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Nai-Ching ChiView profile

Associate Professor

• Data Science
• Health Technology
• Dementia Care
• +4 more

Dr. Nai-Ching Chi is a tenured Associate Professor at the University of Iowa College of Nursing. She is a nurse scientist and informaticist conducting pioneering research at the intersection of data science, technology, and health, focusing on dementia care, multimorbidity management, pain management, family caregiving, and healthy aging. PhD in Biobehavioral Nursing and Health Informatics (University of Washington) MS in Clinical Informatics and Patient-Centered Technologies (University of Washington) MSN (University of California, San Francisco) BSN (Tzu Chi University, Taiwan) Dr. Chi's research integrates advanced data science and AI to develop digital interventions for vulnerable populations. Notable projects include the PACE-app for dementia caregiver pain management, AI-powered nursing communication tools, and NIH-funded studies on multimorbidity patterns in Alzheimer's patients. Her work informs clinical guidelines and leverages predictive modeling for early risk detection. Recent publications focus on AI-driven pain assessment, machine learning in multimorbidity analysis, usability of caregiving apps, and rural age-friendly ecosystems. Her work spans comorbidity indices, geriatric pain, and health informatics innovations. National Academy of Medicine Emerging Leader Forum nomination NIA Butler-Williams Scholar NIA Aging Initiative MCCs Scholar Hospice and Palliative Nurses Association Emerging Leader Award Dr. Chi mentors students in aging research and technology-driven healthcare. She serves on editorial boards, grant review panels, and university committees, while volunteering in nursing homes and international medical missions.

• Internet of Things (IoT)
• Wireless Communications
• Statistical Signal Processing
• +3 more

Professor Jinho Choi is a Chair and Professor in Radio Frequency at the School of Electrical and Mechanical Engineering, University of Adelaide, Australia. He holds a B.E. (magna cum laude) from Sogang University, and M.S.E. and Ph.D. degrees from KAIST. His research focuses on advancing wireless communication and sensing technologies, particularly in IoT, 5G/6G, non-terrestrial networks, and cognitive satellite systems. He authored three books and has been recognized with the 1999 EURASIP Best Paper Award, IEEE Fellowship, and inclusion in Stanford's Top 2% Scientists list since 2020. He currently serves as a Senior Editor of IEEE Wireless Communications Letters and editorial roles in multiple journals. Education: B.E. (Electronics Engineering) - Sogang University, Seoul (1989) M.S.E. (Electrical Engineering) - KAIST (1991) Ph.D. (Electrical Engineering) - KAIST (1994) Research Interests: Professor Choi's work addresses connectivity challenges in non-terrestrial networks, leveraging statistical signal processing and machine learning. Current projects include UAV-assisted LEO satellite technologies, cognitive satellite radios, and semantic communication protocols. His research aims to enhance global connectivity and efficiency in terrestrial and satellite networks. Publications: His recent work spans semantic communication, satellite quantum key distribution, federated learning optimization, and coverage diversity in mega constellations. These studies reflect trends in 6G-ready technologies, AI-driven communication systems, and hybrid satellite-terrestrial networks. Awards: 1999 Best Paper Award for Signal Processing (EURASIP) IEEE Fellow (Leadership in technical excellence) World’s Top 2% Scientists (Stanford University, 2020–present) Grants & Supervision: As a senior academic, he oversees grants in wireless innovation and has advised numerous students on advanced communication systems. His lab focuses on next-generation networks, integrating theoretical insights with practical implementations. Labs/Teams: Active in interdisciplinary teams at the University of Adelaide, collaborating on projects funded by industry and government to bridge gaps between academic research and real-world applications.

