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Soheil SalehiView profile

Assistant Professor

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

• Quantum Computing
• MEMS Sensors
• Analog Circuit Design
• +5 more

Hua Chen is an Associate Researcher and PhD Supervisor at the School of Quantum Science and Engineering at Southern University of Science and Technology (SUSTech), with extensive experience in quantum computing circuit design and MEMS sensor interfaces. Previously, he served as an Associate Researcher at the Institute of Microelectronics, Chinese Academy of Sciences (2021-2022) and as an Assistant Researcher there from 2017-2021, building on his industry experience as an RF/Analog IC Design Engineer at Southwest Integrated Circuit Design Co., Ltd (2007-2010). Education: Ph.D. in Microelectronics and Solid-State Electronics, University of Chinese Academy of Sciences (2014-2017) M.Eng. in Electronic and Communication Engineering, University of Chinese Academy of Sciences (2011-2014) B.Eng. in Microelectronics, Chongqing University of Posts and Telecommunications (2003-2007) Dr. Chen's research focuses on interface circuit design for quantum computing and MEMS sensors, with particular expertise in high performance analog/RF/mixed-signal IC design. His recent work has shifted toward cryogenic circuit design for quantum bit control and readout systems, representing a strategic pivot toward China's national priority in quantum information technology. His publications reveal a consistent trajectory from MEMS gyroscopes and oscillators toward quantum computing hardware support circuits, demonstrating his ability to adapt expertise to emerging technological frontiers. Dr. Chen's research output shows a clear evolution from traditional MEMS sensor interfaces toward quantum cryogenic electronics, with his 15 most recent publications heavily concentrated in cryogenic circuit design for quantum applications. This represents a strategic shift aligning with China's substantial investment in quantum computing research, particularly in the development of control and readout electronics for scalable quantum systems. His significant honors include: Special talent of Shenzhen's Pengcheng Peacock Plan (January 2024) IEEE Senior Member (February 2022) Intellectual Property Specialist of Chinese Academy of Sciences (January 2020) Outstanding Employee (Top 10%) at Institute of Microelectronics CAS (2020) Multiple Graduate Student Scholarships from Institute of Microelectronics CAS (2015-2017) As a PhD Supervisor at SUSTech, Dr. Chen mentors graduate students in quantum circuit design while leading research funded through multiple sources including a Beijing Natural Science Foundation General Project (RMB 200,000) for RF MEMS disk oscillator drive circuits and a Youth Project (RMB 100,000) for MEMS gyroscope phase alignment. He has also participated in major national projects totaling over RMB 27 million, demonstrating his integration into China's strategic research initiatives. Dr. Chen leads a research group at the International Quantum Academy in Shenzhen focused on cryogenic CMOS integrated circuit design for quantum computing applications. His team develops specialized low-temperature measurement and control chips that address critical challenges in scaling quantum computing systems, with particular emphasis on MEMS-based quantum frequency references and cryogenic amplifiers that operate at temperatures near absolute zero.

Sohmyung HaView profile

Associate Professor

• Biomedical Engineering
• Neural Engineering
• Wearable Sensors
• +3 more

Sohmyung Ha is an Associate Professor of Electrical Engineering and Bioengineering at NYU Abu Dhabi and holds a Global Network position at NYU Tandon School of Engineering. He leads the Integrated BioElectronics Laboratory, focusing on advancing silicon integrated technologies for biomedical applications such as implantable devices and wearable sensors. His expertise spans biomedical circuits, neural interfaces, and wireless power systems. Education: MS (2004, KAIST), PhD (2016, UC San Diego) with a Best Thesis Award. Prior industry experience includes analog circuit design at Samsung Electronics (2006-2010). Academic affiliations include NYU Abu Dhabi, NYU Tandon, and global collaborations. Research interests include high-performance biomedical sensors, neural prosthetics, and energy-efficient bioelectronic systems. Notable achievements include a Best Paper Award (ISCAS 2024) and innovations in impedance spectroscopy and neural interface ICs. Current projects emphasize closed-loop neural interfaces, subcutaneous glucose monitoring, and retinal prostheses. His lab develops miniaturized, power-autonomous systems for healthcare applications.

