Find Academic Supervisors

• Ocean Renewable Energy
• Robotics
• Biomechanics
• +2 more

Dr. Boyin Ding is an Associate Professor at the University of Adelaide , serving as Academic Director at Haide College and researcher in the Mechanical Engineering department within the Faculty of Sciences, Engineering and Technology. He leads the Wave Energy Research initiative established in 2014, while also contributing to Robotics and Biomechanics through his work with the Flinders Medical Device Research Institute. Research Areas: Ocean Wave Energy Harvesting Control Systems for Renewable Energy 6DOF Robotic Testing Spine Biomechanics Transnational Education Programs Key Collaborations: Australia-China Joint Research Centre for Offshore Wind & Wave Energy Acoustics, Vibration and Control Research Group Scientific Awards: Australian Endeavour Fellowship Malcolm Kinnaird Engineering Excellence Award (2012) His recent publications focus on hybrid offshore energy systems, nonlinear hydrodynamics in wave energy converters, and biomechanical testing technologies. He has developed control algorithms for floating offshore wind-wave systems and pioneered 6DOF robotic platforms for medical applications. As an eligible PhD supervisor, he actively collaborates with global industries and academic institutions.

Vikram IyerView profile

Assistant Professor

• Robotics
• Ubiquitous Computing
• Sensing & Embedded Systems
• +7 more

Vikram Iyer is an Assistant Professor at the Paul G. Allen School of Computer Science and Engineering and holds an Adjunct Appointment in Mechanical Engineering at the University of Washington. He co-directs the CS for Environment Initiative , focusing on interdisciplinary solutions that bridge computing, biology, and physical systems for environmental sustainability. Education : Ph.D. in Electrical & Computer Engineering (University of Washington), B.S. in Electrical Engineering and Computer Sciences (UC Berkeley) Research Interests revolve around bio-inspired wireless systems , environmentally sustainable electronics , and miniaturized autonomous robotics . His work includes: Biodegradable circuit boards Battery-free wireless sensors Insect-scale vision systems Wind-dispersed environmental monitors AI tools for sustainable design Article Trends highlight contributions to green hardware , energy-autonomous robotics , and environmental sensing networks , often integrating machine learning with physical world interaction . Awards include: NSF CAREER Award SIGMOBILE Dissertation Award Marconi Society Paul Baran Young Scholar Best Paper Awards (SIGCOMM 2016, Sensys 2018) Google/Amazon Research Awards Students advised include Kyle Johnson (NSF Fellow), Vicente Arroyos (GEM Fellow), and Qiuyue Xue (co-advised with Shwetak Patel). His lab collaborates with the Networks & Mobile Systems Lab and Urban Innovation Initiative .

• Food Engineering
• Thermal Engineering
• Biophysics
• +3 more

Thijs Defraeye is a Senior Scientist at Empa (Swiss Federal Laboratories for Materials Science and Technology) and Adjunct Professor at Dalhousie University. He holds a PhD in Building Physics from KU Leuven (2011) and a Master's in Civil Engineering (2006). His work focuses on optimizing food supply chains through multiphysics simulations and digital twins, addressing challenges in refrigerated transport, postharvest quality preservation, and energy-efficient food processing. He leads the SimBioSys group, developing solutions for perishable goods logistics and electrohydrodynamic technologies. Research interests include: Biophysics of food systems Digital twin applications in agriculture Electrohydrodynamic drying Thermal management in cold chains Sustainable food technologies Recent work emphasizes reducing food loss through physics-based modeling of refrigerated containers, ventilated packaging optimization, and scalable evaporative cooling systems. His studies bridge engineering principles with biological processes, aiming to enhance global food security and environmental sustainability.

