Find Academic Supervisors

• Biomedical Engineering
• Electrical Impedance Tomography (EIT)
• Medical Device Design
• +6 more

Professor Alistair McEwan, affiliated with the University of Sydney's School of Biomedical Engineering, specializes in biomedical devices and instrumentation for neurological and cardiovascular diagnostics. As the Cerebral Palsy Chair of Technology and Engineering and Associate Head (External Engagement), he focuses on low-cost medical solutions for resource-limited settings, including neonatal care and stroke detection. His research bridges biophysics and clinical translation, with applications in electrical impedance tomography, wearable sensors, and neuroprosthetics. PhD from University of Oxford Member of the Sydney Nano Institute, Brain and Mind Centre, and Charles Perkins Centre His work explores how tissue electrical properties can enhance understanding of neural signaling and implant design. Clinical collaborators include the Bill & Melinda Gates Foundation for newborn nutrition monitoring. Recent projects involve AI-assisted critical care modeling, bionic devices for stress measurement, and adaptive control systems for neonatal resuscitation equipment.

• Internet of Things (IoT)
• Cybersecurity
• Sensor Networks
• +3 more

Shiwei Fang is an Assistant Professor in the Department of Computer & Cyber Sciences within the School of Computer and Cyber Sciences at the University of North Georgia. He holds a Ph.D. in Computer Science from the University of North Carolina (2021) and a B.E. in Computer Science from the State University of New York (2015). His research focuses on IoT systems, cybersecurity, sensor networks, and edge computing, with notable contributions to multimodal analytics, privacy visualization tools, and geospatial tracking datasets. He advises the Graduate Student Organization and serves on the SCCS Academic Web Oversight Committee. Education: Ph.D., Computer Science, University of North Carolina, 2021 B.E., Computer Science, State University of New York, 2015 Research interests include IoT security, context-aware systems, and sensor fusion. His work on IoBT-MAX and GDTM datasets highlights expertise in experimentation frameworks and geospatial tracking. Recent publications explore privacy risks in IoT, AR-based privacy visualization, and efficient inference models for edge computing. He has contributed to over 25 peer-reviewed articles since 2015, with a focus on real-world IoT applications and hardware-software co-design. Service roles include faculty advising and committee participation. He teaches courses like CSCI 3170/5170 on Computer Organization, bridging theoretical computer science with practical hardware concepts.

• Immersive Media
• Extended Reality (XR)
• Virtual Reality (VR)
• +6 more

Prof. Jan-Niklas Voigt-Antons is a Professor of Applied Computer Science specializing in Immersive Media at Hamm-Lippstadt University of Applied Sciences. His work focuses on Extended Reality (XR), Virtual Reality (VR), Augmented Reality (AR), and their applications in healthcare, education, and human-machine interaction. He holds a Dr.-Ing (Engineering Doctorate) and has extensive industry experience with organizations like Daimler AG, Telekom Innovation Laboratories, and the German Research Center for Artificial Intelligence (DFKI). Research interests include user experience (UX) design, emotion analysis in virtual environments, and accessibility for aging populations. He has led projects on wearable health tech, AR/VR usability, and immersive training systems. Notable areas of impact include developing guidelines for inclusive XR interfaces and advancing telemedicine through immersive technologies. Prof. Voigt-Antons has collaborated with Charité – Universitätsmedizin Berlin on healthcare applications and has contributed to standardization efforts in telecommunications. His technical competencies include agile project management, statistical analysis, and mobile application development for iOS/Android. He advises on UX evaluations, usability testing, and physiological data analysis for industry partners. Key achievements include creating the Story Time Dataset for video quality research and developing the ColorTable system for flavor perception studies. His work emphasizes real-world deployment, with projects addressing mobility challenges for seniors in rural areas and improving dementia care through tablet-based interventions.

Sheheeda Mariam ManakkaduView profile

Associate Professor

• Robotics
• Data Analytics
• Machine Learning
• +4 more

Sheheeda Mariam Manakkadu is an Associate Professor in the Department of Computer Science at Southern Illinois University Carbondale. She teaches graduate courses in Data Structures, Object-Oriented Programming, Data Mining, Text Mining, and Cloud Architecture, along with undergraduate courses in Operating Systems and Data Analytics. Ph.D., Computer Engineering M.E., Biomedical Engineering Her research spans robotics, data analytics, and parallel computing. Key areas include adaptive control of robotic manipulators, big data processing via MapReduce, IoT resource allocation, and computational bioinformatics for protein networks. Recent publications focus on neuro-sliding mode control, cloud architecture, and scalable recommender systems. She actively participates in academic service as a committee member for graduate courses and the IEEE Erie Section. Her work integrates machine learning, optimization algorithms, and distributed systems across diverse domains.

Enzo MastinuView profile

Associate Professor

• Biomedical Engineering
• Prosthetics and Neuroprosthetics
• Embedded Systems
• +4 more

Enzo Mastinu is an electronic engineer specialized in embedded systems for biomedical applications, holding an Associate Professor qualification in Bioengineering. He earned his bachelor's and master's degrees in electronic engineering from the University of Cagliari and a PhD in biomedical signals and systems from Chalmers University of Technology, Sweden. His research focuses on advanced prosthetics and neuroprostheses for upper limb amputations, incorporating embedded systems design, control algorithms, sensory feedback, signal processing, AI, and osseointegration. Key projects include the HAND and HAND2 initiatives, funded by the EU and the Italian Ministry of Research, aiming to develop semi-autonomous prosthetic hands. He has published 25 journal articles (75% in Q1) and 21 conference papers, contributing to a PCT patent. Mastinu is a Senior Member of IEEE EMBS and RAS, reviews for ~90 journals/conferences, and edits Transactions on Medical Robotics and Bionics (IEEE) and Scientific Data (Nature). He has supervised ~40 students across PhD, master's, internships, and postdocs, and teaches courses in biomedical engineering and STEM education. His scientific awards include the Marie Skłodowska-Curie Fellowship (2021), National Qualification as Associate Professor (2024), and a Young Researcher Grant (2025). Research emphasizes clinical implementation of prosthetics with neural feedback and intuitive control, as highlighted in high-impact journals like the New England Journal of Medicine.

Jiju PoovvancheriView profile

Associate Professor

• Computer Graphics
• 3D Vision
• Machine Learning
• +8 more

Dr. Jiju Poovvancheri is an Associate Professor in the Department of Math & Computing Science at Saint Mary’s University, Halifax, Canada. He holds affiliations with the Graphics & Spatial Computing Lab and previously held postdoctoral positions at the University of Victoria and University of Calgary. His research focuses on computer graphics, 3D vision, and machine learning, with applications in virtual/augmented reality, autonomous robotics, urban planning, and bio-mechanical studies. Key research areas include point cloud processing, semantic surface reconstruction, spatial data structures, and geometric deep learning. Education: PhD from Indian Institute of Technology Madras (2011–2014), supervised by Prof. Ramanathan Muthuganapathy. Postdoctoral work at University of Calgary (EYES-HIGH Fellowship, 2015–2017) and University of Victoria (MITACS Elevate Fellowship, 2018). Research & Awards: Winner of MITACS Elevate Fellowship (2018), EYES-HIGH Fellowship (2015–2017), and multiple grants including NSERC DG (2019–2026). His work has been supported by NVIDIA GPU hardware, NSERC, CFI, and industry partners like Modest Tree Media and Caterpillar. Professional Activities: Associate Editor for IEEE Access , Guest Editor for special issues in Remote Sensing and Sensors , and reviewer for top conferences like CVPR, ICCV, and ECCV. Member of ACM SIGGRAPH, Solid Modeling Association, and IEEE Geoscience & Remote Sensing Society. Lab & Collaborations: Leads the Graphics & Spatial Computing Lab, collaborating with institutions globally. Current projects include "Interaction and navigation in virtual spaces" and industry partnerships with Modest Tree Media for real-time object recognition. Advising: Supervised over 20 graduate and undergraduate students, with notable alumni advancing to roles at ReelData AI, Royal Canadian Air Force, and academic institutions like Dalhousie University.

