Austin Rovinski is an Assistant Professor in the Department of Electrical and Computer Engineering at New York University’s Tandon School of Engineering. He specializes in chip design, electronic design automation (EDA), and open-source hardware methodologies. His research focuses on VLSI design, domain-specific accelerators, and chiplet-based systems. Prior to NYU, he held a postdoctoral position at Cornell University and earned all his degrees (Ph.D., M.S., and B.S.) from the University of Michigan. Education: Ph.D., Electrical Engineering, University of Michigan - Ann Arbor Master’s, Electrical Engineering, University of Michigan - Ann Arbor Bachelor’s, Electrical Engineering, University of Michigan - Ann Arbor Research Focus: Developing open-source EDA frameworks like OpenROAD Optoelectronic interconnect systems for 2.5D packaging Agile hardware design methodologies Reconfigurable sparse matrix accelerators RISC-V-based manycore processors (e.g., Celerity project) Key Contributions: Austin led the development of the OpenROAD RTL-to-GDS flow and contributed to the Sirius and Celerity projects. His work emphasizes reproducibility, democratizing chip design through open-source tools. Awards: IEEE Micro Top Picks (2015) Michigan EECS Outstanding Research Award (2016) NSF Graduate Research Fellowship Honorable Mention (2017, 2018) Advising & Grants: Actively mentors graduate students in chip design and EDA. His research is supported by NYU’s Tandon School of Engineering and collaborations with industry partners. Labs & Teams: Core contributor to the OpenROAD project, part of NYU’s hardware design and EDA initiatives, and collaborator on the Celerity manycore processor project.
Mervi Paulasto-Kröckel is a Professor in the Department of Electrical Engineering and Automation at Aalto University, specializing in Electronics Integration and Reliability. With a doctoral degree in Engineering and Technology from Helsinki University of Technology (1995) and a Master's degree from the same institution (1990), her work focuses on microelectronics packaging, MEMS, and sustainable electronic manufacturing. Doctoral Degree: Engineering and Technology, Helsinki University of Technology (1995) Master's Degree: Engineering and Technology, Helsinki University of Technology (1990) Her research explores advanced packaging techniques like SLID bonding, reliability of microbumps, and thermally conductive materials. Recent work includes buried aluminum nitride for silicon-on-insulator and fatigue crack analysis in IGBT modules. Her publications emphasize low-temperature processes, interdiffusion, and MEMS reliability. Awards include the JVST A Best ALD Paper Award (2021) and a Best paper award (2000). She leads projects like PowerizeD and 3DPiezoMems, focusing on digitalization and 3D MEMS development. Best paper award (2000) JVST A Best ALD Paper Award (2021)
Mark Jenkinson is a Professor of NeuroImaging at the University of Oxford's Nuffield Department of Clinical Neurosciences and also holds positions at the University of Adelaide's Australian Institute for Machine Learning and the South Australian Health and Medical Research Institute (SAHMRI). He heads the Structural Modelling and Analysis Group at the FMRIB Centre, where his research focuses on multimodal population modeling and structural brain segmentation. Education: DPhil in Robotics Research (University of Oxford, 1999) BSc (Hons I) in Mathematical Physics (University of Adelaide, 1994) BE (Hons I) in Electrical and Electronic Engineering (University of Adelaide, 1993) Professor Jenkinson's research spans two major themes: multimodal modeling of populations to describe disease processes and apply to individual patient diagnoses, and structural segmentation and analysis of brain anatomy and pathology, particularly focusing on sub-cortical structures and lesions. His work integrates advanced computational methods with neuroimaging to develop tools for understanding neurological disorders. As the developer of key components of the FMRIB Software Library (FSL), he has significantly contributed to standard neuroimaging analysis pipelines used worldwide. His recent publications demonstrate a strong focus on deep learning applications in neuroimaging, uncertainty quantification in medical AI, and advanced segmentation techniques. There's a clear trend toward developing more robust, anatomically plausible models that preserve topological structures while improving diagnostic capabilities for conditions like multiple sclerosis, Huntington's, and Parkinson's diseases. Scientific Awards: Highly Cited Researcher (Clarivate Analytics 2018-2021, Thomson Reuters 2014-2016) ISMRM Outstanding Teacher Award (2009, 2014) Teaching Excellence Award, University of Oxford (2012) David Phillips Fellowship from BBSRC (2005-2010) Professor Jenkinson has supervised over 25 doctoral students whose work spans brain segmentation, connectivity analysis, and clinical applications of neuroimaging. His research is supported by significant grants including the Medical Research Future Fund (AU$2m), Wellcome Trust Centre for Integrative Neuroimaging (£11m), and NIH Human Connectome Project (US$30m), reflecting the high impact and translational potential of his work. As head of the Structural Modelling and Analysis Group at FMRIB, Jenkinson leads a team developing the FSL (FMRIB Software Library), one of the most widely used neuroimaging analysis packages globally. His group collaborates extensively with clinical researchers on applications ranging from multiple sclerosis to traumatic brain injury, translating computational advances into clinical practice.