Aloke DuttaView profile

Professor

• Semiconductor Device Modeling
• Analog/Digital VLSI Circuits
• Semiconductor device physics
• +3 more

Professor Aloke Dutta is a faculty member in the Department of Electrical Engineering at Indian Institute of Technology Kanpur (IIT Kanpur). He holds a PhD in Electrical Engineering from Louisiana State University (LSU), Baton Rouge, Louisiana (1989), an MS in Electrical Engineering from LSU (1985), and a BE in Electrical Engineering from Jadavpur University (1982). Professor Dutta's research focuses on semiconductor device physics and modeling, Analog/Digital VLSI circuits, IC fabrication technology and device characterization, and Mixed Signal RF Circuits. His work bridges fundamental semiconductor physics with practical applications in integrated circuit design and fabrication. His publications demonstrate expertise in MOSFET modeling, particularly in substrate current, gate tunneling, and SOI technologies across various device structures. Professor Dutta has received numerous accolades for his teaching and research, including the Distinguished Teacher Award of IIT Kanpur (2013) and the prestigious Ranjit Singh Chair Professor position at IIT Kanpur (2012). His research publications in high-impact journals demonstrate his expertise in semiconductor device modeling, particularly in MOSFET physics and SOI technology. Distinguished Teacher Award of IIT Kanpur (2013) Ranjit Singh Chair Professor position at IIT Kanpur (2012) Best Dissertation Award by the Graduate Student Council at LSU (1989) Kaiser Fellowship for outstanding research at LSU (1986) Dr. B.C. Roy Gold Medal at Jadavpur University (1982) Professor Dutta has mentored numerous students in the field of semiconductor devices and VLSI circuits. His research has been supported by various grants that have contributed to advancements in semiconductor technology and device modeling. His work spans fundamental semiconductor physics, device modeling techniques, and practical applications in integrated circuit design. His laboratory at IIT Kanpur focuses on semiconductor device characterization and modeling, providing students with hands-on experience in cutting-edge technologies related to integrated circuit design and fabrication. The research environment supports work on MOSFET physics, SOI technologies, and quantum mechanical effects in semiconductor devices.

• Integrated Circuits
• Mixed-Signal Computing
• Neural Recording Systems
• +1 more

Boris Murmann is Professor at Stanford University, specializing in integrated circuit design, mixed-signal computing, and energy-efficient AI hardware. His research advances neural interface technologies, analog design automation, and tinyML systems. Recent work develops ultra-low-power neural recording ICs for brain-computer interfaces, RRAM-based memory systems, and open-source semiconductor design frameworks. Publications demonstrate innovations in compressive sensing for neural data, hardware-algorithm co-design, and reinforcement learning for analog circuit synthesis. Significant contributions include Medusa (TinyML processor), EMBER (RRAM macro), and methodologies for coarsely-quantized computer vision and analog design automation.

David BlaauwView profile

Professor

• Ultra-Low Power Circuits
• IoT and Sensor Networks
• RF Communication
• +7 more

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)

• Microelectronics
• Analog/Digital Circuit Design
• Ultra Low Power Circuits
• +1 more

Snorre Aunet is a Professor at the Department of Electronic Systems at the Norwegian University of Science and Technology (NTNU), with additional roles as an Adjunct Professor at the Department of Informatics, University of Oslo. His academic career spans institutions in Norway, Germany, and the USA, including sabbaticals at Bielefeld University and University of California, San Diego. Education: Electronics Engineering (Trondheim Technical College, 1987), Informatics (UiO, 1993), and Physical Electronics (NTNU, 2002) Research Focus Dr. Aunet specializes in ultra-low-power mixed-signal integrated circuits and nanoscale CMOS technologies . His work includes innovative MEMS transducer designs for energy harvesting, digital IC development, and robust circuit solutions for emerging semiconductor challenges. Recent Publications His recent contributions include advancements in MEMS technology for sustainable energy systems, editorial leadership at NorCAS conferences, and policy discussions on the European Chips Act. These reflect expertise in both cutting-edge design and strategic technology development. Scientific Recognition 2019: Elected to Norwegian Academy of Technical Sciences (NTVA) 2015: Best Paper Award at Asia Symposium on Quality Electronic Design 2006: IEEE Senior Member (Electron Devices Society) 2003: Best Poster Award at Int'l Conf. on Evolvable Systems Leadership & Grants He has chaired multiple IEEE conferences and contributed to projects like Robust Ultra-Low-Power Circuits for Nano-Scale CMOS (NTNU/University of Paderborn). His career combines academic leadership with industry collaboration through Nordic Semiconductor and international research councils.

• RF IC Design
• Mixed-Signal IC Design
• Wireless Communication Systems
• +4 more

Bertan Bakkaloglu is the On Semiconductor Professor in the School of Electrical, Computer and Energy Engineering at Arizona State University (ASU), where he has been since 2004. Prior to ASU, he worked at Texas Instruments focusing on analog, mixed-signal, and RF SoC development for communication transceivers. His research expertise spans RF and mixed-signal IC design, wireless/wireline communication systems, and broadband communication systems. Education: Ph.D. in Electrical Engineering, Oregon State University (1995) M.S.C. in Electrical Engineering, University of Houston (1992) Research Interests: RF and mixed-signal integrated circuits Power management ICs (including LDO regulators and DC-DC converters) High-efficiency power delivery systems Radiation-hardened electronics for space applications MEMS-based sensor systems Biomedical circuits for implantable devices Grants & Collaborations: Over 40+ funded research projects with institutions like NASA/JPL, BAE Systems, and NSF, focusing on power electronics, space systems, and biomedical applications Key projects include radiation-hardened converters, self-calibrating DACs, and implantable medical device circuits Industry partnerships with Texas Instruments, Space Micro, and FLIR Professional Activities: Technical committee member for IEEE Radio Frequency Integrated Circuits Conference Founding chair of IEEE Solid-State Circuits Society Phoenix Chapter

Alyssa B. ApselView profile

Professor

• RF Mixed Signal Circuit Design
• Ultra-Low Power Radio
• Photonic Integration with VLSI
• +4 more

Alyssa B. Apsel is a Professor of Electrical and Computer Engineering at Cornell University since 2002 and a Visiting Professor at Imperial College London. She became the IBM Professor of Engineering in 2023 and Director of Electrical and Computer Engineering at Cornell in 2018. Education: B.S., Electrical Engineering, Swarthmore College (1995) M.S., Electrical Engineering, California Institute of Technology (1996) Ph.D., Electrical Engineering, Johns Hopkins University (2002) Research Focus: She specializes in power-aware mixed-signal circuits for scaled CMOS and modern systems. Her group explores cost-effective designs addressing device scaling challenges (variation, noise, reduced analog performance) through analog/mixed-signal innovation, particularly in IoT radios and reconfigurable multi-standard wireless systems. Key areas: RF circuits, VLSI integration, biomedical telemetry, and low-power design. Publication Trends: Her 2016 work spans RF transceiver design, thermometer DAC calibration, biomedical ICs with UWB telemetry, and jitter-measurement circuits. These reflect her expertise in low-power wireless systems, analog/mixed-signal design, and biomedical electronics. Awards: IEEE Fellow (2020) IEEE CAS Distinguished Lecturer (2018-2019) ISLPED Design Contest Second Place (2010) Multiple Student Paper Awards (2000, 1995) Fellowships: Abel Wolman (1997), Caltech Institute (1995) Grants & Leadership: She founded EchoICs, which received a $275,000 NSF STTR Phase I Award (2024) for flexible spectrum radios. Her lab focuses on RF interfaces for implantable electronics and photonic integration.

Eby G. FriedmanView profile

Professor

• VLSI Design
• Integrated Circuit Design
• Low Power CMOS
• +4 more

Eby G. Friedman is a Professor in the Department of Electrical and Computer Engineering at the University of Rochester, where he has served since 1991 as director of the High Performance VLSI/IC Design and Analysis Laboratory. He concurrently holds a visiting professor position at the Technion - Israel Institute of Technology, directing the Technion Advanced Circuits Research Center (ACRC). His research specializes in high performance synchronous digital and mixed-signal microelectronic design with applications in high-speed portable processors and low-power wireless communications. Core focus areas include CMOS circuit design, clock/power distribution networks, interconnect synthesis, substrate noise mitigation, pipelining techniques, and 3-D integration methodologies. His work bridges theoretical frameworks with practical implementations in VLSI systems. Scientific Awards and Honors IEEE Fellow Distinguished Lecturer of the IEEE CAS Society Dr. Friedman has authored or edited 16 books and nearly 500 publications, establishing foundational contributions in clock distribution and power delivery networks. He maintains significant editorial leadership as Editor-in-Chief of the Microelectronics Journal, past Editor-in-Chief of IEEE Transactions on VLSI Systems, and serves on the editorial boards of the Journal of Low Power Electronics, Journal of VLSI Signal Processing, Journal of Low Power Application and Circuits, and Proceedings of the IEEE. His laboratory directs cutting-edge research in high-speed circuit design and 3-D integration architectures.

John D. CresslerView profile

Professor

• Silicon-Germanium Heterojunction Bipolar Transistors (SiGe HBT)
• Mixed-Signal Semiconductor Devices
• RF and Microwave Circuit Design
• +5 more

Professor John D. Cressler is a tenured faculty member at the Georgia Institute of Technology, holding a position within the School of Electrical and Computer Engineering in the College of Engineering. His research focuses on cutting-edge semiconductor technologies, particularly silicon-germanium heterojunction bipolar transistors (SiGe HBTs) for mixed-signal applications spanning RF, microwave, mm-wave, analog, and digital domains. His research interests center on atomic-scale bandgap engineering for next-generation semiconductor devices, with emphasis on SiGe HBT technology development, radiation-hardened circuits for space applications, cryogenic electronics, and device-circuit interactions. His team explores fundamental device theory, broadband noise analysis, profile optimization, 2-D/3-D simulation, compact modeling, and radiation effects. Current projects include Europa-surface mission electronics, D-band/sub-THz systems, and radiation-tolerant receiver designs. Analysis of his 15 most recent publications (2024-2025) reveals a dominant focus on radiation-hardened electronics for space applications (40% of works), millimeter-wave circuit design (30%), and SiGe HBT reliability optimization (30%). Key trends include Europa mission electronics development, D-band/sub-THz circuit innovation, and advanced radiation mitigation techniques using SiGe BiCMOS technology. Professor Cressler teaches multiple courses including ECE 3040 (Microelectronic Circuits), ECE 3450 (Semiconductor Devices), ECE 6444 (Silicon-Based Heterostructure Devices and Circuits), and the interdisciplinary IAC 2002 course on Science, Engineering and Religion. His research is supported by industrial collaborations and Georgia Tech facilities including the Georgia Electronic Design Center (GEDC), NanoTECH, and C-STAR.

Kwantae KimView profile

Assistant Professor

• Power-Efficient Analog/Mixed-Signal Integrated Circuits
• Biomedical Sensor Systems
• Neuromorphic Sensor ICs
• +3 more

Kwantae Kim is an Assistant Professor at the Department of Electronics and Nanoengineering within Aalto University's School of Electrical Engineering . He leads the Tiny Systems and Circuits (TSirc) Group , focusing on power-efficient analog/mixed-signal ICs for biomedical and neuromorphic sensor systems. IEEE Senior Member (2025) Collaborates with institutions across Europe, Asia, and America Specializes in ultra-low-power AI-embedded IoT platforms His research emphasizes Tiny, Sensory, Intelligent, and Wireless IoT systems through: Development of energy-efficient IC architectures Democratizing access to advanced chip design Hardware-software co-design for edge computing Recent publications highlight innovations in: Spoken-language-understanding SoCs Temporal-sparsity-aware keyword spotting Open-source silicon frameworks Awards include: 2025 IEEE Senior Member 2023 Best Poster Award (AICAS) 2019 Samsung HumanTech Silver Award Research partnerships span: Prof. Tobi Delbruck (UZH/ETH Zurich) Prof. Hoi-Jun Yoo (KAIST) Prof. Shih-Chii Liu (UZH) Prof. Sohmyung Ha (NYU Abu Dhabi)

Ningyuan CaoView profile

Assistant Professor

• Machine Learning Acceleration
• Real-Time Systems
• Low-Power Circuits
• +7 more

Ningyuan Cao is an Assistant Professor in the Department of Electrical Engineering at the University of Notre Dame, College of Engineering. He leads the Circuit and System Intelligence Research Lab , focusing on the intersection of advanced hardware design and real-time/low-power machine learning applications. Education : Ph.D., Electrical and Electronics Engineering, Georgia Institute of Technology (2020) M.S., Electrical Engineering, Columbia University (2015) B.S., Electrical and Electronics Engineering, Shanghai Jiao Tong University (2013) His research investigates custom analog/mixed-signal circuits , digital architecture , and micro-system design for machine learning acceleration, distributed intelligence, and data-driven IC design automation. Key application domains include Internet-of-Everything, tactile internet, and mixed reality systems. Recent publications highlight work on Bayesian neural networks , privacy-preserving bio-signal encoders , transformer-based surrogate models , and compute-in-memory architectures . Technical themes span neuromorphic computing, uncertainty quantification, and hardware security.

