John Heron is an Associate Professor in the Department of Materials Science and Engineering at the University of Michigan. His research focuses on epitaxial growth of complex oxide thin films and heterostructures to engineer new electronic phenomena for next-generation devices. B.S. in Physics, University of California, Santa Barbara (2007) M.S. in Materials Science and Engineering, University of California, Berkeley (2011) Ph.D. in Materials Science and Engineering, University of California, Berkeley (2013) His work explores ferroic materials like (anti)ferromagnets and (anti)ferroelectrics, utilizing techniques such as X-ray diffraction, scanning probe microscopy, and magnetotransport measurements. The Ferroelectronics Lab (http://ferroelectronicslab.com) employs in-situ transfer systems for high-quality oxide and metal growth. Recent publications emphasize magnetoelectric switching, entropy-stabilized oxides, and spintronic devices. Current teaching includes MSE500 Materials Physics and Chemistry. No explicit scientific awards or students are listed in the provided texts.
Aldo Mozzanica is a Researcher at the Paul Scherrer Institute (PSI) in Switzerland, affiliated with the Laboratory for X-ray Nanoscience and Technologies. He holds a degree in Physics from Insubria University and a Ph.D. from the University of Milan, where his doctoral work focused on scintillating fiber vertex detectors for CERN's Antiproton Decelerator facility. At PSI, he leads detector development projects for synchrotron and free-electron laser applications. His research centers on advancing X-ray detector technology, including: Developing next-generation integrating pixel/strip detectors (JUNGFRAU, GOTTHARD) Improving frame rates, noise performance, and radiation hardness Exploring novel detector concepts for XFEL/synchrotron applications Enabling new experimental capabilities in structural biology and materials science Mozzanica's 135+ publications focus on X-ray detector innovation, with recent work emphasizing: Hybrid pixel detector optimization for 4th-generation light sources On-chip digitization and charge transport modeling High-speed data acquisition systems Applications in crystallography, spectroscopy, and phase-contrast imaging As principal developer of the JUNGFRAU detector, he oversees: ASIC design, testing, and characterization Readout electronics and firmware development Module production and supply chain management Commissioning at SwissFEL endstations
Said Hamdioui serves as a full Professor in the Department of Computer Engineering within the Faculty of Electrical Engineering, Mathematics and Computer Science at Delft University of Technology. His research focuses on cutting-edge hardware architectures for neuromorphic computing and energy-efficient AI acceleration, with particular emphasis on memristor-based systems, emerging memory technologies, and fault-tolerant designs for edge applications. His research interests span Neuromorphic Computing , Memristor-Based Architectures , and Energy-Efficient AI Hardware , addressing critical challenges in hardware security, computation-in-memory, and reliable edge AI deployment. Recent work demonstrates significant advancements in RRAM/FeFET testing methodologies, spiking neural network implementations, and spin wave computing alternatives to traditional CMOS. His publications reveal strong trends toward real-world deployment of brain-inspired hardware with practical constraints like power efficiency, testability, and security. Award highlights include: DATE'20 Best Paper Award DFT'21 Outstanding Student Paper ETS 2021 Best Paper Award LATS 2018 & 2022 Best Paper Awards Professor Hamdioui actively contributes to the research community through editorial roles at IEEE Transactions on VLSI Systems , IEEE Design & Test , and Journal of Electronic Testing from 2017-2018. His leadership in multi-partner projects like CONVOLVE and NEUROKIT2E demonstrates strong industry-academia collaboration for edge AI solutions. Current work shows increasing focus on practical deployment challenges including in-field fault monitoring, security vulnerabilities in neuromorphic systems, and realistic brain simulation frameworks.
