Kaiyuan Yang is an Associate Professor in the Department of Electrical and Computer Engineering at Rice University, leading the Secure and Intelligent Micro-Systems (SIMS) Lab. His research focuses on low-power integrated circuits and bioelectronic implants for applications like the Internet of Everything and medical devices. He holds a B.S. from Tsinghua University (2012) and M.S./Ph.D. degrees from the University of Michigan (2017). Research Interests: Low-power digital/analog/mixed-signal systems Bioelectronics and implantable devices Hardware security and PUF design Mixed-signal computing and emerging materials Recent work emphasizes magnetoelectric-powered implants, secure backscatter communication, and in-memory computing architectures. His publications span top venues like IEEE ISSCC, IEDM, and ACM MobiCom. Awards: 2022 NSF CAREER Award 2022 IEEE Top Picks in Hardware Security 2016 IEEE SSCS Predoctoral Achievement Award Dr. Yang serves on editorial boards for IEEE TVLSI and program committees for ISSCC/CICC. His lab develops miniature, secure, and energy-efficient systems for healthcare and IoT applications.
Michel M. Maharbiz is a Professor in the Department of Electrical Engineering and Computer Science at the University of California, Berkeley. He leads research on miniaturized bioelectronic interfaces, including neural dust implants and cyborg insects. He holds affiliations with the Berkeley Sensor & Actuator Center (BSAC), Center for Neural Engineering & Prostheses (CNEP), and SWARM Lab. His education includes a Ph.D. in EECS from UC Berkeley (2003) and a B.S. in EE from Cornell University (1997). Maharbiz's research integrates MEMS, ultrasonic systems, and synthetic biology to develop wireless neural interfaces, implantable sensors, and biohybrid devices. Key focus areas are neural dust technology for peripheral nerve recording, magnetoelastic strain sensors for medical applications, and electrochemical biosensing using bacterial flagellar motors. His publications emphasize neural interfaces, ultrasonic implants, and biomedical monitoring. Recent articles explore ultrasonic power delivery (2025), radiation detectors for oncology (2025), and fracture-healing smart plates (2019). Trends include miniaturization of wireless implants, closed-loop therapeutic systems, and novel biomaterials. Scientific Awards: McKnight Technological Innovations in Neuroscience Award (2017) Chan-Zuckerberg Biohub Investigator (2017) NSF CAREER Award (2009) MIT TR10 Top Emerging Technology (2009) Bakar Fellows Spark Award (2012) He directs the Maharbiz Lab, advancing neural dust and bioelectronic interfaces. Projects include impedance-based fracture monitoring, carbon fiber neural arrays, and hernia repair sensors. Funding includes NSF and industry partnerships for implantable device development.
Rajeev Alur is the Zisman Family Professor in the Department of Computer and Information Science at the University of Pennsylvania, leading the School of Engineering and Applied Science. He is the Founding Director of the ASSET Center for Trustworthy AI and a member of the PRECISE Center. His research focuses on formal methods for system design, integrating AI, cyber-physical systems, and machine learning with logical reasoning to ensure safety in autonomous systems. Alur has held leadership roles in major NSF projects like ExCAPE and has directed the Embedded and Multi-Scale Systems (EMBS) program. His research interests span formal verification, temporal logics, programming abstractions, and synthesis techniques. Notable contributions include the development of Nested Words (visibly pushdown languages), streaming string transducers, and tools like AutomataTutor for education. He has advised over 60 PhD students and postdocs, many of whom now hold academic and industry leadership positions. Alur’s awards include the 2024 Knuth Prize and the 2016 Alonzo Church Award. His work on Verisig and compositional verification of neural networks has advanced safety-critical AI applications. He teaches foundational courses like CIS 2620 and develops educational tools, emphasizing both theoretical rigor and practical impact. Key projects include the ASSET Center’s focus on trustworthy AI, integration of logical specifications in reinforcement learning, and formal verification of closed-loop systems with neural components. His publications span over 350 papers, with recent work addressing neurosymbolic learning, security in large language models, and efficient neural network verification.