Guoquan HuangView profile

Assistant Professor

• Robotics
• Computer Vision
• Robot Learning
• +5 more

Guoquan Huang is an Assistant Professor in the Department of Mechanical Engineering at the University of Delaware. He holds a B.Eng. in Automation from the University of Science and Technology, Beijing (2002), and M.Sc. and Ph.D. degrees in Robotics from the University of Minnesota (2009 and 2012). Prior to his current role, he was a Postdoctoral Associate at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL). His research focuses on robotics, computer vision, and autonomous systems, emphasizing probabilistic perception, estimation, and control for ground, aerial, and underwater vehicles. He leads the development of the OpenVINS platform for visual-inertial estimation and has contributed to advancements in SLAM (Simultaneous Localization and Mapping), sensor fusion, and multi-robot coordination. Education: B.Eng in Automation (Electrical Engineering), University of Science and Technology, Beijing, 2002 M.Sc. in Robotics, University of Minnesota, Twin Cities, 2009 Ph.D. in Robotics, University of Minnesota, Twin Cities, 2012 His research interests span robotics, computer vision, and autonomous systems , with a focus on: Visual-inertial navigation and SLAM Sensor fusion (LiDAR, IMU, camera) Autonomous vehicle control and safety Multi-robot cooperative localization His recent publications (2023–2025) emphasize robust algorithms for navigation in GPS-denied environments, real-time sensor calibration, and dataset development for aerial visual localization. He has pioneered techniques like decoupled error-state estimation and consistent parallel frameworks for SLAM. Labs/Teams: Leads the development of the OpenVINS research platform, focusing on visual-inertial state estimation. Collaborates on projects involving human-swarm interactions and resilient ground vehicle navigation.

• Model-based Systems Engineering
• Safety-Critical Systems
• Systems Engineering
• +3 more

Dr. Siyuan Ji is a Reader in Model-based Systems Engineering (MBSE) at Loughborough University, serving as Deputy Head of the Manufacturing, Systems & Management Academic Community and Deputy Director of the Doctoral Training Centre in MBSE. He previously held a Senior Lecturer position in Systems Engineering at the University of York, where he led the MSc Programme in Safety-Critical Systems Engineering. His academic journey includes a PhD and MSc in Physics from the University of Nottingham, followed by research roles in model-based systems engineering at Loughborough University. His research focuses on advancing model-based techniques for systems engineering, particularly in safety-critical systems, formal methods, and complex system design. He has contributed to areas such as hazard management (e.g., BSafeML framework), response time analysis in real-time systems, and model synchronization for requirements engineering. His work bridges theoretical foundations with practical applications in automotive systems, embedded software, and educational technology. Dr. Ji holds the title of Fellow of the Higher Education Academy and has published extensively on topics ranging from quantum technology reporting to conversational tutoring systems. His research emphasizes interdisciplinary collaboration, evident in projects like the EPSRC-funded analysis of vehicles as complex systems. He actively contributes to both academic and industrial advancements in systems engineering methodologies and education innovation. His professional roles include managing doctoral training programs, overseeing academic communities, and advancing systems engineering education. Collaborations span industry partnerships and international academic networks, reflecting his commitment to impactful research and training the next generation of systems engineers.

Sharad MehrotraView profile

Professor

• Data Management
• Distributed Systems
• Database as a Service
• +7 more

Sharad Mehrotra is a Distinguished Professor at the University of California, Irvine (UCI), leading the Center for Emergency Response Technologies (CERT) and directing the NSF-funded RESCUE project. He previously served at the University of Illinois, Urbana-Champaign, and holds a Ph.D. from the University of Texas at Austin (1993). His research focuses on data management, IoT systems, privacy-preserving technologies, and smart spaces, with contributions to frameworks like TIPPERS and MARS. Education: Ph.D., Computer Science, University of Texas at Austin, 1993 Research Interests: His work bridges database systems, security, and IoT, emphasizing privacy in smart environments. Notable projects include sentient space technologies for disaster response, cryptographic methods for encrypted data queries, and semantic IoT integration. Recent efforts address privacy in multi-owner data systems and resilient community water infrastructure. Awards & Recognition: ACM Fellow (2024) SIGMOD Best Paper (2001), DASFAA Best Paper (2004) NAVWAR Innovation Award (2021) Outstanding Graduate Mentor (2005) Grants & Leadership: As RESCUE PI, he managed $12.5M NSF funding, developing crisis-response software deployed by emergency agencies. Collaborations include the Cal-IT2 institute (UCSD/UCI) and the US Navy’s TIPPERS platform. He co-leads initiatives like the NSF Civic Innovation Challenge for disaster resilience in aging communities. Labs & Teams: Directs UCI’s Information Systems Group and CERT, fostering interdisciplinary research with 60+ members. His teams produce open-source tools (e.g., SEMIoTIC, PrivacySphere) and engage in global partnerships via Fulbright Visiting Scholar programs.