Marianna Ivashina is a Professor and Head of the Antenna Systems Research Group at Chalmers University of Technology's Department of Electrical Engineering . Her work focuses on array antennas , antenna integration with electronics , optimal beamforming , and over-the-air measurement methods . The group has achieved international recognition for innovations in ultra-wideband (UWB) feeds , Gap waveguide antennas , and Doherty-power-amplifier-integrated antennas for 5G/6G and radio telescope applications. Key projects include the SSF Sweden-Taiwan collaboration , EU Horizon 2020 MyWave , and VINNOVA ENERGETIC initiatives. Her recent publications emphasize millimeter-wave (mmWave) communication and reconfigurable intelligent surfaces (RIS) , with applications in 5G/6G networks , satellite communication (SatCom) , and advanced antenna testing chambers . She explores beamforming optimization , self-interference mitigation , and hybrid OTA environments to enhance wireless system performance. The group's work bridges theoretical advancements with practical implementations, including RFSoC testbeds and high-efficiency antenna arrays . Marianna leads major research programs funded by Ericsson , VINNOVA , and EUREKA EURIPIDES2 , addressing challenges in beamforming , antenna-IC integration , and automated design for 5G/6G . These projects highlight her role in advancing millimeter-wave communication and sensor integration technologies.
Nicola Nicolici is a Professor in the Department of Electrical and Computer Engineering at McMaster University. His research focuses on methods and algorithms for the design of digital integrated circuits and systems, with significant contributions in manufacturing test, post-silicon validation and debug. His work has expanded to include embedded systems, low-energy computing, and custom hardware-accelerated computing systems. Professor Nicolici's research interests span multiple areas of digital system design and validation. His early work focused on manufacturing test methodologies and power-aware testing strategies for integrated circuits. More recently, he has made significant contributions to post-silicon validation techniques, including constrained-random stimuli generation, trace signal selection, and bit-flip detection. His research has evolved to address emerging challenges in embedded computing systems, low-energy design, and specialized hardware acceleration for various applications including deep neural networks and signal processing. His recent publications reveal a strong trend toward hardware acceleration for specialized computing tasks. The research spans matrix multiplication algorithms (Strassen and Karatsuba), memory system optimization (DDR5 calibration), FPGA-based radar processing, and neural network acceleration. His work consistently bridges theoretical algorithm development with practical hardware implementation considerations, particularly focusing on precision analysis, fault tolerance, and energy efficiency. The research demonstrates a clear progression from traditional digital circuit testing to more complex system-level validation and acceleration techniques. Professor Nicolici has been actively involved in teaching courses related to system-on-chip design and test, digital systems, and embedded systems. His teaching portfolio includes advanced courses such as System-on-Chip (SOC) Design and Test and Digital Systems Design , reflecting his expertise in the field. While specific grant information isn't detailed in the provided text, his extensive publication record suggests ongoing research funding support. His research has contributed significantly to the fields of digital circuit testing, post-silicon validation, and hardware acceleration. The work has practical applications in semiconductor manufacturing, embedded systems design, and specialized computing architectures. His recent focus on neural network acceleration and memory system optimization reflects the evolving landscape of computer architecture research.
Jinsong Huang serves as Adjunct Professor in the Materials Science and Engineering department at the University of North Carolina at Chapel Hill, where he leads an interdisciplinary research group focused on perovskite-based electronic materials and devices. His laboratory, housed in Murray Hall 1115, maintains active collaborations with academia, industry, and national laboratories while training next-generation scientists and engineers for competitive job markets. Dr. Huang earned his educational credentials through a rigorous academic path: Ph.D. in Materials Science & Engineering from UCLA (2007), M.S. in Semiconductor Physics from Chinese Academy of Sciences (2003), and B.E. in Materials and Photoelectronic Physics from Xiangtan University (2000). His research program spans Perovskite Solar Cells , Photodetectors , and X-ray Imagers , with particular emphasis on fundamental material physics, device design, stability enhancement, and scalable manufacturing. The group's work bridges applied research with deep scientific understanding, focusing on high-performance, low-cost electronic materials that address critical energy and medical imaging challenges. Current projects include self-powered photon-counting detectors, bifacial perovskite modules, and all-perovskite tandem solar cells. Analysis of recent publications reveals a strategic research trajectory toward commercialization of perovskite technologies, with increasing focus on stability, scalability, and real-world performance metrics. The work spans fundamental science (defect engineering, crystal