Michael McAlpine is a Professor in the Mechanical Engineering department at the University of Minnesota . He also holds affiliations with the Biomedical Engineering and Electrical and Computer Engineering departments. His research focuses on 3D printing functional materials & devices , Nanoscale inks , Biomedical devices , Bioelectronics , and Flexible Microsystems . Research Interests : 3D Printing, Biomedical Engineering, Nanotechnology, Flexible Electronics, Microfluidics Labs : ME 361/363 Contact : mcalpine@umn.edu , (612) 626-3303, ME 117 Recent Research Trends include 3D Printed Biomedical Devices , Flexible Electronics , and Bioprinting Applications . His work spans from Spinal Organoid Formation to Programmable Drug Release Capsules . Scientific Award : Circulation Research 2020 Best Manuscript Award
Danick Briand is a Senior Scientist at the Soft Transducers Laboratory within the Microsystems for Space Applications Group (LMTS) at École Polytechnique Fédérale de Lausanne (EPFL). His work focuses on MEMS and Microsystems for environmentally friendly technology , integrating flexible and printed electronics with applications in energy harvesting , smart sensing systems , and advanced gas sensing . Research Themes : Environmental sensors using microsystem technology Green microtechnologies and micromanufacturing Ultra-low energy MEMS Energy-saving and harvesting systems Recent Publications : Developed transient biodegradable sensors and microwave sensing technologies using printed and degradable materials Explored flexible piezoelectric systems and wearable sweat analyzers for biomedical applications Advanced inkjet-printed biosensors and eco-friendly fabrication methods Labs & Collaborations : Soft Transducers Laboratory (EPFL) Laboratory for Microsystems (LMTS)
Dr. Akhilesh Jaiswal serves as Assistant Professor of Electrical and Computer Engineering at the University of Wisconsin-Madison, where his research pioneers device-circuit co-design for next-generation computing systems. His work focuses on enabling extreme-edge intelligence through processing-in-pixel technology, in-memory computing architectures, and bio-inspired neuromorphic systems. His academic credentials include: PhD in Nano-electronics from Purdue University (2019) MS from the University of Minnesota (2014) Bachelor of Technology from Shri Guru Gobind Singhji Institute of Engineering and Technology (2011) Dr. Jaiswal's research program centers on revolutionizing edge computing through hardware innovations that integrate sensing and processing. His device-circuit co-design approach leverages alternate state variables to create energy-efficient systems for real-time applications, with particular emphasis on retina-inspired sensors and photonic memory architectures. This work bridges semiconductor physics with AI acceleration needs, targeting applications from autonomous systems to biomedical devices. Analysis of his 2023-2025 publications reveals dominant themes in photonic SRAM-based in-memory computing (40% of output), retina-inspired motion processing (30%), and secure hardware architectures (20%). His team consistently develops novel bitcell designs that enable XOR logic execution within memory arrays while maintaining compatibility with CMOS fabrication processes. Recent work shows increasing focus on biomedical applications of processing-in-pixel technology. His distinguished recognition includes: Three consecutive ISI Exploratory Research Awards (2020-2023) IEEE Brain Community Best Paper Award (2022) 27 issued US patents with multiple pending applications Nomination for USC Moore Inventor Fellowship (2022) Dr. Jaiswal actively mentors graduate researchers through ECE 790/890/990 courses while securing exploratory funding through ISI and Keston Foundation awards. His patent portfolio demonstrates exceptional translational impact, with industry game-changer classifications from USPTO. The 2022 VLSI-SoC nomination and multiple research highlights in major outlets validate his contributions to hardware security and neuromorphic vision sensors. His laboratory develops integrated hardware platforms combining magnetic tunnel junctions, photonic memory, and CMOS image sensors to create unified processing-in-sensor systems. Current projects include retina-inspired motion segmentation for event cameras and electro-optic frequency transducers for quantum computing interfaces, with strong industry collaboration through patent licensing.
