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Sheng Shen is a Professor in the Mechanical Engineering Department at Carnegie Mellon University (CMU) , with courtesy appointments in the Departments of Electrical and Computer Engineering and Materials Science and Engineering . He earned his Ph.D. in Mechanical Engineering (Minor in Electrical Engineering) from Massachusetts Institute of Technology (MIT) , and his B.S. and M.S. from Huazhong University of Science and Technology in China. Prior to joining CMU in 2011, he conducted postdoctoral research at UC-Berkeley . Education: Ph.D., Mechanical Engineering, MIT (2010) B.S. & M.S., Power Engineering & Engineering Thermophysics, Huazhong University of Science and Technology (2000 & 2003) Research interests include nanophotonics , nanoscale energy transport and conversion , nanofabrication , and advanced manufacturing , with applications in thermal management , light sources and devices , thermal emission control , solar energy conversion , infrared sensing , and multifunctional materials . His work leverages interdisciplinary expertise in thermal and optical measurements , material synthesis , device fabrication , and theoretical modeling . Recent publications highlight advancements in infrared radiation control , thermal interface materials , metasurface engineering , and graphene-based nanosystems . His scientific awards include: NSF CAREER Award DARPA Director's Fellowship DARPA Young Faculty Award Elsevier/JQSRT Raymond Viskanta Award CMU Dean's Early Career Fellowship Philomathia Foundation Research Fellowship Hewlett-Packard Best Paper Award Best Paper Award, Julius Springer Forum Advising spans Ph.D. and postdoctoral researchers in nanoscale energy systems, with alumni contributing to solar energy conversion , infrared sensing , and flexible electronics . His lab receives funding from ARL, DARPA, DOE, DTRA, NASA, NSF, and ONR , and recently secured a DURIP award for instrumentation.

• Nanophotonics
• Nanoscale Energy Transport and Conversion
• Advanced Manufacturing
• +7 more

Priyanka Raina is an Assistant Professor of Electrical Engineering at Stanford University, with a courtesy appointment in Computer Science. She leads the Stanford Accelerate research group, focusing on domain-specific hardware architectures and agile hardware-software co-design. Her work emphasizes high-performance, energy-efficient accelerators for emerging technologies. Education: B.Tech. from IIT Delhi (2011), M.S. and Ph.D. from MIT (2013/2018). Postdoctoral experience includes NVIDIA Research (2018) and Amazon Visiting Academic (2023–present). Awards include the Sloan Research Fellowship (2024), NSF CAREER Award (2023), and Terman Faculty Fellowship (2018). Research Interests: Domain-specific architectures, near-memory computing, design productivity, and machine learning acceleration. Her group develops frameworks like AHA (Agile Hardware) for efficient accelerator design and compilers. Awards: Over 10 major awards, including best paper recognitions at VLSI, MICRO, and JSSC. Active roles as Associate Editor for IEEE JSSC and Program Chair for IEEE Hot Chips (2020). Advising & Teaching: Supervises multiple PhD and MS students in hardware design, CGRAs, and ML accelerators. Teaches VLSI design courses (EE271/272/372) and oversees independent studies in embedded systems and chip design. Labs & Collaborations: Affiliated with Stanford PORTAL Center, AHA Center, and SystemX Alliance. Projects include MINOTAUR (edge AI accelerator), Amber (CGRA-based SoC), and EMBER (RRAM macros).

• Domain-Specific Architectures
• Hardware/Software Co-design
• Energy-Efficient Computing
• +3 more