• Materials Science
• Energy Systems
• Magnetic Materials
• +5 more

Ian Baker is the Sherman Fairchild Professor of Engineering and Senior Associate Dean for Research and Graduate Programs at Dartmouth College's Thayer School of Engineering. His research focuses on materials for energy systems, mechanical behavior of materials, and advanced characterization techniques. He holds degrees from the University of Oxford (BA, 1979; D.Phil, 1982) and has been recognized as a Fellow by multiple prestigious organizations. Education: BA in Metallurgy and Science of Materials (Oxford, 1979), D.Phil in Metallurgy and Science of Materials (Oxford, 1982). Research Interests: Magnetic materials, high entropy alloys, snow/ice microstructure, biomaterials, and energy-efficient materials systems. Dr. Baker’s work bridges materials science with applications in energy systems and biomedical engineering. His recent publications emphasize sustainable magnet manufacturing and advanced materials characterization using machine learning. Awards: AAAS Fellow (2015), TMS Fellow (2012), Materials Research Society Fellow (2011). Professional Roles: Editor-in-Chief of Materials Characterization (2009–2020), Field-Chief-Editor of Frontiers in Metals and Alloys (2022–). He advises graduate students in materials science and leads projects funded by grants related to energy systems and biomaterials development.

Kenneth KentView profile

Professor

• Hardware/Software Co-Design
• Virtual Machines
• Reconfigurable Computing
• +5 more

Dr. Kenneth Kent is a Professor in the Department of Computer Science at the University of New Brunswick (UNB), where he has served for 14 years. He is the Director of the Information Technology Centre (ITC) and heads the Reconfigurable Computing Group. He also serves as Director of the IBM Centre for Advanced Studies - Atlantic and holds an Honorary Professorship at Hochschule Bonn-Rhein-Sieg. His research focuses on hardware/software co-design, reconfigurable computing, virtual machines, and embedded systems. Dr. Kent earned his PhD and Master of Science in Computer Science from the University of Victoria. His work has led to over 100 refereed publications and the supervision of 70+ graduate students. He co-founded WEnTech Solutions Inc., a software firm addressing waste-to-energy optimization. His awards include the IBM Faculty Fellow of the Year and Project of the Year (as Principal Investigator) for contributions to the J9 Java Virtual Machine. His articles span FPGA acceleration, compiler optimization, cloud storage security, and IoT intrusion detection. Recent work emphasizes energy-efficient Node.js systems and advancements in CAD tools like VTR 9 for FPGA architecture. Dr. Kent’s advising and grants include leading the IBM CAS Atlantic and directing industry-academia collaborations. He has pioneered technologies such as the Eclipse OpenJ9 JVM and the CephArmor storage interface, balancing academic research with commercial innovation. He leads the Reconfigurable Computing Group at UNB and collaborates with the Institute for Visual Computing in Germany. His research bridges theoretical computing and practical applications, with a focus on scalable systems and embedded technologies.

Seeram RamakrishnaView profile

Professor

• Circular Economy
• Nanotechnology
• Materials Engineering
• +4 more

Seeram Ramakrishna is a Professor of Materials Engineering at the Department of Mechanical Engineering, National University of Singapore (NUS), affiliated with the College of Design and Engineering. He holds a PhD from the University of Cambridge and a TGMP from Harvard University. His research focuses on circular economy, nanotechnology, and sustainable materials engineering, with notable contributions to electrospinning, biomaterials, and energy storage systems. Key educational background includes: PhD in Materials Science (University of Cambridge) TGMP in Advanced Manufacturing (Harvard University) Research interests span cross-disciplinary areas such as: Development of eco-friendly nanocomposites Electrospun nanofiber applications in healthcare and energy Circular economy frameworks for sustainable materials Advanced manufacturing techniques for biomedical devices His publications highlight innovations in: High-efficiency solar steam generation via core-shell fibers Flexible wearable sensors for health monitoring Green synthesis of supercapacitor materials Plastic waste circularity through informatics-driven approaches Notable projects include books on circular economy fundamentals and biomaterials. His work bridges material science with environmental sustainability, addressing global challenges in energy, healthcare, and pollution control.

Jagath SamarabanduView profile

Professor

• Artificial Intelligence
• Explainable AI
• Machine Learning
• +5 more

Jagath Samarabandu is a Professor in the Department of Electrical and Computer Engineering at Western University. He holds a Ph.D. and M.S. in Electrical Engineering from SUNY Buffalo, and a B.Sc. in Electronics and Telecommunication Engineering from the University of Moratuwa, Sri Lanka. His academic career spans since joining Western University in 2000, with prior post-doctoral experience at SUNY Buffalo and industry work at Life Imaging Systems Inc. Education: Ph.D. Electrical Engineering, SUNY Buffalo M.S. Electrical Engineering, SUNY Buffalo B.Sc (Eng) Electronics and Telecommunication, University of Moratuwa His research focuses on Artificial Intelligence, Machine Learning, Image Analysis, and Cyber Security , with applications in biomedical imaging, network intrusion detection, and civil infrastructure monitoring. He has supervised numerous graduate students working on topics ranging from chromosome analysis to smart grid security. Recent publications highlight his work in medical AI applications (auditory processing disorder diagnosis), industrial time-series analysis (using contrastive predictive coding), and network security frameworks (INSecS system development). He has contributed to 3D ultrasound segmentation, prostate motion compensation algorithms, and synthetic aperture radar systems. Key projects include NSERC-funded intelligent home monitoring systems for elderly care and low-cost synthetic aperture radar development for search-and-rescue applications.

Georgios B. GiannakisView profile

Professor

• Data Science
• Power Systems
• Network Science
• +7 more

Georgios B. Giannakis is a Full Professor, Endowed Chair, and Presidential Chair in the Department of Electrical and Computer Engineering at the University of Minnesota since 1999. He directs the Digital Technology Center and has held academic roles at the University of Virginia (1987-1999) and USC (1982-1986). His research spans Data Science, Wireless Communications, Network Science, and Statistical Signal Processing , with applications to IoT and power systems. Diploma in Electrical Engineering, NTUA (1981) MSc in Electrical Engineering, USC (1983) MSc in Mathematics, USC (1986) PhD in Electrical Engineering, USC (1986) His publications (470+ journals, 770+ conferences, 34 patents) focus on fading channel modeling, UWB localization, blind signal estimation, and cross-layer wireless design . Articles emphasize multicarrier systems, time-varying channels, and ultra-wideband communication , with citations exceeding 76,000 (H-index 145). Scientific Awards : EURASIP 'Athanasios Papoulis' Society Award (2020) IEEE Fourier Technical Field Award (2015) Gugliermo Marconi Prize Paper Award (2003) 9 Best Journal Paper Awards (IEEE/SPS & ComSoc) IEEE SPS Technical Achievement Award (2001) He has mentored over 50 PhD students and 25 postdocs, served IEEE as Distinguished Lecturer, and contributed to Greek university accreditation panels. His work bridges theoretical signal processing and practical communication systems .

Hari SubramonyamView profile

Assistant Professor

• Human-Computer Interaction
• Artificial Intelligence in Education
• Learning Sciences
• +4 more

Hari Subramonyam is an Assistant Professor (Research) at Stanford University's Graduate School of Education with a courtesy appointment in Computer Science. He serves as the Ram and Vijay Shriram Faculty Fellow at Stanford's Institute for Human-Centered AI (HAI) and is a core faculty member of Stanford HCI. Subramonyam earned his PhD in Information from the University of Michigan under advisor Eytan Adar. His research focuses on the intersection of Human-Computer Interaction (HCI) and Learning Sciences, specifically developing AI systems to augment human learning through cognitively informed design, co-design with educators, and transformative learning experiences. His work prioritizes ethical AI, responsible design practices, and human values in technology creation. Research spans generative AI for education, human-AI interaction paradigms, and accessible learning technologies. Subramonyam's publications demonstrate strong focus on human-centered AI systems for education, visualization, and creative applications. His recent work (2023-2025) concentrates on generative AI interfaces for writing assistance, educational tools, and collaborative systems, while maintaining consistent exploration of visualization techniques and AI transparency frameworks. Awards & Honors: Best Paper Award at CHI (2025, 2020, 2019) Honorable Mention Award at CHI (2025) Best Paper Award at IUI (2021) Ram and Vijay Shriram Faculty Fellow HAI Hoffman Yee Grant (2024) Cover Story in Interactions Magazine (2024) Advising & Grants: Leads 27 students including PhD advisee Neha Rajagopalan (co-advised) and diverse MS/BS researchers. Received HAI Hoffman Yee Grant (2024) for "Integrating Intelligence: Building Shared Conceptual Grounding for Interacting with Generative AI" as co-investigator. Teaches courses on data visualization (CS 448B) and educational technology design (EDUC 432). Labs & Leadership: Core faculty at Stanford HCI group, directing research on human-centered AI systems. Organizes workshops including "Tools for Thought" (CHI 2025) and "Human–AI Coevolution" (ICLR 2025). Maintains collaborations with National University of Singapore and University of Michigan.

Shawki M. AreibiView profile

Professor

• VLSI Physical Design Automation
• Reconfigurable Computing Systems
• Hardware/Software Co-Design for Embedded Systems
• +7 more

Shawki M. Areibi is a Professor and Area Head of Engineering Systems and Computing in the School of Engineering at the University of Guelph. His research focuses on VLSI Physical Design Automation, Reconfigurable Computing Systems, and Hardware/Software Co-design for Embedded Systems. He leads efforts in developing advanced algorithms for CAD tools, FPGA design, and machine learning applications. His work addresses challenges in VLSI layout optimization, parallel processing, and embedded systems design. Affiliations: AI Affiliated Faculty, Area Heads, Computer Engineering, Engineering Systems and Computing Research. Research Interests: VLSI Circuit Layout, Reconfigurable Computing, Machine Learning, and FPGA-based Accelerators. His research integrates meta-heuristics like Genetic Algorithms and Tabu Search to solve complex optimization problems. He has contributed to hardware acceleration frameworks for machine learning algorithms and embedded systems, with applications in domains like signal processing and data mining. His recent work includes congestion-estimation models for modern FPGAs and analytic placement tools for ultra-scale architectures. Publications span VLSI design, reconfigurable computing, and machine learning, emphasizing algorithmic innovation and hardware-software co-design. His students have explored topics ranging from FPGA placement to domain adaptation in remote sensing. Grants and Advising: Advises graduate and undergraduate students on projects involving FPGA acceleration, machine learning, and embedded systems. His labs focus on developing next-generation CAD tools and hardware accelerators.

• Networking and Communications
• Blockchain Technology
• Smart Grids and Energy Systems
• +5 more

Roberto Rojas-Cessa is a Professor in the Department of Electrical and Computer Engineering at New Jersey Institute of Technology (NJIT), affiliated with the School of Applied Engineering and Technology. His research focuses on networking, blockchain applications in smart cities, energy systems, wireless communications, and high-performance switching. He has led multiple National Science Foundation (NSF)-funded projects, including initiatives on controlled delivery power grids and next-generation network quality of service. Notably, his work explores blockchain for energy metering, sustainable environmental measures, and smart grid optimization. He is also a Senior Member of the National Academy of Inventors (2024). His research interests span network protocols, distributed systems, and IoT applications. Recent projects include AMI-Chain (a blockchain-based power metering system) and studies on indirect free-space optical communications for vehicular networks. He has contributed to advancements in medium access control for crowded networks and energy packet switches for digital microgrids. Rojas-Cessa’s work integrates machine learning for network management and flood impact analysis. He has developed tools for time-lapse analysis of urban data and agent-based models to evaluate electric vehicle adoption. His publications emphasize scalability, security, and efficiency in both traditional and emerging technologies. Grants: Collaborative Research on Power Grids (NSF, 2016–2018), NeTS-NR: Quality of Service Networks (NSF, 2004–2008) Awards: Senior Member of the National Academy of Inventors (2024) His lab activities include experimental evaluations of digital microgrids and blockchain implementations for carbon footprint tracking. He actively collaborates on projects addressing emergency communications and resilient energy distribution systems.