Robert M. Weikle, II is a Professor in the Charles L. Brown Department of Electrical and Computer Engineering at the University of Virginia, with a courtesy appointment in the Department of Physics. He earned his B.S. from Rice University (1986), M.S. (1987), and Ph.D. (1992) in Electrical Engineering from Caltech, followed by postdoctoral work at Chalmers University of Technology (1992). His research focuses on millimeter-wave and terahertz electronics , applied electromagnetics, integrated antennas, low-noise sensors, and heterogeneous integration of compound semiconductors. His work bridges electronics and photonics for spectrum access, with applications in astronomy, spectroscopy, and metrology. He has published extensively on micromachined silicon substrates, superconducting materials, and emerging technologies. Scientific Awards: IEEE Microwave Prize (1993) David A. Harrison III Award (1999) University of Virginia All-University Outstanding Teaching Award (2000) Edlich-Henderson Innovator of the Year (2016) Fulbright Scholar (2001) As Chief Technology Officer and co-founder of Dominion Microprobes, Inc., he commercializes micromachined wafer probes for high-frequency metrology. His lab, located in E220 Thornton Hall and the Jesse W. Beams Physics Building, has produced 15+ recent publications on submillimeter-wave devices, THz probes, and calibration techniques.
Douglas C. Hopkins is a Research Professor and Director of the Laboratory for Packaging Research in Electronic Energy Systems (PREES) at North Carolina State University's Department of Electrical and Computer Engineering. He joined the ECE faculty in 2011 and is affiliated with the FREEDM Systems Center and the Center for Additive Manufacturing and Logistics (CAMAL). He holds a Ph.D. in Electrical Engineering from Virginia Tech (1989). His research focuses on Very High-Frequency power electronics, Wide Band Gap (WBG) devices (GaN/SiC), advanced packaging, and solid-state protection systems . He has pioneered work in integrated power electronics, harsh-environment systems, and 3D power electronics integration. His leadership includes founding conferences such as the International Symposium on 3D Power Electronics Integration and Manufacturing (3D-PEIM) and the International Symposium on Advanced Power Electronics Packaging (APEPS). Prof. Hopkins has authored over 200 publications and co-founded DensePower, LLC as CEO/CTO. He serves as Associate Editor for the IEEE Journal of Emerging and Selected Topics in Power Electronics and holds editorial roles in multiple journals. His awards include the IMAPS Outstanding Educator Award (2013) and IMAPS Fellow (2007). He has held visiting appointments at the Army Research Lab, NASA, and Lawrence Livermore National Lab, and served as a National Academy of Sciences reviewer. His consulting firm, DCHopkins & Associates, LLC, provides engineering expertise in power electronics and packaging. Key Contributions: Director of PREES Lab and FREEDM Center member Co-founder of 3D-PEIM and APEPS symposiums IEEE PELS Technical Committee member (TC2, TC-6) Recipient of IMAPS Fellow and multiple conference recognitions
Professor John D. Cressler is a tenured faculty member at the Georgia Institute of Technology, holding a position within the School of Electrical and Computer Engineering in the College of Engineering. His research focuses on cutting-edge semiconductor technologies, particularly silicon-germanium heterojunction bipolar transistors (SiGe HBTs) for mixed-signal applications spanning RF, microwave, mm-wave, analog, and digital domains. His research interests center on atomic-scale bandgap engineering for next-generation semiconductor devices, with emphasis on SiGe HBT technology development, radiation-hardened circuits for space applications, cryogenic electronics, and device-circuit interactions. His team explores fundamental device theory, broadband noise analysis, profile optimization, 2-D/3-D simulation, compact modeling, and radiation effects. Current projects include Europa-surface mission electronics, D-band/sub-THz systems, and radiation-tolerant receiver designs. Analysis of his 15 most recent publications (2024-2025) reveals a dominant focus on radiation-hardened electronics for space applications (40% of works), millimeter-wave circuit design (30%), and SiGe HBT reliability optimization (30%). Key trends include Europa mission electronics development, D-band/sub-THz circuit innovation, and advanced radiation mitigation techniques using SiGe BiCMOS technology. Professor Cressler teaches multiple courses including ECE 3040 (Microelectronic Circuits), ECE 3450 (Semiconductor Devices), ECE 6444 (Silicon-Based Heterostructure Devices and Circuits), and the interdisciplinary IAC 2002 course on Science, Engineering and Religion. His research is supported by industrial collaborations and Georgia Tech facilities including the Georgia Electronic Design Center (GEDC), NanoTECH, and C-STAR.
