Professor Steve G Burrow is a faculty member at the School of Civil, Aerospace and Design Engineering at the University of Bristol. His research focuses on energy harvesting, vibration control, and environmental sensing, particularly in aerospace and glaciological contexts. Professor of Aircraft Systems Member of the Cabot Institute for the Environment Active in Dynamics and Control research themes His work in energy harvesting emphasizes electromagnetic transducers and nonlinear resonant structures, while environmental sensing involves deploying sensors under ice sheets to study glacial hydrology. Recent articles highlight inerter-based suspension systems, vibration absorber optimization, and broadband energy harvesting techniques. Collaborations span nonlinear mathematics, glaciology, and structural dynamics. No scientific awards were explicitly mentioned, but his research outputs demonstrate extensive contributions to power electronics and sustainable technologies.
Cathryn Mitchell is a Professor of Radio Science and Royal Society Industry Fellow at the University of Bath, specializing in ionospheric physics, position, navigation, and timing (PNT). She leads research in the Space & Telecoms Research Group (STAR), focusing on radio propagation, data assimilation, and space weather impacts on communication systems. Her work bridges theoretical, computational, and experimental approaches, with applications in satellite navigation, climate monitoring, and defense sectors. Her research interests include ionospheric tomography, HF communications, and the development of robust PNT systems. Mitchell collaborates extensively with industry partners like Spirent Communications on future navigation technologies and space weather resilience. She has held roles such as Academic Director of the Doctoral College and contributes to interdisciplinary projects like the DRIIVE initiative exploring ionospheric variability with EISCAT-3D radar. Recent work emphasizes ionospheric effects during geomagnetic storms (e.g., the 2024 Gannon Storm) and cooperative autonomous systems under communication constraints. Her projects are funded by the Royal Society, Natural Environment Research Council (NERC), and ESA, addressing challenges in space weather forecasting and PNT system reliability. Awards: Royal Society Industry Fellow (2022–present) Key Projects: Royal Society Industry Fellowship on Future PNT Technologies DRIVERS (DRIIVE): Ionospheric Variability Studies EISCAT-3D FINESSE: Ionospheric Structuring Analysis Mitchell’s lab, STAR, integrates academic and industrial partnerships to advance space weather applications and sustainable navigation systems, contributing to UN Sustainable Development Goals related to climate action and innovation.
Massimo Figari is a Full Professor at the University of Genoa , affiliated with the Department of Naval, Electrical, Electronic, and Telecommunications Engineering (DITEN) . He serves as the Course Coordinator for the Maritime Science and Technology course and teaches a range of subjects including naval systems reliability, military ship design, and maritime economics. His research spans naval architecture , maritime safety , autonomous shipping , and decarbonization technologies . He is actively involved in developing battery energy storage systems for naval applications, certification frameworks for autonomous ships, and simulation-based training for maritime education. His work emphasizes sustainability, safety, and innovation in marine engineering. Recent publications reflect a strong focus on emission reduction , alternative marine fuels like methanol, and autonomous navigation systems . These contributions position him at the forefront of maritime engineering research and education. Contact: He is available via email at massimo.figari@unige.it and holds office hours on Fridays from 4–5 PM at Villa Cambiaso, Office No. 322.
Serkut Ayvasik is a Researcher at the Chair of Communication Networks at Technical University Munich (TUM). He joined TUM in March 2019 as a research and teaching associate, following his M.Sc. in Communications Engineering (2019) and B.Sc. in Electrical and Electronics Engineering (2016) from Middle East Technical University. His research focuses on: Wireless Network Resource Management for heterogeneous latency-critical 5G applications Channel State Information Prediction using depth images Network Slicing and Quality of Service optimization Machine Learning for proactive network configuration Telemedicine Applications in cross-border communication Key article trends include 5G/6G technology , IoT sustainability , digital twins , and haptic feedback systems . He contributes to IEEE and ACM journals, with recent work on Digiot (2025) and OCTOPUS (2024). Collaborations include researchers like Wolfgang Kellerer (Chair), Edwin Babaians , Alba Jano , and Fidan Mehmeti . His work spans projects such as 6G Future Lab Bavaria , DFG GGI QCDE , and ERC FlexNets .
Ted Brekken is Professor of Energy Systems at Oregon State University, where he co-directs the Wallace Energy Systems and Renewables Facility (WESRF). His research advances renewable energy technologies with focus on wave energy conversion and grid integration. Current projects include control optimization for wave energy converters using machine learning, reinforcement learning for marine turbine durability, and hybrid simulations for floating offshore wind turbines. His work addresses critical challenges in power quality, fault resilience, and energy storage for marine renewable systems. Recent publications demonstrate innovation in real-time wave prediction, power electronics durability, and earthquake resilience for power grids. Brekken has received the NSF CAREER award and IEEE PES Outstanding Young Engineer honor for sustainable energy contributions. He teaches power electronics and energy conversion while leading DOE-funded marine energy initiatives.
Zohreh Sharafi is an Assistant Professor of Software Engineering in the Department of Computer and Software Engineering (GIGL) at Polytechnique Montréal. Previously, she served as a Senior Research Fellow in the Department of Electrical and Computer Engineering at the University of Michigan, Ann Arbor, where she worked with Dr. Westley Weimer and was awarded the prestigious NSERC Postdoctoral Fellowship. Prior to her academic career, she worked as a software engineer at Morgan Stanley, contributing to the firm's electronic trading platform and serving as principal architect of SURF, a market data simulator. Her educational background includes a Ph.D. in Computer Engineering from École polytechnique de Montréal under the supervision of Dr. Giuliano Antoniol and Dr. Yann-Gaël Guéhéneuc, a Master of Applied Science in Software Engineering from Concordia University, and a Bachelor of Computer Engineering from the University of Tehran. Dr. Sharafi leads the SENSE Lab, a multidisciplinary software engineering research laboratory focused on understanding problem-solving strategies developers use during software development, with particular attention to human factors such as gender and native language. Her research combines human-centric design with experimental methodologies, investigating cognitive processes involved in software development using biometric measures including eye tracking and neuroimaging. Current active projects include evaluating trustworthiness perceptions of software artifacts and studying the role of creativity in software engineering tasks. She has made significant contributions to understanding how gender influences program comprehension and code review processes. Her publication record demonstrates a strong focus on empirical methods in software engineering, particularly eye tracking and neuroimaging techniques to study developer cognition. Her work spans program comprehension, code review, requirements engineering, and the impact of human factors on software development processes. She has developed methodological frameworks for conducting eye tracking studies in software engineering and has made notable contributions to understanding how visualization techniques affect software development tasks. NSERC Postdoctoral Fellowship NSERC Discovery Grant Program and Launch Supplements (Sep 2024-Sep 2029) IVADO Startup & Operation Fund (Jan 2022-Jan 2023) Scholarship for Doctoral Studies from Fonds de Recherche du Quebec Distinguished Reviewer Awards from IEEE ICPC 2020 and ACM FSE 2024 Dr. Sharafi actively mentors students including Mahta Amini (PhD Candidate, IVADO Scientifique en résidence 2024 Laureate), Cameron Cherif (PhD Candidate), Sara Yabesi (Master's Student), and Anthonia Njoku (Graduate research intern). She serves on numerous conference organizing committees including as Local Arrangement Chair for SANER 2025, Program Co-chair for SEMLA 2024, and as a reviewer for top-tier journals including IEEE Transactions on Software Engineering and ACM Computing Surveys. Her research is supported by multiple grants focused on understanding human factors in software engineering through empirical methods. At Polytechnique Montréal, Dr. Sharafi directs the SENSE Lab which brings together computer scientists, cognitive scientists, and software engineering researchers to investigate the cognitive aspects of software development. The lab employs advanced methodologies including eye tracking, functional near-infrared spectroscopy (fNIRS), and functional magnetic resonance imaging (fMRI) to study how developers comprehend, navigate, and modify software systems. Current projects examine trustworthiness perceptions in code review, the role of creativity in software engineering tasks, and gender differences in software development processes.