• Testability
• Built-in Self Test (BIST)
• Digital Circuit Testing
• +3 more

Professor Jacob Savir is a distinguished academic in the Department of Electrical and Computer Engineering at the New Jersey Institute of Technology . He specializes in testability, built-in self-test (BIST), and fault detection for digital and analog circuits. His work focuses on improving integrated circuit testing methodologies, including BIST pretesting, defect level analysis, and reliability optimization in safety-critical systems. His research interests span BIST architectures, delay fault analysis, analog circuit testing, and power-constrained test synthesis . He has contributed extensively to the development of testing algorithms for embedded memories, scan designs, and fault diagnosis in complex systems. Notable contributions include studies on the impact of BIST pretesting on IC defect levels and yield optimization. His work bridges theoretical advancements with practical applications in aerospace and industrial electronics. Despite no awards listed, his substantial citation count (1,897) and h-index (22) reflect his influential contributions to the field. Prof. Savir has collaborated on 114 research outputs since 1977, with a focus on enhancing circuit testability and reliability across domains like FPGA-based systems and embedded memory diagnostics. His research emphasizes both academic rigor and industrial relevance, addressing challenges in modern VLSI design and testing.

Azadeh DavoodiView profile

Professor

• Electronic Design Automation (EDA)
• Integrated Circuit Design
• Machine Learning in Hardware
• +5 more

Azadeh Davoodi is a Vilas Distinguished Achievement Professor and Associate Chair of Undergraduate Studies in the Department of Electrical and Computer Engineering at the University of Wisconsin-Madison. Her research focuses on Electronic Design Automation (EDA), integrated circuit debug, and machine learning applications in VLSI design. She holds editorial roles in journals like IEEE TCAD and ACM TRETS, and has chaired major conferences such as ISPD 2015 and served on technical program committees for DAC, ICCAD, and others. Education: PhD in Electrical Engineering, University of Maryland-College Park (2006) Research Interests: Machine learning for VLSI chip design VLSI design automation for machine learning IC-CAD for emerging nanotechnologies Hardware security Recent Research Trends: Her work bridges machine learning and hardware design, with publications on neural network optimization, distributed inference, and explainable AI for circuit design. She emphasizes energy-efficient CNNs, latency reduction in edge computing, and security in split manufacturing. Awards: 2025 DATE Best Paper Candidate 2024 Vilas Distinguished Achievement Professor 2015 ACM Best Paper Award 2011 NSF CAREER Award Service and Grants: Leads NSF-funded projects on explainable ML for CAD and holds grants for distributed neural network synthesis. Her service includes roles as IEEE HKN member and editorial board positions. Labs/Teams: Engages in interdisciplinary research teams at UW-Madison, focusing on EDA innovation and hardware-software co-design.

• Smart Grids
• Renewable Energy Integration
• Optimization of Power Systems
• +4 more

Cuo Zhang is a Lecturer of Power Engineering and ARC DECRA Fellow at the University of Sydney's School of Electrical & Computer Engineering. He holds a B.E. (Hons.) from the University of Sydney (2014) and a Ph.D. in Electrical Engineering from UNSW (2018). His research focuses on smart grids, renewable energy integration, voltage control, and optimization of power systems. Key interests include distributed generation planning, energy storage systems, and demand response mechanisms. Dr. Zhang leads research on enhancing distribution network resilience through advanced control strategies and participates in the Net Zero Institute. He has secured grants such as the 2024 ARC DECRA project on renewables hosting capacity. Supervised students include Yunqing Zhang, working on robust renewables integration. His recent publications emphasize data-driven approaches, decentralized energy trading, and adaptive control for unbalanced networks. He explores machine learning applications in energy management and stochastic optimization under uncertainty. Awards include the University Medal for academic excellence. Awards: ARC DECRA Fellow Grants: 2024 Robust Renewables Hosting Capacity Enhancement Labs/Teams: Member of the Net Zero Institute

