Ruonan Han is a Professor of Electrical Engineering and Computer Science at MIT and serves as Associate Director of the Microsystems Technology Laboratories (MTL) and Director of the MIT-MTL Center for Integrated Circuits and Systems . His research focuses on ultra-high-frequency microelectronic circuits , particularly addressing the 'terahertz gap' in sensing, metrology, security, and communication. He leads the Terahertz Integrated Electronics Group at MIT's MTL, established in 2014. Education: B.S. in Microelectronics, Fudan University (2007) M.S. in Electrical Engineering, University of Florida (2009) Ph.D. in Electrical and Computer Engineering, Cornell University (2014) Research Interests: Terahertz (THz) integrated circuits and systems High-frequency CMOS technologies Quantum sensing and magnetometry RF systems for imaging, radar, and molecular sensing Energy-efficient communication systems His work bridges electronic circuits , electromagnetics , and quantum physics , with applications in defense, healthcare, and environmental monitoring. Awards & Recognition: 2023 IEEE SSCS New Frontier Award 2020 NSF CAREER Award 2019 Intel Outstanding Researcher Award 3× IEEE RFIC Best Student Paper Awards (2012, 2017, 2021) Advising & Leadership: Ph.D. advisor to over 10 students (many recipients of MIT MTL Dissertation Awards) Co-advises with Prof. Anantha Chandrakasan and Prof. Tomás Palacios Editorial roles at IEEE Transactions on Quantum Engineering and VLSI Systems Technical committee member for ISSCC, RFIC, and IMS Labs & Teams: Terahertz Integrated Electronics Group at MIT MTL: Focuses on chip-scale THz systems, quantum devices, and next-generation RF circuits Collaborations with industry (e.g., Apple, MediaTek) and academic groups (e.g., D. Englund's lab at MIT)
Romain Fleury is an Associate Professor at the Laboratory of Wave Engineering (LWE) , part of the École Polytechnique Fédérale de Lausanne (EPFL) School of Engineering and Institute of Electrical and Micro Engineering (IEL) . He earned a Ph.D. in Electrical and Computer Engineering from the University of Texas at Austin in 2015 under Andrea Alù, followed by a Marie-Curie Postdoctoral Fellowship at ESPCI Paris-Tech and CNRS Langevin Institute (2016). His research explores wave physics and engineering , focusing on topological insulators , nonreciprocal wave propagation , and time-modulated metamaterials . He has co-authored over 70 peer-reviewed articles in journals like Science , Nature , and Physical Review series, with recent work on topological acoustics , active metamaterials , and wave-based analog computing . Dr. Fleury received the Eccellenza Grant (2021) from the Swiss National Science Foundation and an ERC Starting Grant (2022) . He co-founded Minwave , a startup selling miniaturized microwave devices patented by his lab, which has garnered awards such as ESA-BIC CH , FIT , and Venture Kick . He has served as Technical Program Committee Chair for Eucap 2019 and on the Editorial Board of the New Journal of Physics . Recognized for teaching excellence with the STI Polysphere Award (2019) and IEL Best Teacher Award , he teaches courses including Electromagnetics , Antennas , and Advanced Photonics . His work bridges fundamental wave physics with applied technologies , emphasizing topological effects , nonlinear systems , and metamaterials . Collaborations span institutions such as ESPCI Paris , University of Texas at Austin , and University of Vienna , with applications in acoustic imaging , 5G antennas , and optical signal processing . His recent publications highlight ultrafast anti-lasing , reconfigurable metasurfaces , and disorder-assisted photonic crystals , reflecting a career dedicated to advancing wave engineering through topological and nonreciprocal designs .