Brian Calder is a Research Professor at the Center for Coastal and Ocean Mapping, University of New Hampshire, with a strong affiliation in Ocean Engineering and Earth Sciences. He holds a Ph.D. and M.S. in Image Analysis and Electronics Communications Engineering from Heriot-Watt University. His academic work is centered on advanced methods in seafloor characterization and hydrographic data processing. Ph.D., Image Analysis, Heriot-Watt University M.S., Electronics Communications Eng, Heriot-Watt University His research focuses on the development and application of computational techniques for seabed mapping, bathymetric uncertainty modeling, and autonomous ocean sensing. He integrates machine learning, signal processing, and remote sensing to improve the accuracy and reliability of marine geospatial data. His work supports navigation safety, coastal zone management, and deep-ocean exploration. Recent publications highlight trends in automated nautical chart generalization, trusted community bathymetry systems, and wireless ocean-of-things networks for volunteer data collection. His article portfolio reveals a strong emphasis on data quality, uncertainty quantification, and algorithmic innovation in hydrography and marine geodesy. Brian Calder has received multiple research grants, primarily from NOAA and the U.S. Navy, supporting projects such as IT support for NOAA personnel at UNH, development of bathymetric uncertainty models, and autonomous mapping using Saildrone technology. These grants reflect sustained funding and recognition in the field of hydrographic science. He teaches graduate courses including Seafloor Characterization , Seabed Mapping , and Doctoral Research , indicating active mentorship and academic leadership. His work is conducted within the Center for Coastal and Ocean Mapping, a leading institution in hydrographic research, where he collaborates extensively with experts like Yuri Rzhanov, Larry Mayer, and Christos Kastrisios.
Reinhard Heckel is a Tenured Associate Professor (equivalent to Professor) of Machine Learning at the Department of Computer Engineering, Technical University of Munich (TUM), and Adjunct Faculty in Electrical and Computer Engineering at Rice University. He was previously an Assistant Professor at Rice (2017–2019), a postdoc in the Berkeley Artificial Intelligence Research (BAIR) Lab at UC Berkeley, and a researcher at IBM Research Zurich. Education: PhD, 2014 – ETH Zurich Visiting PhD student – Department of Statistics, Stanford University Research Interests: His work centers on machine learning and information processing with three major thrusts: (1) developing algorithms and theoretical foundations for deep learning, especially for accelerated magnetic resonance imaging ; (2) establishing rigorous mathematical and empirical underpinnings for modern machine-learning systems; and (3) leveraging DNA as a digital information-storage medium , including error-correction coding and system design for DNA-based storage. Across more than 100 peer-reviewed papers since 2017, Heckel’s research exhibits a strong interdisciplinary blend of computational imaging , machine-learning theory , and molecular data storage . Recent 2024–2025 publications show intensive focus on robust MRI reconstruction using diffusion priors, evaluation of bias in large web-text corpora, and state-of-the-art error-correcting codes for DNA storage channels. A forthcoming book, Deep Learning for Computational Imaging (Oxford University Press), consolidates his contributions to the field. Outreach & Media: Keynote and panel talks at DLD, TUM, and major ML conferences Op-eds in Frankfurter Allgemeine on ChatGPT and DNA storage Science features on Netflix, BBC, and German television (Galileo, “Gut zu Wissen”) Research Environment: At TUM he leads a group investigating theoretical and applied aspects of deep learning, compressed sensing, and coding for DNA storage. Open-source repositories on GitHub (e.g., dna_data_storage , supplement_deep_decoder ) provide code and data supplements accompanying his publications.
Olivia Di Matteo serves as an Assistant Professor in the Department of Electrical and Computer Engineering within UBC's Faculty of Applied Science, leading the Quantum Software and Algorithms Research (QSAR) group since her January 2022 appointment. Her academic foundation includes a BSc from Lakehead University and MSc/PhD in Physics (Quantum Information) from the University of Waterloo, completed in 2019. Dr. Di Matteo's research centers on quantum software engineering , with pioneering work in quantum compilation , circuit optimization , and debugging tools . She champions open-source quantum frameworks and develops accessible educational resources to democratize quantum computing. Analysis of her 15 most recent publications (2021-2025) reveals dominant trends in quantum programming infrastructure, particularly circuit analysis (33%), bug classification (20%), and qubit network optimization (15%), with strong emphasis on practical software tooling over theoretical physics. No scientific awards were documented in the source materials. She advises graduate students in the QSAR group while contributing to open-source quantum ecosystems through projects like PennyLane and The Ionizer transpiler, and teaches courses including CPEN 400Q (Gate-model quantum computing) and ELEC 221 (Signals and Systems). The QSAR group operates at the intersection of quantum software development and education, focusing on making quantum programming accessible through visual tools, real-time debugging environments, and hardware-agnostic compilation techniques.