• Robotics
• Artificial Intelligence
• Machine Learning
• +3 more

Dr. Danesh Tarapore is an Associate Professor at the University of Southampton specializing in robotics and AI. He focuses on human-robot interaction, swarm intelligence, and autonomous systems. His current research involves developing resilient robotic teams and optimizing learning algorithms for constrained environments. He supervises 6 PhD students in the iPhD MINDS and Computer Science programs. Dr. Tarapore's work bridges theoretical advancements with practical applications in autonomous navigation, multimodal dataset creation, and quality-diversity optimization. His publications span conferences like HRI and journals in robotics and AI. He collaborates with institutions like the University Hospital Southampton and the Boldrewood Innovation Campus. Research Interests: Human-robot collaboration, swarm systems, machine learning, and adaptive control Key Contributions: HRI-SENSE dataset, evolutionary subset selection algorithms, forest navigation frameworks Grants and Funding: Active projects in multi-agent systems and resilient robotics Dr. Tarapore maintains active roles in the robotics community through conference participation and interdisciplinary collaborations.

• Neural control of movement
• Infant development
• Motor control
• +5 more

Beth Smith, PT, DPT, PhD is an Associate Professor of Pediatrics and Biokinesiology & Physical Therapy at the University of Southern California. She directs the Infant Neuromotor Control Laboratory, where she leads research on neural control of movement during infancy and develops interventions for infants with or at risk for developmental delay. Dr. Smith's research focuses on several critical areas in pediatric development: Neural mechanisms underlying infant motor development Application of wearable sensor technology for objective movement measurement Early identification of developmental delays through quantitative analysis Evaluation of intervention effectiveness for at-risk infants Cross-cultural studies of infant development in diverse settings including rural Guatemala Her work demonstrates a strong integration of technology and clinical practice, with recent publications highlighting innovative approaches to measuring infant movement in natural environments. Dr. Smith's research on algorithmic detection of developmental disabilities using wearable sensors represents a significant advancement in early identification methods. Her studies on telehealth administration of developmental assessments have gained particular relevance following the COVID-19 pandemic, potentially expanding access to early intervention services globally. As director of the Infant Neuromotor Control Laboratory, Dr. Smith oversees a research program that bridges neuroscience, engineering, and clinical practice to improve outcomes for infants with developmental challenges. Her work has important implications for developing evidence-based interventions that can be implemented across diverse healthcare settings.

• Robotics
• Machine Learning
• Reinforcement Learning
• +3 more

Pawel Ladosz is a Lecturer in Engineering Systems for Robotics at the Department of Mechanical and Aerospace Engineering, The University of Manchester. His research focuses on applying machine learning and computer vision to mobile robots, particularly in extreme environments such as total darkness or cluttered spaces. He is actively involved in developing autonomous navigation systems, wireless signal mapping, and high-level decision-making for robotic swarms. He teaches courses including Robotic Systems Design Project and Autonomous Mobile Robots. Education: PhD in Establishing and Optimising Unmanned Airborne Relay Networks (Loughborough University, 2014–2019) MEng in Aerospace Engineering (The University of Manchester, 2010–2014) Research Interests: Ladosz’s work emphasizes reinforcement learning for robotics, vision-based autonomous systems, and exploration in challenging environments. His projects often intersect with UN Sustainable Development Goals, contributing to innovations in robotic autonomy and sensor networks. Awards: He received the 2nd Autonomous Flying Technology Competition award in 2021, recognizing his contributions to autonomous flight systems. His research has also led to the establishment of the Centre for Robotic Autonomy in Demanding and Long-Lasting Environments (CRADLE), fostering cross-disciplinary collaborations. Grants & Projects: As Principal Investigator in the Aerospace Engineering initiative (2010–2035), he explores UAV communication networks and trajectory planning. His work addresses urban environment challenges, including relay positioning and signal prediction. Labs/Teams: Ladosz contributes to CRADLE, advancing robotic autonomy in extreme scenarios. His lab focuses on integrating AI and robotics for real-world applications.