Larry Pileggi is the Coraluppi Head and Tanoto Professor of Electrical and Computer Engineering at Carnegie Mellon University (CMU). He is also the Department Head of CMU’s ECE Department and has held prior roles at Westinghouse Research and Development and the University of Texas at Austin. His work bridges academic research and industry innovation, with co-founding ventures like Fabbrix Inc., Extreme DA, and Pearl Street Technologies. Dr. Pileggi earned his Ph.D. in Electrical and Computer Engineering from CMU (1989), following an M.S. (1984) and B.S. (1983) in Electrical Engineering from the University of Pittsburgh. His research focuses on three core areas: secure integrated circuit hardware (mitigating supply-chain threats), integrated circuits design methodologies (supporting sub-20nm CMOS and heterogeneous technologies), and power systems simulation (developing robust grid analysis tools like SUGAR). He has been recognized with numerous awards, including the prestigious 2023 Phil Kaufman Award for contributions to electronic system design, and is an IEEE Fellow. His academic leadership includes fostering maker initiatives and interdisciplinary research programs to address future challenges in energy and computing systems. Pileggi’s advising record includes over 47 Ph.D. students, many of whom collaborate with him in industry ventures. Current and past grants support his work on resilient power grids and novel memory technologies, reflecting a commitment to both theoretical and applied research. His lab, the Pileggi Lab, develops cutting-edge solutions for energy and integrated systems, emphasizing scalable simulation, secure hardware design, and next-generation memory architectures. Collaborations span institutions like ETH Zurich and industry partners in EDA and semiconductor sectors.

• Secure Integrated Circuit Hardware
• Integrated Circuits Design Methodologies
• Power Systems Simulation and Optimization
• +3 more

Subhasish Mitra is the William E. Ayer Professor of Electrical Engineering and Computer Science at Stanford University, holding dual appointments in both departments. He leads the Stanford Robust Systems Group and serves on the leadership team of the Microelectronics Commons AI Hardware Hub under the US CHIPS and Science Act. His research spans Robust Computing, NanoSystems, Electronic Design Automation (EDA), and Neurosciences, with breakthroughs in X-Compact test compression, carbon nanotube computing, and 3D integration. He has held international roles like the Carnot Chair at CEA-LETI and Visiting Professorships globally. Education & Honors: Recipient of over 40 awards including the IEEE Computer Society’s Harry H. Goode Memorial Award, ACM/IEEE’s A. Richard Newton Technical Impact Award, and the Intel Achievement Award. He earned top academic accolades from IIT Kharagpur and Jadavpur University, and is a Fellow of ACM and IEEE. Research Impact: Pioneered first-of-their-kind systems like the carbon nanotube computer and monolithic 3D integration. His work on robust computing techniques like QED validation and X-Compact compression has industry-wide adoption, saving billions in manufacturing costs. Collaborates with industry leaders like Intel, Google, and Samsung. Publications & Grants: Over 400 publications, including award-winning papers in DAC, ISSCC, and IEEE journals. Leads grants from NSF, DoE, and industry partnerships. His lab explores cutting-edge topics like neuromorphic computing, 3D thermal scaffolding, and AI hardware acceleration. Administration & Outreach: Serves as Associate Chair (Faculty Affairs) for Stanford’s Computer Science Department. Recognized by students for mentorship, and frequently invited to global forums like the World Economic Forum and National Academy of Engineering.

• Robust Computing
• NanoSystems
• Electronic Design Automation (EDA)
• +3 more

Rakesh Kumar is a Professor and John Bardeen Faculty Scholar in the Electrical and Computer Engineering Department at the University of Illinois at Urbana-Champaign. His work focuses on computer architecture, system-level design automation, and low-power computing. PhD in Computer Engineering from University of California, San Diego BS in Electrical Engineering from IIT Kharagpur His research spans all layers of the computing stack, with key contributions to flexible computer systems , waferscale computing , error-resilient architectures , and approximate computing . He has pioneered work on voltage-reliability tradeoffs and peak power management techniques. Recent publications highlight trends in space microdatacenters , printed microprocessors , and neural graph accelerators . His work on plastic chips was recognized as one of the three biggest semiconductor headlines of 2022 by IEEE Spectrum. IEEE Fellow (2024) ISCA Influential Paper Award MICRO Test-of-Time Award ICCAD Ten Year Retrospective Most Influential Paper Award Best Paper Awards at CASES, SELSE, HPCA He has received teaching accolades including the Stanley H. Pierce Faculty Award and Ronald W. Pratt Outstanding Teaching Award . His research group explores hardware-software co-design for emerging applications in AI, IoT, and sustainable computing.