Stéphanie P. Lacour is a Full Professor at the School of Engineering, École Polytechnique Fédérale de Lausanne (EPFL), where she holds the Foundation Bertarelli Chair in Neuroprosthetic Technology. She leads the Laboratory of Soft Bioelectronic Interfaces (LSBI) and is affiliated with multiple departments including INX-STI, STI-SMT, SV-SSV, and AVP-DLE-EDOC. Since 2025, she has served as EPFL’s Vice-President for Support to Strategic Initiatives, overseeing institutional research strategy. Her research is centered at Campus Biotech in Geneva, where she was the founding director of the Neuro-X Institute. PhD in Electrical Engineering, INSA Lyon, France (1998–2001) Postdoctoral Research, Princeton University and University of Cambridge Joined EPFL in 2011 Her research focuses on soft bioelectronic interfaces that seamlessly integrate with biological tissues. She pioneers the development of stretchable, compliant electronics for implantable and wearable applications, using techniques from MEMS and microelectronics adapted to elastomeric substrates. Her work enables long-term, minimally invasive neural interfacing for applications in neuroprosthetics, rehabilitation, and health monitoring. Key innovations include soft electrocorticography arrays, liquid metal sensors, and encapsulation methods for chronic implants. Her recent publications span high-impact journals such as Nature , Science Robotics , Advanced Materials , and Nature Nanotechnology , covering topics like neural stimulation, soft robotics, wireless implants, and hydrogel-based interfaces . The work demonstrates a strong trend toward multimodal, closed-loop, and translational neurotechnologies with real-world clinical potential. Scientific Awards: No scientific awards explicitly mentioned in the provided text. She advises a large cohort of PhD students and postdoctoral researchers, many of whom have completed their theses under her supervision. Her team has received funding for projects in neural interfacing, bioelectronics, and soft robotics. She is actively involved in teaching courses such as Soft Microsystems Processing and Devices and Neural Interfaces . Lacour leads the Laboratory of Soft Bioelectronic Interfaces (LSBI) , a multidisciplinary research team focused on the fabrication, characterization, and in vivo evaluation of soft bioelectronic systems. The lab collaborates extensively across EPFL and with clinical partners to translate technologies from bench to bedside.
Oussama Damen is a Professor at the University of Waterloo's Department of Electrical and Computer Engineering. His research focuses on advanced wireless communication systems, particularly in MIMO (Multiple-Input Multiple-Output) systems, signal processing, and machine learning applications in telecommunications. He is actively involved in developing innovative solutions for beamforming, hybrid precoding, and distributed decoding in massive MIMO and millimeter-wave networks. Damen's work also extends to optical fiber communication, federated learning in wireless systems, and optimization of resource allocation in next-generation networks like 5G/6G. His research interests include wireless communication theory, antenna system design, channel modeling, and algorithm development for improving spectral and energy efficiency. He has contributed extensively to the theoretical foundations of MIMO detection, lattice reduction techniques, and statistical signal processing methods. Notable trends in his publications emphasize bridging theoretical performance limits with practical implementations, particularly in scenarios involving channel impairments, limited backhaul capacity, and multi-core fiber transmission. His work often addresses fairness and optimization in distributed systems, including federated learning frameworks and hybrid beamforming architectures. No scientific awards or grants are explicitly mentioned in the provided information. Damen has advised no listed students, and no specific lab affiliations are noted.
Tural Khudiyev is an Assistant Professor at the Department of Materials Science and Nanotechnology , National University of Singapore (NUS), focusing on multimaterial electronic fibers for human-fabric interaction, soft robotics, and neural probes. He previously worked as a postdoctoral researcher at MIT's Research Laboratory of Electronics. B.Sc. in Nuclear Engineering, Hacettepe University Ph.D. in Materials Science and Nanotechnology, Bilkent University His research spans implantable and wearable electronics , stimuli-responsive drug delivery , and AI in healthcare , with a strong emphasis on scalable nanomanufacturing techniques. His publications in journals like Nature , Nature Nanotechnology , and Advanced Materials highlight innovations in thermally drawn fibers and soft bioelectronic interfaces . Key trends include flexible electronics , machine learning in textiles , and bio-integrated devices , with applications in neural engineering and power textiles . His work has been featured in media outlets such as Reuters and Business Insider . Selected as MIT’s top research story of 2021 #1 Most Read Article in Applied Optics (2015) Featured in Virtual Journal of Nanoscale Science & Technology Khudiyev's contributions to thermally drawn fibers and soft robotics demonstrate interdisciplinary collaboration between materials science, neuroscience, and wearable technology.
