Find Academic Supervisors

Richard MolyetView profile

Senior Lecturer

• Automatic Control
• Robotics
• Sensor Development
• +7 more

Dr. Richard Molyet is a Senior Lecturer and Undergraduate Director in the Department of Electrical Engineering and Computer Science at the University of Toledo's College of Engineering. After retiring as Associate Professor in 2002, he returned to academia in 2005 as Visiting Professor and transitioned to Associate Lecturer in 2008. Education: Ph.D. in Engineering Science (1981) from University of Toledo His research spans Automatic Control , Robotics , Smart-Grid Systems , and Biomedical Applications . Recent publications focus on deep learning for medical diagnostics and hybrid power network optimization , while earlier work explored repetitive control algorithms and microprocessor-based motion analysis . Scientific Recognition: IEEE Third Millennium Medal (2000) IEEE-USA Professional Achievement Award (2002) University of Toledo Outstanding Teacher Award (2016) Currently advising 3 PhD students and multiple Master’s candidates, Dr. Molyet has served on numerous academic committees since the 1980s. He maintains an active role in IEEE Toledo Section's executive board for 39 years .

Brock J. LaMeresView profile

Professor

• Radiation Tolerant Computer Systems
• Reconfigurable Computing
• Engineering Education
• +4 more

Brock J. LaMeres is a Professor and Director of the Montana Engineering Education Research Center (MEERC) at Montana State University. With joint appointments in Electrical & Computer Engineering and engineering education leadership, he has pioneered radiation-tolerant computer systems and reconfigurable computing technologies for space applications while reforming engineering pedagogy through innovative teaching methods. Ph.D., Electrical Engineering, University of Colorado-Boulder (2005) M.S., Electrical Engineering, University of Colorado-Colorado Springs (2001) B.S., Electrical Engineering, Montana State University (1998) His research interests span radiation-hardened computer architectures, space radiation effects on electronics, and engineering education reform. Notably, he developed the RadPC technology for NASA lunar missions and created the MEERC to align engineering graduates with workforce needs. His work integrates unconventional teaching tools like Minecraft for spatial skill development and created the STEM Storytellers program to enhance graduate students' communication skills. Key article trends demonstrate dual focus areas: (1) radiation-tolerant computing for space missions with subfields like FPGA-based design, memory protection algorithms, and AI processing in radiation environments, and (2) engineering education innovations including e-learning platforms, spatial reasoning training, and oral communication development. 2023: MSU VPR Meritorious Technology/Science Award 2022: NACOE Excellence in Outreach Award 2020: Fox Faculty Award for multidisciplinary excellence 2018: ASEE Distinguished Educator Award As director of MEERC, he has secured $20M+ in grants from NASA, NSF, and national labs. His lab has deployed multiple CubeSats to the International Space Station and developed 15+ U.S. patents in digital signal propagation and radiation-hardened computing. He mentors graduate students in both technical and educational research areas.

Victor LazzariniView profile

Professor

• Computer Music
• Digital Signal Processing
• Electroacoustic Music
• +3 more

Victor Lazzarini is a Professor of Music at Maynooth University, Ireland, specializing in computer music and audio signal processing. He holds a BMus from Universidade Estadual de Campinas (UNICAMP), Brazil, and an AMusD from the University of Nottingham, UK. His research spans electroacoustic music, digital signal processing, and music technology. He leads the Csound project, a widely used sound and music computing system, and authored libraries like Aulib and Aurora. Education: Bachelor of Music (BMus), UNICAMP, Brazil Advanced Music Degree (AMusD), University of Nottingham, UK His research interests include sound synthesis, computer music languages, and the intersection of music with technology. He has authored over 150 peer-reviewed publications and books such as Spectral Music Design: A Computational Approach (Oxford UP, 2021) and co-edited volumes like Ubiquitous Music Ecologies (Routledge, 2020). His work bridges academic and industrial sectors through projects like the Enterprise-Ireland-funded commercialization initiative. Prof. Lazzarini’s contributions to music technology include pioneering tools like Csound, which enable real-time audio synthesis and processing. His articles span topics from digital filter design to historical computer music archaeology, reflecting his expertise in both theoretical and applied domains. Awards: AIC/IMRO International Composition Prize (2006) He advises on interdisciplinary projects such as the BeatHealth initiative, integrating ubiquitous computing and music. His creative output includes electroacoustic compositions performed globally and released on labels like FarPoint Recordings. Lazzarini actively collaborates with international teams, contributing to conferences like DAFx and ICMC, and leads initiatives like the Ubimus (Ubiquitous Music) research network.

