Find Academic Supervisors

• Ubiquitous Computing
• IoT
• Wearables
• +3 more

Josiah Hester is an Associate Professor at the School of Interactive Computing within the College of Computing at Georgia Institute of Technology. His work focuses on sustainable computing, wearables, IoT, and ubiquitous computing with an emphasis on energy harvesting and culturally relevant technology design. Research Themes: Dr. Hester’s research integrates hardware-software co-design to enable battery-free and low-power systems. His projects include batteryless UAVs, sustainable smart masks (VeriMask), and culturally responsive educational tools for Hawaiian immersion schools. He also explores human-centered wearables, environmental sensors for climate justice, and energy-aware computing frameworks. Grants & Collaborations: His work is supported by NSF awards including DESC: Life-time aware design frameworks for sustainable edge devices, and collaborative research initiatives with international partners. Notable projects include the NSF-funded EquityWare (co-designing wearables for low-income communities) and Protean (adaptive hardware for battery-free computing). Labs: Directs the Josiah Hester Lab , though the current website link appears inactive. The lab focuses on Intermittent Computing and Sustainable Embedded Systems .

Bashima IslamView profile

Assistant Professor

• Machine Learning
• Mobile Computing
• Embedded Systems
• +6 more

Bashima Islam is an Assistant Professor in the Department of Electrical and Computer Engineering at Worcester Polytechnic Institute (WPI). Her research focuses on sustainable intelligent systems, energy-efficient AI for audio/speech, TinyML for edge devices, and AI-driven behavioral health outcomes. She earned her PhD in Computer Science from the University of North Carolina at Chapel Hill (2021) and a BSc from Bangladesh University of Engineering and Technology. Education: PhD in Computer Science, University of North Carolina at Chapel Hill, 2021 BSc in Electrical and Computer Engineering, Bangladesh University of Engineering and Technology Research Interests: Machine Learning, Mobile Computing, Embedded Systems, Ubiquitous Computing, and interdisciplinary applications in healthcare and sustainability. Her work bridges foundational AI with real-world impact through sensor fusion and energy-efficient designs. Awards & Honors: NSF CRII Award (2022) Forbes 30 Under 30 in Science (2021) EECS Rising Star (UC Berkeley, 2020) World Finalist, Microsoft Imagine Cup (2013) Teaching: Courses include On-Device Deep Learning, Embedded Systems Analysis, and graduate seminars. Current courses in Spring 2025: ECE/CS/DS 556 and ECE Graduate Seminar. Labs & Teams: Director of the BASH Lab, focusing on wearable health sensors and edge-AI systems. Collaborations include NIH-funded projects on multimodal health monitoring.

Davide BrunelliView profile

Associate Professor

• Energy Harvesting
• Wireless Sensor Networks
• Internet of Things
• +18 more

Davide Brunelli is an Associate Professor in the Department of Industrial Engineering at the University of Trento, Italy. His research focuses on energy harvesting, ultra-low-power embedded systems, and wireless sensor networks, with applications in IoT, environmental monitoring, and smart infrastructure. He has led numerous EU-funded and industrial research projects and maintains active collaborations with institutions such as ETH Zurich and the University of Bologna. Education: Ph.D. in Electrical Engineering, Telecommunications and Computer Science, University of Bologna (2007) M.Sc. in Electrical Engineering (summa cum laude), University of Bologna (2002) His research interests include energy scavenging for embedded systems, low-power wireless sensor networks, energy-aware communication protocols, battery-less systems, indoor positioning, and IoT applications in agriculture, structural health, and smart buildings. His work bridges hardware and software optimization for sustainable, self-powered sensing systems. The most recent publications reflect a strong trend toward self-powered and transiently-operated systems, energy-neutral architectures, and intelligent sensing with applications in environmental monitoring, industrial IoT, and localization. Key themes include energy harvesting integration, ultra-low power communication, and real-time adaptive algorithms. Scientific Awards: Best Paper Awards at IEEE/ACM conferences (2011, 2014, 2016, 2017, 2018, 2020, 2021) Research.com Computer Science in Italy Leader Award (2024, 2025) Research.com Electronics and Electrical Engineering in Italy Leader Award (2025) Brunelli has supervised numerous research projects and advised EU and national funding agencies as an independent expert. He has led key initiatives such as IoT Proto Lab, GreenDataNet, and EnerViS, and has secured significant industrial partnerships with Telecom Italia, STMicroelectronics, and Hewlett-Packard. He serves as Editor-in-Chief of the journal Sensors and has organized major conferences including IEEE Metrology for Industry 4.0 and ACM ENSSys. He is actively involved in technology transfer, co-founding WISPES srl and transferring energy harvesting innovations to Telecom Italia. His lab supports a testbed for CPS and WSN applications, including deployments in tunnels and smart buildings.