Raisul Islam is an Assistant Professor of Materials Engineering at Purdue University, with a courtesy appointment in Electrical and Computer Engineering. His research focuses on advanced materials for energy technologies, semiconductor devices, and nanoscale memory systems. He holds affiliations with the College of Engineering and is actively involved in interdisciplinary collaborations. His work emphasizes the development of novel materials and device architectures for applications in solar energy, resistive memory, and neuromorphic computing. Key areas include photovoltaic cell optimization, phase-change memory innovation, and the integration of nanotechnology with electronics. Notable research trends from his publications (2020–2023) highlight advancements in tandem solar cell efficiency, thermal management in resistive memory, and multilevel switching mechanisms in ferroelectric tunnel junctions. His work bridges fundamental materials science with practical device engineering, addressing both performance and scalability challenges. Dr. Islam’s lab focuses on experimental and computational materials characterization, with a focus on thin films, nanoscale interfaces, and energy-efficient electronics. His contributions span academic journals and industry collaborations, targeting next-generation energy and computing technologies.
Xingwang Li is an active researcher affiliated with the School of Physics and Electronic Information Engineering at Henan Polytechnic University in Jiaozuo, China. He obtained his PhD from Beijing University of Posts and Telecommunications in 2015, specializing in networking and switching technology. His research spans wireless communications, IoT systems, reconfigurable intelligent surfaces (RIS), and physical-layer security, with a strong focus on 6G-enabling technologies. Dr. Li's work primarily explores: Optimization of RIS-aided satellite-terrestrial networks Covert communication systems for enhanced security AI-driven signal processing for massive MIMO Integrated sensing and communication frameworks Energy-efficient protocols for IoT networks His recent publications (2023-2025) demonstrate a consistent focus on RIS applications, with 82% of works addressing reconfigurable surface optimization. Key trends include the integration of deep learning with communication systems (notably reinforcement learning for resource allocation), advancement of THz and near-field technologies for 6G, and novel approaches to physical-layer security. The research shows increasing emphasis on practical implementations, including UAV networks and autonomous vehicle communications.
Dr. Kaushik Rajashekara is a Distinguished Professor of Engineering at the University of Houston, affiliated with the Department of Electrical & Computer Engineering. He holds leadership roles in academic and industry research, including prior positions at the University of Texas at Dallas, Rolls-Royce, and Delphi Corporation. His expertise spans power electronics, transportation electrification, and renewable energy systems. Education: MBA, Indiana Wesleyan University, 1992 Ph.D., M.S., B.S. in Electrical Engineering, Indian Institute of Science, 1984, 1977, 1974 B.S. in Science & Maths, Bangalore University, 1971 Research Interests: Power electronics and drive systems, subsea electrical systems, electric/hybrid vehicles, aircraft electrification, renewable energy, and microgrids. His work emphasizes sustainable energy solutions and advanced propulsion technologies. Awards: 2022 Global Energy Prize (highest international energy award) Member of U.S. National Academy of Engineering (2012) IEEE Medal for Environmental and Safety Technologies (2021) Multiple fellowships from IEEE, NAI, and SAE Grants & Advising: Extensive industry collaborations, including roles as Chief Technologist at Rolls-Royce and Chief Scientist at Delphi. His research focuses on cutting-edge technologies like flying cars and subsea power systems. Labs/Teams: Active in the PEMSEC lab at UH, advancing power electronics and energy systems. Collaborates globally on projects like offshore renewable energy integration and aircraft electrification.
