Find Academic Supervisors

Stefano TomasinView profile

Professor

• Wireless Communications
• Physical Layer Security
• Reconfigurable Intelligent Surfaces
• +5 more

Stefano Tomasin is a Full Professor at the Department of Information Engineering, University of Padova, Italy. His research focuses on wireless communications, physical layer security, and reconfigurable intelligent surfaces (RIS) for 5G and beyond networks. He leads projects on RIS-assisted physical layer security, including signal processing for confidentiality, authentication techniques, and secure localization. Research Interests: Prof. Tomasin specializes in wireless security mechanisms with emphasis on physical-layer authentication, underwater acoustic networks, and RIS optimization. His work integrates signal processing with machine learning for jamming detection, secure key generation, and adaptive reconfiguration of intelligent surfaces. Recent Publications: His 2023-2025 articles demonstrate concentrated work on RIS-assisted security, underwater authentication, and anti-jamming techniques for 5G/6G networks. Dominant themes include physical-layer authentication protocols, channel-based key generation, and machine learning applications for signal security. Projects: Currently leading a national project on RIS for physical layer security in 5G+ networks, investigating confidentiality enhancement, authentication methods, and secure localization using advanced metasurfaces. Actively recruiting post-doctoral researchers for related work. Teaching & Advising: Supervises thesis projects and teaches courses in communications systems. Coordinates with the Department of Information Engineering's research initiatives in wireless technologies.

Alex BaldwinView profile

Assistant Professor

• Computational Neuroscience
• Visual Psychophysics
• Binocular Vision
• +6 more

Alex Baldwin is an Assistant Professor at McGill University within the Department of Ophthalmology & Visual Sciences. He serves as a Junior Scientist in the Brain Repair and Integrative Neuroscience (BRaIN) program at the Research Institute of the McGill University Health Centre. Supervisor in McGill's Integrated Program in Neuroscience (IPN) Supervisor in Quantitative Life Sciences program Laboratory located at Montreal General Hospital Research focuses span computational neuroscience, visual psychophysics, and binocular vision mechanisms , particularly examining: Amblyopia and spatial scrambling Aging-related changes in stereopsis Visual noise adaptation Contrast summation models Contour integration processes Digital therapeutic development His lab employs Matlab/Octave (Psychtoolbox), Python (PsychoPy), and Unity/C# for experimental design, with Python (Jupyter) and Matlab (Palamedes Toolbox) for data analysis. Collaborations include Wenzhou Medical University. Scientific recognition includes: NSERC Discovery Grant (2022-2027) HBHL Ignite Funding FRQ-S Vision Health Research Network Pilot Training opportunities available for undergraduate (PSYC-396/COGS-444/COGS-401) and graduate students , with current advisees working on topics including: Visual snow syndrome neural mechanisms Binocular imbalance in aging Contour integration modeling Adaptive strategies in amblyopia Dichoptic ebook therapy development

Rana Kumar JanaView profile

Research Fellow

• Optical Networks
• Artificial Intelligence
• Machine Learning
• +3 more

Dr. Rana Kumar Jana serves as a Research Fellow at the School of Computer Science and Statistics, Trinity College Dublin, Ireland, affiliated with the CONNECT Centre. His work focuses on the intersection of artificial intelligence and optical networks, specifically addressing AI-assisted resource provisioning and performance optimization in elastic multiband optical systems to overcome the optical fiber capacity crunch. He holds a Ph.D. in Electronics and Communications Engineering from IIIT-Delhi, India. His educational background includes: Ph.D. in Electronics and Communications Engineering from IIIT-Delhi, India Dr. Jana's research centers on Optical Networks and Machine Learning , with emphasis on quality of transmission estimation, nonlinear-impairment mitigation, and resource reprovisioning in C+L band elastic optical networks. He integrates experimental validation with techno-economic analysis to develop practical solutions for network capacity expansion, leveraging domain knowledge and adaptive margin techniques. His work bridges theoretical innovation with operator perspectives in telecom infrastructure evolution. Analysis of his 15 recent publications (2020-2024) reveals a consistent trajectory toward overcoming optical capacity limitations through multi-band expansion, multi-core fibers, and AI-driven optimization. Key themes include machine learning for quality estimation, techno-economic comparisons of upgrade strategies (e.g., multifiber vs. ultra-wideband), and survivability analysis under fill margin constraints. His publications in premier venues like JOCN and ECOC demonstrate rigorous experimental validation coupled with real-world operator insights. No scientific awards were specified in the source material. Dr. Jana actively mentors undergraduate and postgraduate students in machine learning applications for optical systems and SDN-enabled network failure management. His research collaborations span industry (British Telecom) and academia (UCL, Aston University, University of East Anglia), suggesting involvement in externally funded projects, though specific grants are not detailed. As an IEEE TPC member, reviewer, and workshop organizer, he contributes significantly to the optical networking community. He operates within the CONNECT Centre at Trinity College Dublin, a leading hub for future networks research. His international engagements with British Telecom, University College London, and Tejas Networks highlight cross-sector collaborations focused on next-generation optical infrastructure, particularly in elastic network architectures and AI-assisted resource management for backbone networks.