Natalia BerloffView profile

Professor

• Applied Mathematics
• Theoretical Physics
• Quantum Computing
• +6 more

Professor Natalia Berloff is a Professor of Applied Mathematics at the University of Cambridge's Department of Applied Mathematics and Theoretical Physics (DAMTP), where she has been a faculty member since 2002. She is also a Fellow of Jesus College, Cambridge. From 2013 to 2016, she served as Professor, Dean of Faculty, and Director of the Photonics and Quantum Materials Program at Skoltech. Previously, she held positions at the University of California, Los Angeles, including UC President's Research Fellow (1997-1999) and PIC Assistant Professor (1999-2002). Her research focuses on quantum fluids, physics-inspired computing, and non-equilibrium quantum systems. Key areas include coherence in quantum systems, superfluidity, Bose-Einstein condensates, and classical/quantum simulators. Her work bridges applied mathematics and theoretical physics, with applications in optical computing and quantum technologies. Recent studies emphasize Ising machines, photonic networks, and analog computing solutions for optimization problems. Her publications span over two decades, with recent trends in analog optical computing, gain-based systems, and quantum annealing. She leads the Quantum Fluids group, exploring novel computational paradigms using quantum fluids and polariton condensates. Her contributions have advanced interdisciplinary fields like quantum simulation and photonic-based AI. Education: Doctorate in Applied Mathematics (details not explicitly stated but implied via career progression). Grants/Awards: No specific grants or awards listed, though her leadership roles imply significant external funding. Labs/Teams: Leads the Quantum Fluids group and the Physics-inspired Computing team at DAMTP.

• Cybersecurity
• Machine Learning
• Data Analytics
• +5 more

Dr Zhiyuan (Thomas) Tan is an Associate Professor at Edinburgh Napier University’s School of Computing, Engineering and the Built Environment . He is internationally recognised for his cybersecurity research and has been listed among Stanford University’s Top 2% Scientists for 2021–2023. Education BEng (2005) with high distinction – North-eastern University, China MEng (2008) – Beijing University of Technology, China PhD in Computer Systems (2014) – University of Technology Sydney, Australia Research Interests Dr Tan’s research integrates cybersecurity with machine learning and data analytics. His core areas include: Intrusion detection and defence of critical service systems Adversarial machine learning for malware and anomaly detection Virtualisation security through non-parametric behaviour modelling IoT and vehicular network security—cloud/edge/cloudlet frameworks Privacy-preserving AI and federated machine unlearning Smart-city digital forensics and cyber-physical system resilience Research Output Trends His recent articles (2020–2025) reveal a strong focus on federated learning, edge & mobile computing, UAV coordination, and AI-driven security. Topics span advanced steganography, metamorphic malware, graph injection attacks, and trustworthiness in vehicular platoons, all anchored in real-world IoT and transportation applications. Awards & Distinctions Stanford University Top 2% Scientists List (2021, 2022, 2023) National Research Award 2017 – Research Council of the Sultanate of Oman Best Paper Awards (three instances) Kaspersky Lab Student Cyber Security Conference – Finalist Award SICSA Supervisor of the Year 2019 – Honourable Mention Grants & Leadership Dr Tan has attracted over £200k in external funding including: Carnegie Trust (£73,564) – Federated Machine Unlearning ENU Development Trust (£29,998) – Machine Unlearning Royal Society (£12,000) – VANET Security & Privacy SICSA & other awards for MemoryCrypt, AI Secrets, behaviour biometrics, and visiting-fellow schemes. Supervision & Mentoring Since 2013 he has supervised or co-supervised 16 doctoral candidates and several master’s students; six PhDs have successfully graduated. Roles range from Director of Studies to additional supervisor across diverse topics from malware evolution to VR olfactory interfaces. Research Groups & Collaboration He is affiliated with the Centre for Artificial Intelligence and Robotics , the Centre for Distributed Computing, Networking and Security , and the Centre for Cybersecurity, IoT and Cyber-physical Systems at ENU, fostering interdisciplinary collaboration with national and international partners.