growth) to applied technologies (medical imaging detectors, flexible solar cells), demonstrating remarkable breadth while maintaining technical depth in perovskite material systems. Highly Cited Researcher 2021 in Material Science and Chemistry Principal Investigator for $1.5 million UNC System Research Opportunities Initiative (2025) Multiple student/postdoc awards including Postdoctoral Awards for Research Excellence Consistent high-impact publications in Nature, Science, and Advanced Materials Huang actively mentors students and postdocs, with notable alumni including four of the 41 Tar Heels ranked as 'highly cited researchers' in December 2023. His research group has secured significant funding including the recent $1.5 million UNC System grant for 'Ultra-High Efficiency Perovskite Tandem Solar Cells' focusing on North Carolina's energy production and reduced fossil fuel dependence. The laboratory maintains strong industry partnerships that facilitate technology transfer and real-world implementation of research findings. The Huang Research Group operates as a dynamic interdisciplinary team with scientists from chemistry, materials science, physics, and electrical engineering backgrounds. Their collaborative culture has produced numerous breakthroughs including record-efficiency perovskite modules certified by NREL, self-powered photon-counting detectors published in Nature, and lead-recycling technologies highlighted in Nature Communications. Current facilities support crystal growth, device fabrication, and advanced characterization of perovskite materials for both energy and radiation detection applications.
Matthias Bucher is a Professor at the Department of Electronics and Computer Engineering, Technical University of Crete. He specializes in analog/RF integrated circuits design, MOSFET compact modeling, and device characterization. His research focuses on nanoscale CMOS, wide-band semiconductor devices, and high-voltage MOSFETs. He leads the Electronics Laboratory and teaches courses such as Electronics II and CMOS Analog IC Design. Education: Ph.D. in Electrical Engineering, Swiss Federal Institute of Technology (EPFL), 1999 M.S. in Electrical Engineering, Swiss Federal Institute of Technology, 1993 Research Interests: Prof. Bucher’s work emphasizes charge-based compact models (e.g., EKV3), RF device modeling, and noise analysis in MOSFETs/JFETs. His contributions include open-source tools for Verilog-A modeling and parameter extraction methodologies for advanced CMOS technologies. Labs/Teams: He directs the Electronics Laboratory , focusing on nanoelectronics and high-reliability circuits. His team collaborates on semiconductor device modeling for aerospace and industrial applications. Grants/Awards: While not explicitly listed, his extensive publication record and leadership in open-source projects indicate sustained recognition in semiconductor research communities.
Jeff Zhang is an Assistant Professor in the School of Electrical, Computer and Energy Engineering at Arizona State University. He joined ASU in January 2023 after completing a postdoctoral fellowship at Harvard University. His research spans deep learning, computer architecture, embedded systems, and EDA, with particular emphasis on energy-efficient and fault-tolerant design for AI/ML systems and hardware accelerators. Education: Ph.D., New York University M.Eng., B.Eng., Hunan University Dr. Zhang's research bridges theoretical machine learning with practical hardware implementation, developing novel architectures that optimize performance, power consumption, and reliability. He has pioneered approaches for hardware acceleration of large language models, efficient sparse matrix operations, and novel memory technologies for AI workloads. His work has received multiple awards including IEEE Top Picks in Test and Reliability (2023) and IEEE Micro Best Paper Award (2022). His recent publications demonstrate a strong trend toward heterogeneous computing, with significant work in chiplet-based AI accelerators, photonic computing for AI, and 2.5D/3D integration techniques. The research spans from high-level compiler frameworks to circuit-level innovations, with a consistent theme of co-designing algorithms and hardware for optimal AI performance. His work on the SODA toolchain has been particularly influential in bridging Python to silicon. Scientific Awards: IEEE Top Picks in Test and Reliability, IEEE ITC, 2023 Best Paper Award, IEEE Micro, 2022 Best Paper Award Candidate, IEEE DATE, 2022 Best Presentation Award Nomination, ACM SIGDA DATE PhD Forum, 2020 Best Paper Award Nomination, IEEE VLSI Test Symposium, 2018 Ernst Weber Ph.D. Fellowship, New York University, 2015, 2016 Dr. Zhang actively mentors a diverse group of graduate and undergraduate students, with several alumni now working at leading technology companies including Apple, TSMC, and Ansys. His research is supported by prestigious grants from NSF, Sandia National Labs, and industry partners. He serves on technical program committees of numerous top conferences and has organized special sessions on emerging topics like Gen AI for Chip Design and LLM-Aided Design. Dr. Zhang leads a vibrant research group that collaborates extensively with industry partners and national laboratories. Current projects focus on next-generation AI hardware, including chiplet-based systems, photonic accelerators, and novel memory technologies for large language models. His group has developed several open-source tools and frameworks, including the SODA toolchain for bridging Python to silicon.