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 .
Jalaa Hoblos is an Associate Professor of Practice in the Department of Computer Science at Stony Brook University, part of the College of Engineering and Applied Sciences. She holds a B.S. from the Lebanese University in Beirut, Lebanon, and an M.S. and Ph.D. in Computer Science from Kent State University. Prior to Stony Brook, she served as an Assistant Professor at Penn State Behrend, a Visiting Assistant Professor at Hiram College, and adjunct faculty at Kent State University and the University of Akron. Her primary roles include teaching and research. Her research focuses on Data Quality Analysis, Cloud Computing (particularly load balancing and security), Wireless Networks Security, and Statistical Mathematics. She has explored topics such as fairness and throughput in multi-hop wireless networks, malicious behavior detection in clouds, and protocol modifications like the adaptive 802.11 MAC. Her work integrates statistical methodologies with network optimization and security challenges. Recent publications emphasize anomaly detection in time-series data and fairness-enhancing protocols. She has also applied techniques like Latent Semantic Analysis to educational technology. No scientific awards are explicitly mentioned in the texts. While no advising or grant details are provided, her teaching includes courses like CSE 114 (OOP), CSE 101 (Principles), CSE 310 (Computer Networks), and security-focused courses such as ISE 331 (Fundamentals of Computer Security). She has maintained consistent academic engagement across institutions and disciplines.
Hui Wu is a Professor of Electrical and Computer Engineering at the University of Rochester, affiliated with the Hajim School of Engineering & Applied Sciences. He leads the Laboratory for Advanced Integrated Circuits and Systems. Educations: BSc (Electrical Engineering), Tsinghua University (1996) MSc (Microelectronics), Tsinghua University (1998) PhD (Electrical Engineering), California Institute of Technology (2003) Research Interests: Focuses on high-speed electronics, RF/microwave circuits, silicon photonics, electronic-photonic integration, ultra-wideband radios, and nanoelectronics. Specializes in optical/electrical interconnects, high-performance clocking, and spintronics. Labs & Teams: Directs the Laboratory for Advanced Integrated Circuits and Systems, advancing research in integrated circuits and systems.
Serkut Ayvasik is a Researcher at the Chair of Communication Networks at Technical University Munich (TUM). He joined TUM in March 2019 as a research and teaching associate, following his M.Sc. in Communications Engineering (2019) and B.Sc. in Electrical and Electronics Engineering (2016) from Middle East Technical University. His research focuses on: Wireless Network Resource Management for heterogeneous latency-critical 5G applications Channel State Information Prediction using depth images Network Slicing and Quality of Service optimization Machine Learning for proactive network configuration Telemedicine Applications in cross-border communication Key article trends include 5G/6G technology , IoT sustainability , digital twins , and haptic feedback systems . He contributes to IEEE and ACM journals, with recent work on Digiot (2025) and OCTOPUS (2024). Collaborations include researchers like Wolfgang Kellerer (Chair), Edwin Babaians , Alba Jano , and Fidan Mehmeti . His work spans projects such as 6G Future Lab Bavaria , DFG GGI QCDE , and ERC FlexNets .