Muslum Ozgur OzmenView profile

Assistant Professor

• Systems Security
• IoT Security
• Privacy
• +5 more

Muslum Ozgur Ozmen serves as an Assistant Professor in the School of Computing and Augmented Intelligence at Arizona State University, where his research centers on enhancing security and privacy for emerging computing platforms and their physical-world interactions. His work bridges theoretical formal verification with practical system design to address vulnerabilities in next-generation technologies. Dr. Ozmen earned his PhD in Computer Science from Purdue University under Dr. Z. Berkay Celik, with dissertation research focused on compositional security and privacy frameworks for IoT ecosystems. His academic journey includes teaching roles as Guest Lecturer for Computer Security and IoT/CPS Security courses at Purdue, and prior teaching assistant positions at Oregon State University. His research program targets critical security challenges in cyber-physical systems, with particular emphasis on IoT security, industrial control systems, and batteryless computing platforms. Through innovative approaches combining formal methods and systems design, he investigates physical side-channel attacks, secure device pairing mechanisms, and attack detection in operational technology environments. Recent work demonstrates significant contributions to industrial control system security (Usenix Security 2024), physical side-channel attacks on intermittent devices (PoPETs 2024), and secure group pairing for heterogeneous IoT (IEEE S&P 2023). Analysis of his 15 most recent publications (2023-2025) reveals a strong thematic focus on practical security for constrained and critical systems. Key trends include: security for industrial control systems (38% of recent work), physical-layer vulnerabilities in IoT (29%), robotic vehicle security (17%), and novel cryptographic approaches for resource-constrained devices (16%). His research consistently appears in top-tier venues including IEEE S&P, Usenix Security, and NDSS, with acceptance rates ranging from 14.5% to 29%. Dr. Ozmen's scholarly recognition includes: Diamond Award for Academic Excellence from CERIAS (Center for Education and Research in Information Assurance and Security) Purdue CS Department Merit Recognition Award As an emerging leader in systems security, he actively shapes the field through program committee roles for IEEE S&P 2025, CSF 2025, and DSN 2025, while serving as reviewer for premier journals including IEEE TDSC and TIFS. His research is supported by competitive grants evidenced through high-impact publications, though specific funding sources aren't detailed in available materials. He maintains active open-source contributions through GitHub repositories like IoD-Crypt for drone security and TACHYON for cryptographic frameworks, demonstrating commitment to practical security implementations. Dr. Ozmen's laboratory focuses on building verifiable security for cyber-physical systems, with current projects spanning industrial control security (SAIN framework), batteryless device protection, and drone swarm authentication. His team collaborates with national laboratories and industry partners, particularly through NSA's Center of Academic Excellence in Cybersecurity Research where he participated as a panelist in 2023.

• Wireless Networks
• Internet of Things (IoT)
• Energy Harvesting
• +4 more

Jeroen Famaey is a Professor at Ghent University's Department of Information Technology, Faculty of Engineering and Architecture. His research focuses on wireless communication systems, IoT, energy-efficient networking, and millimeter-wave technologies. He leads projects in 5G/6G enablers, battery-less devices, and extended reality (XR) networking. Key contributions include energy-aware scheduling algorithms for industrial IoT, mmWave-based VR systems, and standardization efforts in nanoscale localization. His work spans over 200 publications across journals like IEEE Internet of Things Journal and conferences such as GLOBECOM. He collaborates extensively with industry partners, advancing practical applications of wireless technologies in smart cities and industrial automation. Current research emphasizes zero-energy devices and terahertz communication for future networks.