Xiaodong Yan is an Assistant Professor in the Department of Materials Science and Engineering and an affiliated faculty member in the Department of Electrical and Computer Engineering at the University of Arizona . His research bridges materials science, nanoelectronics, and quantum computing, with a focus on developing novel quantum materials and devices for next-generation computing systems. Education : BS in Physics (Peking University, China), MS in Electrical Engineering (University of Notre Dame), PhD in Electrical and Computer Engineering (University of Southern California). Postdoctoral Training : Materials Science and Engineering, Northwestern University (2021-2023). Dr. Yan’s research explores the synthesis and physics of emerging quantum materials, particularly 2D materials and van der Waals heterostructures , to create advanced devices for neuromorphic computing , quantum sensing , and low-power electronics . His work spans nanofabrication, device characterization, and algorithm integration. His recent publications in Nature and Nature Electronics highlight breakthroughs in Moiré synaptic transistors with room-temperature neuromorphic functionality and reconfigurable heterojunction transistors for machine learning hardware. These studies emphasize 2D material integration , reconfigurable electronics , and bio-mimicking systems . Scientific Awards : MHI Ph.D. Scholar, Ming Hsieh Department of ECE at USC. Dr. Yan leads the Yan Research Group , which focuses on material and device solutions for neuromorphic computing and quantum sensing . The group actively recruits graduate and undergraduate researchers.
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.
Dr. Michael Choma is an Adjunct Associate Professor in the Radiology & Biomedical Imaging department at Yale School of Medicine . He also serves as Vice President Clinical at LookDeep Health , a Bay-Area startup developing AI/computer vision technologies for inpatient telemedicine and patient monitoring. Dr. Choma holds a PhD (2004) and MD (2006) from Duke University , completed pediatric training at Boston Children’s Hospital , and pursued postdoctoral research at the Wellman Center for Photomedicine, Massachusetts General Hospital/Harvard Medical School . His research spans biomedical optics , medical imaging , and developmental biology , with a focus on optical coherence tomography (OCT) for studying pulmonary and cardiovascular physiology . He has developed OCT technologies to quantify cilia-driven fluid flow in respiratory systems, investigated embryo heart physiology , and designed novel light sources for speckle-free imaging. His work also bridges clinical medicine and engineering innovation , particularly in digital health and AI-driven diagnostics . Dr. Choma’s publications from 2015-2016 highlight trends in medical imaging , biophotonics , and computational diagnostics , with subfields including optical coherence tomography , fluid dynamics , and point-of-care testing . His scientific awards include the Numenta Startup Prize (2015) and Theodore von Kármán Fellowship (2014) . At Yale, Dr. Choma previously led an NIH-funded biophotonics laboratory and contributed to clinical radiology . He also served as an attending physician in the Yale-New Haven Primary Care Clinic . His interdisciplinary approach integrates medical practice , engineering , and data science , with recent interests in AI bias in medicine , digital pathology , and healthcare innovation .