Sunday EkpoView profile

Senior Lecturer

• Communication Systems Engineering
• Satellite Systems Engineering
• RF and Microwave Engineering
• +7 more

Dr. Sunday Ekpo is a Senior Lecturer in Electrical & Electronic Engineering at Manchester Metropolitan University (MMU), UK. He holds multiple advanced qualifications, including a PhD in Electrical & Electronic Engineering and certifications such as Chartered Engineer (CEng) and Senior Fellow of the Higher Education Academy (SFHEA). His research focuses on Communication and Space Systems Engineering, with expertise in 5G/6G networks, satellite-cellular convergence, RF engineering, and IoT applications. He leads projects on energy-efficient wireless systems, additive manufacturing for electronics, and smart sensor development. Education: BEng (Hons) in Electrical & Electronic Engineering MSc in Communication Engineering MA in Higher Education PhD in Electrical & Electronic Engineering Research Interests: RF and microwave transceiver design Satellite communication subsystems Energy harvesting for IoT AI-driven signal processing Smart sensor systems Awards: Best Paper Award (2023) Best Overall Powerhours (British Council) Huawei’s Influential Thinkers Award (2019) Grants & Projects: £1.3m+ external grants secured Lead on Sony-funded Spresense-managed drone connectivity projects SmOp Cleantech collaborations on green wireless systems UK Space Agency and 6G policy advisory roles Labs & Teams: Leads the Advanced Electronic Design, Communication and Space Systems Engineering teams, and chairs international conferences like the Adaptive and Sustainable Science, Engineering and Technology (ASSET) series.

Tsung-Yi HoView profile

Professor

• Design Automation for Microfluidic Biochips
• Nanometer Integrated Circuits
• Embedded Systems
• +3 more

Tsung-Yi Ho is a Professor in the Department of Computer Science at National Tsing Hua University, Taiwan. He holds the Hans Fischer Fellowship at the Technical University of Munich's Institute for Advanced Study (TUM-IAS). His primary research focuses on design automation for microfluidic biochips and nanometer integrated circuits, emphasizing reliability, optimization, and interdisciplinary applications in bioengineering. Ho received his Ph.D. in Electrical Engineering from National Taiwan University in 2005. He has held positions at National Cheng Kung University and National Chiao Tung University before joining National Tsing Hua University. His work bridges algorithmic design with practical biochip fabrication, addressing challenges like contamination control, routing optimization, and fault tolerance in microfluidic systems. His research interests span design automation for emerging technologies, including paper-based biochips and 3D microfluidic architectures. He has pioneered methods for integrating hardware-software co-design principles into biochip development, enhancing both functionality and reliability. His contributions include novel routing algorithms, contamination mitigation techniques, and reliability-aware synthesis frameworks. Ho has authored over 100 publications, including influential papers in IEEE Transactions on CAD and ACM journals. He serves on the editorial boards of multiple top-tier journals and chairs professional chapters for ACM and IEEE. His awards include the Humboldt Research Fellowship, Dr. Wu Ta-You Memorial Award, and Best Paper Awards at VLSI Test Symposium and IEEE Transactions on CAD. His current projects involve optimizing control-fluidic co-design for paper-based biochips and developing AI-driven frameworks for microfluidic functionality prediction. He collaborates widely, leading cross-disciplinary initiatives at TUM-IAS and Taiwan's academic institutions.

Ahmed SherifView profile

Associate Professor

• Cybersecurity
• Cryptography
• Autonomous Vehicles
• +2 more

Ahmed Sherif is an Associate Professor specializing in cybersecurity and privacy-preserving systems, likely affiliated with the University of Southern Mississippi. He holds a Ph.D. from Tennessee Technological University (2017) and M.S. from Egypt Japan University of Science & Technology (2014). His research focuses on cryptographic solutions for autonomous vehicles, IoT networks, and smart grid security. Research interests span privacy-preserving systems across transportation and critical infrastructure, with emphasis on authentication protocols and hardware security. Teaches courses including Digital Logic, Network Security, and Advanced Security Techniques. Publications show strong focus on privacy engineering in emerging technologies (2021-2025), particularly in vehicular/drone networks and medical AI. No awards listed. Research includes federated learning for medical diagnosis and hardware-accelerated security frameworks.

