Mark R. Greenstreet is a Professor in the Department of Computer Science at the University of British Columbia (UBC). He holds a BSc from Caltech (1981), MA (1988), and PhD (1993) in Computer Science from Princeton University. His primary research focuses on formal verification of analog and mixed-signal (AMS) circuits, VLSI design, and hybrid systems. Notable contributions include the STARI signaling technique, tools like Coho for reachability analysis, and PReach for parallel model checking. He has advised numerous graduate students and collaborators, including Brad Bingham, Chao Yan, and Yan Peng. His work has been recognized with a Best Paper Award at the ASYNC Symposium. Supported by NSERC, Intel, and Oracle, his research bridges theoretical foundations and practical challenges in circuit design and verification. He teaches courses on formal methods, computer architecture, and automata theory at UBC.
Dr. Yiran Chen is the John Cocke Distinguished Professor at Duke University's Department of Electrical and Computer Engineering, leading the NSF AI Institute for Edge Computing (Athena) and the Duke Center for Computational Evolutionary Intelligence (DCEI). A global leader in neuromorphic computing, emerging memory systems, and edge AI, he holds prestigious roles including IEEE Fellow and Editor-in-Chief of IEEE Transactions on Circuits and Systems for AI. His research spans machine learning accelerators, security-hardened hardware, and co-design of EDA tools with LLMs. With over 700 publications and 96 patents, he has been awarded 15 paper awards and 17 nominations, including rare Technical Achievement Awards from IEEE societies. He advises over 60 PhD students and 4 postdocs, many of whom hold academic positions worldwide. His work bridges academia and industry, contributing to startups and venture capital through his board roles. Education: B.S. (Tsinghua, 1998) → M.S. (Tsinghua, 2001) → Ph.D. (Purdue, 2005). Career path: Assistant/Associate Professor at University of Pittsburgh (2010–2014) → Duke since 2014. Awards include the ACM SIGDA Outstanding New Faculty Award (2014), NSF CAREER Award (2013), and the Stansell Family Distinguished Research Award (2022). Research focuses on innovations in: (1) Non-volatile memory architectures for AI acceleration, (2) Hardware-software co-design for edge computing, (3) Security in neuromorphic systems, and (4) Large-scale ML for EDA. His group pioneered ReRAM-based accelerators like ReBNN and MARC, and introduced novel edge AI frameworks like Ecco and Prosperity. These works address scalability, energy efficiency, and real-time performance challenges. Key initiatives include the NSF IUCRC for Alternative Sustainable & Intelligent Computing (ASIC), advancing sustainable computing through novel materials and architectures. His leadership in standard-setting bodies like the IEEE Circuits and Systems Society ensures cutting-edge research translates into industry practices. Grants: Lead PIs for multiple NSF AI Institutes and industry partnerships. Labs: Directs the Athena Institute and DCEI, fostering collaboration between academia and industry. Current projects include quantum computing placement algorithms (QPlacer), federated learning frameworks (FedGPT), and neuro-symbolic architectures.
Dr. Pradip Sharma is an Associate Professor of Cybersecurity & AI at the University of Aberdeen, UK, within the School of Natural and Computing Sciences, Department of Computing Science. He is a globally recognized academic and researcher with expertise in Cybersecurity, Artificial Intelligence, Blockchain, and Edge Computing. His research interests span multiple domains including Cybersecurity, Blockchain, Edge Computing, Software-defined Networking, and IoT Security. Dr. Sharma's work focuses on developing innovative solutions for security challenges in emerging technologies, with particular emphasis on privacy-aware AI systems, secure data sharing frameworks, and intelligent network security mechanisms. His interdisciplinary approach bridges theoretical foundations with practical implementations across healthcare, smart mobility, and consumer electronics domains. Senior Fellowship Advance HE (SFHEA) IEEE Senior Member (SMIEEE) Dr. Sharma actively supervises doctoral researchers and is accepting new PhD students in Computing Science. His funded research portfolio exceeds £1M from sources including EPSRC, Innovate UK, and international agencies. Current projects include 'Secure, Privacy-aware, and Trusted Data Share in Smart Mobility' (EPSRC, £200K), 'ZECURE Data Exchange Platform' (Innovate UK, £236K), and 'Quantum-resistant Cybersecurity' (Royal Embassy of Saudi Arabia, £73K). He also serves as an editor for leading journals and is a regular keynote speaker at international conferences.