Dr. Samuel Cheng is an Associate Professor at the Gallogly College of Engineering , University of Oklahoma , specializing in Electrical and Computer Engineering . He holds a Ph.D. in Electrical Engineering from Texas A&M University (2004), preceded by M.S. and M.Phil. degrees from the University of Hawaii and Hong Kong University of Science and Technology. Education: B.S. (University of Hong Kong, 1995), M.Phil. (HKUST, 1997), M.S. (University of Hawaii, 2000), Ph.D. (Texas A&M, 2004) Professional Experience: Senior Research Engineer at Advanced Digital Imaging Research (2004-2005), prior internships at Microsoft Asia and Panasonic Technologies His research focuses on Information Theory , Signal and Image Processing , and Pattern Recognition , with applications in remote sensing, urbanization analysis, and disaster monitoring. His publications span topics including urban impervious surface mapping , nighttime light analysis , and machine learning for environmental data . His work often integrates multi-source datasets (e.g., Landsat, LiDAR, social media) for spatiotemporal modeling. Technical Expertise: Spectral unmixing, machine learning, thermal remote sensing, GIS integration Key Applications: Power outage detection, vegetation-crime correlation, PM2.5 estimation, smart meter data fusion Dr. Cheng holds three US patents in digital watermarking and is affiliated with IEEE, Sigma Xi, and AAAS. His recent articles demonstrate a trend toward leveraging AI for remote sensing challenges and analyzing urbanization impacts on ecosystems.
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.
David Blaauw is the Kensall D. Wise Collegiate Professor of Electrical Engineering and Computer Science (EECS) at the University of Michigan. His research focuses on ultra-low-power analog/mixed-signal circuits, mm-scale sensors, neural networks, and biomedical applications. He leads the Blaauw Lab, which has pioneered innovations like the Michigan Micro Mote (M^3) and neural recording probes. His work emphasizes real-world deployability, with applications in environmental monitoring (e.g., monarch butterflies), medical devices, and robotics. Education: B.S. in Physics and Computer Science, Duke University (1986) Ph.D. in Computer Science, University of Illinois Urbana-Champaign (1991) Research Interests: Blaauw’s lab explores ultra-low-power computing, mm-scale systems, RF communication, in-memory computing, and genomics acceleration. Key projects include: Millimeter-scale computers (e.g., 0.04mm³ temperature sensors) Wireless neural interfaces for brain-machine communication Energy-efficient accelerators for edge AI and genomics Micro-robotics with sensing/actuation/computation Awards: IEEE Fellow 2016 SIA-SRC Faculty Award Motorola Innovation Award Best Paper Awards at ISSCC, ISCA, and RFIC Advising & Impact: Over 600 publications, 65 patents, and 4 startup companies spun from his lab. Current research includes genome sequencing accelerators (GenAx) and neural recording dust for brain mapping. He directs the Michigan Integrated Circuits Lab and chairs major conferences like ISSCC and DAC. Labs/Teams: Blaauw Lab (University of Michigan) Michigan Integrated Circuits Lab (MICAL)
Hui Pan is a distinguished academic holding dual positions as Nokia Chair in Data Science and Professor of Computer Science at the University of Helsinki, and Chair Professor of Computational Media and Arts at the Hong Kong University of Science and Technology (HKUST). His research spans networking, mobile computing, augmented reality, and computational social science. He earned his Ph.D. in Computer Science from the University of Cambridge in 2007. His work bridges social networks with mobile systems, pioneering fields like mobile social networks and opportunistic forwarding algorithms. Research interests include data science, complex networks, and innovative applications of augmented reality. His recent publications focus on low-latency AR frameworks, blockchain for computation offloading, and mobile web visualization. He has received prestigious awards, including IEEE Fellow (2018), ACM Distinguished Scientist (2016), and the Nokia Chair Endowment (2017). He has supervised over 15 PhD and 12 MPhil graduates, with 13 current Ph.D. students and 2 MPhil students. His editorial roles include Associate Editorships at IEEE Transactions journals and guest editorships at top venues like IEEE JSAC and ACM Transactions. He has organized conferences such as WWW Track Chair and ExtremeCom General Chair.