• Control Systems
• Machine Learning
• Robotics
• +6 more

Marko Tanasković is a researcher at Singidunum University's Faculty of Informatics and Computing, specializing in control systems, robotics, and electrical engineering. He holds a PhD from ETH Zurich (2015) in Information Technology and Electrical Engineering, following degrees from University of Belgrade (BEng, 2009) and ETH Zurich (MEng, 2011). His research focuses on adaptive control systems, machine learning applications in engineering, and sensorless motor control. Key contributions include: Development of predictive algorithms for traffic systems and industrial automation Innovations in rotor orientation determination for PMSM motors Integration of AI in fraud detection and building climate control Recent work includes a 2024 study on wearable health monitoring devices and a 2022 paper on drone forensics. He has authored/co-authored over 15 peer-reviewed articles and holds patents in motor control technologies. Current affiliations include Singidunum University's Department of Electrical Engineering and Collaboration with ETH Zurich alumni networks. Active in international conferences such as Sinteza and IEEE events.

Luca MottolaView profile

Professor

• Battery-less IoT
• Mobile Space Robotics
• Smart Cities
• +3 more

Luca Mottola is a Full Professor at Politecnico di Milano and Senior Researcher at RI.SE Sweden. He leads the Networked Embedded Software Lab (NESLab), focusing on next-generation IoT, battery-less systems, and mobile robotics. His work bridges embedded computing, wireless networks, and cyber-physical systems, with applications in smart cities and space robotics. Education: No explicit details provided in texts. Research interests include energy-harvesting IoT, drone communication, and real-time systems. Notable awards include the ACM SENSYS Test of Time Award (2022) and multiple Best Paper Awards at top conferences like MOBICOM and RTCSA. Grants/Projects: Overseen projects on battery-less IoT, drone localization, and energy-efficient systems. Editorial roles include IEEE Transactions on Mobile Computing and ACM Transactions on Sensor Networks. Labs/Teams: NESLab, FlyZone Testbed for aerial drones, and collaborations with NXP Technologies, TU Graz, and USC.

Urs HengartnerView profile

Associate Professor

• Information Privacy
• Computer Security
• Network Security
• +3 more

Urs Hengartner is an Associate Professor at the Department of Computer Science, University of Waterloo. His research focuses on information privacy, computer and network security with emphasis on smartphones, IoT, and machine learning-based authentication systems. He holds a Ph.D. (2005) and M.Sc. (2003) from Carnegie Mellon University, and a Diploma from ETH Zürich (1997). His work spans Adaptive security attacks on ML systems Implicit user authentication frameworks Privacy-preserving technologies for location and genomic data Secure authentication systems resilient to voice/spoofing attacks Recent publication trends show a strong focus on adversarial attack detection (e.g., watermarking evasion, diffusion model attacks) and context-aware authentication systems . His frameworks like MRAAC and SHRIMPS address multi-stage authentication challenges in mobile ecosystems. Key contributions include frameworks for evaluating multi-user authentication systems (SHRIMPS), risk-aware access control (MRAAC), and novel defense strategies against collaborative robot traffic fingerprinting. His work bridges security mechanisms with user-centric design principles.

Sisi ZhouView profile

Researcher

• Quantum Metrology
• Quantum Error Correction
• Quantum Learning
• +2 more

Sisi Zhou is a Research Faculty member at the Perimeter Institute for Theoretical Physics, specializing in quantum information science. Her work focuses on quantum metrology, quantum error correction, and quantum learning, with a particular emphasis on advancing methodologies for noisy quantum systems. Her research explores theoretical frameworks to enhance precision in quantum measurements, optimize error-correcting codes, and apply machine learning techniques to photonic platforms. Recent contributions include studies on non-Markovian metrology, Gaussian measurement limitations, and entanglement-enabled protocols for bosonic channels. Zhou has delivered seminars at institutions such as the Banff International Research Station and the University of Calgary, addressing topics like quantum metrological limits in noisy environments and error mitigation strategies for near-term quantum processors.