• Computer Architecture
• System-Level Design Automation
• Low Power Computing
• +3 more

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

• 3D Printing
• Nanotechnology
• Biomedical Engineering
• +4 more

Olindo Isabella serves as a Full Professor within the Faculty of Electrical Engineering, Mathematics and Computer Science at Delft University of Technology. She heads the Photovoltaic Materials and Devices (PVMD) research group, driving innovation in solar energy conversion technologies. Her academic role encompasses teaching, research leadership, and extensive collaboration with industry and international institutions to advance photovoltaic science and engineering. Professor Isabella's research spans multiple domains of photovoltaics, including silicon and perovskite solar cells, thin-film technologies, offshore floating systems, and agrivoltaics. She investigates material properties, device physics, and system performance to enhance efficiency, reliability, and environmental sustainability of solar energy solutions. Her work integrates experimental and computational approaches for comprehensive analysis. Analysis of her recent publications indicates a strategic focus on machine learning for PV-climate classification, impedance spectroscopy of silicon solar cells, offshore floating platform engineering, and perovskite crystallization processes. These studies collectively address key barriers to large-scale solar deployment, such as performance prediction, structural integrity in marine environments, and novel material synthesis. Scientific Awards: The available information does not mention any specific awards or honors for Professor Isabella. She has guided the research of 20 students and secured competitive funding for impactful projects. Currently, she leads SYMBIOSYST (2023-2026), which explores symbiotic relationships between solar PV and agriculture, and recently completed TRUST-PV (2020-2024), aimed at improving PV plant integration across market segments through machine learning and monitoring technologies. The PVMD group under her direction operates state-of-the-art laboratories for solar cell fabrication and characterization. The team collaborates with global partners on field trials, data analysis, and technology development, contributing to both fundamental knowledge and practical applications in renewable energy.

• Photovoltaics
• Solar Cells
• Silicon Solar Cells
• +5 more

Dr. Can Bayram is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign. He serves as a resident faculty member at the Nick Holonyak, Jr. Micro and Nanotechnology Laboratory and leads the Innovative Compound Semiconductor Laboratory (ICORLAB). His research focuses on semiconductor technologies, particularly cubic GaN and diamond-based devices for next-generation electronics and photonics. Current research includes cubic GaN quantum wells for green LEDs Diamond semiconductor devices for high-power applications Photonic technologies and nanoscale device fabrication Investigation of efficiency cliff phenomena in micro-LEDs Recent Article Trends : His work spans photonic devices, power electronics, and nanoscale systems, with particular emphasis on diamond photoconductive switches and cubic GaN efficiency improvements. Notable contributions include record-breaking diamond diodes and efficiency droop mitigation in green LEDs. Scientific Awards : IEEE Electron Devices Society Early Career Award NSF CAREER Award AFOSR Young Investigator Award Dean's Award for Early Innovation (2024) SPIE Fellow (2025) Editor's Pick & Front Cover Article, Applied Physics Letters (2024) Dr. Bayram teaches courses in electronics, including ECE 110: Introduction to Electronics, ECE 443: LEDs and Solar Cells, and ECE 500: ECE Colloquium.

• Semiconductor Devices
• Optoelectronics
• Compound Semiconductor Technology
• +6 more