• Applied Mathematics
• Inverse Problems
• 3D Structure Modeling
• +6 more

Pasi Raumonen is a Professor of applied mathematics at the Faculty of Information Technology and Communication Sciences, Tampere University. His research focuses on 3D structural modeling of trees and forests using laser scanning, uncertainty quantification, and their applications in ecological studies. He is a Principal Investigator in the Academy of Finland’s Centre of Excellence in Modelling and Imaging (2018–2025) and the FAME Flagship (2024–). His work integrates applied mathematics, remote sensing (Lidar/point cloud analysis), and computational methods to address ecological and environmental challenges. Key contributions include methodologies for non-destructive biomass estimation, tree architecture analysis, and quantitative structure models for forest ecosystems. Raumonen has developed tools like the 4DRoot software for root phenotyping and SimpleTree for TLS-based tree modeling. Publications span interdisciplinary topics such as tropical forest fragmentation impacts, tree biomass quantification, and the role of auxin gradients in branching patterns. His research bridges mathematical modeling with real-world ecological applications, emphasizing precision and scalability in environmental monitoring. Grants and collaborations include the FAME flagship and international projects in Amazonian forests and African savannas. He actively contributes to open-source tools and data-sharing initiatives, promoting reproducibility in ecological research.

• Evolutionary Algorithms
• Machine Learning
• Optimization
• +7 more

Giovanni Iacca is an Associate Professor at the University of Trento's Department of Information Engineering and Computer Science (DISI), where he serves as Coordinator of the Master's Degree in Computer Science and Deputy Director of the Information Engineering and Computer Science Doctoral School. He leads the Distributed Intelligence and Optimization Lab (DIOL) and teaches courses including Computer Architectures, Introduction to Machine Learning, Bio-Inspired Artificial Intelligence, and Optimization Techniques across multiple academic programs. PhD in Computer Science, University of Jyväskylä, Finland (2011) MSc in Computer Engineering, Technical University of Bari, Italy (2006) Professor Iacca's research focuses on the intersection of evolutionary computation, machine learning, and optimization with applications in distributed systems and robotics. His work spans from theoretical foundations of memetic computing and multi-objective optimization to practical implementations in soft robotics, embedded systems, and healthcare applications. Recent efforts emphasize interpretable AI, particularly in reinforcement learning contexts, where his team develops methods to make decision processes transparent while maintaining performance. His research bridges the gap between fundamental algorithmic development and real-world engineering challenges, with over 15 years of industrial experience in optimization applied to engineering, logistics, and scheduling. Analysis of his recent publications reveals a strong trend toward interpretable AI systems, particularly in reinforcement learning contexts, with significant contributions to federated learning optimization, evolutionary neural architecture search, and applications in healthcare scheduling. His work consistently combines evolutionary algorithms with modern machine learning techniques to solve complex optimization problems across diverse domains including soft robotics, batteryless edge computing, and supply chain management. Scientific Awards: EvoApplications Best Paper Award (2017) UKCI AWARENESS Best Paper Award (2012) IEEE CIS Outstanding Student-Paper Award (2011) Professor Iacca actively supervises a large research group with numerous PhD students across multiple doctoral programs, including Information Engineering and Computer Science, Industrial Innovation, and the National PhD in Artificial Intelligence for Society. His lab has secured significant research funding through collaborations with industry partners and international research consortia. Recent grants support work on interpretable reinforcement learning, federated optimization, and applications of evolutionary computation in healthcare and robotics. He has also been appointed to editorial roles for prestigious journals including IEEE Transactions on Evolutionary Computation and Evolutionary Intelligence. The Distributed Intelligence and Optimization Lab (DIOL) under Professor Iacca's leadership comprises over 30 researchers including postdocs, PhD students, and master's students. The lab maintains strong international collaborations and has developed specialized expertise in evolutionary computation, interpretable AI, and optimization for embedded systems. Current projects include work on the EIC Pathfinder Challenge "Awareness Inside," development of methods for batteryless edge intelligence, and applications of evolutionary algorithms to healthcare scheduling problems.

