Rikky Muller is an Associate Professor of Electrical Engineering and Computer Sciences at UC Berkeley, holding the S. Shankar Sastry Professorship in Emerging Technologies. She is Co-director of the Berkeley Wireless Research Center (BWRC), a Core Member of the Center for Neural Engineering and Prostheses (CNEP), and an Investigator at the Chan-Zuckerberg Biohub. Her research focuses on implantable/wearable medical devices, low-power wireless systems, and neurotechnology for neurological applications. Education: PhD (2013), UC Berkeley; BS and M.Eng. (2004), MIT, all in EECS. Prior roles include IC designer at Analog Devices and co-founder of Cortera Neurotechnologies (acquired). Research interests include neural interfaces, closed-loop neuromodulation, and biomedical microelectronics. Notable contributions include Neural Dust (ultrasonic implants), wireless EEG systems, and seizure prediction hardware. Awards: MIT TR35 Innovator, NAE Gilbreth Lectureship, NSF CAREER Award, IEEE SSCS New Frontier Award Grants: Bakar Fellows, Hellman Fellowship, NSF CAREER Labs: Muller Lab (UC Berkeley EECS), Chan-Zuckerberg Biohub collaborations
Songbin Gong is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Illinois at Urbana Champaign, where he has been a faculty member since August 2013. He was promoted from Assistant Professor to Associate Professor in August 2019 and holds the Intel Alumni Fellowship. His research is centered at the Micro and Nanotechnology Lab, where he leads the Integrated RF Microsystems research group. Professor Gong's research focuses on RF and microwave photonics, microwave acoustics, and Micro-Electro-Mechanical Systems, with particular expertise in lithium niobate-based devices. His work spans the development of acoustic resonators, filters, and transducers operating from VHF to Sub-THz frequencies. Recent publications demonstrate significant advances in high-frequency acoustic devices, including GHz resonators with high electromechanical coupling and low loss characteristics. His research has direct applications in 5G communications, wireless sensing, and imaging systems. Gong has established himself as a leader in the field of RF MEMS and acoustic devices, with numerous high-impact publications in top journals including IEEE Transactions on Microwave Theory and Techniques, Journal of Microelectromechanical Systems, and Optics Express. His work shows a clear progression toward higher frequency operation, improved device performance, and novel integration approaches for next-generation communication systems. Among his notable achievements is the development of thin-film lithium niobate devices that overcome traditional frequency limitations of MEMS resonators, enabling operation beyond 10 GHz. This work addresses critical challenges in 5G and future wireless technologies where conventional approaches face scaling limitations. IEEE Ultrasonics Early Career Investigator Award DARPA Young Faculty Award 2014 NASA Early Career Faculty Award 2017 Intel Alumni Fellow 2017-present Multiple Best Paper Awards at major conferences including International Ultrasonic Symposium and International Microwave Symposium Professor Gong actively mentors graduate and undergraduate students, with several of his PhD students achieving notable success, including Ruochen Lu who joined UT Austin as a tenure-track assistant professor. His research group has secured significant funding from agencies including DARPA and NASA, supporting cutting-edge work in RF microsystems. The group maintains strong industry connections, particularly with Intel, reflecting the practical relevance of their research to commercial communication technologies. The Gong Research Group leverages micro/nano electro mechanical systems (N/MEMS), integrated photonic, and compound semiconductor technologies to develop chip-scale hybrid microsystems for RF communication, sensing, and imaging applications. Their current work focuses on pushing the boundaries of acoustic device performance while maintaining compatibility with standard semiconductor manufacturing processes.