Professor Dragan Jovcic is the Chair in Engineering at the University of Aberdeen's School of Engineering , where he has been a faculty member since 2004 and a full professor since 2012. Concurrently he serves as Director of the Aberdeen HVDC Research Centre , a role he has held since 2015. Education: PhD in Electrical Engineering, University of Auckland, 1999 Diploma Engineer in Control Systems, University of Belgrade, 1993 Postgraduate Certificate in University Teaching, University of Ulster, 2003 Research Interests: Professor Jovcic’s research centres on high-power electronics and HVDC transmission systems , with particular emphasis on the development of DC transmission grids that will enable large-scale integration of offshore wind energy . His work spans DC/DC converters , DC circuit breakers , modular multilevel converters (MMC) , flexible AC transmission systems (FACTS) , and advanced power system modelling and control . The overarching goal is to underpin the transition from fossil-fuel generation to renewable-dominated power systems, especially in the North Sea and European contexts. Publication Trends: Recent publications (2020-2023) reveal a strong focus on DC protection technologies —notably circuit breakers and energy absorbers—and on modelling methodologies for HVDC grids and offshore wind integration. The works address both theoretical advances (phasor and state-space models) and experimental validation (kV-level prototypes), reflecting a balanced portfolio of fundamental research and practical demonstration. Scientific Awards & Recognition: IEEE Fellow (2021) IEEE PES Distinguished Lecturer (since 2015) IET Fellow (2019) and Chartered Engineer (2018) Research Funding & Supervision: With over £5.5 million in external research income, Professor Jovcic is principal investigator or work-package leader on numerous EU Horizon Europe and EPSRC projects. He has supervised 9 PhDs to completion and is currently mentoring 2 PhD students and 2 post-doctoral fellows . Major grants include the €35 million PROMOTioN project on multiterminal DC networks and the €4 million MoWiLife project on wide-bandgap power electronics. Laboratory & Facilities: The Aberdeen HVDC Research Centre hosts a 0.9 kV DC grid demonstrator , 30 kW thyristor- and IGBT-based DC/DC converters , and 5 kV, 2 kA DC circuit breaker test benches , providing a world-class platform for experimental research and student training.
Dr. Emanuele Pelucchi is a Research Professor and Head of the Epitaxy and Physics of Nanostructures (EPN) group at Tyndall National Institute, University College Cork. His research focuses on quantum technologies, epitaxial growth (MBE/MOVPE), quantum dot physics, and photonic integration. He leads a world-class MOVPE facility, pioneering developments in site-controlled quantum dots and entangled photon emitters. Pelucchi's work has resulted in over 129 international publications with an h-index of 28 (Scholar), including contributions to Nature Photonics and NanoLetters. He has held a Science Foundation Ireland Principal Investigator grant since 2006, establishing his group at Tyndall in 2007. His expertise spans semiconductor nanostructures, including III-V materials and quantum optics. Pelucchi actively reviews for top journals and chairs international conferences, contributing to the field's academic discourse. His MOVPE laboratory is recognized as a key resource for III-V materials, serving as a secondary supplier to the UK National Centre for III-V Materials. Pelucchi's research bridges fundamental physics and applied photonics, driving advancements in quantum information processing and optoelectronic devices.
Muhannad S. Bakir is the Dan Fielder Professor in the School of Electrical and Computer Engineering at Georgia Institute of Technology, and Director of the 3D Systems Packaging Research Center . His research focuses on heterogeneous integration , electrical/photonic interconnects , thermal modeling , and electronics for healthcare , with over 180 publications and 12 U.S. patents. Research areas include: Advanced cooling and power delivery for emerging systems Biosensor-CMOS integration 2.5D/3D IC packaging Polylithic integration technology Nanofabrication for microsystems Scientific accolades include: 2018 IEEE EPS Exceptional Technical Achievement Award 2013 Intel Early Career Faculty Honor Award 2012 DARPA Young Faculty Award 2011 IEEE CPMT Outstanding Young Engineer Award Best paper awards at IEEE ECTC, IITC, and CICC 2020 Georgia Tech Doctoral Thesis Advisor Award His lab explores integrated 3D systems with emphasis on co-design of thermal, power, and electrical networks for machine learning and healthcare applications.