Onur Mutlu is a Professor of Computer Science at ETH Zurich, affiliated with the Department of Information Technology and Electrical Engineering. He also holds adjunct professorships at Carnegie Mellon University and Bilkent University. His research focuses on computer architecture, systems security, bioinformatics, and energy-efficient computing. He has pioneered work on memory-centric computing paradigms, RowHammer security vulnerabilities, and bio-inspired computing systems. He teaches courses such as Digital Design & Computer Architecture and supervises the SAFARI research group, which explores cutting-edge topics in memory systems, AI accelerators, and genomics. Recent activities include keynote talks at ISCA, HiPEAC, and IEEE conferences, emphasizing emerging hardware-software co-design principles. Key contributions include foundational work on memory reliability, cross-layer system design, and accelerating genomic data analysis. His research has been showcased in over 200 publications and industry collaborations with tech leaders like Intel, Huawei, and Micron.
Simon Yang is a Professor in the School of Engineering at the University of Guelph, part of the College of Engineering and Physical Sciences. His research focuses on artificial intelligence, robotics, sensors, control systems, and bio-inspired intelligence. He has contributed to advanced robotics applications, including mobile robot navigation, underwater vehicle control, and agricultural automation. Dr. Yang holds editorial roles for journals such as the International Journal of Robotics and Automation and IEEE Transactions on Cybernetics . His work bridges theoretical advancements with practical implementations in areas like sensor networks, machine learning, and multi-agent systems. Recent projects include developing robust control frameworks for autonomous systems, digital twin applications, and bio-inspired neural network algorithms. His research emphasizes real-world challenges in robotics, environmental monitoring, and precision agriculture, with a focus on integrating AI-driven solutions for enhanced decision-making and system reliability. Professional contributions include advisory roles in multiple journals and conference committees, reflecting his leadership in the field.
Dr. Gowri Sankar Ramachandran is a Senior Lecturer in the School of Information Systems at Queensland University of Technology (QUT), specializing in cybersecurity and distributed systems. She holds a PhD from KU Leuven (Belgium) and a postdoctoral position at the University of Southern California (USC). Her research focuses on open-source software security, runtime threat detection, blockchain applications, and IoT vulnerabilities. Notable contributions include the FUSE tool for detecting malicious packages and the discovery of hyperlink hijacking vulnerabilities affecting millions of domains. Research interests span software supply chain security, metadata-based risk analysis, and generative AI for cyber risk modeling. Awards include Best Paper Awards at ACM CBSE (2016), Mobiquitous (2017), and BigMM (2019). Collaborations include projects with CSIRO, the City of Los Angeles, and the University of São Paulo. She teaches courses on cybersecurity, database management, and network security, and actively supervises PhD students in cybersecurity and blockchain domains. Recent publications address blockchain-based data governance, quantum-resilient IoT protocols, and decentralized identity systems. Her work bridges academic research with real-world impact, addressing critical challenges in digital systems security and privacy.
Thorsten Schumm - Academic Overview Thorsten Schumm is an Associate Professor at Vienna University of Technology (TU Wien), leading the Quantum Metrology research group within the Atomic Institute. He is a key member of the Erwin Schrödinger Center for Quantum Science & Technology (ESQ) and the Vienna Center for Quantum Science and Technology (VCQ). His research focuses on developing novel quantum measurement techniques, particularly nuclear clocks using thorium-229 isotopes and matter-wave interferometry with collective many-body states. Key Affiliations & Roles Associate Professor, TU Wien (since 201X) ERC Synergy Grant recipient (2019) for the 'Thorium Nuclear Clock' project Principal Investigator for EU-funded MoSaiQC network (2019) and AQUclock project (2022) Research Interests His work bridges quantum metrology with nuclear physics , precision spectroscopy , and many-body quantum systems . He pioneers the development of nuclear clocks—next-generation timekeeping devices using nuclear transitions instead of electronic transitions for unprecedented accuracy. Recent breakthroughs include direct measurement of the thorium-229 isomer energy and advances in laser-driven nuclear excitation techniques. Notable Achievements 2019 ERC Synergy Grant: Enabled global collaboration toward the world's most precise atomic clock 2022 AQUclock project: TU Wien collaboration with Austrian authorities to build state-of-the-art atomic infrastructure 2019: First experimental determination of thorium-229 isomer energy published in Nature Academic Leadership He has mentored 5 PhD students and hosted 5 postdoctoral researchers. His group actively participates in the Vienna Graduate Program on Complex Quantum Systems (COQUS), training the next generation of quantum scientists.
Emma Tegling is a Senior Lecturer (Associate Professor) at the Department of Automatic Control, Faculty of Engineering (LTH), Lund University, