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Dr. Ava Hedayatipour is an Assistant Professor of Electrical Engineering at California State University at Long Beach (CSULB), where she joined in Fall 2020. She holds a Ph.D. from the University of Tennessee, Knoxville (2020), and degrees from Iran University of Science and Technology (B.S., 2012) and Shahid Rajaee Teacher Training University (M.S., 2015). Her research focuses on analog/mixed-signal circuit design, bio-implantable devices, low-power systems, and hardware security. Notable contributions include a first-of-its-kind integrated secure multimodal sensor and a flexible paper electrode for remote electrochemical experiments. Education: Ph.D., Electrical Engineering, University of Tennessee, Knoxville, 2020 M.S., Electrical Engineering, Shahid Rajaee Teacher Training University, Iran, 2015 B.S., Electrical Engineering, Iran University of Science and Technology, 2012 Research Interests: Analog and mixed-signal circuit design Biomedical devices and lab-on-chip applications Low-power, low-noise microelectronics Hardware security for IoT and biomedical sensors Flexible electrodes for wearable systems Awards: University of Tennessee Fellowship Award (2019) Outstanding Teaching Assistant Award (2018) BEST PAPER AWARD at IEEE DCAS 2025 2nd Place Winner at IEEE BIOCAS 2023 Innovation Challenge Advising & Grants: Lead CSULB LEAP program project on medical imaging braces Funded NSF project on chaotic analog security (2018–present) Collaborated with industry partners like Applied Medical and Synaptics Labs & Teams: Next Generation Wearable Lab at CSULB Focus on sensor design, hardware security, and biomedical applications

• Analog Integrated Circuit Design
• Bio-implantable and Biomedical Devices
• Low-Power and Low-Noise Designs
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Donald Lie is a Professor and the Keh-Shew Lu Regents Chair in Electrical and Computer Engineering at Texas Tech University's Whitacre College of Engineering. His research focuses on low-power RF/analog integrated circuits, System-on-a-Chip (SoC) design, and interdisciplinary applications in medical electronics, biosensors, and biosignal processing. PhD, Electrical Engineering, California Institute of Technology (1995) MS, Electrical Engineering, California Institute of Technology (1990) BS, Electrical Engineering, National Taiwan University (1987) Donald Lie's research bridges RF/analog circuit design with biomedical engineering, emphasizing millimeter-wave power amplifiers for 5G systems and non-contact vital signs monitoring using software-defined radio (SDR). His work explores CMOS FD-SOI, GaN HEMTs, and SiGe technologies for high-efficiency, linear RF front-end modules and wearable biosensors. His 15 most recent publications focus on 5G communication systems , millimeter-wave power amplifier design in CMOS FD-SOI and GaN , digital predistortion techniques, and non-contact biosensors . These works highlight advancements in wideband amplifiers for 5G FR2 bands and wireless power transfer for medical devices. Institute of Electrical and Electronics Engineers (2017) Excellent Paper Award Winner (2019) Best Student Poster Paper Award Winner (2019) Donald Lie has secured NSF Student Travel Grants for conferences like RFIC 2022 and 2020. He leads the RF/Analog System-on-a-Chip (SoC) Design Lab , which develops innovative solutions for 5G RF front-ends and biomedical sensing systems.

• Low-Power RF/Analog Integrated Circuits
• System-on-a-Chip (SoC) Design
• Medical Electronics
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Yiorgos Makris is a Professor in the Department of Electrical and Computer Engineering at the Erik Jonsson School of Engineering & Computer Science, The University of Texas at Dallas, since July 2011. Previously, he was a faculty member at Yale University for over a decade. He holds a Ph.D. in Computer Engineering from the University of California, San Diego, and a Diploma in Computer Engineering from the University of Patras, Greece. Education: Ph.D. in Computer Engineering, University of California, San Diego (2001) M.S. in Computer Engineering, University of California, San Diego (1997) Diploma in Computer Engineering and Informatics, University of Patras, Greece (1995) Research Interests: Hardware Security and Trustworthiness Statistical Side-Channel Fingerprinting Machine Learning in Semiconductor Manufacturing Trusted and Reliable Integrated Circuits Hardware Trojans in Wireless Cryptographic ICs On-Die Learning and Emergent Technologies His work focuses on enhancing hardware security through statistical methods, machine learning, and formal verification, with applications in analog/RF ICs, post-production calibration, and secure IC design. Key Contributions: Co-Founder and Site-PI of NSF CHEST I/UCRC (Hardware and Embedded System Security and Trust) Leader of the Safety, Security, and Healthcare Thrust at TxACE (Texas Analog Center of Excellence) Director of the Trusted and RELiable Architectures (TRELA) Lab Grants and Funding: NSF, NIH, SRC, ARO, AFRL, AFWERX, DARPA, DOE, and industry partnerships with Boeing, Northrop Grumman, IBM, Intel, Qualcomm, etc. Recent grants include projects on DNA storage security, analog neural networks, and malicious hardware detection. Awards and Recognition: IEEE Fellow (2025) Best Paper Awards at DATE'13, VTS'15, DCAS'22 Best Hardware Demonstration Awards at HOST'16 and HOST'18 Erik Jonsson School Faculty Research Award (2020) Labs and Teams: TRELA Lab (Focus: Secure Hardware Design, Trusted Architectures) CHEST I/UCRC (Industry-University Collaboration)

• Hardware Security
• Trusted Systems
• Machine Learning in Semiconductor Manufacturing
• +9 more

Sonali Das is a Lecturer in the Department of Electrical and Computer Engineering at the University of Central Florida. She earned her Ph.D. in Electrical Engineering from the Indian Institute of Engineering Science and Technology, India, in 2017. Research Interests: Her work focuses on device electronics, RF and microwave MEMS, solar cells, phototransistors, optoelectronic synaptic and neuromorphic devices, and emerging micro-nano fabrication technologies. She investigates light-trapping mechanisms in solar cells, develops biomimetic photovoltaic structures, and explores 2D material-based memristors for neuromorphic computing. Professional Activities: Das has served as a technical reviewer for the UCF Seed Funding Program (2019), instructor for Camp Connect I and II lab tours (2017–2019), and mentor for Camp Connect III programs at UCF (2019). She is an IEEE member. Scientific Awards: GAP Award, UCF Research Foundation and UCF Office of Technology Transfer (2019) Fulbright Bhaskara Advanced Solar Energy (BASE) Fellowship (2015) Teaching: She teaches courses including Semiconductor Devices (EEE 3350), Electronics I and II (EEE 3307/4309), Linear Circuits II (EEL 3123), Electromagnetic Fields (EEL 3470), Signal Analysis & Analog Communication (EEL 3552), Linear Control Systems (EEL 3657), and Digital Systems (EEE 3342).

• Device Electronics
• RF and Microwave MEMS
• Solar Cells
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Albert H. Titus is a Professor in the Department of Biomedical Engineering and an Adjunct Professor in the Department of Electrical Engineering at the University at Buffalo, State University of New York. He serves as Associate Vice President for Regulatory Support in the Office of the Vice President for Research and Economic Development. His research focuses on analog VLSI design for neuromorphic visual processing, biosensors, wearable devices, optoelectronic systems, and neural networks. Education: PhD in Electrical and Computer Engineering, Georgia Institute of Technology (1997) MS in Electrical Engineering, University at Buffalo (1991) BS in Electrical Engineering, University at Buffalo (1989) Research Interests: His work spans wearable and implantable sensors, bioinstrumentation, neural network-based visual processing, analog VLSI implementations, optoelectronics, and electronic packaging. He pioneered CMOS-based neuromorphic systems and developed patented technologies for glare sensing and RF power calorimetry. Publication Trends: His recent articles emphasize CMOS-integrated sensors, machine learning for bioimpedance analysis, implantable medical devices, and xerogel-based optical biosensors. These works bridge biomedical engineering and microelectronics. Scientific Recognition: He is a Fellow of the National Academy of Inventors and has received the SUNY Chancellor’s Award for Excellence in Service (2017), NSF CAREER award, and Western New York Inventor of the Year (2010). His inventions include a patented low-power glare sensor (U.S. Patent 7,586,079) featured in Popular Science’s 2011 Top Ten Inventions. Academic Leadership: As a faculty member, he has supervised nearly 20 PhD and over 40 MS students, while teaching courses in circuits, IC design, sensors, and signal processing across electrical and biomedical engineering disciplines.

• Wearable Sensors
• Biosensors
• Bioinstrumentation
• +5 more

Ankit Mittal is a Research Fellow in the Department of Electrical and Computer Engineering at Northeastern University. His research focuses on energy-efficient systems, wireless power transfer, IoT infrastructure, analog circuit design, and biomedical applications such as neural implants. He is based at 360 Huntington Ave, Boston, MA 02115, and can be reached at a.mittal@northeastern.edu. Mittal's work emphasizes secure analog circuit design, energy harvesting techniques for ultra-low power applications, and the integration of magnetoelectric antennas for medical and IoT devices. His research bridges electronics, signal processing, and biomedical engineering, with a particular emphasis on practical implementations for precision agriculture and neural monitoring systems. His publications highlight advancements in IoT security, RF rectifier optimization, and the development of compact, efficient energy harvesting systems. The articles collectively reflect a trend toward low-power, high-efficiency solutions for wireless communication and biomedical engineering challenges. No scientific awards or grants are explicitly mentioned in the provided information. Mittal currently has no listed advisees or students. Labs or collaborative teams associated with his work are not detailed in the available text.

• Energy-Efficient Systems
• Wireless Power Transfer
• IoT Infrastructure
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Dr. Afshin Daryoush is a Professor in the Department of Electrical and Computer Engineering at Drexel University’s College of Engineering. He earned his Ph.D. and M.S. in Electrical Engineering from Drexel and a B.S. in Electrical Engineering from Case Western Reserve University. His academic career spans decades of innovation in microwave photonics, with a focus on RF circuits, wireless communications, and biomedical applications. Research interests include Microwave Photonics Systems Nonlinear Microwave Circuits RFIC and Wireless Communications Antennas and Radiating Systems Electromagnetic Interaction with Biological Systems His recent publications emphasize advancements in microwave photonics and optical engineering, particularly in all-optical analog-to-digital converters, optoelectronic oscillator design, and 3D-printed microwave components. These works span disciplines like Electrical Engineering, Photonics, and Materials Science, with subfields covering frequency synthesis, tunable antennas, photonic crystals, and high-speed signal processing. Scientific achievements include Microwave Prize at the 16th European Microwave Conference (1986) Elevation as Fellow of IEEE (1998) for contributions to nonlinear microwave photonics Drexel University College of Engineering Outstanding Innovation Award (2020) Drexel Alumni Association Award (2018) IEEE Philadelphia Section Benjamin Franklin Key Medal (2015) Dr. Daryoush has advised students whose works have won best paper awards at IEEE conferences. He has secured grants from US government agencies and aerospace/telecom companies, held visiting scholar roles at NTT and CNRS, and contributed to over 200 publications and five book chapters. His collaborations extend to institutions in France, Japan, and the US.

• Microwave Photonics
• Nonlinear Microwave Circuits
• RFIC and Wireless Communications
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Mark F. Bocko is a Professor of Electrical and Computer Engineering and Physics at the University of Rochester, serving as Chair of the Department of Computer and Electrical Engineering since 2004. He holds a BA from Colgate University and advanced degrees (MS/PhD) in Physics from the University of Rochester. His research spans superconducting digital electronics, quantum computing, music signal processing, and smart sensor systems. Notable awards include the Excellence in Undergraduate Teaching Award (1991, 2002) and Professor of the Year (2002). His research groups focus on high-frequency digital signal processing using Josephson junctions, quantum coherence in superconducting circuits, and applications in music technology such as internet-based real-time musical collaboration. Collaborations include work with the Eastman School of Music and local industries on sensor networks and wireless technologies. Key contributions include developing GHz-rate analog-to-digital converters, quantum bit control systems, and music encoding algorithms. His NSF-funded projects explore internet2 applications for musical interaction and physical modeling in music systems.

• Superconducting Digital Electronics
• Quantum Computing
• Digital Signal Processing
• +4 more

Guofu Niu is a Professor in the Department of Electrical and Computer Engineering at Auburn University, holding the Ed and Peggy Reynolds Family endowed chair. His research specializes in semiconductor device physics, compact modeling of SiGe heterojunction bipolar transistors (HBTs), FinFETs, and cryogenic electronics for RF and power applications. Key research areas include RF linearity characterization, avalanche effects, thermal noise, and low-temperature device performance. He has developed advanced models (e.g., Mextram) for circuit simulation tools, enhancing the accuracy of semiconductor design workflows. Publications focus on nano-scale device reliability, tunneling currents, and optimization of RF amplifiers, with applications in 5G technology and extreme-environment electronics. Collaborative projects span industry and academia to advance semiconductor modeling frameworks.

• Semiconductor Devices
• Compact Modeling
• RF Circuit Design
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Yong-Bin Kim is a Professor in the Department of Electrical and Computer Engineering at Northeastern University, part of the College of Engineering. He has held prior positions at Intel Corp., Hewlett Packard Co., Sun Microsystems, and the University of Utah. His research focuses on integrated circuit design, nanoelectronics, bio-chip interfaces, and low-power VLSI systems. He has contributed to initiatives like the HPVLSI Lab and Microsystems and Electron Devices Lab. Education includes a B.S. in Electronic Engineering from Sogang University (Seoul, South Korea), an M.S. from the New Jersey Institute of Technology, and a Ph.D. in Computer Engineering from Colorado State University (1996). Research interests encompass high-speed low-power VLSI design, system-on-chip (SoC), physical VLSI CAD, and nanoelectronics. Specific areas include bio-sensor interface circuits, electronic neuron design, and adaptive robot controllers. Key projects involve compact power-efficient integrated circuits and high-speed transceiver design. Outstanding Paper Award, 2020 IEEE ISOCC South Korean Patent for Autonomous Impedance Calibration (2021) Best Paper Award, 2016 International SoC Design Conference Patent for Improved Receiver Circuit (2020) Patent for Method to Detect Trojan Circuits (2018) Advisees include graduate student Yixuan He. He has led research projects funded by Winchester Technology and Hynix Semiconductor, focusing on semi-self-calibration transceivers and tunable RF inductors. Labs include the HPVLSI Lab and Microsystems and Electron Devices Lab at Northeastern University, which focus on high-speed/low-power IC design and microfabrication technologies.

• Integrated Circuit Design
• Nanoelectronics
• High-Speed System Integration
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Matthew Heins is an Associate Professor of Instruction in Electrical Engineering at The University of Texas at Dallas, affiliated with the Erik Jonsson School of Engineering and Computer Science. He holds an office in ECSN 4.608 and can be reached via email at Matthew.Heins@utdallas.edu or phone at +1 (972) 883-3846. His research interests focus on high-speed electronics, semiconductor device applications, and advanced amplifier design for optical and microwave systems. Key areas include transimpedance amplifiers, GaAs-based HEMT technologies, and millimeter-wave systems. Matthew has contributed to the development of high-performance integrated circuits for fiber-optic communications, coherent optical receivers, and low-noise amplifiers operating at Ka-band and beyond. His publications highlight advancements in SiGe BiCMOS technology for optical receivers (2017), quad-channel transimpedance amplifiers (2016), and X-band GaAs mHEMT LNAs (2004). Earlier work includes pioneering contributions to metamorphic HEMT applications (2003), 40-Gb/s optical driver amplifiers (2002), and W-band HBT frequency sources (1999). Matthew’s research emphasizes practical implementations of semiconductor devices in high-frequency systems, blending theoretical analysis with hands-on circuit design. No awards or grants are explicitly mentioned in the text, though his extensive publication record reflects sustained contributions to the field.

• Electrical Engineering
• Semiconductor Devices
• Optical Communications
• +3 more

Emre Salman is a Professor in the Department of Electrical and Computer Engineering at Stony Brook University (SUNY), where he directs the Nanoscale Circuits and Systems (NanoCAS) Lab. His research focuses on nanoscale IC design, energy-efficient computing, and biomedical electronics, with notable contributions to 3D integrated circuits and wireless energy harvesting for IoT and healthcare applications. Education : PhD in Electrical Engineering, University of Rochester (2009) MSc in Electrical and Computer Engineering, University of Rochester (2006) BSc in Microelectronics Engineering, Sabanci University, Turkey (2004) Research Interests : Salman’s work spans energy-efficient integrated circuits, secure IoT systems, and implantable medical devices. He pioneers techniques like charge-recycling logic and thermal-aware design for post-Moore computing. His group develops monolithic 3D ICs to address power/thermal challenges in AI accelerators and biomedical implants. Articles Trends : Recent publications highlight advancements in triboelectric energy harvesters for knee implants, thermal covert channel mitigation in 3D processors, and energy-efficient DNN accelerators. He emphasizes sustainability and security in emerging technologies like ReRAM-based computing and AC circuits for wireless IoT. Awards : 2023-2024 IEEE Distinguished Lecturer 2018 IEEE Region 1 Technological Innovation Award 2013 NSF CAREER Award Advising & Grants : Salman has directed multiple NSF, NIH, and industry-funded projects. He advises students on topics like hardware security and biomedical electronics, with a focus on translating research into commercializable technologies. Labs & Teams : The NanoCAS Lab collaborates with Brookhaven National Lab and industry partners (e.g., AMD, Samsung) to bridge academic research with real-world applications in energy-efficient computing and secure 3D ICs.

• Integrated Circuits (ICs)
• VLSI Systems
• Energy-Efficient Computing
• +5 more

Jesús del Alamo serves as the Donner Professor of Science within MIT’s Department of Electrical Engineering and Computer Science, leading cutting-edge research in semiconductor device physics with applications spanning logic, high-frequency, and power electronics. His work bridges fundamental materials science with practical device engineering to address next-generation computing challenges. Academic Credentials: PhD, Stanford University MS, Stanford University Research Focus: Professor del Alamo’s expertise centers on transistor physics and semiconductor device innovation, particularly III-V compound semiconductors (InGaAs, GaN) and diamond MOSFETs. Current investigations target reliability mechanisms in GaN transistors for RF/power applications, novel analog computing architectures, and electrochemical ionic synapses for neuromorphic hardware. His group pioneers atomic-scale fabrication techniques like thermal atomic layer etching for sub-5nm devices while exploring quantum confinement effects in vertical nanowires. Publication Evolution: Recent work (2023-2025) demonstrates a strategic shift toward neuromorphic computing, with 60% of publications focusing on electrochemical synapses and ferroelectric memories for AI acceleration. This builds upon decades of transistor scaling research, now converging with materials innovations in HfZrO 2 ferroelectrics and protonic conductors to enable energy-efficient analog deep learning hardware. Award Recognition: Louis D. Smullin Award for Excellence in Teaching Amar Bose Award for Excellence in Teaching Intel Outstanding Researcher Award Semiconductor Research Corporation Technical Excellence Award Semiconductor Industry Association-Semiconductor Research Corporation University Researcher Award Collaborative Leadership: He directs research within MIT’s Microsystems Technology Laboratories (MTL), collaborating with faculty including Bilge Yildiz (electrochemical systems) and Ju Li (computational materials). Current projects integrate device physics with neuromorphic algorithms, supported by semiconductor industry partnerships focused on translating fundamental discoveries into practical AI hardware solutions. Research Infrastructure: His group operates within MIT’s MTL cleanroom facilities, utilizing advanced characterization tools for in-situ device analysis and leveraging partnerships with industry leaders in semiconductor manufacturing to prototype novel transistor architectures.

• Semiconductor Devices
• Transistor Physics
• III-V Compound Semiconductors
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Professor Ahmet Bindal is a faculty member in the Department of Computer Engineering at San José State University . He earned his B.S. in Electrical Engineering from Bogazici University, Turkey, followed by M.S. and Ph.D. degrees from the University of California, Los Angeles. Industry Experience : 20 years at IBM, Intel, Philips, and Cadence Design Systems. Current Research : Nano-scale electron devices, silicon nanowire transistors, robotics, and VLSI architecture. Research Trends : His work focuses on silicon nanowire transistors for VLSI, FPGA, and robotics. Key themes include low-power/high-speed integrated circuits , dynamic logic design , neuromorphic engineering , and advanced semiconductor processing . Patents and Publications : He holds four U.S. patents (three with IBM, one with Intel). His 30+ journal and conference publications span nanowire transistors, FPGA architecture, robotics, and semiconductor process modeling. Teaching Contributions : Developed an undergraduate System-on-Chip (SoC) course and a MOSFET design laboratory at SJSU. Books Authored : Fundamentals of Computer Architecture and Design (Springer, 2017). Electronics for Embedded Systems (Springer, 2017). Silicon Nanowire Transistors (Springer, 2017).

• Nano-scale Electron Devices
• Silicon Nanowire Transistors
• VLSI Architecture
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Jennifer Kitchen is an Associate Professor at the School of Electrical, Computer and Energy Engineering, Arizona State University. She joined ASU in 2013 and has focused on efficiency enhancement and linearization techniques for RF power amplifiers, high-efficiency power management systems using gallium-nitride (GaN), and integrated circuit design for wireless and SATCOM applications. Education: Ph.D. in Electrical Engineering, Arizona State University (2007). Research Interests: Her work spans RF integrated transceivers on silicon and III-V processes (GaN), power management systems for green energy (solar arrays, batteries), and programmable broadband transceivers for 5G wireless communication. She explores exotic materials like GaN to improve circuit integration and energy efficiency. Scientific Awards: Recognized as a National Science Foundation Graduate Fellow and Semiconductor Research Corporation Master’s Scholar during her graduate studies. Teaching: She teaches courses such as EEE 334: Circuits II and EEE 335: Analog and Digital Circuits , alongside advising graduate students in research, thesis, and dissertation projects. Industry Experience: Prior to her academic role, she worked at Motorola Inc., Freescale Semiconductor, and held leadership positions at Ubidyne Inc. and ViaSat Inc., focusing on wireless basestations and military-grade integrated circuits.

• RF Integrated Transceivers
• High-performance Power Management
• Green Energy Systems
• +3 more