Halim Yanikomeroglu is a Full Professor and Chancellor's Professor at Carleton University's Department of Systems and Computer Engineering, part of the Faculty of Engineering and Design. His research focuses on wireless communications, including 5G/6G networks, non-terrestrial systems (HAPS/LEO satellites), MIMO, and cognitive radio. He has supervised numerous graduate students and holds IEEE Fellow status and the Harold Sobol Award. His work integrates machine learning, federated learning, and sustainability into next-generation networks. Affiliations: Carleton University, IEEE Education: Ph.D. (Toronto), M.A.Sc. (Toronto), B.Sc. (Middle East Technical University) Research interests span cellular networks, relay architectures, and energy-efficient systems. He pioneered cell-switching strategies for green networks and contributed to HAPS and UAV-based infrastructure. His recent work addresses NTN integration, AI-driven spectrum management, and 6G innovations. Awards include IEEE Fellow (2017) and multiple Research.com leadership accolades. His 150+ publications span journals like IEEE Transactions and conferences like ICC. Advising over 50 students, he emphasizes interdisciplinary solutions for future wireless challenges.
Prof. Xiaojing Huang is a Professor of Information and Communications Technology at the University of Technology Sydney (UTS), serving as Head of Discipline for SEDE Communications and Electronics within the School of Electrical and Data Engineering. He leads the Mobile Sensing and Communications program at the Global Big Data Technologies Centre. With over 30 years of experience, he has authored over 300 publications and 31 patents, focusing on wireless communications, signal processing, and antenna technologies. Education: PhD (Electrical Engineering, Shanghai Jiao Tong University, 1989). Previous roles include Principal Research Scientist at CSIRO (2009-2014), Associate Professor at University of Wollongong (2004-2009), and key industry roles at Motorola and Shanghai Yang Tian Science and Technology Corporation. Research interests include full-duplex wireless systems, millimeter-wave and terahertz communications, massive antenna arrays, and mixed-signal processing platforms. His work on the CSIRO Ngara backhaul system earned multiple awards, including the 2012 CSIRO Chairman's Medal and Australian Engineering Innovation Award. Recent grants include $4.2M (AUD) for projects like 'Radio Frequency Camera for Radar Imaging' (ARC DP220101158) and 'Terabit mm-Wave Backbones for Integrated Space Networks' (ARC DP200101532). He has supervised numerous students in high-speed communication systems and full-duplex technologies. Awards include: 2013 CSIRO Leadership Achievement Award, 2012 Australian Engineering Innovation Award, and IEEE Sumner Award (nominee). Active in IEEE standards (802.11/802.15) and collaborations with institutions like Tsinghua University.
Dr. Chih-Hung (James) Chen is a Professor in the Department of Electrical & Computer Engineering at McMaster University. His research focuses on noise-related issues in semiconductor devices, low-noise circuit design for medical and communication applications, and thermal noise characterization in nano-scale transistors. He holds senior member status in IEEE and is a licensed Professional Engineer in Ontario. Education: Ph.D., McMaster University, 2002 M.A.Sc., Simon Fraser University, 1997 B.Sc., National Central University, Taiwan, 1991 Research interests include biomedical technologies, microelectronics & VLSI, and digital/smart systems. He has collaborated with companies like Sony Corporation, United Microelectronics Corporation, and Focus Microwaves. His work is supported by grants from the Canada Foundation for Innovation (CFI), NSERC, and the Ontario Innovation Trust (OIT). Notable achievements include serving on the International Advisory Committee of the International Conference on Noise and Fluctuations (2015) and as an editor for the Journal of Low Power Electronics and Applications since 2022. Teaching includes courses like Analysis and Design of RF ICs for Communications and Electronic Devices and Circuits 2. His research lab focuses on advancing noise measurement techniques and designing ultra-low-power analog circuits for emerging applications.
Dr. Hillel Adesnik is a Professor in the Department of Neuroscience at the University of California, Berkeley, and a leading researcher in the neural basis of sensory perception. His lab focuses on cortical microcircuits, optogenetics, and neural coding, with emphasis on visual processing and memory formation. Key Research Areas: Cortical Microcircuits Optogenetic Tools Gamma Band Rhythms Neural Coding Mechanisms Dr. Adesnik has pioneered high-speed optical methods like 3D-MAP and 3D-SHOT to manipulate neural activity. His work spans cortical dynamics, synaptic plasticity, and cortical layer interactions, with applications in understanding learning algorithms and sensory inference. Selected Trends from Publications: Recent preprints and papers highlight advancements in cortical VIP neuron function, channelrhodopsin structures, and inter-areal computations. His team utilizes two-photon holography, cryo-EM, and computational modeling to decode perception-related neural codes. Scientific Awards: NIH Director's New Innovator Award (2013) Dr. Adesnik's lab collaborates with institutions like NIH and develops tools for awake animal studies. Funding includes grants from the Beckman Young Investigator Program and NIH.
Jaime Cardenas serves as an Assistant Professor at The Institute of Optics and holds a joint appointment as Assistant Professor of Physics at the University of Rochester. He joined the faculty in July 2016 after earning his Ph.D. in Optical Science and Engineering from the University of Alabama in Huntsville and gaining industry experience as a process engineer followed by research at the Cornell Nanophotonics Group. His educational background includes: Ph.D. in Optical Science and Engineering, University of Alabama in Huntsville Professor Cardenas' research centers on integrated photonics, nanophotonics, and nonlinear photonics, with current projects targeting photonic packaging, 2D materials integration, nonlinear optical phenomena, and on-chip quantum photonics. His group develops nanostructured photonic devices that manipulate light within chip-scale platforms, enabling applications in precision sensing, communications, and quantum technologies. This work bridges fundamental optical physics with practical engineering solutions for real-world implementation. Analysis of his recent publications reveals dominant themes in chip-scale photonic systems, particularly advancements in silicon nitride and lithium niobate platforms. Key research trajectories include weak-value amplification for ultra-precise optical gyroscopes, adiabatic frequency conversion in microring resonators, photonic packaging innovations via laser fusion splicing, and multispectral imaging sensor development. His work consistently emphasizes translating theoretical concepts into manufacturable integrated photonic devices with applications spanning navigation systems, spectroscopy, and quantum information processing. Professor Cardenas leads the Cardenas Lab, which specializes in creating photonic devices that fit on the tip of a needle. The lab's research portfolio spans from fundamental nonlinear optical phenomena to applied educational initiatives, including hands-on photonic kits designed to train the next generation of integrated photonics engineers. Current projects focus on developing robust, manufacturable photonic systems for industrial and defense applications while maintaining strong connections to quantum photonics research.
Kostas Daniilidis is the Ruth Yalom Stone Professor at the University of Pennsylvania in the School of Engineering and Applied Science , specifically the Department of Computer and Information Science . He is also affiliated with the GRASP Laboratory and Archimedes, Athena Research Center, Greece . Education : PhD in Computer Science (1992) from the University of Karlsruhe with Hans-Hellmut Nagel Diploma in Electrical Engineering (1986) from the National Technical University of Athens Research Interests : Kostas Daniilidis is a leading researcher in Computer Vision and Robotics , with significant contributions to event-based vision , equivariant learning , 3D human pose estimation , and hand-eye calibration . His work spans neural rendering , dynamic scene modeling , and low-latency sensing systems . Article Trends : Daniilidis’s recent publications focus on event cameras for low-light and high-speed applications, Gaussian splatting for real-time 3D reconstruction, and equivariant neural architectures for robust motion estimation. His work bridges deep learning with geometric vision , emphasizing human mesh recovery and multi-agent coordination . Scientific Awards : Best Conference Paper Award at ICRA 2017 IEEE Fellow (2012) Teaching : He has taught courses such as CIS580: Machine Perception and CIS121: Data Structures , alongside advanced topics in robotics and computer vision. Lab & Collaborations : As director of the GRASP Laboratory (2008–2013), he fostered interdisciplinary research in robotics, and currently collaborates with institutions like the Athena Research Center in Greece.
Michal Lipson serves as the Eugene Higgins Professor of Electrical Engineering and Professor of Applied Physics at Columbia University's Fu Foundation School of Engineering and Applied Science. Elected to both the National Academy of Engineering and National Academy of Sciences, she pioneered critical building blocks in silicon photonics that have transformed the field, with over 50,000 related publications annually. Her research has generated more than 250 scientific publications and 45 issued patents. Lipson's research focuses on nanophotonics and silicon photonics, where she demonstrated the ability to tailor electro-optic properties of silicon in landmark 2004 and 2005 Nature papers. Her work has enabled the development of photonic devices and circuits that now form the foundation of over 1,000 papers published yearly. She investigates novel optical phenomena while developing practical applications that address major bottlenecks in microelectronics. Her research spans fundamental physics to practical device implementation, with particular emphasis on integrated photonic systems. Analysis of her recent publications reveals a strategic expansion from foundational silicon photonics into emerging applications including quantum information processing, machine learning acceleration, biomedical sensing, and topological photonics. While maintaining core expertise in silicon-based devices, her work increasingly incorporates 2D materials, heterogeneous integration, and novel optical phenomena to push performance boundaries. The research demonstrates consistent progression from fundamental device physics to system-level implementations with practical applications. National Academy of Engineering (2025) National Academy of Sciences MacArthur Fellowship Blavatnik Award Optica's R.W. Wood Prize IEEE Photonics Award John Tyndall Award NAS Comstock Prize in Physics Thomson Reuters Top 1% Highly Cited Researcher (annually since 2014) Professor Lipson has mentored an exceptional research group, graduating 40 PhD students and 2 MS students, with numerous postdocs and visiting researchers. Her alumni occupy prominent positions including professorships at major universities (Rochester, Ottawa, UNICAMP, Johns Hopkins), leadership roles at Intel, Bell Labs, and startups she co-founded (HyperLight, Voyant Photonics). Her laboratory has received substantial research funding supporting cutting-edge work in nanofabrication, optical characterization, and device development. Current research directions include quantum photonics, AI-accelerated optical systems, and novel materials integration. The Lipson Research Group operates state-of-the-art facilities for nanophotonic device design, fabrication, and characterization. The team comprises principal investigators, postdoctoral researchers, PhD students, and administrative staff working collaboratively across disciplines including electrical engineering, materials science, physics, and applied physics. The group maintains strong industry partnerships while pursuing fundamental scientific advances in light-matter interactions at the nanoscale.
Xilin Liu is an Assistant Professor at the Edward S. Rogers Sr. Department of Electrical & Computer Engineering (University of Toronto) and the Center for Advancing Neurotechnological Innovation to Application (CRANIA) . He obtained his PhD from the University of Pennsylvania and previously worked at Qualcomm Inc. in California. Expertise in integrated circuits and systems for brain-machine interfaces , neuromodulation , and edge AI Published in top venues including Nature Electronics , IEEE JSSC , and ISSCC Recipient of multiple best paper awards and IEEE Senior Member His research spans three main themes: High-speed data converters for wireless/wireline communication IC design for neural interfacing Accelerating machine learning via hardware Recent publications focus on closed-loop neuromodulation , ultra-wideband transceivers , and flexible biomedical sensors . These works integrate analog IC design , edge AI , and real-time neural interfacing across medical rehabilitation , parkinson's monitoring , and memory research . Awards include: IEEE Solid-State Circuits Society Predoctoral Achievement Award (2016) Best Paper Award at BioCAS (2015) ECE Department Teaching Award (2022) Multiple conference best paper finalists His lab collaborates with UHN , EMBS , and global institutions while maintaining strong commitments to equity, diversity, and inclusion (EDI) in research practices.
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.
Nathan Youngblood is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Pittsburgh , with a secondary appointment in the Department of Physics and Astronomy . His research focuses on reconfigurable photonic materials and devices for energy-efficient artificial intelligence applications. Educational Background: PhD in Electrical Engineering from the University of Minnesota Postdoctoral research at the University of Oxford (2017–2019) His work explores photonic in-memory computing, neuromorphic systems, and phase-change materials to minimize computing latency and energy consumption. Recent publications highlight advancements in magneto-optical non-reciprocity, coherent crossbar arrays, and plasmonic-enhanced phase-change devices. Scientific Awards: NSF CAREER Award (2024) AFOSR Young Investigator Award (2024) William Kepler Whiteford Faculty Fellowship (2024) Dr. Youngblood's lab develops photonic accelerators like LightML and LightBulb for machine learning, emphasizing scalable integration and novel material applications in silicon photonics.
Yogananda Isukapalli is a Teaching Professor and Vice Chair in the Computer Engineering Program at the Electrical and Computer Engineering Department , University of California, Santa Barbara . He joined the faculty in Winter 2017 after a career as a staff scientist at Broadcom (2010–2017), where he designed Wi-Fi chips (11n/11ac/11ax) and worked on underwater wireless communication models during a postdoctoral stint at Scripps Institution of Oceanography (2009–2010). His PhD in Communication Theory and Systems from UC San Diego (2009) forms the basis of his expertise in wireless systems and digital design .
Tzu-Chien Hsueh is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of California, San Diego (UCSD), where he leads the Integrated Communication Circuits Lab. His research focuses on advanced CMOS and heterogeneous process technologies for high-speed, low-power communication systems, including transceiver design, silicon photonics, and data link optimization. He holds a B.S. and M.S. from National Taiwan University (1999-2001) and a Ph.D. from UCLA (2010). Before joining UCSD, he served as a Senior Research Scientist at Intel Labs (2010-2018), leading projects like 200Gb/s SerDes Links and 7nm CMOS Memory I/Os. He currently serves on the Technical Program Committee of IEEE CICC and IEEE SSCS mentoring programs. His honors include the IEEE JSSC Best Paper Award (2015) and multiple Intel recognitions. His lab emphasizes practical design innovations, theoretical analysis, and robust circuit implementations for applications in data centers, cloud computing, and broadband communication networks.
Duminda Wijesekera serves as Professor in the Department of Cyber Security Engineering and Department of Computer Science at George Mason University, where he was inaugural chairman of the Cyber Security Engineering Department until December 2022. He concurrently held the position of visiting research scientist at the National Institute of Standards and Technology (NIST) from 2007-2022 and maintains status as a fellow at the Potomac Institute of Policy Studies. He leads the Mason Innovation Laboratory at Mason Square, driving translational research in cyber-physical security. His educational foundation includes: PhD in Computer Science, University of Minnesota (1997) PhD in Mathematical Logic, Cornell University (1990) BSc in Mathematics, University of Colombo Professor Wijesekera's research centers on cyber-physical system security , with pioneering work in Intelligent Transportation Systems spanning trains, aircraft, and connected vehicles. His digital forensics innovations establish frameworks for evidence-based scenario reconstruction and error management, while his formal methods research provides mathematical guarantees for safety-critical systems. Current projects address Next G-based edge services, digital twin vulnerability detection, and healthcare security architectures, consistently bridging theoretical rigor with real-world infrastructure protection. Analysis of his 2022-2025 publications reveals intense focus on autonomous vehicle security (38% of recent output), including traffic signal control optimization, ramming attack countermeasures, and CARLA-based scenario validation. Digital forensics using AI (20%) and secure manufacturing/edge computing (27%) constitute other major thrusts, demonstrating how formal verification and machine learning converge to solve complex cyber-physical security challenges across transportation, energy, and healthcare domains. His scientific recognition includes: CCI Impact Award (2022) for groundbreaking cyber-physical security contributions Fellowship at the Potomac Institute of Policy Studies for cybersecurity policy leadership Professor Wijesekera has secured substantial research funding through: NIST grants for health record security frameworks (2014-2015) US Department of Transportation projects on wireless frequency mapping for high-speed rail (2013-2014) Cyber Security Research Alliance funding for trust architectures in cyber-physical systems (2014) Commonwealth Cyber Initiative awards for autonomous vehicle security and energy-efficient manufacturing His industry partnerships with Honeywell and NIST ensure practical impact of theoretical research. The Mason Innovation Laboratory under his direction serves as an interdisciplinary hub for cyber-physical security, integrating researchers from computer science, electrical engineering, and policy studies to develop deployable solutions for transportation networks, power grids, and critical infrastructure protection.
Wai Pang Ng is a Professor and Head of the Department of Mathematics, Physics and Electrical Engineering at Northumbria University. He holds a BEng (Hons) in Communications and Electronic Engineering from the University of Northumbria and a PhD in Electronic Engineering from the University of Wales, Swansea. His research focuses on radio-over-fiber systems, distributed fiber sensing, high-speed optical communications, and adaptive signal processing. Ng has held leadership roles in IEEE chapters and conferences, including chairing the IEEE UK&RI Communications Chapter (2011–2015) and serving as publicity chair for IEEE ICC 2015 and 2016. His research interests include innovative fiber optic sensor designs, acoustic wave devices for biomedical applications, and hybrid communication systems combining radio-over-fiber and free-space optics. Recent work emphasizes ultra-sensitive pressure/temperature sensors using microstructured fibers and acoustofluidic platforms for lab-on-a-chip applications. Ng has supervised seven PhD/MSc projects and actively contributes to standards development in optical communication systems. Ng’s publications span advanced sensor technologies, nonlinear compensation in optical systems, and turbulence-resistant free-space optical links. His work bridges academic research with practical applications in telecommunications, environmental monitoring, and healthcare diagnostics. Professional affiliations include IEEE technical committees (SPCE, TCGCC, ONTC) and guest editorships for IET Communications.
Daniele Ielmini is a Professor at the Department of Electronics, Information and Bioengineering at Politecnico di Milano, Italy, where he leads research in non-volatile memory technologies and neuromorphic computing. He received his Laurea (with merit) and Ph.D. in Nuclear Engineering from Politecnico di Milano in 1995 and 2000, respectively, and has held visiting positions at Intel Corporation (2006), Stanford University (2006), and the University of Illinois at Urbana-Champaign (2010). His research focuses on the modeling and characterization of non-volatile memories, including nanocrystal memory, charge trap memory, phase change memory (PCM), resistive switching memory (RRAM), and spin-transfer torque magnetic memory (STT-MRAM). He has co-edited the book 'Resistive switching – from fundamental redox-processes to device applications' and published over 300 papers with more than 10,000 citations and an H-index of 69 (Scopus, September 2023). Prof. Ielmini's recent publications demonstrate a strong trend toward in-memory computing and neuromorphic applications, with particular emphasis on closed-loop analog computing architectures, reservoir computing with 2D materials, and hardware security implementations using emerging memory technologies. His work bridges fundamental device physics with practical computing applications, especially for energy-efficient AI acceleration. Intel Outstanding Researcher Award (2013) ERC Consolidator Grant (2014) IEEE-EDS Paul Rappaport Award (2015) Fellow of the IEEE Prof. Ielmini leads multiple ERC-funded projects including SHANNON (Secure Hardware with Advanced Nonvolatile memories), NEURO2D (neuromorphic systems based on reservoir computing in MoS2), and ANIMATE (closed-loop in-memory computing). His research group includes post-doctoral researchers, PhD students, and M.Sc. students working on various aspects of emerging memory technologies and their applications. He serves as Associate Editor for IEEE Trans. Nanotechnology and Semiconductor Science and Technology (IOP), and has served in several Technical Subcommittees of international conferences including IEEE-IEDM, IEEE-IRPS, and IEEE-ISCAS. His laboratory at Politecnico di Milano is equipped with advanced semiconductor device testing equipment including probe-stations, semiconductor parameter analyzers, high-speed waveform generators, and other specialized instruments for nano-electronic research. The lab collaborates with major semiconductor companies including Micron Technology Inc. and STMicroelectronics, as well as participating in national and international research projects.