Henry DuweView profile

Adjunct Assistant Professor

• Energy Harvesting
• Embedded Systems
• Neural Networks
• +5 more

Henry Duwe is an Affiliate Assistant Professor at Iowa State University, specializing in energy-efficient computing systems and embedded systems design. His research focuses on batteryless intermittent systems, energy harvesting, and low-power hardware architectures. He has contributed to the development of frameworks for dependable computing in resource-constrained environments and explores intersections between design thinking and engineering education. His work includes pioneering studies on lifecycle management protocols for batteryless networks, RF energy harvesting systems, and neuromorphic accelerators. Notably, he received the NSF CAREER Award (2022) for advancing intelligent computing on batteryless devices. Duwe also investigates pedagogical methods such as design thinking to enhance course design in computer engineering, addressing challenges in interdisciplinary education and student skill development. Key areas of exploration include: batteryless networks, neural architecture search for energy-constrained devices, hardware-software co-design, and debugging methodologies in engineering curricula. His publications span both technical innovations in embedded systems and educational strategies for effective learning. Recent projects include the PAIL protocol for robust coordination in batteryless systems (2025) and the Lure simulator for intermittent networks (2024). His research bridges theoretical advancements with practical applications in low-power computing and sustainable energy solutions. Awards and grants include the NSF CAREER Award (2022), which supports his work on dependable intelligent computing systems. His contributions also extend to educational innovations like persona-based course design and reflective learning activities in engineering education.

Wayne BurlesonView profile

Professor

• Embedded Security
• Hardware Security
• VLSI Circuit Design
• +7 more

Wayne Burleson is a Professor in the Department of Electrical and Computer Engineering at the University of Massachusetts Amherst, affiliated with the Manning College of Information and Computer Sciences. His research focuses on embedded security, hardware security, VLSI circuit design, and VLSI architectures for digital signal processing (DSP), cryptography, and graphics. He has pioneered work on physically unclonable functions (PUFs), remote power attacks on FPGAs, and thermal management strategies in chip multiprocessors. He holds a B.S. and M.S. from MIT (1983) and a Ph.D. from the University of Colorado (1989). His honors include the 2011 IEEE Fellow distinction and the 1999 Ben Dasher Award for Best Paper. He is actively involved in IEEE, ACM, ASEE, and Sigma Xi societies. Burleson’s recent work addresses grand challenges in embedded security, including IoT device vulnerabilities, medical device cybersecurity, and mitigation of hardware Trojans. His lab explores novel approaches in reconfigurable hardware security, energy-efficient asynchronous interconnects, and adaptive systems-on-chip.

• Spin-based Computing
• Nanomagnetic Systems
• Low-power Electronics
• +4 more

Erik Folven is a Professor at the Department of Electronic Systems at NTNU. He co-leads a multidisciplinary research group focusing on spin-based computational paradigms. His work includes coordinating the EU FET-Open SpinENGINE project (collaborating with European universities and IBM) targeting extreme low-power computing devices, and leading the NRC-funded SPrINTER project developing batteryless intermittent computing technologies. Research interests span artificial spin systems, superferromagnetism, nanomagnetic ensemble modeling, domain engineering in oxides, and advanced imaging/fabrication techniques (X-PEEM, MFM, EBL). He teaches semiconductor devices (TFE4146) and solid-state electronics (TFE4172) at NTNU. Current projects aim to revolutionize sustainable computing through spin-based technologies that reduce energy waste and integrate computation/memory functions.