Shuangquan WangView profile

Assistant Professor

• Mobile & Wearable Computing
• Activity Recognition
• Smart Health
• +3 more

Shuangquan (Peter) Wang is an Assistant Professor of Computer Science at Salisbury University. He holds a PhD in Computer Science from the College of William & Mary (2020) and a PhD in Pattern Recognition and Intelligent Systems from Shanghai Jiao Tong University (2008), along with earlier degrees from Wuhan University of Technology and Wuhan Institute of Technology. His research focuses on mobile/wearable computing, activity recognition, smart health, and machine learning. He has over 10 years of experience in academia and industry, including roles at Philips Research East Asia and Nokia Research Center (Beijing). His work emphasizes wearable sensor-based health monitoring, such as fall detection, mastication analysis, and Parkinson’s disease monitoring. He leads the WISH Research Lab and serves as an Associate Editor for Elsevier's Smart Health Journal. Recent contributions include papers on salinity anomaly detection (2024), LLM-based user requirement analysis (2024), and socially acceptable food recognition (2022). His research trends emphasize interdisciplinary applications of machine learning in healthcare and sensor-driven human activity analysis. Professional service roles include coordinating Salisbury University’s Center for Applied Mathematics and Science (2021–2024) and chairing ACM/IEEE CHASE conferences. He has delivered invited talks on artificial intelligence and its societal impacts to diverse audiences, including the Institute of Retired Persons at Salisbury University. His lab, WISH Research Lab, explores innovative solutions in smart health and mobile computing, integrating wearable technologies with machine learning for real-world health applications.

• Computer Science
• Electrical Engineering
• Signal Processing
• +3 more

Guo Li is affiliated with the Beijing Institute of Technology, School of Management and Economics. Their research spans computer vision, optimization algorithms, signal processing, and machine learning. Collaborations include work on image super-resolution, sensor networks, and energy systems. Publications are distributed across journals like Comput. Electron. Agric. , IEEE Trans. Circuits Syst. , and Entropy . Research interests focus on computational methods for image processing, algorithm design, and interdisciplinary applications in agriculture and energy. Recent work emphasizes lightweight neural network architectures, sparrow search algorithms, and thermodynamic modeling in materials science. Notable contributions include advancements in citrus fruit detection, fatigue life assessment of superalloys, and load forecasting techniques. Active in international conferences such as CVPR, ICC, and NSDI, with a strong publication record since 1998.

