Kirsten Moselund is a Professor at the Swiss Federal Institute of Technology in Lausanne (EPFL) and Head of the Laboratory for Nano and Quantum Technologies (LNQ) at the Paul Scherrer Institute (PSI) since 2022. She leads LNQ’s six research groups focused on nanotechnology and advanced nanomanufacturing quantum computing technologies with co-location of the ETHZ-PSI Quantum Computing Hub and affiliation to EPFL's Quantum Science and Engineering Center (QSE) . Her research spans semiconductor device physics and technology development, including III-V electronics nanophotonics topological devices cryogenic electronics with applications in quantum computing, optical communication, and integrated photonics. She received an ERC Starting Grant for hybrid photonic-plasmonic nanolasers. Recent publications focus on III-V photodetectors on silicon hybrid laser integration thermal management in nanocavities topological mode emission across Nature Communications , ACS Photonics , and Nature Electronics . Scientific awards include ERC Starting Grant and institutional roles such as Member of IHP Microelectronics Scientific Advisory Board Executive Board of Swiss Photonics Technical Program Committee member for IEDM conference At PSI, she oversees construction of the Park InnovAare cleanroom opening in 2024 and collaborates with international groups on theoretical foundations and simulations.
Dr. Iftikhar Ahmad serves as an Assistant Professor in the Department of Electrical Engineering at the University of South Carolina's Molinaroli College of Engineering and Computing. He joined the faculty in 2018 after eight years in industry as a Senior Scientist developing ultra-wide bandgap materials for UV-LEDs, and prior post-doctoral and research professor roles at USC. His expertise lies in the growth and characterization of wide bandgap semiconductors for advanced electronic and optoelectronic applications. Dr. Ahmad earned his M.Sc. from Govt. College Lahore (ranking first in the state) and completed his M.S. and Ph.D. at Texas Tech University in 2003 and 2005, focusing on wide bandgap semiconductors. He furthered his training with post-doctoral work at Virginia Commonwealth University in MBE and MOCVD growth techniques. His educational background established the foundation for his current research in semiconductor materials engineering. His research centers on ultra-wide bandgap semiconductors, especially gallium oxide and boron nitride, for applications in deep UV LEDs and high-power electronics. He explores novel MOCVD growth methods for these materials and their integration with traditional III-nitrides (AlGaN) to advance device performance in optoelectronics and power electronics. Current projects focus on defect engineering, phase stabilization, and device fabrication for next-generation semiconductor technologies. Analysis of his recent publications reveals a strong emphasis on β-Ga2O3 and h-BN for next-generation devices. Key themes include MOCVD growth optimization, defect characterization, and device integration for radiation detectors, high-temperature transistors, and UV emitters. His work bridges materials science and electrical engineering to address critical challenges in wide bandgap semiconductor technology, with increasing focus on computational modeling and industrial applications. No scientific awards or fellowships were mentioned in the provided materials. Regarding advising, while specific students are not listed, Dr. Ahmad teaches core courses including Introduction to Microelectronics (ELCT 363) and Advanced Semiconductor Materials (ELCT 874), indicating active engagement in graduate and undergraduate education. Grant details are not specified, but his laboratory operations suggest external funding support for semiconductor research. Dr. Ahmad leads the Ultrawide Bandgap Semiconductor Laboratory, equipped with an MOCVD growth system, Oceanoptics spectrometer, and comprehensive characterization tools for electrical, optical, and atomic force microscopy. The lab supports research in materials growth, device fabrication, and testing, fostering innovation in semiconductor technology through collaborations with industry and government research programs.
Dirk Koch is an Associate Professor in the Department of Computer Science at the University of Manchester. He specializes in reconfigurable computing, FPGA architecture, and hardware acceleration. His research addresses challenges in field-programmable gate arrays (FPGAs), high-level synthesis, and stream processing. He leads the Advanced Processor Technology group and contributes to the Digital Futures Institute for Data Science and AI. Education: Doctorate in Computer Engineering Affiliations: Centre for Digital Trust and Society, EPSRC Functional Oxide Reconfigurable Technologies Programme His work focuses on optimizing FPGA performance, reducing power consumption, and advancing reconfigurable hardware systems. Recent projects include bitstream manipulation frameworks, runtime stream processing pipelines, and FPGA fabric optimization techniques. He has collaborated extensively with industry partners like AMD-Xilinx. Dirk Koch has supervised 11 research projects, including work on clock region process variation analysis and FPGA virus scanning. He holds grants from EPSRC and has published 62 peer-reviewed works.