Carlos Errando Herranz serves as an Assistant Professor in the Quantum and Computer Engineering Division at Delft University of Technology's Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) and as a Principal Investigator at QuTech. His research focuses on developing scalable quantum photonic integrated circuits using semiconductor fabrication processes compatible with existing infrastructure for quantum internet applications. He received Bachelor's and Master's degrees from Universitat Politècnica de València (2013) and a PhD in Micro and Nanosystems from KTH Royal Institute of Technology (2018), followed by postdoctoral positions at KTH and MIT as a Marie Curie fellow. His lab investigates quantum photonics, integrated photonics, and color centers with emphasis on diamond tin-vacancy systems and silicon-based quantum emitters. Recent publications demonstrate strong expertise in tuning quantum emitters via strain engineering, heterogeneous integration of spin-photon interfaces, and MEMS-enabled reconfigurable photonics. Key advancements include cavity-enhanced quantum memories, superconducting detector integration, and spectral control of solid-state emitters for quantum networks. Dr. Herranz advises seven graduate students including PhD candidates Vicky Dominguez Tubio, Arjan Mejas, Matteo Pirro, Christian Primavera, Jan Riegelmeyer, and Elena Volkova, along with Master student Bram Zijlstra. His team comprises postdocs Lin Jin and Pat Laferriere, and interns Elsa Herranz Valiente and Ernest Staffetti Cruañas. The Errando Herranz Lab operates within QuTech's Quantum Internet Division at Delft University, maintaining specialized facilities for nanofabrication and optical characterization of quantum photonic devices. Current research directions include developing CMOS-compatible quantum memories operating at telecom wavelengths and scalable architectures for quantum repeaters.

• quantum photonics
• integrated photonics
• color centers
• +3 more

Anantha Chandrakasan is the Vannevar Bush Professor of Electrical Engineering and Computer Science at MIT, serving as Dean of the MIT School of Engineering and Chief Innovation and Strategy Officer. His research focuses on energy-efficient integrated circuits, medical devices, and AI hardware security. He leads the MIT Energy-Efficient Circuits and Systems Group, developing systems for biomedical applications, wireless communication, and quantum computing. He holds appointments at MIT's Microsystems Technology Laboratories and has contributed to collaborations like the MIT-Takeda Program in AI-driven healthcare and a partnership with GlobalFoundries for energy-efficient AI chips. His work spans implantable drug delivery systems, conformable ultrasound patches, and secure edge computing architectures. Chandrakasan's innovations include ultra-low-power circuits for IoT devices, cryptographic processors for post-quantum security, and AI accelerators for edge applications. He emphasizes interdisciplinary research bridging electrical engineering with biomedical and quantum fields, supported by leadership roles in MIT's strategic initiatives. His contributions to energy-efficient computing have led to advancements in wearable health monitors, batteryless sensors, and secure communication protocols for medical devices. Ongoing projects include THz integrated systems and AI-enhanced analog circuit design optimization.

• Energy-Efficient Circuits
• Integrated Systems
• AI Hardware Security
• +3 more

Yan Liu is a full professor in the Thomas Lord Department of Computer Science at the University of Southern California (USC), serving as Director of the USC Machine Learning Center within the Viterbi School of Engineering. He holds courtesy appointments in the Ming Hsieh Department of Electrical Engineering and the Quantitative and Computational Biology Department. Before joining USC in 2010, he was a research staff member at IBM's T.J. Watson Research Center. He earned his M.S. and Ph.D. from Carnegie Mellon University. His research focuses on machine learning for time series, physics-informed AI, and interpretable models, with applications in healthcare, sustainability, and social media. Notable projects include developing AI for surgical training, analyzing misinformation on social platforms, and predicting cancer treatment outcomes. He has held leadership roles in top conferences like ICLR and ACM KDD, and serves as Associate Editor-in-Chief of TPAMI and Board Member of ICLR. Education: Ph.D., Carnegie Mellon University Affiliations: USC Machine Learning Center, Viterbi School of Engineering Service: General Chair (ICLR 2023, ACM KDD 2020), Program Chair roles across multiple conferences His lab, the Melady Group, emphasizes foundational ML advancements and interdisciplinary applications. Recent work includes physics-aware neural networks and time-series foundation models.

