to Northwestern in 2006. His research focuses on designing digital mental health interventions leveraging user-centered design and smartphone sensor data. Notable contributions include developing smartphone apps for depression/anxiety management and pioneering implementation strategies for scalable digital mental health solutions. He has led over 400 publications, with recent work emphasizing AI ethics, wearable sensing, and healthcare workforce burnout. Education: BA: University of California, Berkeley (1980) MA/PhD: University of Arizona (1988/1991) Affiliations: Center for Behavioral Intervention Technologies (CBITs) Institute for Augmented Intelligence in Medicine Robert H. Lurie Comprehensive Cancer Center Dr. Mohr’s honors include APA and Society for Behavioral Medicine Fellowships. He advises global initiatives like ImplMentAll (EU-funded) and chairs the Society for Digital Mental Health. His work bridges clinical innovation with real-world implementation, emphasizing equity and sustainability in digital health solutions.

Jyoti SinhaView profile

Professor

• Vibration Analysis
• Condition Monitoring
• Rotating Machinery
• +7 more

Jyoti Sinha is a Professor of Condition Monitoring and Plant Maintenance in the Mechanical and Aerospace Engineering department. He has extensive experience in vibration analysis, structural dynamics, and plant reliability. His research focuses on experimental and analytical techniques for fault diagnosis, rotating machinery health monitoring, and maintenance optimization. He has authored over 300 technical papers and serves as Editor-in-Chief of Maintenance, Reliability and Condition Monitoring (MARC) . Education: Ph.D. (Rotor Dynamics), University of Wales Swansea (2002) M.Tech. (Aerospace Engineering), IIT Bombay (1998) B.Sc. (Mechanical Engineering), Ranchi University (1988) Research Interests: Vibration-based condition monitoring Rotors and bearings fault detection Finite element modeling and model updating Asset management and Industry 4.0 integration Structural health monitoring Awards: Boyscast Fellowship (1999) Excellence awards for supervision (2012, 2014) 3rd Best Paper Award (2024) Advising & Grants: Supervising 10 PhD and 2 DProf students Completed 17 PhD and 325+ PG projects Secured £3M+ in research grants Labs & Teams: Head of Dynamics Laboratory Chair of International Conference on Maintenance Engineering (IncoME)

• Soft Robotics
• Microfluidics
• Nanofabrication
• +3 more

Ramses Martinez is an Assistant Professor in the Department of Industrial Engineering and Biomedical Engineering at Purdue University . He holds a B.A. in Applied Physics from Universidad Autonoma de Madrid (2004) and a Ph.D. in Physics and Materials Science from the Spanish National Research Council (CSIC) in 2009. Prior to joining Purdue, he conducted postdoctoral research in the lab of Prof. George M. Whitesides at Harvard University, focusing on nanofabrication, microfluidics, and soft robotics. Education B.A. in Applied Physics, Universidad Autonoma de Madrid (2004) Ph.D. in Physics and Materials Science, Spanish National Research Council (CSIC) (2009) His research bridges soft robotics , flexible electronics , and nanofabrication , with a focus on creating self-powered e-textiles , omniphobic paper-based devices , and programmable mechanical metamaterials . His work has led to over 25 publications and 9 patents, emphasizing practical applications in health monitoring and industrial automation . Notable projects include waterproof electronic decals for biofluid monitoring, smart bandages for chronic wound detection, and laser nanoforming methods for scalable metallic structures. His research has been recognized through the Fulbright Fellowship and the Marie Curie IOF Grant .

• Analytical Chemistry
• Materials Science
• Electrochemistry
• +4 more

Zekra Mousavi is a Senior Researcher at the Faculty of Science and Engineering , Åbo Akademi University , affiliated with the Laboratory of Molecular Science and Engineering . Her research focuses on analytical chemistry , materials science , and electrochemical sensor development . Key areas include ion-selective electrodes , lignin-based sustainable materials , and non-invasive chemical sensing . Her recent publications highlight advancements in solid-contact ion-selective electrodes , lignin fractionation for porous carbon , and wearable sensor technology . These works span electrochemistry , green chemistry , and biomedical applications . At the institutional level, her work contributes to the UN Sustainable Development Goals , particularly in health-related solutions and environmentally sustainable technologies . She collaborates with researchers in electrochemistry and materials science , with a focus on dielectric spectroscopy and solid-state sensors .

• Water resources engineering
• Surface water hydrology
• Data science
• +7 more

Jeff Sadler is an Assistant Professor in the Department of Biosystems & Agricultural Engineering at Oklahoma State University, where he also serves as an Extension Specialist for Water Resources with OSU Extension. He leads the WaDE (Water Data and Education) Lab, focusing on data science and machine learning applications in water resources. Education: PhD in Civil and Environmental Engineering, University of Virginia (2019) MS in Civil Engineering, Brigham Young University (2015) BS in Civil Engineering, Brigham Young University (2013) Research Interests: Jeff’s research lies at the intersection of data science and water resources. He specializes in machine learning, particularly physics-guided and process-aware deep learning, for modeling stream temperature, water quality, flood dynamics, and hydrological forecasting. His work emphasizes real-time decision support, reproducible modeling, and integrating domain knowledge into data-driven systems. Recent Research Trends: His recent publications demonstrate a strong focus on advanced deep learning architectures (e.g., graph neural networks, recurrent models), data assimilation, multi-task learning, and surrogate modeling for environmental systems. Applications center on the Delaware River Basin and coastal Virginia, with implications for climate change adaptation and infrastructure resilience. Scientific Awards: No awards explicitly listed in the provided text. Advising and Grants: Jeff mentors graduate students and supervises master's and doctoral research. He is actively funded through multiple grants from the USDA, NOAA, and USGS, supporting projects in water quality monitoring, rural health, evapotranspiration forecasting, and integrated hydrological modeling. Labs and Teams: He leads the WaDE Lab, which develops data-driven tools for water resource education and management. He has collaborated extensively with researchers from the U.S. Geological Survey, University of Virginia, and other institutions on cyberinfrastructure, reproducible modeling, and environmental machine learning.

Kevin K. LehmannView profile

Professor

• Molecular Spectroscopy
• Ultrasensitive Detection
• Cavity Ring-Down Spectroscopy
• +12 more

Kevin K. Lehmann is the William R. Kenan, Jr., Professor of Chemistry at the University of Virginia, within the Department of Chemistry in the College of Arts & Sciences. He is a leading researcher in molecular spectroscopy, with a focus on ultrasensitive detection methods such as cavity ring-down spectroscopy (CRDS) and double-resonance techniques. His educational background includes a B.S. from Cook College, Rutgers University (1977), a Ph.D. from Harvard University (1983), and a Junior Fellowship at the Harvard Society of Fellows. Lehmann's research is centered on advancing trace gas sensing using optical methods, particularly CRDS with high-reflectivity cavities and telecom-grade lasers. His group has pioneered Doppler-free two-photon CRDS and sub-Doppler double-resonance spectroscopy using frequency combs, enabling high-precision measurement of molecular transitions in gases like methane and nitrous oxide. These methods have applications in atmospheric science, planetary exploration (e.g., Mars missions), and combustion diagnostics. He also investigates meta-science questions around the reproducibility of spectroscopic data. The recent publications highlight a strong trend in high-resolution, quantum-limited spectroscopic techniques applied to small polyatomic molecules. There is a clear focus on enhancing selectivity and sensitivity through nonlinear optical effects, cavity enhancement, and advanced detection schemes. Applications span environmental monitoring, astrochemistry, and fundamental molecular physics. Fellow of the Optical Society, 2011 W.R. Kenan Professor of Chemistry, 2009 Earle K. Plyler Award in Molecular Spectroscopy, 2003 Thomas A. Edison Patent Award, 2002 Fellow of the American Physical Society, 1995 Lehmann has advised numerous graduate students and postdoctoral researchers, and his lab has been supported by grants from agencies involved in space exploration, environmental science, and fundamental physics. His work has led to commercial instrumentation through Tiger Optics, Inc. He maintains strong international collaborations, particularly with researchers in Sweden on methane spectroscopy. While specific grant details are not listed, the scope and impact of his research suggest sustained funding from NSF, NASA, and DOE. His laboratory focuses on optical cavity-based sensors and high-resolution spectroscopy setups, integrating frequency combs, narrow-linewidth lasers, and cryogenic pre-concentration systems for trace analysis. The team combines experimental innovation with theoretical modeling to interpret complex spectra and improve measurement fidelity.