Saghi Forouhi is an Assistant Professor at Linköping University, affiliated with the Division of Electronics and Computer Engineering (ELDA) and the Department of Electrical Engineering (ISY). Her research focuses on analog circuits, biochips, and signal processing technologies. Primary Affiliation: Linköping University School: Division of Electronics and Computer Engineering Department: Department of Electrical Engineering In 2025, she co-authored the publication Advanced CMOS Biochips , which explores intersections between CMOS technology and biomedical applications.
Mehdi Asheghi is an Adjunct Professor at Stanford University specializing in advanced thermal management solutions. His research focuses on heat transfer optimization, electronics cooling, and energy-efficient systems using cutting-edge materials science and micro/nanofabrication techniques. His work spans high-heat-flux cooling, phase-change materials, and thermal interface technologies, with applications in power electronics, integrated circuits, and sustainable energy systems. Innovations include microchannel coolers, copper nanowire composites, and porous thermal structures. With publications addressing thermal challenges from chip-scale to industrial systems, his research advances reliability and performance in electronic devices and energy infrastructure.
Christopher Bailey is a Professor of Advanced Semiconductor Packaging and Director of the Centre for Advanced Semiconductor Packaging at Arizona State University (ASU). He previously served as Professor of Computational Mechanics & Reliability and Associate Dean for Research at the University of Greenwich, UK. At ASU, he leads research on advanced semiconductor packaging, including roles as Principal Investigator (PI) and Co-Investigator (Co-I) on major projects such as the SRC-funded Thermo-Mechanical Modelling and US Chips Act initiatives (e.g., SWAP-Hub, SHIELD, ITSI). His research focuses on semiconductor packaging reliability, thermal management, co-design methodologies, and multiphysics modeling. Education: MBA (Technology Management), Open University, UK PhD, Thames Polytechnic, UK Research Interests: Advanced Semiconductor Packaging Thermal Management Solutions Co-Design and Multiphysics Modeling Reliability of Electronic Components His work integrates computational mechanics, materials science, and engineering to address challenges in high-reliability electronics. Recent projects emphasize predictive modeling for semiconductor packaging failures under thermal-mechanical stress. Awards: IEEE Region 8 Europe Award (2024) IEEE David Feldman Award (2022) Visiting Professorships at IIT Kharagpur (2018/2022) and Hong Kong (2018) Service & Leadership: Former President of IEEE Electronics Packaging Society (2020–2021) Associate Editor for IEEE Transactions on Components, Packaging, and Manufacturing Technology Conference Leadership (e.g., Program Chair for IEEE PAINE 2024) He has secured over $40M in research funding and authored 400+ archival papers, with expertise spanning industry collaborations (e.g., BAe Systems, Rolls Royce) and government advisory roles (EPSRC Peer Review College, UK Research Excellence Framework).
Sani Nassif is a Research Fellow at the Technical University of Munich (TUM) under the Rudolf Diesel Industry Fellowship, hosted by Professor Ulf Schlichtmann. With 28 years of experience at Bell Labs and IBM Research, he has led teams in integrated circuit modeling, simulation, statistical analysis, and optimization. Research Interests: His work bridges integrated circuit technology with cross-disciplinary applications in medicine. Key areas include variability analysis in semiconductor manufacturing, low-power circuit design, and reliability engineering for nano-scale systems. He focuses on applying machine learning and statistical methods to solve challenges in energy-efficient computing and biomedical systems. Selected Publications: His research spans circuit variability trends, leakage current modeling, and reliability frameworks for nano-era systems. Work includes foundational studies on SRAM failure analysis and CMOS scaling limitations. Scientific Awards: He is recognized as an IEEE Fellow IBM Master Inventor (75 patents) Rudolf Diesel Industry Fellow
Dr. Patrick W. C. Ho is a Lecturer in the Department of Electrical & Computer Systems Engineering (ECSE) at Monash University Malaysia School of Engineering. He holds a PhD in Electronics Engineering from the University of Nottingham Malaysia Campus (2016), with research focusing on non-volatile FPGA architectures using memristors. His academic journey includes roles as a Scholarly Teaching Fellow and unit coordinator for courses like ECE2131 Electrical Circuits and ECE4063 Large Scale Digital Design. He has industry experience with Intel Microelectronics and Altera Corporation, alongside teaching A-level Physics at Methodist College Kuala Lumpur. Education: BEng (First Class Honours) in Engineering (2009) MSc in Science (2012) PhD in Electronics Engineering (2016) Research Interests: Dr. Ho specializes in memristor-based non-volatile memory systems, VLSI design, and FPGA architectures. His work bridges hardware design with emerging materials, as seen in his Q1 journal article on memristive LUTs. Collaborations with CAD-IT expand his focus into AI, image processing, and object recognition. Recent projects include studies on memristor substrate performance (2023–2026) and UAV communication reliability (2021–2024). Teaching and Industry Engagement: As ECSE’s Industrial Training Advisor and IAP representative, he actively connects academic curricula with industry needs. His teaching spans foundational engineering courses and advanced digital design modules. Labs and Collaborations: Active in CAD-IT partnerships for student FYP co-sponsorship. Research groups focus on nanotechnology, machine learning integration in UAV systems, and memristor material analysis.
Mingda Li is an Associate Professor in the Department of Nuclear Science and Engineering at the Massachusetts Institute of Technology (MIT), holding the Class of 1947 Career Development Professorship. His research spans quantum materials, nanoscale energy transport, and AI-driven materials discovery, utilizing neutron/X-ray scattering techniques and machine learning to address challenges in quantum computing, thermal management, and energy conversion. He leads the Quantum Measurement Group and teaches graduate courses including Quantum Theory of Materials Characterization. Education: Bachelor of Science in Engineering Physics, Tsinghua University, 2009 Doctor of Philosophy in Nuclear Science and Engineering, MIT, 2015 Postdoctoral Research, MIT Mechanical Engineering Department Research Interests: Dr. Li's quantum research develops theoretical frameworks for topological order and defect-engineered quantum materials, with applications in microelectronics and quantum computing. His energy transport studies investigate phonon/electron dynamics at interfaces under non-equilibrium conditions to design materials for thermal management in electronics. The AI program creates symmetry-aware generative models that integrate ab initio calculations with experimental data, enabling closed-loop materials discovery for quantum and energy technologies. Publication Trends: Analysis of 15 recent 2025 publications reveals dominant themes in quantum materials (topological semimetals, 2D magnets), AI-driven design (generative models, symmetry-equivariant networks), and advanced characterization (neutron/X-ray spectroscopy). Key innovations include defect engineering for thermal transport, machine learning for spectroscopic data interpretation, and quantum phenomenon discovery in complex materials, reflecting strong interdisciplinary integration. Scientific Awards: No scientific awards were mentioned in the provided text. Advising and Grants: Dr. Li mentors graduate students in the Quantum Measurement Group, guiding research in quantum materials characterization and AI applications. He has taught core courses including Applied Nuclear Physics and Machine Learning in Nuclear Science and Engineering. His research is supported by grants focused on quantum engineering and nuclear materials, with collaborations spanning national laboratories and industry partners for quantum computing and energy applications. Labs and Teams: The Quantum Measurement Group operates at the intersection of experimental physics and computational science, utilizing neutron scattering facilities (including Spallation Neutron Source) and ultrafast X-ray techniques. The team develops custom software for data analysis and collaborates with institutions like MIT.nano for materials synthesis, maintaining a pipeline from theoretical prediction to device-level validation for quantum and thermoelectric materials.
Dr. Sueda Saylan is an Assistant Professor at the Faculty of Engineering, Özyeğin University, since 2024. Her academic journey includes a Ph.D. in Interdisciplinary Engineering (2016) from Masdar Institute (now Khalifa University), postdoctoral research at Khalifa University (2016-2022), and an MSCA Postdoctoral Fellowship at Bilkent University (2022-2024). She has also held visiting researcher positions at MIT (2014) and the University of Tokyo (2016). Education Doctorate: Interdisciplinary Engineering, Masdar Institute of Science and Technology (2016) Master's: Microelectronic Manufacturing Engineering, Rochester Institute of Technology (2004) Bachelor's: Mechanical Engineering, Middle East Technical University (2002) Dr. Saylan's research focuses on memristive devices , photovoltaics , and light-matter interactions at micro/nanoscale . Her work bridges materials science and electronic engineering, with recent publications on memristor-based sensors, spectral filtering in silicon, and machine learning integration for biomedical diagnostics. Key trends from her 15 most recent articles (2013-2025) include: Advancing memristor technology for radiation sensing and vacuum monitoring Optimizing photovoltaic efficiency through light management and antireflection coatings Developing compact, low-power diagnostic devices for pathogen detection Exploring nanoscale electrode materials and switching mechanisms Applying Fourier transforms and interferometry in optical systems Scientific Awards Marie Skłodowska-Curie Actions (MSCA) Postdoctoral Fellowship (2022-2024) Dr. Saylan has received research support from prestigious programs and has contributed to interdisciplinary projects involving semiconductor physics, optical engineering, and biomedical diagnostics. Her collaborations span institutions like Khalifa University, MIT, and the University of Tokyo.
Andy Shih is a Professor in the Department of Electrical Engineering at École de technologie supérieure (ÉTS) in Montreal, Canada. He holds a B.Eng. and M.Eng. in Electrical Engineering from McGill University and a Ph.D. in Electrical Engineering from Massachusetts Institute of Technology. His research is conducted at the LaCIME (Communications and Microelectronic Integration Laboratory), where he focuses on innovative materials and advanced manufacturing. Dr. Shih's research interests span organic semiconductor devices, microfabrication & nanofabrication, printed and flexible electronics, sustainable electronic materials, organic transistors and sensors, soft MEMS, AI-enhanced sensing, and biomedical monitoring technologies. His work bridges materials science, electrical engineering, and biomedical applications, with particular emphasis on developing smart bandages, printed sensors, and flexible electronics for healthcare monitoring. His publications reveal a strong focus on organic electronics, sensor development, and biomedical applications, with increasing integration of AI techniques for sensor enhancement and data analysis. Dr. Shih teaches courses including Electromagnetism (ELE312), Microsystem Fabrication Processes (ELE676), and Photovoltaic Solar Energy Systems (ENR889). His supervision portfolio includes numerous doctoral and master's students working on diverse projects spanning printed electronics, MEMS, sensor development, AI applications in sensing, and photovoltaic systems. His research has resulted in multiple patents related to thin-film transistors, acoustic resonators, and sensor technologies.
Prof. Dr.-Ing. Marc Reichenbach serves as the Chair of Integrated Systems at the Institute for Applied Microelectronics and Data Technology at the University of Rostock. His office is located at Albert-Einstein-Straße 26, 18059 Rostock, Room 102 (1st floor), with contact information including telephone (0381) 498 7270 and email marc.reichenbach@uni-rostock.de. Professor Reichenbach's research focuses on the intersection of hardware design and artificial intelligence, with particular expertise in memory technologies and computing architectures. His work spans several key areas: Development of specialized computer architectures for deep learning applications Advanced VLSI design and CPU architecture Emerging memory technologies, particularly RRAM (Resistive Random-Access Memory) FPGA-based acceleration systems Hardware implementations for neural networks and AI applications Analysis of Professor Reichenbach's recent publications (2023-2025) reveals a strong focus on memory computing technologies, particularly RRAM-based systems. His work demonstrates expertise across multiple dimensions of computer architecture including ASIC design, FPGA acceleration, and novel memory systems. The publications show a clear trajectory toward implementing AI and machine learning capabilities directly in hardware, with applications ranging from edge computing to satellite systems. A significant portion of his recent work addresses the challenges of implementing neural networks using emerging memory technologies, focusing on efficiency, reliability, and performance optimization. Professor Reichenbach teaches several advanced courses including: Computer architectures for deep learning applications Project seminar Embedded Systems Advanced VLSI Design (Advanced CPU Design) His research group appears to be actively engaged in several cutting-edge projects related to hardware acceleration for AI applications, memory computing, and embedded systems design. The group collaborates on projects involving digital twins for hardware systems, real-time operating systems for heterogeneous architectures, and specialized computing systems for various applications from medical devices to drone technology.
Rod Beresford is a Professor of Engineering at Brown University's School of Engineering, where he has held several leadership positions including Senior Associate Dean for Academic Programs and Associate Provost for Academic Space. He earned his B.S. (1979) and M.S. (1981) in electrical engineering from Yale University and his Ph.D. (1990) from Columbia University. In 2020/21, he served as an IEEE/AAAS Congressional Fellow working on the Senate Energy and Natural Resources Committee. His research focuses on semiconductor nanostructures, including synthesis, modeling, integration with microelectronics, and applications, with a particular emphasis on molecular beam epitaxy. Beresford has published over 80 scientific papers and has worked on molecular beam epitaxial growth of III-V semiconductors since 1987. His current research emphasizes engineering innovations for decarbonization and electrification of the economy. Professor Beresford's scholarly work spans semiconductor materials and devices, quantum structures, nanomaterials, microfluidics, and biosensing. His recent publications demonstrate a strong focus on quantum dot arrays, nanowire electrical properties, and biosensing applications. The research shows evolution from fundamental semiconductor physics toward practical applications in sensing and energy technologies. His honors and awards include: Tau Beta Pi (1978) Sheffield Fellowship (Yale University, 1980–81) Office of Naval Research Fellowship (Columbia University, 1987–90) Sigma Xi (1991) BBV Foundation Chair (Visiting Professor, Polytechnic University of Madrid, 1996) Institute of Electrical and Electronics Engineers, Senior Member (2002) Professor Beresford has been instrumental in Brown's academic infrastructure development, including facilitating the successful development of the Engineering Research Center, an 80,000-sf lab building completed in October 2017. He has served as Academic Director for the Master of Science in Technology Leadership program and has introduced new courses in VLSI Design and Nanoelectronics. His research has been supported by significant grants including: Nanoelectronics Research Initiative / National Science Foundation: "Direct-Write Synthesis of Graphene Devices" (PI, $400,000) National Science Foundation Materials Research Science and Engineering Center: "Micro- and Nano-Mechanics of Electronic and Structural Materials" (co-PI, $9,360,000) Air Force Office of Scientific Research Multidisciplinary University Research Initiative: "Direct Nanoscale Conversion of Biomolecular Signals into Electronic Information" (co-PI, $5,609,969) Professor Beresford leads a research group focused on semiconductor nanostructures and collaborates extensively with colleagues including Jingming Xu, Eric Chason, Brian Sheldon, Alexander Zaslavsky, and David Paine. His laboratory includes molecular-beam epitaxy systems for advanced materials research.
Davide Donadio is a Professor of Chemistry at the University of California, Davis. His research focuses on molecular modeling and simulations of materials, particularly in non-equilibrium processes, thermal transport, and nanostructure assembly. He leads the Naotheory Group, which develops predictive multiscale models for energy-related materials. Education : Habilitation in Materials Science, Italian Ministry for University and Research (2013) Ph.D. in Materials Science, University of Milano (2003) M.S. in Physics, University of Milano (1998) Research Interests : His work spans molecular-level understanding of energy conversion, thermal management, and nanostructure formation. Key areas include phononics, thermoelectrics, and interfacial phenomena in materials like ice surfaces, semiconductors, and clathrates. He employs machine learning and first-principles methods to bridge simulation and experiment. Awards : UC Davis Hellman Fellow (2017–2018) Young Scientist Award, Italian Institute for the Physics of Matter (1998) Grants & Labs : His funding and collaborations drive advancements in nanostructured materials and computational tools like PLUMED tutorials. The Naotheory Group actively publishes in high-impact journals and collaborates internationally on thermal transport and materials design.
Ricardo Zednik is a Professor at the Department of Mechanical Engineering, École de Technologie Supérieure (ÉTS) in Montreal. Holding degrees from Rice University (BA, BS) and Stanford University (MS, PhD), he specializes in piezoelectric materials, fracture mechanics, and microelectronic systems. His research focuses on sensors, innovative materials, and health technologies. Fields of Interest: Piezoelectricity, Fracture Mechanics, MEMS, Smart Materials, Crystallography With over 36 peer-reviewed publications and extensive supervision of graduate research (including 15+ co-directed theses and projects since 2016), Zednik contributes to applied research in materials science and biomedical engineering. He collaborates with LaCIME and PULÉTS laboratories on cutting-edge projects involving ultrasonic transducers, flexible sensors, and high-temperature material characterization. Current courses include Materials Technology (MEC200) and advanced research topics in Functional and Smart Materials (SYS877). His students explore applications like terahertz quality control, piezoelectric earcanal sensors, and Kirigami techniques for wearable electronics.