• Wireless Networks
• Machine Learning
• Federated Learning
• +3 more

Choong Seon Hong is a Professor at Kyung Hee University's Department of Computer Science and Engineering in Yongin, South Korea. He earned his PhD in Instrumentation Engineering from Keio University, Japan, in 1997. His research focuses on next-generation wireless networks, with emphasis on 6G systems, federated learning, edge computing, and network optimization. Recent collaborative work explores semantic communication, UAV deployment, and multimodal learning frameworks. His publications highlight technical innovations in: Wireless network optimization for terrestrial, aerial, and satellite systems Federated learning architectures with knowledge distillation and prototype transfer Energy-efficient resource allocation in IoT and vehicular networks Security frameworks for EV charging stations and Open RAN systems Current trends show strong collaboration with Zhu Han, Walid Saad, and younger researchers like Apurba Adhikary and Yan Kyaw Tun. The work spans technical solutions for 6G non-terrestrial networks, holographic MIMO systems, and semantic communication frameworks.

Fady AlajajiView profile

Professor

• Information Theory
• Communications
• Coding Theory
• +5 more

Fady Alajaji is a Professor of Mathematics and Engineering at Queen's University, with a cross-appointment in the Department of Electrical and Computer Engineering. He holds a B.E. from the American University of Beirut, and M.Sc. and Ph.D. from the University of Maryland, College Park. His research focuses on information theory, coding for communication networks, probability models (e.g., Polya urns, contagion processes), and applications of information theory to machine learning (e.g., generative adversarial networks, data privacy). He has served as Associate Editor for the IEEE Transactions on Information Theory and has received awards for research and teaching. His work spans theoretical foundations (e.g., Shannon limits) and practical coding techniques for wireless systems. Education: B.E. (1988), M.Sc. (1990), Ph.D. (1994) in Electrical Engineering from the University of Maryland. Roles: Professor of Mathematics and Engineering, Cross-appointment in Electrical and Computer Engineering. Research Interests: Information theory, coding for communication networks, stochastic processes (network epidemics, Polya urn models), machine learning applications (information bottleneck, GANs), and data privacy. Recent work includes optimal signaling schemes for sensor networks, privacy-aware estimation, and curing models for contagion networks. Publications: Over 100 journal/conference papers, including foundational work on joint source-channel coding, hybrid digital-analog coding, and theoretical bounds for communication systems. Recent trends focus on information-theoretic machine learning and network science. Awards: Premier's Research Excellence Award (2001), Golden Apple Teaching Award (2015). Grants/Advising: Supervised postdoctoral fellow Jian-Jia Weng. Active in conference organization and editorial roles. Labs/Teams: Member of the Mathematics and Engineering Communications and Information Theory Group at Queen's University.

Arya FarahiView profile

Assistant Professor

• Statistical/Machine Learning
• Algorithmic Fairness
• Astroinformatics
• +3 more

Arya Farahi is an Assistant Professor of Statistics and Data Sciences at the University of Texas at Austin since 2021. His research bridges astroinformatics, urban informatics, and AI ethics, focusing on mitigating algorithmic bias and uncertainty quantification in real-world applications. He holds PhDs in Physics and Scientific Computing from the University of Michigan, where he was a Data Science Fellow at the Michigan Institute for Data Science. Farahi's work includes collaborations with international projects such as the Dark Energy Survey (DES), COsmostatistics Initiative (COIN), and XMM-XXL Consortium. He leads the D3 Lab, which develops AI tools for scientific discovery and societal challenges, emphasizing interdisciplinary collaboration. His open-source contributions include TATTER, KLLR, and PoPE for statistical analysis and visualization. Key awards include the Best Student Paper Award at KDD’18 and a $400k+ grant. He is a volunteer with Statistics Without Borders and actively involved in projects like the Fire and Smoke Digital Twin for urban resilience. His research spans cosmology, healthcare AI, and urban economics, with a focus on trustworthy models and equitable AI systems.

• Robotics
• Human-Robot Interaction
• Autonomous Agent Systems
• +3 more

Mauro Dragone is an Associate Professor at Heriot-Watt University's School of Engineering & Physical Sciences, affiliated with the Institute of Sensors, Signals & Systems. He holds a BSc in Computer Science from Bologna University (1999) and a PhD from University College Dublin (2009). Before academia, he worked as a software developer and project manager. His research focuses on robotics, human-robot interaction, IoT, and Ambient Assisted Living (AAL), with leadership roles in EU projects like METRICS/HEART-MET and the OpenAAL initiative. He co-directs the MSc Robotics program and established the Robotic Assisted Living Tested lab within the UK National Robotarium. Key research interests include assistive robotics for frailty, healthcare robotics, and self-adaptive robotic systems. Notable contributions include the FP7 RUBICON project (2011-2014) and the Cognitive Assistive Robotic Environment (CARE) group. He has received awards such as the 2024 Principal's Research Impact Award and 2022 Research Team of the Year. Recent articles emphasize healthcare applications, modular robotics, and trustworthy AI. His work aligns with UN SDGs addressing healthy aging and sustainable cities.

En-Hui YangView profile

Professor

• Information Theory
• Multimedia Compression
• Digital Communications
• +3 more

Dr. En-Hui Yang is University Professor in Electrical and Computer Engineering at the University of Waterloo and founding Director of the Leitch-University of Waterloo Multimedia Communications Lab. A world-renowned expert in information theory, he co-developed the Yang-Kieffer algorithm for lossless compression and invented soft decision quantization technology used in smartphones and web browsers. His research spans multimedia compression, digital communications, and deep learning. Education: Ph.D. Electrical Engineering, University of Southern California (1996) Ph.D. Probability and Statistics, Nankai University (1991) B.Sc. Applied Mathematics, HuaQiao University (1986) His transformative work in data compression has impacted millions globally through technologies accelerating data transmission efficiency. Articles focus on optimization of video/image compression standards (HEVC/H.264), channel coding theorems, and novel compression algorithms. Scientific Awards: IEEE Eric E. Sumner Award (2021) Canada Research Chair - Tier 1 (2010, 2017) Fellow of the Royal Society of Canada (2009)

• Machine Learning
• Computer Vision
• Human Behavior Analysis
• +5 more

Dr. Harshala Gammulle is a Research Fellow at Queensland University of Technology (QUT), School of Electrical Engineering & Robotics. She holds a PhD in Computer Vision from QUT (2019), receiving the QUT Executive Dean's Commendation for Outstanding Doctoral Thesis. Her expertise spans machine learning, computer vision, and spatio-temporal modeling for human behavior understanding. She leads interdisciplinary projects with funding from DST Group, SmartSat CRC, QLD DESI, and others. Research focuses include: human action recognition, medical anomaly detection, satellite image analysis, and AI for environmental monitoring. Key projects involve quantum-classical hybrid ML for biomedical signal analysis, disaster forecasting via hyperspectral data, and autonomous combat vision systems. She has supervised PhD/MPhil candidates in ML and quantum hybrid ML. Education: PhD (Computer Vision, QUT 2019), BSc (University of Peradeniya, Sri Lanka). Awards: WiT Emerging Achiever Technology Award finalist (2021), University Award for Academic Excellence (2015). Teaching includes units like Digital Signals and Image Processing (EGH444), and Computing & Data for Engineers (EGB103). Current grants involve QLD DESI, SmartSat CRC, and Rheinmetall Defence Australia collaborations. Active in labs like SAIVT and QUT's Early Career Research schemes.