Professor James Im serves as Professor of Materials Science in the Departments of Earth and Environmental Engineering and Applied Physics and Applied Mathematics at Columbia University, with an office at 1106 S.W. Mudd (Mail Code 4701). His academic career spans over three decades at Columbia, where he progressed from Assistant Professor (1991-1994) to Associate Professor (1995-2002), and ultimately to full Professor (2002-present), including a tenure as Chair of the Materials Science and Engineering Program (2002-2014). His educational background includes a B.S. with Distinction in Materials Science from Cornell University (1984) and a Ph.D. in Electronic Materials from MIT (1989), followed by postdoctoral research at Caltech (1989-1991). Cornell University: B.S. Materials Science (1984) MIT: Ph.D. Electronic Materials (1989) Caltech: Postdoctoral Scholar (1989-1991) Im's research centers on ultra-rapid phase transitions in beam-irradiated thin films, specifically focusing on laser crystallization of silicon films , energy-beam-induced melting and solidification , and nucleation in discontinuous phase transitions . His work employs experimental, computational, and theoretical approaches to develop innovative semiconductor materials for advanced displays, solar cells, and integrated circuits. Notably, his invention of Sequential Lateral Solidification (SLS) technology has been licensed to major display manufacturers (Samsung, LG, Sharp) and implemented in products by Apple, Blackberry, and Nokia. Current research focuses on advancing the Spot-Beam Crystallization (SBC) platform using fiber lasers for next-generation microelectronics. His publication record spans environmental aerosol studies (2019-2024), oilfield operations technology (2002-2014), and foundational atmospheric research (1980s), reflecting interdisciplinary expertise bridging materials science, environmental engineering, and petroleum technology. The most recent works emphasize low-cost sensor development and aerosol monitoring. Professional recognition includes membership in prestigious societies: Bohmisch Physical Society Sigma Xi Alpha Sigma Mu Materials Research Society American Physical Society Im's research group maintains strong industry connections through technology licensing and collaborative projects, particularly in display manufacturing. His leadership as former department chair demonstrates administrative commitment alongside scientific innovation. The laboratory leverages state-of-the-art laser systems and beam delivery optics for materials development, with recent focus shifting toward environmental monitoring applications while maintaining core semiconductor research.
Yen-Cheng Liu is a former researcher at École polytechnique fédérale de Lausanne (EPFL), affiliated with the School of Life Sciences (BIOS) and multiple departments including LCOM and CMI. His work focuses on interdisciplinary research at the intersection of biomedical engineering, nanotechnology, and cancer biology. Key research areas include nanoplasmonic biosensors, single-cell analysis, optofluidic systems, and cancer immunology. He holds collaborations with institutions like the University of Lausanne and the Centre Hospitalier Universitaire Vaudois (CHUV). His research emphasizes real-time monitoring of cellular secretions, tumor microenvironment dynamics, and diagnostic platform development for pathogens and genetic diseases. Notable contributions include high-throughput microarray technologies for single-cell secretion profiling and optofluidic platforms for molecular diagnostics. Liu’s publications span journals like Advanced Science , Advanced Functional Materials , and Biosensors and Bioelectronics . His work integrates engineering principles with biological systems to address challenges in precision medicine and cancer therapy.
Soner Sonmezoglu is an Assistant Professor of Electrical and Computer Engineering at Northeastern University's College of Engineering. His research focuses on implantable and wearable medical devices enabled by advanced microelectronics and microfabrication for neurological, diagnostic, and therapeutic applications. He leads the Sonmezoglu Lab and has secured major grants including a $13M ARPA-H award for developing photoacoustic imaging systems for early lung cancer detection. Education: PhD in Electrical and Computer Engineering, UC Davis (2017) BSc and MSc in Electrical Engineering with a minor in Solid-State Physics, Middle East Technical University (2010-2012) Postdoctoral Researcher, UC Berkeley EECS (pre-2022) Research Interests: His work spans integrated circuits, micro/nano electromechanical systems (M/NEMS), neural interfaces, and medical device integration. Key projects include ultrasonic wireless neural interfaces and millimeter-scale oxygen sensors for deep-tissue monitoring. Current initiatives include the PAIL project for lung cancer diagnostics. Awards: UC Davis Graduate Division Fellowship Scientific and Technical Research Council of Turkey Graduate Fellowship Grants & Collaborations: Principal Investigator of ARPA-H's $13M PAIL initiative. Active in the Institute for NanoSystems Innovation, contributing to chip-level technology advancements. Labs/Teams: Directs the Sonmezoglu Lab at Northeastern, focusing on next-generation biomedical device innovation through interdisciplinary microsystems engineering.