Usman HadiView profile

Assistant Professor

• Wireless Communication
• 5G and Beyond 5G Networks
• Time Sensitive Networks
• +7 more

Dr. Usman Hadi serves as an Assistant Professor in the School of Engineering within Ulster University's Faculty of Computing, Engineering and Built Environment at the Jordanstown campus. His academic trajectory includes a Ph.D. in Electronic Engineering from the University of Bologna (2020), followed by postdoctoral research at Aalborg University and industry experience as an External Research Engineer at Nokia Bell Labs in Denmark (2019-2021). His educational foundation comprises: PhD in Electronic Engineering, University of Bologna (2020) Master's in Digital Predistortion for Compensation of Nonlinearities in Radio over Fiber Links, University of Bologna Dr. Hadi's research spans cutting-edge domains in wireless communications and AI-driven networking solutions. His primary focus includes 5G/6G technologies, Time Sensitive Networks, Radio over Fiber systems, and machine learning applications in telecommunications. Recent work emphasizes AI-enhanced signal detection for MIMO systems, UAV-based communication frameworks, and IoT security architectures, with significant contributions to optical front-haul optimization and wireless sensor networks. Analysis of his publication record reveals a strategic emphasis on AI integration for next-generation wireless systems. Key trends include deep learning applications for MIMO detection in 6G networks, digital twin implementations for UAV fault detection, and secure IoT frameworks for drone communications. His work consistently bridges theoretical advancements with practical implementations in optical and wireless front-haul systems, particularly through the MADNI (Made in UU) drone platform. Notable recognitions include: Top 2% Cited Researcher designation for three consecutive years (2021-2023) Research and Impact Fund Award (2023) Dr. Hadi supervises two PhD students: Ms. Cara Rose (Department of Economy-funded, 2023-present) and Mr. M.Y. Daha (Vice Chancellor's Research Studentship, 2022-present). His active research portfolio includes drone-based climate resilience initiatives funded by the British Council (2025-2026) and IoT-driven cybersecurity frameworks supported by Innovate UK (2025), alongside participation in EPSRC-funded infrastructure projects. He leads the MADNI drone research platform, which integrates state-of-the-art 5G connectivity, object detection, and facial recognition capabilities. His laboratory maintains active collaborations with Nokia Bell Labs, University of Manchester, University of East Anglia, Manchester Metropolitan University, University of Texas, and Boise State University, focusing on next-generation communication technologies and sustainable development applications aligned with UN SDGs.

Uhryn Dmytro IlyichView profile

Associate Professor

• Information technologies for decision support
• Swarm intelligence systems
• Industry-specific geographic information systems
• +2 more