Vinod M. Vokkarane is a Professor in the Department of Electrical and Computer Engineering at the University of Massachusetts Lowell, where he serves as Director of the Center for Smart Cyber-Physical Systems (SCyPS) and Director of Advanced Computer Network Labs. Previously, he was an Associate Professor at University of Massachusetts Dartmouth from 2004 to 2013 and a Visiting Scientist at MIT's Research Laboratory of Electronics from 2011 to 2014. His extensive research portfolio spans multiple domains of advanced networking and cyber-physical systems. Dr. Vokkarane earned his educational foundation with a B.S. from University of Mysore, India (1999), followed by an M.S. (2001) and Ph.D. (2004) in Computer Science from the University of Texas at Dallas. His dissertation focused on optical burst-switched networks, establishing the foundation for his future research trajectory. His research interests center on Cyber-Physical Systems, Network Optimization, Reliability, Smart Grids, and Cyber-Security, with particular expertise in the design, analysis, and modeling of architectures, protocols, and algorithms for ultra-high speed networks including Optical networks, Grid/Cloud networks, and Big-data networks. His work bridges theoretical foundations with practical implementations, often addressing critical challenges in network reliability, security, and efficiency. His research has received significant recognition through numerous best paper awards and substantial external funding. Analysis of his recent publications reveals a clear evolution toward increasingly sophisticated integration of cyber-physical systems with power infrastructure, particularly in the areas of grid resilience and observability. His work has expanded from fundamental optical networking research to address critical infrastructure challenges, with a growing emphasis on machine learning applications for network optimization and power system monitoring. The recent focus on PMU networks, disaster resilience, and cyber restoration demonstrates his strategic pivot toward addressing national security and critical infrastructure protection challenges. UMass Dartmouth Scholar of the Year Award (2011) UMass Dartmouth Chancellor's Innovation in Teaching Award (2010-11) University of Texas at Dallas Computer Science Dissertation of the Year Award (2003-04) Multiple Best Paper Awards including IEEE GLOBECOM 2005, IEEE ANTS 2010, ONDM 2015, ONDM 2016, and IEEE ANTS 2016 Texas Telecommunications Engineering Consortium Fellowship (2002-03) Dr. Vokkarane has successfully mentored numerous graduate students who have contributed significantly to his research projects, with several going on to successful careers in academia and industry. His research has been consistently supported by major funding agencies including NSF, DOE, and USMC, with recent projects totaling over $5 million in funding. Current projects include Unified Post-Disaster Restoration Planning for Cyber-Physical Power Distribution Systems (ONR, $550K), CyberCARE: Northeast University Cybersecurity Center (DOE, $3.5M), and Flexible Spectrum Allocation in Next-Generation Optical Networks (NSF, $350K). He leads the Center for Smart Cyber-Physical Systems (SCyPS) and Advanced Computer Network Labs at UMass Lowell, where his research teams work on cutting-edge problems in network architecture, cyber-physical security, and infrastructure resilience. His labs collaborate extensively with national laboratories and industry partners to translate theoretical advances into practical solutions for real-world infrastructure challenges.
Luca Carloni is a Professor of Computer Science and Department Chair at Columbia University's Columbia Engineering. He leads the System-Level Design Group, focusing on heterogeneous system-on-chip (SoC) architectures, networks-on-chip (NoC), and embedded systems. Carloni holds a Laurea Summa Cum Laude in Electronics Engineering from the University of Bologna and a PhD in Electrical Engineering and Computer Sciences from UC Berkeley. His work emphasizes specialized hardware design, energy-efficient computing, and FPGA-based prototyping. Research interests include system-level design methodologies for SoCs, embedded accelerators, and quantum computing hardware. He has pioneered frameworks like Embedded Scalable Platforms (ESP) and tools like MosaicSim for rapid SoC prototyping. Carloni has received numerous awards, including the NSF CAREER Award (2006), IEEE Fellow (2017), and multiple best paper awards at DATE and CloudCom conferences. He has served on editorial boards of IEEE Transactions on CAD and ACM Transactions on Embedded Computing , and chaired key conferences like EMSOFT and ESWeek. His research addresses challenges in heterogeneous architectures, power management, and the intersection of machine learning with embedded systems. Current projects explore quantum control systems, brain-computer interfaces, and energy-efficient datacenter computing.