Matthias Kuhl is a Professor at the Institute of Microsystems Technology (IMTEK) at the University of Freiburg since April 2022. He leads research projects focused on neural probes, biomedical implants, and integrated microelectronic systems. His work includes developing low-power neural interfaces, stress sensors, and energy-efficient circuits for medical applications. Research Interests Neural probes with electronic depth control Implantable biomedical devices CMOS integrated sensors and actuators Energy harvesting for autonomous systems Microfabrication and 3D-printed electronics Key Projects Advanced EDC: Intracortical neural probes with electronic depth control ComBiNE: Bidirectional neural exchange components SEAM-WiT: Implantable neural probe transceivers Multi-material 3D-printed electronics His recent publications emphasize low-power neural front-ends, stress sensor integration, and biomedical system design. He advises numerous graduate students on topics ranging from CMOS circuit design to biohybrid systems. Labs & Teams He leads the Professur für Mikroelektronik lab, specializing in microelectronic systems for biomedical and industrial applications. Collaborates with orthodontic, neurobiology, and materials science groups.
Ju Lu serves as an Assistant Professor at Lehigh University with office location in Iacocca Hall (room 0111), contactable via phone (610.758-3687) and email (jul724@lehigh.edu). Her academic position reflects active engagement in neuroscience research and education within the university's life sciences framework. Education Background: Ph.D. in Neurobiology from Harvard University (2008) B.Eng. in Microelectronics from Tsinghua University (2002) Research Focus: Dr. Lu's work pioneers investigations into neural circuit dynamics and synaptic plasticity mechanisms using advanced optical imaging technologies. Her research spans: Cortical circuit reorganization during motor skill acquisition across species Stress-induced synaptic alterations mediated by microglia in prefrontal circuits Therapeutic applications of psychedelic compounds for neural circuit restoration Development of three-photon microscopy for deep-brain imaging Genetically-encoded neurotransmitter sensors for in vivo studies This multidisciplinary approach bridges molecular neuroscience, systems-level circuit analysis, and translational mental health applications. Publication Trends: Analysis of Dr. Lu's 15 most recent publications (2016-2023) reveals an evolving trajectory from foundational studies on dendritic spine plasticity toward translational neuroscience. Early work emphasized optical imaging methodology and basic plasticity mechanisms, while her 2021-2023 publications increasingly focus on stress-related circuit disruptions and psychedelic therapeutics. A consistent thread involves combining high-resolution in vivo imaging with behavioral models to establish causal links between neural circuit dynamics and cognitive functions. Honors and Awards: No scientific awards or fellowships were documented in the provided materials. Mentorship and Funding: While specific student mentees and grant funding details are not specified in the source text, her extensive collaborative publication record indicates active supervision of research personnel and successful acquisition of research support. Research Infrastructure: Her methodological expertise in advanced microscopy suggests utilization of specialized imaging facilities, though no dedicated laboratory or research team is explicitly identified in the available documentation.
Charles Rizzo is a Research Assistant Professor in the TENNLab neuromorphic computing group at the University of Tennessee, Knoxville, within the Department of Electrical Engineering and Computer Science. He earned his PhD in Computer Science (2024), MS (2021), and BS (2019) from the same institution. PhD in Computer Science, University of Tennessee, Knoxville (2024) MS in Computer Science, University of Tennessee, Knoxville (2021) BS in Computer Science, University of Tennessee, Knoxville (2019) His research focuses on neuromorphic computing, particularly for embedded applications involving event-based vision processing and machine learning with spiking neural networks. He has contributed to neuromorphic control systems, event camera data processing, and spiking network architectures. Recent publications emphasize neuromorphic hardware design (e.g., memristor-based synapses, RISP neuroprocessor), algorithm adaptation (DBSCAN clustering), and real-time applications in vision processing and control. Key subfields include event-based sensors, recurrent spiking networks, and low-power embedded systems. Charles is affiliated with the TENNLab neuromorphic computing group and supports course website development for EECS programs. His work bridges neuromorphic theory with practical implementations in embedded environments.