• Machine Learning
• Physics-Informed Machine Learning
• Interpretable Machine Learning
• +3 more

Dimitra Psychogiou is a Full Professor of Microwave Engineering at University College Cork and Principal Investigator at Tyndall National Institute's CONNECT Centre in Cork, Ireland. She leads the Advanced RF Technology Group, driving innovation in reconfigurable RF systems for next-generation wireless networks. Her academic credentials include: Dipl.-Eng. in Electrical and Computer Engineering, University of Patras (2008) Ph.D. in Electrical Engineering, ETH Zurich (2013) Prof. Psychogiou's research pioneers reconfigurable microwave filters , non-reciprocal RF components , and additive manufacturing for antenna systems . Her work bridges theoretical microwave engineering with practical implementations in 5G/6G front-ends, emphasizing sustainability through hyperflexible filtering architectures that reduce hardware complexity and energy consumption. Key innovations include acoustic-wave resonator filters and 3D-printed RF components enabling unprecedented miniaturization. Analysis of her 2022-2025 publications reveals a strategic shift toward multifunctional RF integration , where filtering coexists with isolation, amplification, and switching in single modules. This trend addresses critical industry needs for compact, software-defined radio front-ends in satellite communications and IoT networks, with increasing emphasis on reflectionless topologies and spatiotemporal modulation techniques. Her scientific recognition includes: 2023 MTT-S Outstanding Young Engineer Award 2021 Roberto Sorrentino Prize 2021 SFI Research Professorship 2020 NSF CAREER Award 2020 URSI Young Scientist Award UC Boulder Junior Faculty Research Award Prof. Psychogiou actively shapes her field through leadership roles as Chair of IEEE MTT-13 Committee and Secretary of USNC-URSI Commission D, while serving as Associate Editor for IEEE MWCL and IJMWT. Her group collaborates extensively with semiconductor foundries and wireless infrastructure companies to transition lab innovations to commercial applications. The Advanced RF Technology Group operates state-of-the-art facilities for GaAs MMIC prototyping, 3D-printed RF component fabrication, and full-wave electromagnetic characterization, supporting Ireland's strategic position in European telecommunications research.

• Microwave Engineering
• RF Filters
• Millimeter-wave Technology
• +4 more

Umut Aydemir is an Associate Professor at the Department of Chemistry, Koç University , where he also serves as Director of KUBAM (Koç University Boron Application and Research Center) . His research focuses on Boron-Based High-Tech Materials, 2D Materials, Electrocatalysis, Thermoelectric Energy Harvesting , and Hydrogen Storage . PhD in Chemistry (2012), Dresden University of Technology MSc in Materials Science and Engineering (2006), Koç University BSc in Chemistry and Physics (2004), Koç University Umut’s work addresses structure-property relationships in advanced materials, with a particular emphasis on boron-containing compounds , MXenes , and thermoelectric systems . His recent publications highlight innovations in electrocatalytic water splitting , hydrogen storage materials , and sustainable coating technologies . His research trends include: Development of metal diborides for water splitting Engineering MXene/polymer composites for corrosion resistance Novel approaches to thermoelectric materials like MgAgSb and Zintl phases Designing hydrogenated borophene for environmental applications Awarded the 2024 Koç University College of Science Outstanding Faculty Award and 2019 TÜBA Young Scientist Award , Umut leads high-impact projects in materials science. He advises graduate students in Nanocatalysis and Advanced Material Synthesis and contributes to interdisciplinary initiatives at KUBAM.

• Boron-Based High-Tech Materials
• Laser Crystals
• Materials Displaying Unusual Properties
• +10 more

