Prof Christina Lim is a Professor at the Department of Electrical and Electronic Engineering, University of Melbourne, Australia. She serves as the Associate Dean of Research for the Faculty of Engineering and Information Technology (FEIT) and manages the Tucker Lab. Previously, she held roles as Research Group Leader of the Electronics and Photonics System group and Deputy Head of Department (Teaching and Operations) Education: PhD and Bachelors from University of Melbourne Research Interests: Radio-over-Fibre, Optical Wireless Communications, Microwave Photonics, Augmented Reality Displays, Reservoir Computing, Optical Crosshaul Networks Recent publications demonstrate expertise in optical waveguide design for AR, underwater optical wireless communications, photonic switching, and network optimization. Her projects focus on next-generation wireless infrastructure, including Photonics Computing Enabled Ultra-Broadband Wireless Communications (2024-2027, $598k ARC grant) and Additive Manufacturing of Optical Elements (2025). She has secured significant funding, including ARC Discovery Projects and Future Fellowships. Scientific Honors IEEE Fellow (2022) Optica Fellow (2018) ARC Future Fellow (2009-2013) ARC Australian Research Fellow (2004-2008) Professional Service Vice-President of Conferences, IEEE Photonics Society Deputy Editor, IEEE/Optica Journal of Lightwave Technology ARC College of Experts (2014-2016)
Naresh R. Shanbhag is the Jack Kilby Professor in the Department of Electrical and Computer Engineering and the Coordinated Science Laboratory at the University of Illinois at Urbana-Champaign. He serves as Director of the Systems on Nanoscale Information fabriCs (SONIC) Center and held the D.J. Gandhi Distinguished Visiting Professorship at IIT Mumbai from 2015-2020. Previously, he was a visiting faculty member at National Taiwan University (2007) and Stanford University (2014). Dr. Shanbhag received his doctorate from the University of Minnesota (1993) in Electrical Engineering. From 1993 to 1995, he worked at AT&T Bell Laboratories as the lead chip architect for AT&T's 51.84 Mb/s transceiver chips over twisted-pair wiring for Asynchronous Transfer Mode (ATM)-LAN and very high-speed digital subscriber line (VDSL) chip-sets. His research focuses on the design of energy-efficient machine learning, communications, and signal processing systems on resource-constrained embedded platforms. He explores fundamental trade-offs between energy efficiency, latency and accuracy of decision-making systems implemented in nanoscale technologies, with applications to computer vision, biomedicine, automatic target recognition, and imaging. His work spans four primary focus areas: Resource-efficient Machine Learning for the Edge, In-memory Computing (IMC), Energy-efficient High Data Rate Communications, and Shannon-inspired Statistical Error Compensation (SEC). Analysis of his recent publications reveals a strong emphasis on in-memory computing architectures (SRAM, MRAM, RRAM) for machine learning acceleration. His work consistently addresses energy-accuracy trade-offs, with increasing attention to security aspects of hardware implementations and applications to MIMO signal processing and edge AI systems. His research demonstrates a progression from theoretical foundations to practical silicon implementations. 2024 Semiconductor Research Corporation Innovation Award 2018 Semiconductor Industry Association/Semiconductor Research Corporation University Researcher Award 2018 IEEE International Symposium on Circuits and Systems Best Paper Award 2006 IEEE Fellow 1996 National Science Foundation CAREER Award Professor Shanbhag has mentored over 50 graduate students who now work at leading technology companies including Qualcomm, Amazon, Nvidia, Intel, and Apple. His research has been generously supported by the National Science Foundation, DARPA, AFRL, Semiconductor Research Corporation, Texas Instruments, Sandia National Laboratories, and industry partners including IBM, GlobalFoundries, and Intel Corporation. He led the Alternative Computational Models research theme (2006-2012) and was the founding Director of the SONIC Center (2013-2017), a 5-year multi-university center funded by DARPA and SRC. Currently, he leads research themes in the SRC and DARPA funded JUMP 2.0 Program's Center for Co-Design of Cognitive Systems and the Center for Ubiquitous Connectivity, and in the NSF IUCRC Center for Advanced Semiconductor Chips with Accelerated Performance (ASAP). As Director of the Systems on Nanoscale Information fabriCs (SONIC) Center, Professor Shanbhag leads a multidisciplinary team exploring novel computing paradigms for the nanoscale era. His group has benchmarked an extensive collection of in-memory computing and digital accelerator IC designs, maintaining a publicly available IMC benchmarking repository of metrics extracted from published IC prototypes. His research philosophy integrates concepts from information theory, statistical signal processing, detection and estimation, VLSI architectures, and digital and analog integrated circuits to develop energy-efficient systems from algorithms to silicon implementations.