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.
Cyrus C.C. Mody is a Professor in the History of Science, Technology, and Innovation and Director of the STS Program at Maastricht University. Formerly an Associate Professor (2014–2015) and Assistant Professor (2007–2014) at Rice University's Department of History, his research focuses on the commercialization of academic science, energy humanities, and the technopolitics of scarcity. He leads the NWO-funded 'Managing Scarcity and Sustainability' project and co-leads the ERC Synergy 'Nanobubbles' initiative examining scientific record correction. His expertise spans applied physics, university-industry partnerships, and countercultural science in the US since 1965. Education: Ph.D. (2004), M.A. (2001), Cornell University, Science and Technology Studies A.B. (1997), Harvard University, Engineering Sciences (magna cum laude) Research Interests: Mody explores how scientific knowledge interacts with industry, policy, and culture. Key themes include: Energy transitions and environmental diplomacy Historical roles of oil and semiconductor industries Responsible innovation frameworks Risk communication in science Grants & Collaborations: NWO Vici Grant (2020–2025): Investigates oil industry's role in sustainability debates ERC Synergy 'Nanobubbles': Addresses scientific discourse integrity Postdoc and PhD supervision in energy humanities and nanotechnology ethics Public Engagement: Mody critiques authoritarian threats to science, advocates for interdisciplinary education, and publishes in venues like Volkskrant and Science & Education . His 2022 MIT Press book The Squares analyzes 1970s scientist activism.
Bing Yan is an Assistant Professor in the Department of Electrical and Microelectronic Engineering at Rochester Institute of Technology (RIT), affiliated with the Kate Gleason College of Engineering. She holds a B.S. in Information Management from Renmin University of China (2010), and M.S. and Ph.D. degrees in Electrical Engineering and Statistics from the University of Connecticut (2012–2017). Prior to RIT, she was an Assistant Research Professor at the University of Connecticut. Dr. Yan’s research focuses on power system optimization , including grid integration of renewables (wind/solar), microgrid operations, distributed energy systems, and manufacturing scheduling. She has published over 30 peer-reviewed articles and secured grants from the National Science Foundation (including a CAREER Award), Department of Energy, and industry partners like Brookhaven National Laboratory and ABB. Her work emphasizes mixed-integer linear programming and machine learning applications in energy systems. Notable contributions include stochastic unit commitment models for wind farms, voltage control via deep reinforcement learning, and multi-layer weather models for PV prediction. She advises on projects involving grid resilience, smart manufacturing, and data-driven optimization. Awards: National Science Foundation Faculty Early Career Development (CAREER) Award Multiple NSF grants, DOE grants, and industry contracts Teaching: Courses include Circuits I , Electric Power Transmission & Distribution , and Advanced Power Systems . She also mentors students through co-op programs and independent studies. Labs/Teams: Leads the Intelligent Lab of Power and Manufacturing (ILPM), focusing on multidisciplinary solutions for energy and manufacturing systems. The lab emphasizes hands-on training and innovation in smart grid technologies and sustainable energy systems.
Elsa A. Olivetti is the Jerry McAfee (1940) Professor in Engineering and Professor of Materials Science and Engineering at MIT, and a MacVicar Faculty Fellow. She leads the Olivetti Group, focusing on sustainable materials design, recycling strategies, and computational models for environmental and economic impact assessment. Her work bridges materials science with sustainability, emphasizing circular economy principles and decarbonization. Education: B.S. in Engineering Science from University of Virginia (2000); Ph.D. in Materials Science and Engineering from MIT (2007). Her doctoral research centered on lithium-ion battery electrode materials. She joined MIT’s Department of Materials Science and Engineering (DMSE) in 2014 as an Assistant Professor, later advancing to full Professor. She co-directs the MIT Climate & Sustainability Consortium and chairs the MIT Climate Nucleus. Research interests include: sustainable materials systems, recycling-friendly material design, waste mining, and AI-driven materials discovery. She develops models for cost prediction, environmental impact analysis, and policy-relevant supply chain dynamics. Notable contributions include high-throughput zeolite design and battery recycling frameworks. Awards include the Bose Teaching Award (2021), NSF Early Career Award (2018), and Minerals, Metals & Materials Society Early Career Fellowship (2019). Her work emphasizes education and curriculum development, including courses for MIT’s Climate Scholars program. Labs/Teams: Olivetti Group (MIT), MIT Climate & Sustainability Consortium. Active in global sustainability initiatives, focusing on materials for energy transition and climate resilience.