Hyuck M. KwonView profile

Professor

• Wireless Mobile Communications
• Communication Systems
• Information Theory
• +6 more

Hyuck M. Kwon is a Full Professor of Electrical and Computer Engineering at Wichita State University (WSU), part of the College of Engineering. His research focuses on wireless communications, including satellite systems, smart antennas, MIMO, and CDMA. He has held academic appointments since 1985, including visiting roles at institutions like KAIST and George Mason University. Kwon has supervised numerous PhD and MS students and has been recognized with prestigious awards, including the Dwane and Velma Wallace Outstanding Educator Award. His work spans over 100 publications and grants from agencies like the Air Force and NASA. He has developed courses such as '5G Wireless Communications' and 'Information Theory'. Education: Ph.D. in Computer, Information and Control Engineering, University of Michigan (1984) MSEE, Seoul National University (1980) BSEE, Seoul National University (1978) Research Interests: Wireless communications and networks Smart antennas and MIMO systems 5G/6G technologies Signal processing for communications Anti-jamming and secure communications Grants and Awards: Over $2M in research funding from the Air Force, NASA, and industry partners Awarded multiple Air Force Summer Faculty Fellowships (2014–2016) Nominated for NAI Fellow (2017) Lab/Teams: Active in developing advanced communication systems, including satellite digital beamforming and nano-antenna research with metamaterials.

• Reliable Hardware Design
• Electronic Design Automation
• Edge Computing
• +4 more

Dr. Abusaleh Jabir is a University Reader at the School of Engineering, Computing and Mathematics, Oxford Brookes University. He holds a DPhil in Computing from the University of Oxford and leads the Advanced Reliable Computer Systems (ARCoS) group. His research focuses on reliable hardware design, memristive nanotechnology, edge computing, and secure authentication systems. He has over 80 peer-reviewed publications and multiple patents, including innovations in error-tolerant circuits and memristive architectures. **Education**: DPhil in Computing (University of Oxford). **Research Interests**: Reliable hardware design, electronic design automation, sensing at the edge, physical uncloneable authentication, and emerging memristor technologies. His work addresses challenges in IoT, edge computing, and cybersecurity through innovative electronic systems. **Funding & Projects**: Current projects include the Leverhulme Trust-funded MONITOR gas sensor array initiative. His research has been supported by the UK Ministry of Defence, EPSRC, and Finance South East. **Awards & Patents**: Multiple patents granted, including EU 17706875.6 (memristive logic) and GB 1914221.5 (reconfigurable memristive logic). Recognized with best paper awards. **Advising & Impact**: Supervised PhD students now leading semiconductor and automotive industries (e.g., Infineon Technologies, Continental Teves AG). Collaborates with academic and industrial partners globally. **Labs & Teams**: Leads the ARCoS group within the Artificial Intelligence, Data Analysis and Systems (AIDAS) Institute, fostering interdisciplinary innovation in secure and reliable electronics.

Andrew SartaView profile

Assistant Professor

• Business
• Management
• Organizational Adaptation
• +3 more

Dr. Andrew Sarta is an Assistant Professor of Strategy at the School of Administrative Studies, York University. He specializes in organizational adaptation and behavioral strategy within socially/technologically changing environments. His research focuses on traditional sectors like financial services (FinTech emergence) and healthcare innovation. Sarta holds a PhD in Strategy from Ivey Business School, Western University. He also serves as an Honorary Research Fellow at UCL School of Management and has held fellowships across institutions including UCL's Innovating Across Sectors Program and Western University's Digital Banking Lab. Research Interests: Business strategy, organizational adaptation mechanisms, managerial attention processes, cognitive configurations in decision-making, and innovation dynamics in FinTech and healthcare sectors. His work bridges strategic management theory with practical industry challenges, emphasizing early-stage adaptation processes. His articles explore AI applications in strategy, digital transformation processes, and cognitive models of organizational behavior. Recent work emphasizes futuring techniques, Bayesian approaches to strategic shifts, and fuzzy-set analyses of technological prisms. Featured in Academy of Management, Strategic Management Society, and EGOS conferences Recipient of two Best Paper Awards Over 10 years strategic management experience in Fortune 500 firms Advising & Grants: While no specific students/advising roles are listed, Sarta's industry experience and academic fellowships suggest active engagement in collaborative research initiatives. Labs/Teams: Active in UCL Innovating Across Sectors Program, Ivey's Digital Banking Lab, and the Dalla Lana School of Public Health.