• Internet of Things (IoT)
• Ubiquitous Sensing
• Edge Computing
• +4 more

Associate Professor Sara Khalifa is a faculty member in the School of Information Systems at Queensland University of Technology (QUT), within the Faculty of Science. Her research focuses on energy-efficient IoT systems, edge computing, and lightweight machine learning for resource-constrained devices. She pioneered foundational work in Energy Harvesting Sensing (EHS) during her tenure at CSIRO's Data61, enabling energy-positive sensing paradigms. Education: PhD in Computer Science and Engineering from UNSW (2017), recipient of the prestigious John Makepeace Bennett Award for best dissertation in Australasia. Research interests span ubiquitous sensing, machine learning for IoT, and sustainable energy harvesting technologies. Her work bridges theoretical advances with real-world applications such as speech emotion recognition and wearable health monitoring systems. Awards: 2017 John Makepeace Bennett Award (CORE) 2017 NSW Mobility Innovation of the Year Merit R&D Award at APICTA (Asia Pacific ICT Alliance) Her research has generated significant IP and attracted commercial interest. Current supervision topics include energy harvesting techniques for environmental monitoring systems. Key contributions include developing self-powered IoT systems and energy-neutral activity recognition frameworks, advancing both theoretical foundations and practical implementations.

Nicolas ConstantinView profile

Professor

• Analog and RF microelectronics
• Microwave circuits
• Wireless communications
• +5 more

Nicolas Constantin is a Professor in the Department of Electrical Engineering at École de technologie supérieure (ÉTS), Université du Québec, where he teaches courses including Electrical Circuits (ELE105) and Analog Microelectronics (SYS811). His research focuses on analog and RF microelectronics, microwave circuits, and wireless communications, with specific expertise in RF transmitters and receivers, test methods for analog and RF circuits, and power integrity in high-speed switching systems. His educational background includes: B.Eng. from École de technologie supérieure (ÉTS) M.Sc.A. from Polytechnique Montréal Ph.D. from McGill University Dr. Constantin's research spans multiple domains within electrical engineering, with a consistent focus on improving the linearity and efficiency of RF power amplifiers through innovative techniques like positive envelope feedback. His work bridges fundamental circuit design with practical applications in wireless communications, aerospace systems, and power electronics. Recent research has expanded into GHz-range power integrity modeling for switch-mode converters, millimeter-wave identification systems, and integrated solutions for avionic applications, demonstrating both depth and evolution in his technical contributions. Analyzing his publication record from 1995 to 2025 reveals a clear progression from fundamental device characterization to sophisticated integrated system solutions. Early work focused on GaAs FET behavior and nonlinear analysis of power amplifiers, while more recent publications address system-level challenges in power integrity, millimeter-wave identification, and aerospace electronics. A consistent thread throughout his career has been the development of envelope feedback techniques for RF power amplifiers, which has resulted in multiple patents and continues to drive innovation in wireless communication systems. Dr. Constantin has actively supervised numerous graduate students through doctoral and Master's research projects. His students have explored topics including positive envelope feedback techniques, power integrity in SiP implementations, millimeter-wave antenna systems, and integrated control circuits for aerospace applications. His supervision spans both theoretical analysis and practical implementation, preparing students for careers in both industry and academia. As a key member of the LACIME (Communications and Microelectronic Integration Laboratory) at ÉTS, Dr. Constantin contributes to a research environment that spans from functional materials to communication protocols. The laboratory's multidisciplinary approach enables innovative solutions in micro- and nanofabrication, integrated circuit design, and photonic systems, with strong industry partnerships that facilitate technology transfer and real-world application of research findings.

• Wireless Sensor Networks
• Energy Harvesting
• Ultra-Low-Power Electronics
• +5 more