Elisa Riedo is a tenured Professor of Chemical and Biomolecular Engineering at New York University (NYU) Tandon School of Engineering, with joint appointments as Professor of Physics in NYU’s College of Arts and Science and as affiliated Professor of Mechanical Engineering at Tandon. She serves as Director of Faculty Development at NYU Tandon and has held prior tenured positions at Georgia Tech (2003–2015) and CUNY ASRC (2015–2018). Her academic career spans over two decades, with a Ph.D. in Physics from the University of Milano (2000) and postdoctoral work at EPFL. Her research focuses on nanotechnology , graphene and 2D materials , and thermal scanning probe lithography (tSPL) , with applications in biomedical diagnostics quantum electronics electromagnetic interference shielding mechanical reinforcement of materials She pioneered tSPL for sustainable nanofabrication and discovered diamene—a single-layer diamond structure from graphene under pressure. Her recent work involves transparent infrared electrodes using silver nanowires (2025) and self-organized graphene stacking domains for quantum technologies (2024). She has secured major grants from National Science Foundation , Department of Defense , and Army Research Office . Scientific honors include: 2023 NYU Tandon Excellence in Research Award 2013 American Physical Society Fellow 2005 CREA Innovation Award Membership in the Academy of Europe (2023) She contributes to editorial boards for journals like 2D Materials and Applications and advises companies such as Mirimus Inc. and SwissLitho AG .
Dr. John G. Hayes is a Senior Lecturer at University College Cork (UCC) in the Department of Electrical & Electronic Engineering . He holds a Ph.D. from UCC (1998), an M.S.E.E. from the University of Minnesota (1989), an M.B.A. from California Lutheran University (1993), and a B.E. from UCC (1986). His academic career began at UCC in 2000, and he directs the Power Electronics Research Laboratory (PERL) , focusing on industrial collaborations with companies like Analog Devices and General Motors. Research Interests : Power electronics, magnetic components, electric vehicles, renewable energy systems, smart grids, and energy storage. Notable Work : Joint author of Electric Powertrain: Energy Systems, Power Electronics and Drives for Electric, Hybrid and Fuel Cell Vehicles (Wiley, 2018) and its Chinese edition (2021). Scientific Awards : 2011 IEEE William M. Portnoy Award for Best Paper/Presentation at IEEE ECCE. Advising : Supervised 10+ Ph.D. students across powertrain modeling, magnetic materials, and converter control. Current advisee: Conor Healy (Doctoral Degree). Labs : Leads PERL, which develops high-power converters for automotive and renewable energy applications, partnering with industry leaders like SMA Magnetics and United Technologies.
Professor Timothy P. Bender is a distinguished faculty member at the University of Toronto, holding a primary appointment in the Department of Chemical Engineering and Applied Chemistry with cross-appointments in the Department of Chemistry and the Department of Materials Science and Engineering. His research laboratory focuses on developing novel organic electronic materials for applications in sustainable energy technologies, particularly organic solar cells and light-emitting devices. Professor Bender earned his B.Sc. and Ph.D. from Carleton University before joining the University of Toronto faculty in 2006. Prior to his academic appointment, he was a research staff member at the Xerox Research Centre of Canada from 2000-2006, where he filed over 65 US patents and published numerous peer-reviewed papers. His industrial research experience provides valuable perspective on the commercialization pathway for academic discoveries. Professor Bender's research program centers on the design, synthesis, and engineering of new materials for organic electronic devices, particularly organic photovoltaics (OPVs) and organic light-emitting diodes (OLEDs). His group has made significant contributions to the understanding and application of boron subphthalocyanines (BsubPcs) and silicon phthalocyanines (SiPcs), establishing methodologies for tailoring their chemical structure to optimize device performance. The Bender Lab employs a comprehensive 'applied chemistry-device continuum' approach, integrating computational modeling, synthetic chemistry, physical characterization, and device engineering to establish molecular structure-property relationships. Their research spans fundamental chemistry to applied device engineering, with strong emphasis on sustainability considerations throughout the materials development process. Analysis of Professor Bender's recent publications reveals a strong focus on developing BsubPcs as triplet harvesting materials in organic photovoltaics, engineering silicon phthalocyanines for enhanced electron transport, and exploring halogen bonding to control solid-state arrangements of these materials. His work demonstrates how molecular engineering can overcome traditional limitations in organic electronic materials, particularly regarding solubility, charge transport, and environmental stability. The research shows consistent progression toward higher efficiency devices with improved longevity. 