Takeshi Ikenaga is a Professor at Waseda University’s School of Fundamental Science and Engineering and Graduate School of Information, Production and Systems . He earned his Ph.D. in Information & Computer Science from Waseda University in 2001, following B.E. and M.E. degrees in Electrical Engineering (1988–1990). His career spans roles at NTT LSI Laboratories (1990–2002), Kitakyushu Foundation for Advancement of Industry, Science and Technology (FAIS) (1999–2002), and visiting researcher at the University of Massachusetts (1999–2000). Research Interests : Application-specific SoCs for video/image processing, including compression (H.264/AVC, H.265/HEVC), filters (super-resolution, noise reduction), recognition systems (feature detection, object tracking), and communication (UWB, LDPC). He also works on many-core processor design, ultra-low-delay vision systems, and sports analytics (volleyball, figure skating) with real-time 3D pose estimation and ball tracking. Awards : Recipient of the Furukawa Sansui Award (Waseda University, 1988) IEICE Research Encouragement Award (1992) Multiple Best Paper/Presentation Awards (2006–2022) at conferences including DAC/ISSCC, LSI IP Design, ISOCC, ISPACS, and CVIT APSIPA Distinguished Lecturer Certificate (2015) Waseda University Presidential Teaching Award (2020)
Aydin Babakhani is a Professor in the Department of Electrical and Computer Engineering at the University of California, Los Angeles (UCLA), affiliated with the College of Life Sciences. He directs the Integrated Sensors Laboratory (ISL), which focuses on the design and implementation of integrated sensors and systems. His research spans high-speed wireless communication, terahertz technology, medical implants, radar systems, and industrial monitoring solutions. Research Interests: Prof. Babakhani's work integrates silicon-based technologies with applications across multiple domains. Key areas include: Silicon mm-Wave/THz transceivers and on-chip antennas for communication and sensing Wirelessly powered medical implants for biopotential monitoring and neural stimulation THz radar systems for micrometer-resolution imaging and vibration detection Energy harvesting solutions for batteryless sensors in industrial and biomedical applications CMOS-based optoelectronic systems and photonic computing accelerators His recent publications (2021-2025) demonstrate a strong emphasis on terahertz systems, wireless power transfer, and miniaturized medical electronics. Over 80% of his latest articles involve silicon-integrated solutions for biomedical implants or THz sensing, with emerging focus on AI-accelerated photonic computing and multi-Gbps wireless links.
Shiyu Su is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Waterloo. His research focuses on high-speed data converters, wireless transceivers, digital phase-locked loops (PLL), and AI-assisted analog/mixed-signal design automation. He holds a Ph.D. from the University of Southern California (2019) and teaches courses such as ECE 340 (Electronic Circuits 2) and ECE 432 (Radio Frequency Integrated Devices and Circuits). Education: B.S. from Beijing University of Post and Telecommunication (China) and Queen Mary, University of London (UK), 2011; M.S. and Ph.D. from USC, 2013 and 2019, all in electrical engineering. Research Interests: High-speed ADCs/DACs RF/mm-wave transceivers Time-approximation filters (TAF) Analog/mixed-signal design automation Memristor-based computing Biomedical interfaces Key Awards: IEEE SSCS Predoctoral Achievement Award (2017–2018) Best Student Paper Award at IEEE RFIC (2022) Ming Hsieh Institute Scholar (2019–2020) Lab Focus: The Shiyu Su Lab develops integrated circuits for communications, sensing, and computing, with a focus on AI-driven methodologies and digital-analog co-design. Collaborations include work with Prof. Wei Wu (USC) on memristor-based systems.
Andrew Miller is an Associate Professor in the Electrical and Computer Engineering department at the University of Illinois, specializing in Programming Languages, Formal Methods, Software Engineering, Security and Privacy, and Systems and Networking. His research focuses on blockchain technologies, cryptography, and secure systems. Professor Miller's research spans multiple critical areas in modern computer security. His work primarily focuses on blockchain technologies , where he has made significant contributions to understanding and improving the security, privacy, and performance of systems like Bitcoin and Ethereum. He has conducted empirical analyses of privacy in the Lightning Network and developed protocols for confidential smart contracts. His work in cryptography includes research on multiparty computation, zero-knowledge proofs, and formal methods for cryptographic protocol design. Miller also investigates security vulnerabilities in proof-of-stake systems and resource exhaustion attacks, contributing to the robustness of decentralized systems. His applied security research extends to privacy-preserving health applications, as evidenced by his work on the Safer Illinois platform for COVID-19 contact tracing. Miller's publication record demonstrates consistent contributions to top security and systems venues including IEEE Security & Privacy, ACM CCS, Financial Cryptography, and USENIX Security. His research shows a clear trajectory from foundational work in blockchain security to more applied systems addressing real-world privacy and security challenges. Recent work focuses on making multiparty computation services publicly auditable and developing decentralized identity solutions that maintain compatibility with existing systems. Distinguished Reviewer Award, IEEE Security & Privacy 2018 Professor Miller has advised students including Vivek Nair, who joined the prestigious Hertz Fellows program in 2022. He has taught various courses including Introduction to Algorithms & Models of Computation, Advanced Computer Security, Cryptography, Applied Cryptography, and Ideal Functionality in Cryptography. His research has received support through grants including the SaTC: CORE: Medium project on "Automated Support for Writing High-Assurance Smart Contracts" in 2018. Miller is actively involved in research groups focusing on blockchain security, cryptographic protocols, and privacy-preserving systems. His lab appears to collaborate extensively with researchers across multiple institutions, as evidenced by the diverse author lists on his publications. Current work seems to be focused on making decentralized systems more secure, privacy-preserving, and accessible for real-world applications.
Frede Blaabjerg is a Professor at Aalborg University (AAU Energy) , affiliated with the Faculty of Engineering and Science . Since 1998, he has pioneered power electronics research in applications such as wind turbines , photovoltaic (PV) systems , reliability engineering , and Power-2-X technologies. Education : PhD in Electrical Engineering (1995, Aalborg University) Honorary Degrees : Honoris Causa at University Politehnica Timisoara (2017) and Tallinn Technical University (2018) His research focuses on power electronics control , system optimization , and reliability for renewable energy and electric mobility . Recent work includes grid-forming converters , virtual synchronous generators , and smart EV charging systems. Key publication trends span 15+ years , with over 3,733 peer-reviewed articles and 900+ journal papers in power electronics , renewables , and energy storage . Notable book series: Control of Power Electronic Converters and Systems (4 volumes, Elsevier). Scientific Awards : 46 IEEE Prize Paper Awards 2020 IEEE Edison Medal 2019 Global Energy Prize 2014 IEEE William E. Newell Power Electronics Award Leadership Roles : Editor-in-Chief, IEEE Transactions on Power Electronics (2006–2012) Chairman, Danish Council for Research and Innovation Policy (2020–) President, IEEE Power Electronics Society (2019–2020)
Prof. Dr. Christian Breitsamter is a Professor at the Technische Universität München (TUM), leading the Chair of Aerodynamics and Fluid Mechanics within the TUM School of Engineering and Design. He has held this position since 2007 and has been a member of key committees such as the ICAS Programme Committee and STAB-Programmleitung. His research focuses on aerodynamics of aircraft and rotorcraft configurations, including vortex dynamics, aeroelasticity, and fluid-structure interaction. Education: PhD in Aerodynamics (1997) Master’s in Aerospace Engineering (1989) Research Interests: Prof. Breitsamter’s work spans experimental and numerical studies of high-agility aircraft, helicopter aerodynamics, and advanced wing designs. Key areas include leading-edge vortices, gust load mitigation using flexible wings, and flow control techniques. His group investigates cutting-edge topics like deep learning for buffet prediction and hybrid neural networks for aerodynamic modeling. Awards: Willy Messerschmitt Preis (1999) AIAA Associate Fellow (2007) Advising & Grants: While specific student names are not listed, his research involves collaborative projects with industry partners (e.g., RACER Compound Helicopter) and EU initiatives like the FURADO program. His team contributes to the NFDI4ING infrastructure for engineering data. Labs/Teams: Active in the Aerodynamics Wind Tunnel facilities (Windkanäle A/B/C) and leads the SAGITTA flying wing demonstrator project. His group also explores membrane wings and elasto-flexible morphing technologies.
Professor Peter F. Driessen is a faculty member in the Department of Electrical and Computer Engineering at the University of Victoria, with a cross-appointment in the School of Music. He holds a BSc and PhD from the University of Victoria and is a Professional Engineer (PEng). His research focuses on communication systems, signal processing, control, and interdisciplinary projects in computer music and wireless technologies. Key areas include audio/video signal processing, radio propagation, sound recording, and multimedia systems. He leads the University of Victoria Propagation Laboratory, which explores radio wave propagation and Amateur radio integration with engineering education. His work spans theoretical research and applied projects like ECOSat satellite systems, software-defined radio (SDR), and innovative musical instruments such as the Radio Drum. He supervises undergraduate and graduate projects in these domains through ELEC 499 courses. Notable contributions include the APEGBC Editorial Board Award for Best Paper (2002) and patents in wireless networking and signal processing. His teaching includes courses in signal analysis and electromagnetics, and he collaborates on interdisciplinary programs like the Music/Computer Science degree. Education: BSc in Electrical Engineering, University of Victoria PhD in Electrical Engineering, University of Victoria Research Interests: Audio and video signal processing for music and media Software-defined radio and Amateur radio technologies Satellite communication and ground station development Gesture-based interfaces and musical instrument design Error mitigation in streaming audio/video Optical and microwave-photonic systems Labs & Collaborations: Propagation Laboratory (radio wave research) UVic Experimental Radio Group (Amateur radio club) UVic Satellite Design Team (ECOSat projects) UVic Centre for Aerospace Research Grants & Awards: APEGBC Editorial Board Award (2002) Multiple US patents in wireless systems and signal processing
Nam Sung Kim is the W. J. "Jerry" Sanders III-Advanced Micro Devices Inc. Endowed Chair and holds a Professorship in Electrical and Computer Engineering at the University of Illinois. He is also affiliated with the Siebel School of Computing and Data Science, Coordinated Science Lab, and National Center for Supercomputing Applications (NCSA). His research focuses on computer architecture, memory systems, chiplet integration, and hardware security. Key areas include energy-efficient computing, processing-in-memory (PIM), and mitigating hardware vulnerabilities like rowhammer attacks. Kim has received prestigious awards including IEEE Fellow (2016), MICRO Hall of Fame (2018), NAI Fellow (2023), and NSF CAREER Award (2015). His work spans publications in top venues like ASPLOS and IEEE journals, addressing topics such as CXL-based memory systems, DRAM module optimization, and GPU architecture improvements. Collaborations emphasize interdisciplinary research in hardware-software co-design and emerging technologies. His labs and teams at Coordinated Science Lab and NCSA drive innovations in scalable computing, near-memory processing, and cloud infrastructure for AI workloads. Ongoing projects include developing resilient memory hierarchies and accelerating large-scale machine learning models through novel architecture designs.
Azita Emami serves as the Andrew and Peggy Cherng Professor of Electrical Engineering and Medical Engineering at the California Institute of Technology (Caltech), where she concurrently holds leadership roles as Executive Officer for Electrical Engineering and Director of the Center for Sensing to Intelligence. Appointed to Caltech's faculty in 2007, she progressed from Assistant Professor to her current endowed professorship through demonstrated scholarly excellence. Her academic foundation includes: B.S. in Electrical Engineering from Sharif University of Technology (1996) M.S. in Electrical Engineering from Stanford University (1999) Ph.D. in Electrical Engineering from Stanford University (2004) Professor Emami pioneers mixed-mode integrated circuit systems that bridge theoretical innovation with practical applications. Her research emphasizes ultra-low power consumption and high reliability in scalable semiconductor technologies, targeting transformative solutions across multiple domains. Key thrusts include: Biomedical implantables for neural recording/stimulation and gastrointestinal monitoring Photonics-electronics co-design for energy-efficient optical interconnects Machine learning-enhanced signal processing for brain-computer interfaces Miniaturized magnetic sensors with unprecedented noise performance Her work consistently demonstrates how circuit-level innovations enable breakthrough capabilities in medical diagnostics and high-speed computing. Analysis of her 2021-2024 publications reveals a strategic convergence of biomedical sensing and intelligent signal processing . While maintaining strong contributions to optical interconnects (accounting for ~40% of recent output), her lab increasingly focuses on closed-loop medical systems where low-power analog neural networks interpret physiological signals. This evolution reflects growing NIH and industry interest in implantable/wearable health technologies, with her group leading in CMOS-based sensor miniaturization and energy efficiency. Her professional recognition includes: IEEE Solid-State Circuits Society Distinguished Lecturer appointment Mentorship excellence is evidenced by students receiving prestigious awards including the Jakob van Zyl Predoctoral Research Award (Saransh Sharma, Ryoto Sekine) and Charles Wilts Prize (Kuan-Chang Chen). Her research program leverages strategic partnerships with Heritage Medical Research Institute and industry collaborators, supported through center-based funding like the Center for Sensing to Intelligence. Administrative leadership spans departmental governance (as Executive Officer) and conference organization (ISSCC technical committees). She directs Caltech's Mixed-mode Integrated Circuits and Systems Lab (MICS) , which operates as a nexus for cross-disciplinary innovation between electrical engineering and medical applications. The lab's industry-collaborative framework accelerates translation of circuit concepts into real-world biomedical solutions through the Center for Sensing to Intelligence.
Dr. Benjamin C.K. Tee is an Associate Professor at the National University of Singapore (NUS), affiliated with the College of Engineering and the Department of Materials Science and Engineering. He leads the Sensors.AI Labs, focusing on transforming materials science, mechanics, and biology into cutting-edge technologies for robotics and healthcare in the AI era. His research explores novel materials and fabrication techniques to develop flexible, stretchable electronic sensors. These innovations enable applications in human-machine interfaces, biomedical devices, and AI-driven robotic systems. Key areas include self-healing materials, large-scale tactile sensing, and wireless health monitoring. His work has garnered international acclaim, including the James Dyson Foundation Prize (International Winner, 2021), MIT TR35 Innovator (2015), and recognition as a World Economic Forum Young Scientist (2019). His inventions have been commercialized through co-founded startups Privi Medical (acquired in 2021) and Hannah Life Technologies. Scientific Awards: National Research Foundation Fellowship (2017) MIT TR35 Innovator (Global) (2015) World Economic Forum Young Scientist (2019) James Dyson Foundation Prize - International Winner (2021) IES Prestigious Engineering Award (2020) Stanford University Top 2% Scientists (2021)
Dr. Kanchana Thilakarathna is a Senior Lecturer in Distributed Computing at the University of Sydney's School of Computer Science, and a member of the Centre for Distributed and High Performance Computing. They hold a PhD from the University of New South Wales (UNSW) and a B.Sc. Eng (Hons) from the University of Moratuwa, Sri Lanka. Prior to academia, they worked as a Research Scientist at CSIRO/Data61 and had industry experience as a Mobile Radio Network Engineer. Research Interests : Dr. Thilakarathna focuses on cybersecurity, privacy in mobile and IoT systems, mixed reality privacy, and distributed computing platforms. Their work emphasizes user-centric solutions like the Yalut social media app, which enables decentralized data sharing. Key themes include privacy-preserving techniques, edge computing, and secure federated learning frameworks. Recent Work : Recent articles (2023–2025) explore machine unlearning for large language models, federated learning security, and IoT network slicing using P4 programmability. Their work on synthetic video traffic generation (VideoTrain++) and drone detection (DronePrint) demonstrates cross-disciplinary innovation. Awards : Malcolm Chaikin Prize (2015), Meta Research Awards (2020/2022), and Heidelberg Laureate Fellowship (2019). Grants : ARC Research Hub for Future Digital Manufacturing (2024), NSW Defence Innovation Network Projects (2024/2021), and Facebook Research Awards (2022/2020). Students : Advising 4 current PhD students on topics like wireless trust establishment and machine unlearning. Labs/Teams : Part of the Centre for Distributed and High Performance Computing and Sydney Nano Institute.