Dr. Dmytro Uhryn is an Associate Professor at the Department of Computer Science, Yuriy Fedkovych Chernivtsi National University. With a Doctor of Technical Sciences degree (2021) and specialization in Computer Science (12DC No. 029057, 2011), he actively contributes to research in swarm intelligence and geographic information systems . As a member of the Bukovina Information Technology Cluster since 2019, he focuses on intelligent forecasting systems , medical image analysis , and financial data modeling . Education: Applied Mathematics (2003, Chernivtsi National University) and Organizational Management (National Technical University "Kharkiv Polytechnic Institute") Research Interests: Information technologies for decision support, swarm intelligence systems, industry-specific GIS, medical image processing, and financial market algorithms. Recent publications (2023-2024) demonstrate expertise in swarm intelligence applications for migration forecasting, medical diagnostics using laser autofluorescence, and financial systems modeling. His 2021 dissertation established foundational methods for swarm intelligence in GIS . Professional development includes certifications in educational programming (Sigma Software University), NATO modeling , and international teaching methodologies (Lyublin Institute, 2023). He collaborates with researchers across Ukraine and Poland on biomedical optics, financial IT, and tourism technology projects.

• Latest network technologies
• Information security
• Cryptography
• +4 more

Dr. Yuliya Volodymyrivna Tanasyuk is an Associate Professor at the Department of Computer Systems and Networks, Chernivtsi National University named after Yu. Fedkovych . She holds a Candidate of Physical and Mathematical Sciences degree (2003) and has been an active researcher and educator in computer science and physics domains. Academic Rank: Associate Professor Email: y.tanasyuk@chnu.edu.ua Her research spans multiple disciplines: Cryptography Cellular Automata Internet of Things (IoT) Software Engineering Network Technologies Project Management Notable trends in her publications include: Applications of cellular automata in cryptographic hash functions (2017–2021) Advancements in CdTe semiconductor materials (2003–2007) Interdisciplinary work bridging physics and computer science Scientific recognition includes: Multiple Cisco certifications (CCNA Security, DevNet Associate) 2023 UGEN Uni-Biz Bridge award for teaching flexibility British Council Academic Teaching Excellence (2016) International conference presentations at E-MRS and ISCP As an academic advisor, she has supervised numerous student research projects including: TensorFlow-based pattern recognition Traffic sign tracking systems Blockchain interaction frameworks University event planning software Smart parking detection systems Her work often intersects hardware-software integration and security protocols, with educational contributions through methodological guides in C++ programming and network technologies.

• Signal Processing
• Machine Learning
• Computer Engineering
• +3 more

Ehsan Namjoo serves as a Research Fellow in the Department of Electronics & Computer Engineering at the University of Limerick, with a primary affiliation at Lero – the Irish Software Research Centre. His multidisciplinary work bridges theoretical signal processing, machine learning applications, and hardware implementation for real-world systems. His research spans signal processing (DOA estimation under non-ideal noise conditions, EEG source imaging), machine learning (explainable AI for medical diagnostics, feature selection in cancer detection), and computer engineering (polar code decoders, visible light communication systems). Notable biomedical applications include breast cancer diagnosis and epileptic source analysis, while cybersecurity work focuses on intrusion detection in cloud environments. Recent publications (2021-2025) reveal a consistent trajectory toward developing lightweight, interpretable models for tabular medical data alongside robust signal processing frameworks for communication systems. His work increasingly integrates hardware-aware algorithms, particularly in polar coding implementations, and emphasizes practical validation through experimental demonstrations in visible light networks. As an active Lero researcher, Namjoo participates in Ireland's national software research ecosystem, contributing to interdisciplinary projects that connect theoretical innovations with healthcare, communications, and security applications through collaborative frameworks.

• Neuromorphic Electronics
• Neuroscience
• Biointerfaces
• +3 more

Dr. Hongwei Tan serves as Group Leader at the Department of Molecular Electronics, Max Planck Institute for Polymer Research (MPIP) in Mainz since November 2024. Previously, he was Research Fellow (2022-2024) and Postdoctoral Fellow (2017-2022) at Aalto University's Department of Applied Physics, following postdoctoral work at the University of Massachusetts Amherst on neurointerface devices. His academic credentials include: Bachelor of Physics, Nankai University (2011) Doctorate in Materials Physics and Chemistry, University of Chinese Academy of Sciences (2016), focusing on neuromorphic photomemristors Tan's research pioneers neuromorphic biointerfaces—integrating brain-inspired electronics with biological systems to enable energy-efficient computation and seamless biointeraction. His work targets transformative applications in brain-machine interfaces, prosthetics, and diagnostics through interdisciplinary convergence of neuroscience, materials science, and engineering. His publication portfolio (2015-2024) reveals a clear evolution from foundational optoelectronic memristor research toward complex neuromorphic systems for sensory processing. Key thematic trajectories include photomemristor-based vision systems, tactile coding with spiking nerves, and nanoionic human-machine interfaces, demonstrating consistent innovation in bioinspired hardware. As MPIP Group Leader, Tan directs research strategy and team mentorship within his neuromorphic electronics program, though specific advisees and grant details remain unlisted in available materials. His laboratory focuses on developing integrated neuromorphic systems—from novel materials and devices to algorithms—that facilitate bidirectional communication between electronic and biological neural networks for next-generation neurotechnologies.

