Giuliana Di Martino is an Associate Professor in Device Materials at the Department of Materials Science & Metallurgy, University of Cambridge. She leads the Di Martino Lab, which focuses on sustainable power solutions for non-volatile memory (NVM) and brain-like computing systems. Education : Bachelor and Master degrees from Università di Catania and Scuola Superiore di Eccellenza di Catania; PhD in Nanoplasmonics for Materials Innovation at Imperial College London (2014). Her research bridges plasmon-enhanced light-matter interactions and optically-accessible memristive devices , leveraging ultra-concentrated light in plasmonic nanocavities to study atomic-scale dynamics in memory nano-devices. Recent work includes self-assembly of nanomaterials , surface-enhanced Raman spectroscopy (SERS) , and low-power electronics for sustainable IT. Scientific Awards : Winton Advanced Research Fellowship (2018) Her grants include funding from EPSRC , Leverhulme Trust , Isaac Newton Trust , Royal Society , and ERC Starting Grant . The Di Martino Lab collaborates within the Device Materials Group (DMG), which includes three Principal Investigators.
Professor B M Azizur Rahman is a distinguished academic in the field of photonics at City University London, where he has served as Professor of Photonics in the Department of Electrical and Electronic Engineering since 2000. Previously, he was Reader in Photonics (1996-2000) and Lecturer (1988-1996) at the same institution. His academic journey began with a BEng (1971-1976) and MSc (1976-1979) from Bangladesh University of Engineering and Technology, followed by a PhD from University College London (1979-1982). His educational background laid the foundation for his extensive research career focusing on photonics, integrated waveguides, and optical sensors. Professor Rahman has made significant contributions to fields including plasmonic biosensors, fiber optic sensing technologies, supercontinuum generation, and metamaterial-based sensing systems. His research bridges theoretical modeling with practical applications in environmental monitoring, healthcare diagnostics, and engineering solutions. An analysis of his most recent publications (2022-2025) reveals a strong focus on advanced sensing technologies with applications across multiple domains. His work demonstrates expertise in combining photonics principles with nanotechnology, artificial intelligence, and novel materials to develop highly sensitive detection systems. Key research trends include the integration of deep learning with optical sensing, development of plasmonic-enhanced biosensors, and innovative waveguide designs for improved optical performance. Professor Rahman has maintained a highly productive research career with over 443 publications documented in his ORCID profile. His work shows extensive international collaboration with researchers from institutions in the UK, Bangladesh, Thailand, and other countries. While specific grant information is not provided in the available data, his sustained publication record across high-impact journals indicates successful research funding and supervision of numerous research projects over his career. His research group appears to focus on experimental photonics, computational modeling of optical systems, and development of novel sensing platforms.
Stefano Grivet-Talocia is a Full Professor at the Department of Electronics and Telecommunications at the Polytechnic University of Turin, where he also serves as Director of the Doctoral School and President of the Doctoral School Council. He is a member of the Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory, the University Committee for Research, Technology Transfer and Services to the Territory, and the Commission for the Promotion of Library, Archive and Museum Heritage. His academic career spans over two decades at Politecnico di Torino, where he has established himself as a leading researcher in electromagnetic modeling and signal integrity. Grivet-Talocia earned his Laurea degree (summa cum laude) in Electronic Engineering in 1994 and his Ph.D. in Electronic and Communication Engineering in 1998, both from the Polytechnic University of Turin. Between 1994 and 1996, he conducted research at NASA/Goddard Space Flight Center in Greenbelt, Maryland. His educational background laid the foundation for his expertise in electromagnetic modeling, wavelet analysis, and signal processing. His research focuses on behavioral modeling, electromagnetic compatibility, macromodeling, model order reduction, numerical modeling, passivity, power integrity, signal integrity, transmission lines, and wavelets . Grivet-Talocia is particularly renowned for his work on passive macromodeling of interconnect structures, development of the TOPLine technique for transmission line simulation, and pioneering contributions to passivity enforcement algorithms. He has co-authored the first book entirely dedicated to Macromodeling (2016) and developed innovative approaches to waveform relaxation and wavelet-based signal processing. His recent publications (2024-2025) demonstrate continued leadership in model order reduction, with significant contributions to data-driven modeling of linear and nonlinear systems, power integrity analysis, and electromagnetic compatibility. His work spans both theoretical advances in numerical methods and practical applications in circuit design, with strong industry relevance particularly for semiconductor and electronic design automation companies. IEEE Fellow (2018-present) Three Intel SRS Grants (2022-2024) Three IBM SUR Grant Awards (2007-2009) Best Associate Editor Award - IEEE Transactions on Components, Packaging and Manufacturing Technology (2020) Multiple Best Conference Paper Awards (2006-2020) URSI Young Scientist Awards (1999) Ranked among the "top 2% worldwide researchers" (Stanford) since 2019 Grivet-Talocia actively supervises doctoral students including Michele Cusano, Sara Paknezhad Panahi, Antonio Carlucci, and Kun Zhao. He has secured numerous research grants from competitive national calls (PRIN) and commercial contracts with industry partners including Intel, IBM, Nokia, Hitachi, Infineon, and Cadence. His technology transfer activities include co-founding the spin-off IdemWorks (2007-2016), which was acquired by CST in 2016. He also developed the autoCircuits web service for automated circuit problem generation, widely used in electrical engineering education. He leads the EMC Group (Electromagnetic Compatibility) at DET and has been instrumental in establishing the Compact Dynamical Modeling research area. His work has practical applications in high-speed electronics design, with algorithms embedded in commercial tools like IBM PowerSPICE. Grivet-Talocia maintains strong industry connections through his research projects and serves as Associate Editor for IEEE Transactions on Components, Packaging and Manufacturing Technology.
Dushan Boroyevich is a University Distinguished Professor at Virginia Tech's Bradley Department of Electrical and Computer Engineering and serves as Deputy Director of the Center for Power Electronics Systems (CPES). He holds adjunct roles at Tsinghua, Xi'an Jiaotong, Zhejiang, and National Cheng-Kung Universities. His research focuses on power electronics systems, including multi-phase power conversion, electronic power distribution, and modular multilevel converters. He pioneered the geometric modeling approach for high-frequency converters and has led over 200 students in generating 1000+ publications and 20 patents. Education: Dipl. Ing. (University of Belgrade, 1976), M.S. (University of Novi Sad, 1982), Ph.D. (Virginia Tech, 1986). Awards include IEEE Fellow, IEEE William E. Newell Award, and election to the U.S. National Academy of Engineering (2014). His CPES leadership has driven global advancements in power electronics integration and modularization. Research emphasizes high-power density, EMI mitigation, and next-gen SiC-based converters. Recent work includes medium-voltage PEBB designs, common-mode noise reduction, and grid-interface systems. He collaborates closely with industry through CPES's 80+ member consortium. Awards: IEEE Fellowships, Owen Distinguished Service Award, European Power Electronics Association Awards Labs/Teams: CPES, Virginia Tech Power Electronics Research Group Grants/Projects: NSF National Engineering Research Center funding, Industry Consortium projects
Professor Antonio Griffo holds the position of Professor of Power Electronics and Electric Drives at the University of Sheffield's School of Electrical and Electronic Engineering. He leads the Electrical Machines and Drives Research Group and is involved in the High Reliability Drives Group. His academic journey includes a MSc (2003) and PhD (2007) in Electrical Engineering from the University of Naples, followed by research roles at Bristol and Sheffield Universities before becoming a Lecturer in 2013 and later a Professor. His research focuses on advanced control of electric drives, SiC-based power electronics for aerospace/renewables, fault detection in machines, and thermal management. Key projects include modeling hybrid AC/DC power systems for 'More Electric Aircraft', sensorless control techniques, and real-time simulation methodologies. He has pioneered work on SiC converter reliability, insulation monitoring, and condition-based maintenance systems. Publications (15+ in top journals like IEEE Transactions) emphasize innovative solutions for power electronics challenges, including voltage stress mitigation, thermal modeling, and fault tolerance. His work bridges theory and application, addressing critical issues in aerospace, renewable energy, and electric vehicle systems. Griffo also contributes to educational advancements through modular training platforms for power electronics education. Labs/Teams: Active in the Electrical Machines and Drives Research Group, focusing on high-reliability drive systems and sustainable energy technologies. Collaborates with industry on projects like the EPSRC Offshore Wind Prosperity Partnership.
Dr.-Ing. Thomas Wild serves as an Academic Director at the Technical University of Munich (TUM), working within the TUM School of Computation, Information and Technology at the Chair of Integrated Systems. He maintains an active research and teaching role at the institution, with his office located in Building N1 (Theresienstr. 90), Room N2136 in Munich, Germany. Dr. Wild's research focuses on advanced computing architectures, with particular emphasis on manycore system on chip (SoC) architectures, network processor (NPU) architectures, on-chip communication architectures including networks on chip (NoC), and system level design methodologies. His work bridges theoretical research with practical implementation, often exploring design space exploration techniques to optimize system performance. The evolution of his research over two decades demonstrates a consistent focus on improving communication architectures and system-level design for embedded and high-performance computing platforms. His recent publications (2023-2025) reveal a growing integration of machine learning techniques with traditional hardware design, particularly in optimizing power-performance tradeoffs in embedded systems. There's a clear trend toward hardware-software co-design approaches, with significant work on SmartNICs, Linux system optimization, and network processing acceleration. His research shows strong interdisciplinary connections between computer architecture, networking, and machine learning. EUROPRACTICE representative for TUM city campus, facilitating access to commercial EDA tools for academic purposes Active collaborator with Professor Andreas Herkersdorf and other researchers at TUM Focus on practical implementations with FPGA-based prototyping and real system modifications Dr. Wild teaches several hardware design courses including VHDL Lab, SystemC Lab, and HW/SW Codesign, contributing to the education of next-generation computer engineers. His teaching directly complements his research in system design and hardware acceleration, providing students with hands-on experience in cutting-edge technologies.
Mendel Rosenblum is the Cheriton Family Professor and holds dual appointments as Professor in the Departments of Computer Science and Electrical Engineering at Stanford University. He is a co-founder of VMware Inc. and served as its Chief Scientist for its first decade, playing a pivotal role in designing foundational virtualization technologies. Rosenblum's research focuses on system software, distributed systems, and computer architecture, with notable contributions to virtualization, data center networks, and operating systems. He leads the Platform Lab at Stanford, exploring next-generation data center technologies and high-performance computing systems. Administrative Role: Faculty Director of Stanford Computer Forum (2012–present) Education: PhD (UC Berkeley, 1992), MS (UC Berkeley, 1989), BA (University of Virginia, 1984) His research interests span disk storage management, computer simulation, scalable operating systems, and security. Recent work emphasizes deployable consensus algorithms, programmable smartNICs, and self-programming networks. Rosenblum has authored over 80 publications and holds multiple patents in virtualization and system software. Awards & Recognition: ACM System Software Award (2009) IEEE Computer Entrepreneur Award (2011) ACM Thacker Breakthrough in Computing Award (2018) Member, National Academy of Engineering (2013) He advises PhD and Master's students, including current advisees Sina Jandaghi Semnani and Zixi Liu. Rosenblum teaches advanced courses on web applications, distributed systems, and independent research projects.
Emin Gün Sirer is an Associate Professor at the Department of Computer Science , College of Engineering , Cornell University . He co-directs the Initiative for Cryptocurrencies and Smart Contracts and leads the Meridian and HyperDex projects. Research in operating systems, networking, and distributed systems Focus on secure operating systems, high-performance cloud infrastructure, and peer-to-peer networks Developed systems like Nexus (secure OS), OpenReplica (Paxos implementation), and Trickles (stateless network protocol) Prominent Projects : Meridian - Lightweight network location service without virtual coordinates Cubit - Decentralized peer-to-peer search Kimera - Network-centric Java verification SPIN - Extensible microkernel for application-specific services Scientific Contributions : Leading work in blockchain security and peer-to-peer systems Patents in executable content rewriting and distributed virtual machines Advising & Collaborations : Advises projects in network positioning and content distribution Collaborates with institutions like Usenix , SIGCOMM , and NSDI Personal Background : Ph.D. and M.S. in Computer Science from the University of Washington B.S.E. in Computer Science from Princeton University High school at Robert College
Canan ATILGAN is a Professor at the Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul, Turkey. She has held leadership roles including Dean (2018-2020), Director of the Graduate School (2018-2020), and President of the Science Academy (2021-present). Her research focuses on computational tools for protein conformational transitions, allosteric communication, and antibiotic resistance mechanisms. Ph.D. (1996) and B.S. (1991) in Chemical Engineering from Boğaziçi University A pioneer in perturbation-response scanning and network-based protein modeling, her work bridges biophysics, structural biology, and molecular evolution. She has supervised 15 PhD and 17 MS students, emphasizing accessible computational biophysics education through workshops and seminars. Her recent publications highlight allosteric mechanisms in biosensors, β-lactam resistance via TolC dynamics, and evolutionary fitness landscapes. Awards include EMBO and Academia Europaea membership, L’Oréal Turkey Young Women Scientist Fellowship, and TÜBA-GEBİP Distinguished Young Scientist Award. President, Science Academy (2021) EMBO Elected Member (2023) TÜBA-GEBİP Distinguished Young Scientist (2004) She leads the MIDST Lab, contributes to Turkish science communication via sarkac.org, and organizes 'Dialogues in the MIDST' workshops for graduate students. Her work integrates theoretical models with experimental validation in iron transport proteins and resistance mechanisms.