Fred A. Kish is the MC Dean Distinguished Professor and Director of the NC State Nanofabrication Facility at North Carolina State University. He holds a Ph.D. in Electrical Engineering from the University of Illinois at Urbana-Champaign (1992). His research focuses on Photonics, Optoelectronic Devices, and Compound Semiconductor Materials , with emphasis on photonic integrated circuits (PICs), quantum information science, and semiconductor material engineering. He has co-invented foundational technologies for LEDs, VCSELs, and large-scale PICs, contributing over $7B in commercialized products. His leadership includes roles at Hewlett-Packard, Agilent Technologies, and Infinera Corporation, where he pioneered optical communication systems. Dr. Kish is a Fellow of the National Academy of Inventors, Optica, and IEEE, and a member of the National Academy of Engineering. His awards include the IEEE David Sarnoff Award and the John S. Risley Entrepreneur of the Year Award. He has authored 170+ peer-reviewed publications, 135+ patents, and 5 book chapters. His current work drives advancements in wide bandgap semiconductors and photonic integration for next-generation communications and sensors. Labs/Teams: Directs the NC State Nanofabrication Facility, a hub for semiconductor innovation. Collaborates on the CLAWS Hub, a $39.4M CHIPS Act-funded regional semiconductor innovation initiative.
Suresh K. Sitaraman is a Regents' Professor and Morris M. Bryan, Jr. Professor in Mechanical Engineering at the Georgia Institute of Technology's George W. Woodruff School of Mechanical Engineering. His primary research focuses on Computer-Aided Engineering (CAE) and Design, manufacturing processes, micro/nano engineering, and mechanics of materials. He leads the Computer-Aided Simulation of Packaging Reliability (CASPaR) Lab and is involved in flexible hybrid electronics research through the Flexible Electronics Center . Dr. Sitaraman holds a Ph.D. from The Ohio State University (1989), M.A.Sc. from the University of Ottawa (1985), and B.E. from the University of Madras (1982). His research includes developing novel techniques like fixtureless magnetic actuation for interfacial fracture testing, compliant micro-scale interconnects for stress mitigation, and synchrotron X-ray diffraction analysis for through-silicon vias (TSVs). He has pioneered studies on carbon nanotube forests' mechanical properties and reliability challenges in 3D microsystems. His awards include the NSF CAREER Award (1997-2002), ASME Fellow designation (2004), and Sigma Xi Sustained Research Award (2008). He has authored over 150 publications and holds multiple patents on compliant interconnect technologies and packaging reliability solutions. Key Research Themes: Micro/nano-scale material characterization, physics-based predictive modeling, flexible electronics, 3D integration, and thermal management. Labs/Initiatives: CASPaR Lab ( caspar.gatech.edu ), Flexible Hybrid Electronics Center. Industry Impact: Contributions to semiconductor packaging, wearable electronics, and advanced manufacturing techniques.
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.
Yinzhi Cao is an Associate Professor at the Johns Hopkins University Department of Computer Science . He serves as Technical Director of the Johns Hopkins Information Security Institute and is affiliated with the Data Science and Artificial Intelligence Institute and the Institute for Assured Autonomy . Cao joined JHU in 2018 from Lehigh University, where he was an Assistant Professor. Doctor of Philosophy (PhD) in Computer Science, Northwestern University (2014) Bachelor of Engineering (BE) in Electronic Engineering, Tsinghua University (2008) Research Interests focus on security and privacy of web, mobile, and machine learning systems . Key projects include Vulnerability Analysis of Web Applications and Security, Privacy, and Fairness Analysis of ML Systems . His work addresses prototype pollution in JavaScript, node.js vulnerabilities, browser fingerprinting, federated learning privacy, and automated exploit generation. Scientific Recognition includes the NSF CAREER Award (2021) DARPA Young Faculty Award (2022) & Director's Fellowship (2024) Amazon Research Awards (2022, 2017) IEEE Security & Privacy Test of Time Award (2025) Distinguished Paper Awards at IEEE S&P 2025, CCS 2023, USENIX Security 2022 Advising & Grants highlight mentorship of 20+ PhD and Master’s students across institutions. Major grants include $1.2M collaborative CICI TCR grant (2024-2026) with Dr. John Aucott $750K DARPA YFA grant (2022-2025) $500K NSF SaTC grant (2022-2025) NSF EAGER grant (2016-2017) Labs & Teams : Affiliated with Johns Hopkins Information Security Institute , Data Science AI Institute , and Institute for Assured Autonomy . Collaborates with institutions like Columbia, UC Santa Barbara, and SRI International. His group investigates real-world vulnerabilities in over 2,500 websites and NPM packages, uncovering 80+ zero-day issues.
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.
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.