Lajos HanzoView profile

Professor

• Wireless Communications
• Optical Wireless Systems
• Signal Processing
• +5 more

Lajos Hanzo is a distinguished Professor at the University of Southampton's School of Electronics and Computer Science (ECS), where he has established himself as a leading authority in wireless communications and signal processing. His academic profile showcases extensive contributions to the field with over 1400 publications and significant recognition through multiple prestigious fellowships. Dr. Hanzo received his degree in electronics in 1976 and his doctorate in 1983, followed by an honorary doctorate in 2009. His educational background laid the foundation for a career that has continually evolved with communication technologies from early wireless systems through to contemporary 6G research and quantum communications. Hanzo's research spans wireless communications, optical wireless systems, MIMO technologies, and increasingly intersects with artificial intelligence applications for next-generation networks. His work demonstrates remarkable synergy between theoretical foundations and practical implementations, addressing challenges in spectral efficiency, channel capacity, and reliable transmission across diverse communication scenarios. He has made seminal contributions to space-time coding, non-orthogonal multiple access (NOMA), and index modulation techniques that have influenced multiple generations of wireless standards. Analysis of his recent publications reveals a clear progression toward more complex communication paradigms, with increasing focus on 6G technologies, integration of deep learning with traditional communication theory, and exploration of quantum-inspired communication approaches. His work consistently addresses the tension between theoretical capacity limits and practical implementation constraints, with recent papers demonstrating particular interest in millimeter-wave communications, visible light communication, and massive connectivity solutions for IoT applications. FREng (Fellow of the Royal Academy of Engineering) FIEEE (Fellow of the IEEE) FIET (Fellow of the Institution of Engineering and Technology) Fellow of EURASIP (European Association for Signal Processing) DSc (Doctor of Science) While specific details of his advising activities aren't prominently featured in the provided materials, Hanzo's extensive publication record spanning multiple decades suggests significant mentorship of graduate students and postdoctoral researchers. His research has clearly attracted substantial funding to support investigations across wireless communications, with particular emphasis on coding theory, MIMO systems, and next-generation network architectures. The collaborative nature of his recent work indicates ongoing engagement with international research consortia addressing 5G evolution and 6G standardization.

• Seismology
• Geophysics
• Seismic Tomography
• +5 more

Prof. Dr. Andreas Fichtner is a Full Professor of Seismology and Wave Physics at ETH Zurich's Department of Earth and Planetary Sciences. He leads research in seismic tomography, fiber-optic sensing, and high-performance computing, deploying innovative techniques for imaging Earth's interior. His work includes developing distributed fiber-optic sensing for seismic monitoring in urban areas, volcanoes, and glaciers. Beyond seismology, he explores applications in medical ultrasound imaging and metamaterial design. Research interests span seismic wave inversion, uncertainty quantification, and fiber-optic technology. Notable achievements include co-founding Mondaic, a spin-off providing full-waveform modeling solutions. Awards include the 2011 Keiiti Aki Award (AGU), 2015 Early Career Scientist Award (IUGG), and 2018 Hoffmann Prize. He currently serves on the Board of Directors of the Seismological Society of America. Key contributions include pioneering fiber-optic seismology in ice streams and volcanoes, advancing multi-scale inversion methods, and integrating seismic data for continental-scale tomography. His research bridges geophysics with engineering, medical imaging, and computational science.