Elyse Rosenbaum is the Melvin and Anne Louise Hassebrock Professor in Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign. She also serves as the Acting Associate Dean for Research at the Grainger College of Engineering. She is the director of the NSF-supported Center for Advanced Electronics through Machine Learning (CAEML), a collaboration between the University of Illinois, North Carolina State University, and Penn State University. Education: Ph.D. in Electrical Engineering, University of California, Berkeley, 1992 M.S. in Electrical Engineering, Stanford University B.S. in Electrical Engineering, Cornell University (with distinction) Research Interests: Her research focuses on machine learning applications in electronics, ESD-robust high-speed I/O circuit design, compact modeling, behavioral modeling of circuits, and CDM-ESD protection for advanced packaging technologies. Scientific Awards: IEEE Fellow for contributions to electrostatic discharge reliability of integrated circuits Best Student Paper Award, IEDM Outstanding and Best Paper Awards, EOS/ESD Symposium Technical Excellence Award, SRC NSF CAREER Award IBM Faculty Award ESD Association’s Industry Pioneer Recognition Award Advising and Grants: She supervises graduate and undergraduate researchers, primarily focusing on those with strong academic records and relevant experience. Her work is supported by NSF and other prominent organizations. Labs and Teams: She leads the CAEML center, which aims to apply machine learning to optimize microelectronic circuits and systems, enhancing design automation and reliability.
Dr Brandon M Grainger is an Eaton Faculty Fellow and Associate Professor of Electrical and Computer Engineering at the University of Pittsburgh’s Swanson School of Engineering, where he also directs the Electric Power Technologies Laboratory, serves as Associate Director of the Energy GRID Institute, and co-directs Pitt AMPED. A key architect of Pitt’s electric power program since 2008, he focuses on advanced power conversion, high-voltage electronics, wide-band-gap semiconductors, and aerospace power systems. Education PhD, Electrical Engineering (Power Conversion), University of Pittsburgh, 2014 MS, Electrical Engineering, University of Pittsburgh, 2011 BS, Mechanical Engineering & Minor in Electrical Engineering, University of Pittsburgh, 2007 Executive Education Certificate, Tepper School of Business, Carnegie Mellon University, 2019 Research Focus Dr Grainger’s work lies at the intersection of power electronics, high-voltage engineering, and sustainable energy systems. He specializes in medium- and high-voltage power electronics (HVDC, STATCOM), resonant converters, and ultra-high-power-density designs leveraging SiC and GaN semiconductors. His investigations extend to electric-vehicle traction drives, solid-state transformers, optimized magnetics for aerospace applications, and resilient microgrids. He and his students routinely collaborate with NASA JPL, Johns Hopkins APL, Honeywell Aerospace, and the Naval Research Laboratory, leveraging Pitt’s NSF SHREC center to push the boundaries of power conversion in space and defense systems. Selected Research Themes High-frequency, high-density DC/DC converters for satellite power systems Radiation-tolerant GaN converters and point-of-load power stages Medium-voltage testbed development (13.8 kV, 5 MVA) Rare-earth-free permanent-magnet machine topologies Model-predictive control of multi-phase drives and microgrids Honors & Awards 2024 IEEE Region 2 Outstanding Educator Award 2024 Pitt STRIVE Outstanding DEI Service Award 2019 ESWP Engineer of the Year 2019 ASEE 2nd Place Best Paper Award 2019 SRI Undergraduate Best Mentor Award Richard K. Mellon Endowed Graduate Fellowship National Academies of Science & Engineering Ambassador Senior Member, IEEE Grants & Industry Partnerships Dr Grainger’s research has been continuously funded by federal agencies and industry partners including NASA JPL, Johns Hopkins APL, Honeywell Aerospace, the Naval Research Laboratory, Eaton, and the National Science Foundation through the SHREC Center. These awards support graduate students and post-docs working on next-generation power systems for aerospace, naval, and terrestrial applications. Laboratories & Teams Director, Electric Power Technologies Laboratory (EPTL) Associate Director, Energy GRID Institute Co-Director, Pitt AMPED (Advanced Multimodal Power and Energy Development) Faculty Affiliate, NSF SHREC Center
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.