Christoph Keplinger serves as Managing Director of the Max Planck Institute for Intelligent Systems (MPI-IS) in Stuttgart, Germany, leading the Robotic Materials Department since 2020 and assuming overall institute leadership in 2023. He holds dual academic appointments as Honorary Professor at the University of Stuttgart and Eminent Visiting Professor of Soft Robotics at the University of Colorado Boulder, establishing him as a pivotal figure in bridging fundamental materials science with advanced robotics. His interdisciplinary approach integrates physics, chemistry, and engineering to pioneer breakthroughs in soft robotic systems. Keplinger's academic foundation includes a PhD in Soft Matter Physics from Johannes Kepler University Linz, Austria, followed by postdoctoral research at Harvard University focusing on mechanics and chemistry of soft materials. This unique background enabled his transition into robotics innovation, particularly in electrohydraulic actuation systems. His research program centers on three synergistic pillars: (I) soft robotics development through novel actuator technologies like HASEL artificial muscles; (II) energy capture mechanisms using soft materials; and (III) functional polymers engineered for robotic applications. This work produces transformative hardware that mimics biological functionality, with significant implications for human-robot interaction, medical devices, and sustainable robotics systems. His group employs cutting-edge materials synthesis and characterization techniques to create lifelike robotic components. Analysis of recent publications reveals dominant trends in wearable haptic interfaces, electrohydraulic actuation systems, and tremor-suppression technologies. The research consistently leverages HASEL (Hydraulically Amplified Self-healing Electrostatic) technology to achieve muscle-like performance in soft actuators, with applications spanning from fingertip haptic feedback to underwater manipulation systems. This trajectory demonstrates a clear progression from fundamental material properties toward practical implementations in medical rehabilitation and human augmentation. His exceptional contributions have earned prestigious recognition: 2017 Packard Fellowship for Science and Engineering, awarded for high-impact interdisciplinary research 2021 Alexander von Humboldt Professorship (declined to remain at MPI-IS), Germany's most valuable international research award 2013 EAPromising European Researcher Award from the European Scientific Network for Artificial Muscles As principal investigator, Keplinger leads a dynamic interdisciplinary research group while securing competitive funding for frontier projects. His entrepreneurial vision materialized in 2018 through co-founding Artimus Robotics, where he serves as Chief Science Officer to commercialize HASEL technology. This dual commitment to academic research and industry translation exemplifies his dedication to real-world impact, particularly in creating biodegradable and sustainable soft robotic solutions. The Robotic Materials Department operates state-of-the-art facilities for materials fabrication, robotic integration, and haptic interface development. The team maintains strong collaborations across MPI-IS departments and external institutions including the University of Colorado Boulder, fostering innovation in sustainable robotics through initiatives like biodegradable electrohydraulic actuators. Current projects focus on wearable tremor suppression systems, electrohydraulic locomotion platforms, and energy-autonomous soft robots that address critical challenges in medical rehabilitation and human augmentation.
Dr Bahareh Zaghari (MSc, PhD, CEng, FHEA) is a Lecturer in the Electrical Power Engineering group at the University of Southampton's School of Electronics and Computer Science. Her research focuses on electrified aircraft systems, sensors with machine learning applications, electrical power systems, and nonlinear dynamics modeling. Current projects include acoustic sensing for temperature/flow measurement Co-design of electrical machines for aircraft electrification Research activities span hybrid-electric aircraft design (FutPrint50 Horizon project), fully electric aircraft development (EnabEl Innovate UK), and smart sensing systems for aerospace components. Industrial collaborations include KISTLER, iNetic, PALL Aerospace, Safran, ARUP, Embraer, and BAE Systems. Conference coordinator for IEEE Transportation Electrification Council's Electrified Aircraft committee Chair of IEEE/AIAA Electrified Aircraft Technology Symposium (2023) Panel moderator at AIAA Propulsion and Energy (2021) Her work demonstrates innovative applications of acoustic transducers in harsh environments, with contributions to temperature mapping, fault analysis, and energy harvesting systems. She currently supervises PhD student Shikhar Singh.
Nori Franco serves as Professor in the Department of Physics at the University of Michigan and Chief Scientist at RIKEN's Theoretical Quantum Physics Laboratory in Japan. His dual appointments reflect his significant contributions to both American and Japanese academic communities, with continuous service at Michigan since 1990 and at RIKEN since 2002. His research spans quantum information, condensed matter physics, and quantum optics, with particular focus on light-matter interactions, superconducting qubits, optomechanics, and quantum open systems. Franco's work bridges theoretical foundations with experimental implementations, especially in circuit quantum electrodynamics and quantum computing applications. Analysis of his recent publications reveals a strong emphasis on non-Hermitian quantum systems, quantum control techniques, and applications of quantum information science to fundamental physics problems. His research group consistently produces highly cited work, with publications appearing in top journals across quantum physics and condensed matter disciplines. Scientific Awards: Charles Hard Townes Medal (2024) - sole recipient for fundamental contributions to quantum optics and quantum information processing Research Doctorate Honoris Causa from University of Messina (2024) Highly Cited Researcher for eight consecutive years (2017-2024) Member of Academia Europaea (2023) Willis E. Lamb Medal (2023) for quantum electronics research Throughout his career, Franco has secured significant research funding and mentored numerous students and postdoctoral researchers. His work has received international recognition through invitations to deliver prestigious lectures including the Stanislav Ulam Lecture and Sir Nevill Mott Lecture in 2024. His research group maintains strong collaborations across multiple continents, reflecting his global impact on quantum physics. At RIKEN, Franco leads the Quantum Information Physics Theory Research Team within the Quantum Computing Center, directing cutting-edge theoretical work that complements experimental efforts in quantum computing hardware development.