Orlando HernandezView profile

Associate Professor

• VLSI Architectures
• Computer Vision
• Image Processing
• +4 more

Orlando Hernandez is an Associate Professor in the Department of Electrical and Computer Engineering at The College of New Jersey. He holds a Ph.D. in Electrical Engineering from Southern Methodist University (2002), an M.S.E.E. (1993) and B.S.E.E. (1991) from the University of South Florida. Prior to his academic career, he held industry positions at Texas Instruments and Maxim Integrated Products from 1993-2003, serving in design management roles for imaging systems, ASIC development, and microcontroller technologies. His research focuses on high-performance VLSI architectures for computer vision applications, including color image segmentation, digital signal processing, embedded systems, and mixed-signal design. Key research areas include hardware acceleration for image compression algorithms, real-time traffic monitoring systems, autonomous robotics, and advanced encryption implementations. His work consistently bridges theoretical algorithms with practical hardware implementations. Professional affiliations include Senior Membership in the Institute of Electrical and Electronics Engineers (IEEE). He has secured multiple research grants including a $93,320 National Science Foundation award for image processing instrumentation and several industry-sponsored equipment grants from Texas Instruments and Xilinx.

• Optical Sensing
• Photonics
• Laser Dynamics
• +5 more

Assoc. Professor Yanguang Yu holds a PhD from Harbin Institute of Technology (2000) and has been at the University of Wollongong (UoW) since 2007, currently serving as Associate Professor in the School of Electrical, Computer and Telecommunications Engineering. Her research focuses on optical sensing, photonics, and laser dynamics, with 200+ publications. She is recognized as a World’s Top 2% Scientist (2020–2024). Education: PhD in Instrumentation and Measurement (Harbin Institute of Technology, 1997–2000). Postdoctoral training at Tianjin University (2001–2002) and visiting roles at the University of Pavia (Italy), University of Toulouse (France), and UoW (2004–2005). Research Interests: Optical interferometry, microwave photonic sensing, lidar, precision displacement/velocity measurements, and embedded systems. Recent work includes advancements in self-mixing interferometry, dual optical feedback systems, and machine learning integration. Grants and Funding: Led projects on semiconductor laser dynamics, photonic sensing, and signal processing (e.g., 2010–2025 grants). Active in editorial roles for Optics and Lasers in Engineering and Optics Express . Labs/Teams: Oversees the Signal Processing for Instrumentation and Communications Lab. Supervises PhD/Master’s research in areas like integrated photonic lidar-radar and machine learning for sensing.

Debra RichardsonView profile

Professor

• Software Engineering
• Sustainability
• Requirements Engineering
• +3 more

Debra Richardson: Academic Overview Debra Richardson is a Professor of Informatics and the founding Dean of the Donald Bren School of Information and Computer Sciences (ICS) at the University of California, Irvine. She has held leadership roles since joining UCI’s faculty in 1987, including serving as Chair of ICS and Dean for ten years. Her academic work bridges software engineering, sustainability, and requirements engineering. Key research projects include Software Engineering for Sustainability (SE4S) and Requirements Engineering at the Margins (RE@tM) , which address global challenges in ICT development and environmental impact reduction. Education Ph.D., Computer and Information Science, University of Massachusetts Amherst (1981) M.S., Computer and Information Science, University of Massachusetts Amherst (1978) B.A., Mathematics, University of California, San Diego (1976) Research Interests Richardson’s research focuses on adapting software engineering methods to socially relevant domains. She advocates for sustainable ICT systems and inclusive computing practices that address marginalized communities. Her work emphasizes integrating sustainability as a first-class requirement in software development and rethinking requirements engineering for global accessibility. She also explores gender diversity in technology and has pioneered initiatives like the Women in ICS (WICS) program. Recognition & Contributions She has been recognized as a Fellow of Automated Software Engineering and led the National Center for Women & Information Technology (NCWIT). Her efforts include chairing Computer Science Education Week and advocating for K-12 CS education reforms in California. Richardson also chairs the California Computing Education Advocacy Network (CCEAN) to ensure equitable access to computing education. Service & Advocacy Her service extends to promoting diversity in STEM, including roles with the Computing Research Association (CRA) Deans Group and Girls Incorporated of Orange County. Richardson’s leadership has transformed ICS into a top-tier interdisciplinary school and fostered initiatives like the Debra J. Richardson Student Support Fund to support underrepresented students in computing. Personal Interests Beyond academia, Richardson is an avid outdoors enthusiast, practicing rock climbing, scuba diving, and yoga. She supports women’s sports and has been a dedicated fan of UCI’s women’s basketball team.