Prof. Dr.-Ing. Thomas Zwick is a full professor and director of the Institute of High Frequency Engineering and Electronics (IHE) at the Karlsruhe Institute of Technology (KIT). He holds a Dipl.-Ing. (M.S.E.E.) and Dr.-Ing. (Ph.D.E.E.) from the University of Karlsruhe. His career includes roles at IBM Research (2001–2004), Siemens AG (2004–2007 managing automotive radar teams), and KIT since 2007. He leads research in high-frequency technologies, antennas, radar systems, and wireless communications. Research interests include radio wave propagation, antenna design, automotive radar architectures, and millimeter-wave systems. He has authored/co-authored over 400 papers, 20 patents, and received IEEE Fellow status (2018), honorary doctorate from Budapest University (2022), and membership in the Heidelberg Academy and acatech. His work emphasizes integrating sensing and communication systems, 3D-printed RF components, and high-frequency measurement techniques. Teaching focuses on high-frequency engineering, electronic circuits, and radar systems. He oversees the IHE’s laboratories, including the Microwave Engineering Lab and Student Innovation Lab. Recent work explores sub-THz communication, RIS-aided ISAC systems, and beamforming for reduced EMF exposure in urban scenarios.
Dr. Jing Li is an Associate Professor and Eduardo D. Glandt Faculty Fellow at the University of Pennsylvania , holding dual appointments in the Electrical and Systems Engineering and Computer and Information Science departments. As co-director of the CyberSavvy nationwide security research center and director of the Penn Computational Intelligence Lab (PennCIL) , she pioneers innovations in non-von Neumann computing paradigms. Her research spans post-CMOS technologies, in-memory computing, and hardware-software co-design for security and AI applications. PhD in Computer Engineering, Purdue University (2009) BSc in Electrical Engineering, Shanghai Jiaotong University (2004) Research Focus: Dr. Li's work addresses fundamental challenges in computer systems across the stack. Key areas include: In-Memory Computing: Liquid Silicon architecture combining RRAM with silicon CMOS through monolithic 3D integration Security Engineering: Transforming computer security from "Art" to formal "Engineering" discipline within CyberSavvy Virtualization: Cloud FPGA abstraction layers decoupling compilation from runtime resource management Graph Analytics: Degree-aware optimization techniques for massive-scale graph processing Deep Learning Systems: Roofline model extensions for FPGA-based CNN acceleration Scientific Impact: Awarded DARPA Young Faculty Award , NSF CAREER Award , and IBM CEO Milestone Award , her team has achieved world records in energy-efficient computing (ENIAD supercomputer). With 46 U.S. patents and over 80 publications, she leads ecosystem development for emerging computing architectures through initiatives like the open-source MEG simulation platform . Community Leadership: Dr. Li serves on program committees for flagship conferences ( ISCA , FPGA Symposium ), chairs the International Memory Workshop , and contributes to the MLsys conference's inaugural committee. She actively mentors through multiple PhD openings and industry collaborations.