Mark C. Johnson is a Senior Lecturer at the Elmore Family School of Electrical and Computer Engineering at Purdue University, West Lafayette. He serves as Director of Instructional Laboratories and Associate Director for Design - Semiconductor Degree Program , overseeing laboratory infrastructure, CAD software administration, and curriculum development for courses like ECE337, ECE437, and ECE364. Education: Ph.D. in Electrical Engineering (1998), Purdue University M.S. in Electrical Engineering (1991), Wichita State University B.S. in Electrical Engineering (1983), Purdue University - Calumet His research focuses on electrical and computer engineering laboratory curriculum innovation , digital systems design , and CAD for VLSI . Over 15 recent publications highlight his work in SoC prototyping , low-power circuit design , and educational technology , spanning projects like FPGA filter optimization, dual-core processor experiments, and active learning strategies. Leadership Roles: Proceedings Chair (2003), MSE Program Chair (2005), MSE General Chair (2007), MSE Steering Committee Member, MSE & European Workshop on Microelectronics Education Chair, ECE Instructional Innovation Group (2004-2012) Secretary/Webmaster, ASEE Illinois/Indiana Section (2002-2011) He directs the ECE437 Computer Architecture Prototyping Lab and System on Chip Extension Technologies (SoCET) team , and co-advises the STARS semiconductor readiness program. Outside academia, he is an organist at Faith Presbyterian Church and composes keyboard music.
Dr. Kenneth Zick is a Research Professor at the University of Southern California's Information Sciences Institute (USC ISI), where he serves as Research Director of Transformational Computing. His work focuses on game-changing computer architectures, hardware, and systems for solving critical government problems, with expertise in unconventional computing, quantum computing, and bio-inspired systems. Ph.D. in Computer Science & Engineering, University of Michigan-Ann Arbor M.S. in Electrical Engineering, University of Texas at Dallas Bachelor's in Electrical Engineering, University of Michigan-Ann Arbor Dr. Zick's research interests span unconventional computing , bio-inspired systems , Ising machines , quantum annealing , FPGA-based solutions , and neuromorphic computing . His group develops hardware-centric algorithm discovery and Cosm, a heuristic algorithm for sparse Ising optimization. Current projects include superconducting digital architectures, analog-digital hybrid computing, and human-AI co-design for breakthrough hardware. His team leverages advanced facilities such as USC ISI's MOSIS 2.0 and the California DREAMS hub in the DoD Microelectronics Commons, with expertise in high-speed I/O, FPGA prototyping, and radiation-hardened systems. He has received a NASA Fellowship for his Ph.D. work and mentored students like Aditi, who won the USC ECE Outstanding Academic Achievement Award.
Tamal K. Dey is a Professor of Computer Science at Purdue University, specializing in Computational Geometry and Topology with applications to topological data analysis, geometric modeling, and computer graphics. He holds ACM and IEEE Fellowships and has authored/co-authored over 200 publications, including influential books like Curve and Surface Reconstruction and Computational Topology for Data Analysis . His research group, CGTDA, focuses on theoretical and applied aspects of geometry and topology in data science. Education: B.E. from Jadavpur University (1985), M.E. from Indian Institute of Science (1987), Ph.D. from Purdue University (1991). Postdoctoral work at University of Illinois (1992). Previously led the Jyamiti group at Ohio State University (1999–2020) and served as interim department chair (2019–2020). Major contributions include foundational work on 3D reconstruction, mesh generation, and topological algorithms. His awards include ACM Fellow (2018), IEEE Fellow, and Solid Modeling Association Fellow. Advised numerous PhD students and postdocs, with ongoing projects in persistent homology and TDA applications.