Kari Halonen serves as Professor in the Department of Electronics and Nanoengineering at Aalto University School of Electrical Engineering. Leading the Kari Halonen Group, his research focuses on ultra-low-power electronics for energy-constrained applications including wireless sensor networks, wearable systems, and implantable medical devices. His work bridges the Internet of Everything with personalized health technologies through advanced signal acquisition and power management solutions. Research interests center on sensor electronics and energy harvesting with emphasis on ultra-low-power analog/digital implementations for wireless sensor devices. Key application areas include personalized health monitoring through advanced user interfaces and biomedical information acquisition. Current projects demonstrate practical implementations like the Gesture Sensor Interface Demonstrator for gaming applications and urine-powered sensor nodes for smart diapers. Recent publications (2024-2025) reveal strong focus on flexible electronics for biomedical applications, temperature-invariant circuits , and in-memory computing architectures . Work spans neuromorphic computing, printed energy harvesters, and RF-to-DC converters, consistently targeting sub-nW power consumption for batteryless systems. Major venues include IEEE Transactions journals, ISCAS, and FLEPS conferences. Scientific awards include: Beatrice Winner Award at IEEE Solid-State Circuits Conference (2002) Best paper award at Asian Conference on Millimeter-wave circuits and Technology (2007) Second best paper award at ECCTD Conference (2007) As primary advisor, Halonen supervises doctoral researchers including Gaurav Singh and Kazybek Adam. His group develops practical demonstrators like the Gesture Sensor Interface while advancing theoretical foundations in ultra-low-power circuit design. Current projects integrate printed electronics with biological energy harvesting, targeting commercialization through Aalto University's research portal. The Kari Halonen Group operates within Aalto's Department of Electronics and Nanoengineering, utilizing facilities in the TUAS-building at Maarintie 8, Espoo. Collaborations span biomedical researchers (Raimo Sepponen) and semiconductor experts across multiple institutions, with recent work appearing in IEEE IoT Journal and SN Computer Science.

Mimi XieView profile

Assistant Professor

• IoT Systems
• Non-Volatile Memory Optimization
• Energy Harvesting
• +3 more

Mimi Xie is an Assistant Professor in the Department of Computer Science at the University of Texas at San Antonio (UTSA), part of the College of Sciences. She holds a Ph.D. in Electrical and Computer Engineering from the University of Pittsburgh, with prior degrees from Chongqing University. Her research focuses on optimizing energy-efficient, secure, and intelligent IoT systems, particularly in non-volatile memory, energy harvesting, and tiny AI. She leads interdisciplinary efforts addressing challenges in data processing for IoT devices and sustainable computing solutions. Dr. Xie has received the prestigious NSF CAREER Award and co-PI roles in TranSET projects on traffic risk prediction and reinforcement learning. Her work appears in top venues like DAC, ICCAD, DATE, and IEEE journals. She advises multiple Ph.D./Master’s students (Sahidul, Jishnu, Wei, Shyamala) and actively serves on technical program committees for GLSVLSI, IEEE Cloud Summit, and ISVLSI. Key research themes include intermittent systems, energy-efficient AI inference, and secure embedded computing. She has developed frameworks like ELIXIR for self-powered IoT and Autotile for battery-less embedded systems. Over 60+ publications span smart healthcare systems (PPG-based health monitoring), environmental adaptive neural networks, and reinforcement learning for traffic networks. Her academic service includes organizing workshops (e.g., TinyML at DAC 2023), mentoring initiatives like the EDA Job Fair at ICCAD, and outreach efforts such as a virtual summer camp for students with disabilities. She balances technical leadership with educational advocacy, winning the GHC Faculty Award 2020.

Matthew HicksView profile

Associate Professor

• Software Security
• Hardware Security
• Embedded System Security
• +5 more

Matthew Hicks is an Associate Professor in the Department of Computer Science at Virginia Tech, serving as the CACI Faculty Fellow in Cyber Security. His research focuses on software, hardware, and embedded system security, particularly in energy harvesting and IoT systems. He holds a Ph.D. from the University of Illinois Urbana-Champaign (2013), an M.S. from the same institution (2008), and a B.S. from the University of Central Florida (2006). His research interests emphasize hardware security mechanisms, defensive routing against malicious designs, and resilient computing in energy-constrained environments. Notable contributions include work on FPGA fingerprinting, compiler-assisted fuzzing, and intermittent computing paradigms. Recent publications explore countermeasures against hardware trojans, energy-efficient buffering, and secure checkpointing in batteryless systems. Dr. Hicks has no listed academic awards but maintains an active publication record in top-tier conferences. His work bridges theoretical computer science with practical hardware implementations, addressing vulnerabilities at both software and physical layers. While no student advisees or grants are explicitly mentioned, his research portfolio demonstrates sustained engagement with cutting-edge cybersecurity challenges.