Madhav ErraguntlaView profile

Teaching Professor

• Machine Learning
• Artificial Intelligence
• Healthcare Technology
• +3 more

Madhav Erraguntla is a Teaching Professor of Industrial & Systems Engineering at Texas A&M University , affiliated with the TEES Center for Remote Health Technologies and Systems . He holds the Mike and Sugar Barnes APT Faculty Fellow title. His research focuses on applying machine learning and AI to healthcare and supply chain management, particularly in diabetes, wearable sensor technologies, and predictive modeling. With over 25 years of industry experience, Dr. Erraguntla has contributed to analytics at AT&T (smart home technologies) and i2 Technologies (retail CRM systems). He leads projects funded by DoD, HHS, and NASA, including national blood inventory surveillance systems. He is a Professional Engineer in Texas and a member of the Institute of Industrial and Systems Engineers (IISE). Education : Ph.D., Industrial Engineering, Texas A&M University (1996); M.Tech., Industrial Engineering, NITIE, India (1989) Key Projects : SBIR grants, mosquito population modeling, diabetes management algorithms, and wearable sensor development His work bridges healthcare innovation and engineering, emphasizing real-world applications in diabetes, emergency hospital management, and public health surveillance. Recent research highlights include AI-driven glucose forecasting, hypoglycemia detection systems, and environmental impacts on disease vectors like Zika virus transmission.

Zhao ZhaoView profile

Assistant Professor

• Wearable Systems
• Human-Computer Interaction (HCI)
• Human-Robot Interaction (HRI)
• +4 more

Zhao Zhao is an Assistant Professor at the School of Computer Science, University of Guelph. Her work focuses on wearable systems, human-robot interaction, and gamification for health and education. She holds a PhD from Carleton University (2019) and completed a postdoctoral fellowship at the University of Toronto (2019–2023) before roles at McMaster University and her current position. Education includes a BSc in Computer Science from University of Electronic Science and Technology of China (2011), MSc from Carleton University (2014), and PhD in Electrical and Computer Engineering (2019). Research interests span physiological computing, AI-assisted creativity tools, and adaptive systems leveraging wearable sensors. Key research areas include: 1) Wearable-based gamification for health and education, 2) Emotion sensing via physiological signals, and 3) Human-robot interaction enhanced by wearable data. Her lab uses Empatica EmbracePlus wristbands and Emotiv EEG headsets to analyze real-time physiological responses in diverse interaction scenarios. Recent publications (2020–2025) emphasize personalized exergame systems, child-robot interaction studies, and AI linguistic competency analysis. She actively seeks graduate students and industry partnerships in wearable technology, education tech, and HRI.

Ahmet TekalpView profile

Professor

• Digital Image Processing
• Video Compression
• Motion-Compensated Video Filtering
• +5 more

Ahmet Tekalp is a Professor in the Department of Electrical and Computer Engineering at Koc University's College of Engineering since 2001. He holds dual citizenship in Turkey and the USA, with prior academic roles at the University of Rochester (1986-2005) and research positions at Eastman Kodak (1984-1987) and Rensselaer Polytechnic Institute (1981-1984). He chairs the Electronics and Informatics Group at TUBITAK since 2004 as a part-time position. B.S. (1980) in Electrical Engineering & Mathematics, Bogaziçi University M.S. (1982) and Ph.D. (1984) in Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute His research focuses on digital image and video processing, including video compression, motion-compensated filtering for high-resolution applications, video segmentation, object tracking, content-based video analysis, multi-camera surveillance processing, and digital content protection. He has led numerous European and U.S. grants, including FP7 STREP projects and NSF awards, emphasizing applications in sensor networks, visual databases, and medical imaging. His scholarly work spans diverse areas such as superresolution reconstruction, head gesture animation, 3DTV streaming, and reversible data hiding. He has played pivotal roles in editorial boards, including serving as Editor-in-Chief of Signal Processing: Image Communication, and has contributed to major standards bodies like ISO MPEG and ANSI NCITS. Member, Turkish Academy of Sciences (TUBA) Fellow, IEEE Fulbright Senior Scholarship (1999) TUBITAK Science Award (2004) IEEE Signal Processing Society Distinguished Lecturer (1998) He has led multiple international research collaborations and projects, including European FP6/FP7 networks and NATO programs, with substantial grant funding from NSF, NYSTAR, and industry partners like Eastman Kodak, Xerox, and Siemens.