Junfei Li is an Assistant Professor in the School of Mechanical Engineering at Purdue University. His research focuses on advanced acoustic technologies, including acoustic tweezers, acoustofluidics, metamaterials, and underwater communication systems. He specializes in multiphysics wave propagation, noise control, and energy harvesting. Li's work bridges fundamental science and engineering applications in biomedical devices, sustainable energy, and advanced materials. Research Interests: Acoustic tweezers for microscale manipulation Design of metamaterials for acoustic control Ultrasound and underwater communication systems Energy-efficient noise mitigation strategies His recent publications emphasize innovations in acoustic metasurfaces, nonreciprocal sound propagation, and biomedical acoustic applications. Li’s research has implications for improving medical imaging, energy sustainability, and next-generation acoustic devices. Awards & Recognition: None explicitly listed in the provided materials. Advising & Grants: No student advisees or grant information specified in the text.
Sanjay Jain is a Provost's Chair Professor in the Department of Computer Science at the School of Computing, National University of Singapore (NUS). His research focuses on theoretical computer science with particular emphasis on inductive inference, recursion theory, complexity theory, and computational learning theory. Education: B.Tech. in Computer Science from Indian Institute of Technology Kharagpur, India (1986) M.S. in Computer Science from University of Rochester, USA (1988) Ph.D. in Computer Science from University of Rochester, USA (1990) Professor Jain's research spans multiple areas of theoretical computer science. His primary contributions are in computational learning theory, where he has made significant advances in understanding the intrinsic complexity of language identification and the limits of inductive inference. His work on recursion theory explores fundamental questions about computability and complexity, while his research in complexity theory addresses structural aspects of computational problems. A notable achievement was his work on "Deciding Parity Games in Quasipolynomial Time," which won the prestigious STOC 2017 best paper award and later the EATCS-IPEC Nerode Prize. Professor Jain's publication record shows a consistent focus on theoretical foundations of computer science, particularly in learning theory and computational complexity. His recent work has expanded into automatic structures, semiautomatic models, and connections between computational learning and algebraic structures. There is a clear progression from foundational work on language identification to more complex models involving automatic functions, transducers, and connections to mathematical logic. Scientific Awards: STOC 2017 Best Paper Award for "Deciding Parity Games in Quasipolynomial Time" EATCS-IPEC Nerode Prize (2021) Professor Jain has served on the editorial board of Information and Computation and has been actively involved in the academic community through program committee memberships for major conferences including COLT, ALT, LATA, TAMC, and PRICAI. He has held leadership roles as program co-chair for ALT 2000 and ALT 2013, and conference chair for ALT 2005. His work has been supported by various research grants, though specific details are not provided in the available materials. Professor Jain leads research in theoretical computer science at NUS, where he has built a strong research group focused on computational learning theory and related areas. His work often involves collaborations with researchers from around the world, particularly with Frank Stephan, with whom he has co-authored numerous papers. His research group has made significant contributions to understanding the fundamental limits and possibilities of computational learning models.
Mark Bocko is a Distinguished Professor of Electrical and Computer Engineering at the University of Rochester, affiliated with the Hajim School of Engineering & Applied Sciences. He holds roles as Director of the Center for Emerging and Innovative Sciences (CEIS) and Director of Audio & Music Engineering. He earned his PhD in Physics from the University of Rochester in 1984, focusing on gravitational wave detectors. His research spans audio signal processing, sensors, superconductivity, and quantum computing. Notable contributions include flat-panel loudspeaker development, non-contact ECG sensors, and quantum coherence studies in Josephson junctions. Research interests include audio and acoustic signal processing, computer audition, and sensor technologies. His work integrates interdisciplinary approaches, combining electrical engineering, physics, and computer science. Awards include the 2012 Goergen Award for Teaching and Mercer Brugler Distinguished Teaching Professor (2008–2011). Recent publications address modal crossover networks for loudspeakers, vibrational touch sensing, and room impulse response modeling. He has advised PhD students on topics like spatial audio rendering and musical vibrato analysis. His labs focus on advancing audio engineering and smart sensor systems through collaborative industry partnerships.