Marjan AlaviView profile

Assistant Professor

• Fault Diagnosis
• Prognosis
• Power Electronics
• +3 more

Dr. Marjan Alavi is an Assistant Professor at McMaster University's W Booth School of Engineering Practice and Technology, affiliated with the Mechanical Engineering department as an Associate Member. She holds a Professional Engineer (P.Eng.) license in Ontario and has over 15 years of academic and industrial experience in electrical engineering. Her research focuses on model-based and data-driven approaches for fault diagnosis, prognosis, and fault-tolerant control in hybrid systems, with applications in power electronics, energy systems, and smart infrastructure. Education: B.Sc. (2004) from K.N. Toosi University of Technology, M.Sc. (2007) from Sharif University of Technology, Ph.D. (2014) from Nanyang Technological University (Singapore), and a Postdoc (2015) at the University of Toronto's Energy Systems Group. Teaching: Instructs courses on Real-Time Systems (SEP 6ES3, SFWRTECH 4ES3), Smart Cities and Communities (SMRTTECH 4SC3), integrating real-world engineering challenges with theoretical frameworks. She emphasizes hands-on learning through remote labs and experiential projects. Professional Contributions: Serves as IEEE Toronto Section Executive Member, Technical Reviewer for IEEE Transactions on Industrial Electronics, and Vice Chair of IEEE Industrial Applications Society (2015). Founded Intelligent Diagnosis Corporations, a Canadian startup focused on research and innovation in diagnostics technologies. Key Projects: Developed fault diagnosis strategies for electro-hydraulic actuators, vehicle-mounted infrastructure monitoring systems, and remote laboratory platforms for emergency traffic control. Research spans predictive maintenance, smart city technologies, and railway systems certification benefits. Awards: Recipient of the Singapore International Graduate Award (SINGA) 2010. Recognized for her work in bridging academic research with industrial applications, particularly in enhancing system reliability through advanced control methodologies.

Dimitra GeorgiadouView profile

Associate Professor

• Flexible Nanoelectronics
• Green Manufacturing
• Neuromorphic Computing
• +3 more

Dr Dimitra Georgiadou is an Associate Professor at the University of Southampton's School of Electronics and Computer Science, leading the Flexible Nanoelectronics Lab. She is a UKRI Future Leaders Fellow and serves as Deputy Impact Champion in the UKRI Centre for Doctoral Training in Machine Intelligence for Nanoelectronic Devices and Systems (MINDS-CDT). Her research focuses on green manufacturing of flexible nanoelectronics, photonic synapses for neuromorphic computing, and solution-processed non-toxic materials. Key projects include developing Pb-free perovskite photoelectric memristors and radiofrequency Schottky diodes for IoT applications. Education: PhD in Chemical Engineering/Organic Electronics from the National Technical University of Athens (NTUA). Prior roles include Industrial Fellow at Imperial College London and Marie Skłodowska-Curie Fellow. Research spans nanoscale optoelectronic devices, energy harvesting, and flexible substrates. Publications highlight advancements in photodetectors, memristors, and neuromorphic systems, with recent work on self-powered organic photodetectors and γ-ray-induced memristor effects. She has over 40 peer-reviewed articles, including in Laser & Photonics Reviews , Optica , and Advanced Electronic Materials . External roles include editorial positions at Frontiers in Nanotechnology and IEEE Sensors Letters , and membership in the EPSRC Peer Review College. She actively participates in conferences, delivering invited talks on nanosciences, flexible electronics, and neuromorphic devices.

Soufiene DjahelView profile

Professor

• Connected and Autonomous Vehicles (CAVs)
• Unmanned Aerial Vehicles (UAVs)
• Cyber Security
• +7 more

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.

Omprakash GnawaliView profile

Associate Professor

• Internet of Things
• Smart Devices
• Wireless Sensor Networks
• +3 more

Omprakash Gnawali is an Associate Professor in the Department of Computer Science at the University of Houston, with expertise in Internet of Things, wireless sensor networks, and artificial intelligence. His research focuses on advanced networking protocols, mobility analysis, and safety monitoring systems. Postdoctoral work at Stanford University PhD in Computer Science from University of Southern California Masters and Bachelors from Massachusetts Institute of Technology His research interests include Ultra-Wideband (UWB) localization, network protocol design, edge computing for monitoring systems, and mobile sensor networks. He leads the Networked Systems Laboratory , where he develops frameworks like the Collection Tree Protocol and CodeDrip for efficient data dissemination. Recent publications highlight trends in UWB-based safety monitoring, routing optimization in dual-radio networks, and deception detection in cybersecurity. He has secured NSF Student Travel Grants for ACM SenSys conferences in 2016 and 2017. Scientific Awards NSF Student Travel Grant (2017) NSF Student Travel Grant (2016) He actively mentors students in research projects and teaches courses such as Research Methods in Computer Science and Computer Networks . His service roles include Technical Program Committee memberships and chairing the TinyOS Network Protocol Working Group.