Kshirasagar NaikView profile

Professor

• Mobile and Ad Hoc Networks
• Low Power Software
• Optical Networks
• +15 more

Kshirasagar Naik is a Professor in the Department of Electrical and Computer Engineering at the University of Waterloo, Ontario. He is actively involved in graduate research supervision and has been a member of IEEE since 1994. His academic career spans decades, with a focus on wireless communication, energy efficiency, and cybersecurity. 1992, Doctorate in Computer Engineering from Concordia University, Ontario 1988, Master of Mathematics in Computer Science from University of Waterloo, Ontario 1983, MTech in Computer Engineering from Indian Institute of Technology, Kharagpur, India 1981, BScEng in Electronics and Telecommunication from Sambalpur University, India His research interests include Mobile and Ad Hoc Networks , Cybersecurity , Internet of Things (IoT) , and Intelligent Transportation Systems . He has published extensively on energy optimization in wireless devices, delay-tolerant networks, and security protocols for vehicular systems. Recent publications highlight the integration of Machine Learning and IoT in environmental monitoring, particularly forest fire detection and prediction. Other works focus on cybersecurity , vehicular networks , and energy optimization in data centers and handheld devices. Professor Naik is currently accepting graduate students for research in mobile systems, network protocols, and green computing at the University of Waterloo.

• Nonlinear Dynamics
• Quantum Chaos
• Complex Networks
• +5 more

Ying-Cheng Lai is a Regents' Professor in the School of Electrical, Computer and Energy Engineering at Arizona State University (ASU), where he has been a full-time faculty member since 2005. He holds affiliations with the Center for Biodiversity Outcomes and the Center for Biological Physics. Previously, he served as the Sixth Century Chair in Electrical Engineering at the University of Aberdeen (2009–2017) and returned to ASU as the ISS Endowed Professor (2014–present). His academic journey includes a BS and MS in Optical Engineering from Zhejiang University (1982–1985), followed by MS and PhD in Physics from the University of Maryland, College Park (1989–1992). He completed a postdoctoral fellowship in Biomedical Engineering at Johns Hopkins University School of Medicine (1992–1994). His research focuses on Nonlinear Dynamics and Chaos , Machine Learning applied to complex systems, Relativistic Quantum Chaos , Complex Networks , Mathematical Biology , and Theoretical Ecology . He explores topics such as quantum scars in Dirac materials, synchronization control in networks, and early warning signals for ecological tipping points. His work integrates data analysis techniques with interdisciplinary applications in healthcare, climate science, and cybersecurity. His recent publications highlight advancements in machine learning-driven predictions for critical transitions, quantum transport modeling in graphene, and cybersecurity strategies for power grids. These trends reflect his commitment to bridging theoretical physics with applied engineering solutions. Awards: Regents Professor (ASU's highest faculty honor, 2021) Vannevar Bush Faculty Fellowship (DoD, 2016) Corresponding Fellow of the Royal Society of Edinburgh (2018) Foreign Member of Academia Europaea (2020) Fellow of AAAS (2020) Fellow of the American Physical Society (1999) Ying-Cheng Lai has advised 24 PhD and 20 MS students, supported 15 postdocs, and secured funding from agencies like DOD (AFOSR, ARO, Navy-ONR), NSF, and the National Academies. His grants include projects on quantum billiard systems, sensor applications, and network resilience in multilayer ecological frameworks. He runs a research group focused on advanced topics in electrical engineering and interdisciplinary physics.