Gabriel Alfonso Rincon-Mora is the Motorola Solutions Foundation Professor at the Georgia Institute of Technology's School of Electrical and Computer Engineering. A Fellow of the National Academy of Inventors, IEEE, and IET, he specializes in analog/power integrated circuits, energy-harvesting systems, and microelectronics. With over 200 articles, 44 patents, and 12 books, his work has produced 26 commercial power-chip products. His research spans: Analog and power-management ICs for efficient energy conversion Self-sustaining microsystems powered by thermal, mechanical, and environmental sources Nano-scale circuit designs for biomedical and wireless sensor applications Recent publications focus on piezoelectric energy harvesting, battery charging optimization, and low-power CMOS designs, demonstrating consistent innovation in power efficiency and miniaturization. Awards include the IEEE Charles A. Desoer Technical Achievement Award, National Hispanic in Technology Award, and recognition as one of "The 100 Most Influential Hispanics." He directs research in power IC design and mentors students through the Georgia Tech Analog Consortium. His laboratory develops integrated solutions for energy-constrained applications, including collaborations with industry partners like Texas Instruments.
Jacob P. Covey is an Assistant Professor in the Department of Physics at the University of Illinois at Urbana-Champaign (UIUC). He holds a Ph.D. in Physics from the University of Colorado Boulder (2017) and B.S. in Engineering Physics from the University of Wisconsin-Madison (2011). His research focuses on quantum optics, atomic physics, and quantum information science, particularly in quantum control of ultracold atoms and molecules, superradiance phenomena, and quantum networking. He leads the Covey Lab, which explores topics such as neutral atom quantum processors, Rydberg atom interactions, and precision measurement with optical clocks. Academic Positions: Assistant Professor at UIUC (2020–present); Richard Chace Tolman Postdoctoral Scholar at Caltech (2017–2020). Research highlights include pioneering work on Dicke superradiance in ordered atomic arrays and telecom-band quantum networking with Yb-171 atom arrays. He teaches undergraduate courses in mechanics, electromagnetism, thermodynamics, quantum physics, and quantum information. Scientific Awards: NSF CAREER Award (2024), Young Investigator Awards from AFOSR (2023) and ONR (2022), Springer Thesis Award (2018), and multiple fellowships including the Richard Chace Tolman Postdoctoral Fellowship (2017). His work bridges experimental and theoretical advances in quantum technologies, with contributions to quantum state control, precision metrology, and many-body quantum systems.
Michela Becchi is an Associate Professor in the Department of Electrical and Computer Engineering at North Carolina State University. She specializes in computer architecture, systems software, and applications, with a focus on heterogeneous systems, parallel algorithms, and acceleration techniques for bioinformatics, pattern recognition, and quantum computing. Her work spans multi-core CPUs, GPUs, FPGAs, and distributed clusters, emphasizing the boundary between hardware and software design. Dr. Becchi holds a Ph.D. and Master’s degree in Computer Engineering from Washington University in St. Louis (2009) and a Bachelor’s degree in Computer Engineering from Politecnico di Milano, Italy (2000). Her research has been recognized with prestigious awards, including the NSF CAREER Award (2015) and the University of Missouri System President Award for Early Career Excellence (2016). Her research interests include compiler and runtime techniques for heterogeneous systems, acceleration of bioinformatics algorithms, and high-speed networking applications. She has pioneered frameworks for efficient data transformation, GPU-accelerated compression, and memory-efficient graph algorithms for quantum computing. Her work also explores thread coarsening, mixed-precision auto-tuning, and secure multi-core processor design. Key contributions include the PILOT runtime system for GPU memory management, the GPU-FPtuner auto-tuner for floating-point applications, and innovative approaches to automata processors for genomic analysis. Her publications emphasize reproducible accuracy in scientific simulations and the optimization of irregular applications on many-core platforms.