2008 Professor Diran Basmadjian Teacher of the Year Award from the Department of Chemical Engineering and Applied Chemistry Corporate Special Recognition Award from Xerox Corporation for photoreceptor technology that enabled 'life of machine' parts Professor Bender actively mentors a diverse team of highly qualified personnel (HQP), including undergraduate students, graduate students, and post-doctoral fellows. His laboratory fosters cross-disciplinary collaboration between chemists, materials scientists, and chemical engineers, allowing students to engage with the complete research cycle from molecular design to environmental testing. He has secured funding from NSERC, SABIC Corporation, and other sources to support his research program, which maintains strong industrial partnerships with companies including SABIC Corporation, Siltech Corporation, and Xerox Corporation. His research bridges fundamental academic discoveries with practical commercial applications in the growing field of organic electronics. The Bender Laboratory maintains comprehensive infrastructure for organic synthesis, materials characterization, and device fabrication. Their facilities enable complete development cycles from molecular design to environmental testing of organic electronic devices. The lab's 'applied chemistry-device continuum' approach ensures that fundamental discoveries are rapidly translated into practical device applications, with particular emphasis on sustainability considerations throughout the materials development process. Current research directions include accelerated materials development, sustainable chemical processes, and life cycle analysis of organic electronic devices in real-world environments.
Pradeep Lall is the MacFarlane Endowed Distinguished Professor and Alumni Professor in the Department of Mechanical Engineering at Auburn University’s Samuel Ginn College of Engineering. He serves as Director of the Auburn University Electronics Packaging Research Institute (EPRI) and holds a joint courtesy appointment in the Department of Electrical and Computer Engineering. A leader in flexible hybrid electronics and harsh environment systems, Dr. Lall has built a world-renowned research program focused on additive manufacturing, electronics reliability, and sustainable materials. Ph.D. in Mechanical Engineering, University of Maryland M.B.A. in Finance and Strategy, Northwestern University M.S. in Mechanical Engineering, University of Maryland B.E. in Mechanical Engineering, Delhi College of Engineering Dr. Lall’s research centers on Flexible Hybrid Electronics (FHE) , Harsh Environment Electronics , Semiconductor Packaging , and Prognostics Health Management . His work leverages additive manufacturing techniques such as Aerosol-Jet, InkJet, and screen printing to develop conformal, robust, and sustainable electronic systems. His innovations include the Flexible Biometric Band for monitoring workers in hazardous environments and additively printed antennas for aerospace applications. His recent focus includes eliminating PFAS from electronics and developing water-based inks for eco-friendly manufacturing. The 15 most recent publications reflect a strong trend toward sustainability , additive manufacturing , and real-world applications in defense, aerospace, automotive, and healthcare. His work bridges fundamental research with industrial realization, particularly through partnerships with NextFlex and federal agencies. Themes include reliability under shock and vibration, sensor development for extreme environments, and workforce training in advanced manufacturing. Dr. Lall has received numerous scientific honors, including: SMTA Founder’s Award (2024) SEMI FlexTech R&D Achievements Award (2023) ASME Avram Bar-Cohen Memorial Medal (2022) IEEE Biedenbach Outstanding Engineering Educator Award (2020) IEEE Sustained Technical Contributions Award (2018) NSF Alex Schwarzkopf Prize (2016) Fellow of ASME, IEEE, NextFlex, and Alabama Academy of Science Dr. Lall has secured over $2 million in annual research funding from SRC, NSF, and NextFlex, leading large-scale projects on sustainable electronics and workforce development. He mentors numerous graduate and undergraduate students and leads the NSF-CAVE3 Center. As founding faculty advisor of the SMTA student chapter, he promotes student engagement in electronics manufacturing. His lab, EPRI, features a full prototyping line for additive electronics and collaborates with industry and government to advance domestic manufacturing capabilities. EPRI, under Dr. Lall’s leadership, partners with the Auburn University Research and Technology Park, the Office of Economic Development, and multiple colleges to drive technology commercialization and workforce education in electronic packaging. The institute is at the forefront of the national effort to reestablish U.S. leadership in semiconductor packaging and advanced electronics manufacturing.