Dr. Mohamed Youssef is an Associate Professor in the Department of Electrical, Computer and Software Engineering at Ontario Tech University. He holds a PhD (Electrical and Computer Engineering) from Queen’s University (2005). His primary affiliation is the Faculty of Engineering and Applied Science, with research focusing on propulsion systems, power electronics, railway systems, and renewable energy technologies. Education: PhD, Electrical and Computer Engineering, Queen’s University (2005) MSc, Power Electronics, Concordia University (2001) MSc, Electric Power and Machines, Ain Shams University (1999) BSc, Electric Power and Machines, Ain Shams University (1995) Research Interests: Dr. Youssef’s expertise spans propulsion systems for automotive and hyperloop technologies , power electronics for IoT and renewable energy , railway electromagnetic compatibility , and power system stability . His work emphasizes practical applications in electric vehicles, smart grid integration, and sustainable energy systems. He leads the PEDAL (Power Electronics and Drives Laboratory) at Ontario Tech. Awards and Recognition: Recipient of the NSERC Post-doctorate Scholarship (2006) Best Paper Award at IECON 2004 Award of Merit from Ontario Center of Excellence (2006) Nominated for the Howard Alper Prize (2007) Professional Activities: He serves as a reviewer for IEEE Transactions on Power Electronics , IEEE Transactions on Industrial Electronics , and others. He has held roles as Technical Chair at IEEE SEGE 2015 and Track Chair at IEEE SEGE 2016. Current affiliations include Senior Member of IEEE and Chair of the IEEE Power Electronics Chapter in Toronto. Labs and Teams: He directs the PEDAL Lab , focusing on advanced power electronics and electric vehicle technologies. Collaborations include Bombardier Transportation and Armstrong Pumps.
Yuan Zhong is an Associate Professor of Operations Management at the University of Chicago Booth School of Business . He previously held positions as an Assistant Professor at Columbia University’s Department of Industrial Engineering and Operations Research and was a Postdoctoral Scholar at UC Berkeley’s Computer Science Department. Education: PhD in Operations Research, MIT (2012) MA in Mathematics, Caltech (2008) BA in Mathematics, University of Cambridge (2006) His research focuses on applied probability and stochastic system design , with applications in cloud computing , supply chain management , and e-commerce logistics . Recent work explores multi-period production systems and dynamic resource allocation in data centers and healthcare operations . Recent publications analyze cloud value chains , sparse graph design for delivery networks, and process flexibility in manufacturing. He has contributed to journals like Operations Research , Annals of Applied Probability , and Stochastic Systems . Scientific Awards: 2012 Kenneth C. Sevcik Outstanding Student Paper Award Best Student Paper Award at ACM Sigmetrics (2012) He teaches courses in business process fundamentals and queueing theory , with a future schedule including Operations Management: Business Process Fundamentals (2025–2026). No explicit student advising list was provided.
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.
Dr. Yiting Xia is a tenure-track faculty member at the Max Planck Institute for Informatics (MPI-INF), leading the Network and Cloud Systems research group. She previously worked as a research scientist at Facebook and holds a PhD in Computer Science from Rice University (2018) and a B.S. in Telecommunications Engineering from Beijing University of Posts and Telecommunications and Queen Mary University of London (2011). Her research focuses on high-performance and energy-efficient networking for cloud computing, including reconfigurable data center networks, optical communications, and network protocols. Notable contributions include innovations in transport protocols, time synchronization for optical networks, and failure-resilient network design. Education: PhD in Computer Science, Rice University, 2018 M.S. in Computer Science, Rice University, 2014 B.S. in Telecommunications Engineering, BUPT & QMUL, 2011 Research Interests: Data center networking, optical communications, cloud systems, network protocols, distributed systems, and network security. Her work bridges theoretical contributions with practical implementations, addressing challenges in latency-sensitive flows, traffic engineering, and system reliability. Awards include the Ken Kennedy-Cray Fellowship and the N2Women Rising Star Award (2021). She has co-lectured courses on distributed systems and data networks at Saarland University and previously contributed to teaching at Rice University. Key projects include Aurora (for MoE inference optimization), Lighthouse (an open research framework for optical networks), and Occam (a reliable network management system). Grants & Projects: Focus on deployable optical network architectures and resilient backbone management during pandemic-driven traffic shifts. Labs/Teams: Leads the Network and Cloud Systems group at MPI-INF, collaborating with academia and industry on cutting-edge networking solutions.
Joachim Oberhammer is a Professor in Microwave and THz Microsystems at KTH Royal Institute of Technology in Stockholm, Sweden. He leads research in radio-frequency/microwave/terahertz micro-electromechanical systems (MEMS) and has held academic roles since 2005. His work includes pioneering advancements in THz communication, sub-THz radar concepts, and MEMS-based components. Oberhammer has been awarded the 2023 Young Engineer Award by the European Microwave Association and holds multiple grants, including an ERC Consolidator Grant (2013) and SSF framework grants (2014–2025). He has authored over 200 peer-reviewed publications and holds four patents in MEMS and THz technology. Education: M.Sc. in Electrical Engineering (Graz University of Technology, 2000), Ph.D. in Microwave Engineering (KTH, 2004). Postdoctoral research at Nanyang Technological University (2004) and Kyoto University (2008). Guest professorships at Universidad Carlos III de Madrid (2019–2020) and NASA-JPL (2014). Research focuses on MEMS fabrication, THz systems integration, and radar technologies. Key projects include the EU-funded M3TERA and Car2TERA projects, and leadership in SSF framework grants for electronics research. He coordinates the EU RIA projects TeraMeasure and TESLA, advancing terahertz applications. Teaching responsibilities include MSc and PhD courses in MEMS engineering, radar systems, and integrated circuits. His lab develops high-performance THz components, including waveguide switches, antennas, and filters, with applications in communication, sensing, and aerospace.
Stephen Brown is a Professor at the University of Toronto within the Department of Electrical and Computer Engineering under the Faculty of Applied Science and Engineering. He earned his B.A.Sc and M.A.Sc in Electrical Engineering from the University of Toronto and New Brunswick, respectively, and a Ph.D. in Electrical Engineering from the University of Toronto (1992). His career spans over two decades in academia and industry collaboration. Education : B.A.Sc, University of New Brunswick M.A.Sc, University of Toronto Ph.D, University of Toronto Professor Brown’s research focuses on field-programmable gate arrays (FPGAs) , CAD algorithms , and computer architecture , with applications in machine learning and high-level synthesis . He is a principal investigator in the LegUp project , an open-source high-level synthesis framework that bridges software and hardware design. His work also extends to optimizing FPGA interconnect delays, physical synthesis, and logic block architectures. Key trends in his publications include advancements in high-level synthesis tools, FPGA architecture evaluation, and timing-driven design methodologies. His contributions often intersect with design automation , resource sharing , and embedded systems . Scientific Awards : NSERC 1992 Doctoral Prize Hart Professorship for Innovation in Teaching (2017) Multiple teaching excellence awards Best Paper Award at ICCAD 1990 Best Paper Award nomination at Canadian Conference on VLSI (1989) As Director of the FPGA University Program at Intel Corporation, he leads industry-academia initiatives. His teaching portfolio includes courses like ECE253 (Digital Logic) and ECE1733F (Switching Theory).