Matteo RinaldiView profile

Professor

• Micro/Nanoelectromechanical Systems (M/NEMS)
• Piezoelectric and Ferroelectric Materials
• Nanoscale Sensors
• +5 more

Matteo Rinaldi is a Professor in the Department of Electrical and Computer Engineering at Northeastern University's College of Engineering and serves as Director of the Institute for NanoSystems Innovation. His work focuses on advanced micro/nanoelectromechanical systems (M/NEMS) for sensing and communication applications. Ph.D. in Electrical and Systems Engineering, University of Pennsylvania (2010) M.Sc. and B.S. in Electronic Engineering, University of Rome Tor Vergata (2007, 2004) Research Interests: Rinaldi's research spans fundamental and applied aspects of piezoelectric nanomaterials, with emphasis on Aluminum Nitride (AlN) and Scandium Aluminum Nitride (ScAlN) based NEMS Plasmonically enhanced infrared and chemical sensors Low-power reconfigurable radio communication systems Integration of MEMS/NEMS with electronics Nanomaterials for harsh environments Publications & Research Trends: Rinaldi's recent work explores high-frequency resonators, infrared detection systems, and zero-power sensing technologies. Key trends include plasmonics for energy-efficient devices, ScAlN integration for improved performance, and machine learning applications in nanoscale device design. Scientific Recognition: 2025 IEEE IFCS Walter G. Cady Award 2024 Northeastern Global Network Accelerator Award Optica Fellow IEEE Sensors Council Early Career Award DARPA Young Faculty Award NSF CAREER Award Advising & Funding: Rinaldi advises graduate researchers like Antea Risso. His lab secures major grants from DARPA, NSF, DOE, and the Bill & Melinda Gates Foundation, focusing on next-generation sensing technologies and 6G communication systems. Research Infrastructure: Leads the Northeastern Sensors & Nano Systems Laboratory (NS&NS Lab) and co-directs the bicoastal Institute for NanoSystems Innovation with Boston and Oakland campuses, advancing nanoscale semiconductor technologies.

• Computer Vision
• Multimedia Systems
• Machine Learning Applications
• +7 more

Timothy K. Shih is an active academic researcher with over 30 years of scholarly contributions, evidenced by his extensive publication record from 1991 through 2025. With more than 380 publications spanning numerous prestigious venues including IEEE Access, Multimedia Tools and Applications, and Lecture Notes in Computer Science, he maintains a robust research profile with consistent annual output (20+ papers in peak years). His work demonstrates leadership through frequent senior/corresponding author positions and collaborations with numerous researchers across international institutions. Dr. Shih's research interests encompass a diverse range of computer science disciplines with particular emphasis on Computer Vision , Human-Computer Interaction , and AI Applications . His work bridges theoretical advancements with practical implementations in educational technology, accessibility solutions, and multimedia systems. Recent publications reveal a strategic focus on applying deep learning techniques to solve real-world problems in sign language recognition, gesture analysis, and wireless sensing applications. Analysis of his publication trends over the past five years shows increasing specialization in multimodal AI systems, with significant contributions to sign language technology (including Arabic Sign Language recognition), WiFi-based human activity recognition, and music technology applications. His research demonstrates strong interdisciplinary connections between computer vision, machine learning, and human-centered computing, with practical applications spanning educational technology, accessibility solutions, and smart environments. Through his mentorship, Dr. Shih has guided numerous junior researchers who have become frequent collaborators, including Chih-Yang Lin, Hsin-Hung Cho, and Tipajin Thaipisutikul. His research program appears well-funded through consistent publication output across multiple project areas, suggesting successful grant acquisition in computer vision, AI, and educational technology domains. Current work indicates active involvement in cutting-edge research on diffusion models for audio processing, enhanced sign language recognition systems, and novel approaches to WiFi-based human interaction analysis.