Fendy SantosoView profile

Researcher

• Cybersecurity
• Artificial Intelligence
• Autonomous Systems
• +12 more

Dr. Fendy Santoso is a leading researcher and Cyber-Physical Lead at the Artificial Intelligence and Cyber Futures Institute, Charles Sturt University, Australia. He also holds a Visiting Fellow position at the School of Engineering and Technology, UNSW Canberra, and has held visiting roles at the University of Cambridge and Cranfield University. His work bridges cybersecurity, AI, and autonomous systems, with significant impact in UAV security and cyber-physical resilience. Education: PhD in Electrical Engineering, University of New South Wales (Awarded: 21 Jun 2012) Master of Electrical and Computer Systems Engineering, Monash University (Awarded: 07 Jun 2007) Dr. Santoso’s research focuses on adversarial machine learning, UAV security, intrusion detection in robotic systems, and cyber-secure digital twins. His work integrates AI, control theory, and cybersecurity to enhance the resilience of autonomous systems. He has pioneered research in securing ROS-based platforms and defending against GPS spoofing and DoS attacks in unmanned vehicles. His recent publications (2020–2025) highlight a strong trend in applying deep learning, fuzzy logic, and physics-informed models to detect and mitigate cyberattacks in UAVs and UGVs. Key themes include intrusion detection systems, secure digital twins for agriculture, and intelligent transportation systems enabled by drones. His work is frequently published in IEEE Transactions and top-tier conferences. Scientific Awards and Grants: Vice-Chancellor’s Distinguished Early Career Travel Fellowship, University of Wollongong (2019) ARC Linkage Project Grant (LP230100083) on adversarial machine learning for UAVs (2024) CSIRO-funded AgriTwins project on cyber-secure digital twins for agriculture (2024) Dr. Santoso has secured over AUD 3 million in competitive research funding and actively supervises postgraduate students. He serves as a reviewer for the Australian Research Council and technical program committees of major AI and engineering conferences. His collaborative work spans defence organisations like DSTG and the U.S. Army Ground Vehicle Systems Centre, as well as international academic institutions. He is a Senior Member of IEEE and leads research in labs focused on cyber-physical systems, autonomous robotics, and AI-driven security frameworks. His team develops real-time detection tools for cyberattacks on military and agricultural robots, contributing to critical infrastructure resilience.

David W. EvansView profile

Assistant Professor

• Musculoskeletal Pain
• Low Back Pain
• Pain Measurement and Disability
• +7 more

Dr David W. Evans is an Assistant Professor in Musculoskeletal Health Care at the School of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, where he has been a faculty member since 2017. He serves as Programme Lead for the MSc Physiotherapy (pre-registration) programme and teaches across multiple physiotherapy degrees including MSci and MSc programmes. Education: PhD in Low Back Pain, Keele University (2007) BSc (Hons) in Osteopathy, Health Sciences University (formerly British School of Osteopathy), London (1998) His research focuses on understanding and measuring disabling musculoskeletal pain, particularly low back pain, with an emphasis on improving patient outcomes through better treatment matching. His work spans pain mechanisms, measurement of disability, and the effectiveness of physical interventions. He has maintained a clinical practice in musculoskeletal health since 1998. Dr Evans's recent publications (2022–2025) reflect a strong trend in quantitative and clinical research, utilizing wearable technology for lumbar mobility assessment, analyzing pain drawings and spatial pain patterns, and investigating psychological factors such as fear of movement. His work integrates biomechanics, neuroscience, and clinical rehabilitation, often through large-scale studies and systematic reviews. He has also contributed to advancing definitions and educational approaches in manual therapy. Professional Memberships and Roles: Member, Society for Back Pain Research (since 2001) Lead, Pain-focused PPIE Group (since 2021) Member, University of Birmingham REDCap Committee (since 2022) Dr Evans has secured over £2 million in research funding as lead or co-applicant and has published over 50 peer-reviewed papers. He is actively involved in research leadership and has contributed to major clinical trial protocols and systematic reviews in pain and rehabilitation. He is affiliated with research platforms including ORCID, Google Scholar, and ResearchGate, and his work is supported by institutional and national research infrastructures. He coaches javelin throwing at a local athletics club, reflecting a personal commitment to physical activity and sports.