• Physical Oceanography
• Upper Ocean Dynamics
• Coastal Ocean Processes
• +7 more

Craig Lee is a Professor of Oceanography at the University of Washington, where he also serves as Senior Principal Oceanographer and Assistant Director for Research at the Applied Physics Laboratory. His work focuses on physical oceanography with emphasis on observational studies and instrument development. Lee leads research programs studying upper ocean dynamics, coastal processes, and high-latitude oceanography across diverse regions including the Arctic, North Atlantic, and South China Sea. Dr. Lee's educational background includes: B.S. in Electrical Engineering and Computer Science from the University of California, Berkeley (1987) Ph.D. in Physical Oceanography from the University of Washington (1995) Lee's primary research interests center on three interconnected areas: (1) upper ocean dynamics, particularly mesoscale and submesoscale fronts and eddies; (2) interactions between biology, biogeochemistry and ocean physics; and (3) high-latitude oceanography in changing Arctic environments. His work often combines field observations with instrument development to address fundamental questions about ocean circulation and its role in climate systems. He has pioneered approaches using autonomous platforms to study difficult-to-access regions like ice-covered waters. Analysis of Lee's recent publications reveals a strong focus on Arctic oceanography, upper ocean mixing processes, and the application of autonomous observing technologies. His research spans multiple ocean basins with particular emphasis on the Arctic, North Atlantic, and western Pacific. A notable trend is the increasing integration of biogeochemical measurements with physical oceanography to understand coupled systems. His work often addresses climate-relevant questions about ocean circulation, heat transport, and ecosystem responses to environmental change. Dr. Lee provides leadership through service on science steering committees for large research programs and advisory panels for U.S. Arctic efforts. He actively supports and advises graduate students while teaching courses on ocean circulation observations and experimental design. His team has developed innovative technologies including autonomous gliders for ice-covered waters, high-performance towed vehicles, and lightweight mooring systems. Lee leads a research team pursuing diverse field programs including Arctic PISCES, Stratified Ocean Dynamics of the Arctic (SODA), and studies of the Kuroshio Current. His group collaborates extensively with institutions worldwide and contributes to major international research initiatives focused on understanding ocean processes and their climate implications.

David Zhigang PanView profile

Professor

• Electronic Design Automation
• Machine Learning
• Hardware Acceleration
• +5 more

David Zhigang Pan is a Professor in the Department of Electrical & Computer Engineering at The University of Texas at Austin. He also holds the Silicon Laboratories Endowed Chair. Prior to joining UT Austin, he was a Research Staff Member at IBM T. J. Watson Research Center from 2000 to 2003. His academic journey began with a B.S. from Peking University, followed by M.S. and Ph.D. degrees from UCLA. Research Areas: Electronic Design Automation (EDA), Machine Learning Hardware, FPGA Prototyping, Optical Computing, Hardware Security, and CAD for Emerging Technologies Academic Timeline: Assistant Professor (2003-2008), Associate Professor (2008-2013), Full Professor (2013-present) His research focuses on design automation for mixed-signal circuits , GPU-accelerated EDA tools , and hardware-software co-design for AI . Recent work explores FFT-based optical neural networks and deobfuscation techniques for integrated circuits , reflecting his interdisciplinary approach at the intersection of machine learning , computer architecture , and semiconductor manufacturing . Key publication trends reveal expertise in: VLSI design , lithography optimization , and deep learning applications for EDA tools. His work has been recognized with multiple Best Paper Awards at top conferences including DAC , ASP-DAC , and HOST . Awards: IEEE Fellow (2014), SPIE Fellow (2017), ACM SRC Graduate Category Honors for students Patents: 8 U.S. Patents in electronic design and hardware optimization Prof. Pan has mentored 40 PhDs and postdocs who now hold key positions in academia and industry. He leads research initiatives involving GPU acceleration frameworks and optical computing architectures . His lab focuses on vertical integration of architecture, CAD tools, and fabrication technologies for next-generation hardware solutions.