Soheil Salehi is a tenure-track Assistant Professor in the Department of Electrical and Computer Engineering at the University of Arizona, with a joint appointment in Systems and Industrial Engineering. He is the Director of the Privacy-preserving, Intelligent, and Secure Computing (PRISM) Lab, established in August 2022. Prior to this, he was an NSF-Sponsored Computing Innovation Fellow and Postdoctoral Research Fellow at the University of California, Davis. Ph.D., Electrical and Computer Engineering, University of Central Florida, 2020 M.S., Electrical and Computer Engineering, University of Central Florida, 2016 B.S., Isfahan University of Technology, Iran, 2014 Dr. Salehi's research focuses on the intersection of hardware, AI, and security. His work spans hardware and AI-enabled security in IoT , Generative AI for hardware design and security , neuromorphic and biologically-inspired AI hardware , emerging spin-based devices , reconfigurable architectures , low-power VLSI circuits , and digital twins and mixed reality for semiconductor workforce development . He also explores the application of Generative AI in personalized education . His recent publications, spanning 2023–2025, reveal a strong trend toward integrating AI and machine learning into hardware security and design. Key themes include automated secure IC design flows , AI-driven hardware obfuscation , firmware and side-channel attack analysis , security in neuromorphic and spiking neural networks , and educational frameworks using digital twins and generative models . His work appears in top venues like DAC, ICCAD, USENIX Security, IEEE TCAS-I, and ISCAS. Outstanding Reviewer Award, IEEE/ACM Design Automation Conference (DAC), 2023 Best Presentation of the Symposium Award, UC Davis Postdoctoral Research Symposium, 2021 UCF Excellence by a Graduate Teaching Assistant (University-Level), 2016 Nominated for 30-under-30 Award, UCF, 2020 Nominated for Postdoctoral Research Excellence Award, UC Davis, 2022 Dr. Salehi has secured significant research funding as PI and Co-PI, including a $300K NSF SaTC EAGER grant on Generative AI-based Personalized Cybersecurity Tutor, a $174,000 University of Arizona PIF Award, and multiple RII grants totaling over $198K. He has also received industry funding from CHEST. He actively mentors students and leads the PRISM Lab, which focuses on privacy-preserving and intelligent secure computing. His service includes roles as Technical Program Committee (TPC) Member and Session Chair at premier conferences such as DAC, ICCAD, CCS, NDSS, and GLSVLSI. The PRISM Lab, under his direction, conducts cutting-edge research in secure and intelligent hardware systems, with applications in IoT, edge computing, and workforce development. The lab emphasizes interdisciplinary collaboration and innovation in both research and education.

• Hardware Security
• AI-Enabled Security
• Internet of Things (IoT) Security
• +15 more

Prof. Baker Mohammad serves as Professor and Director of the System on Chip Lab in the Department of Computer and Information Engineering at Khalifa University. With over 15 years of industrial experience at Intel and Qualcomm designing microprocessors and DSP chips, he bridges academic research with real-world engineering challenges in high-performance computing and low-power systems. His educational background includes: Ph.D. in Electrical and Computer Engineering, University of Texas at Austin (2008) M.S. in Electrical and Computer Engineering, Arizona State University B.S. in Electrical Engineering, University of New Mexico Dr. Mohammad's research spans cutting-edge domains where VLSI design converges with AI acceleration and emerging memory technologies . His work pioneers Memristor applications in environmental sensing (radiation, vacuum, glucose) and neuromorphic computing, while advancing energy harvesting systems for wearable electronics. The integration of in-memory computing with security primitives represents a paradigm shift in hardware design, moving beyond traditional CMOS limitations. His publication trajectory reveals accelerating focus on self-powered neuromorphic systems and RRAM-based architectures, with recent work (2021-2023) emphasizing hardware-software co-design for edge AI. Over 75% of his recent publications involve cross-disciplinary collaborations spanning materials science, chemistry, and biomedical engineering. Notable scientific recognition includes: IEEE TVLSI Best Paper Award 2016 IEEE MWSCAS Myrill B. Reed Best Paper Award Qualcomm Qstar Award for Performance Leadership KUSTAR IP Excellence Award Multiple SRC Techon Best Session Papers As a dedicated mentor, he has supervised over 15 graduate students while securing competitive funding from Khalifa University, ADEK, Qualcomm, Tii, and UAE space agencies. His grant portfolio demonstrates exceptional translational impact, converting fundamental research in memristive devices into drone flight computers and medical sensors. Current projects integrate academic rigor with industrial deployment timelines. The System on Chip Lab operates as a multidisciplinary hub where semiconductor physicists collaborate with AI researchers to develop RISC-V-based secure processors and piezoelectric nanogenerator systems. Recent expansions include partnerships with Tii for aerospace applications and medical device startups for glucose monitoring technology.

• Very-Large-Scale Integration (VLSI)
• Hardware Accelerators for Artificial Intelligence
• Hardware Security
• +7 more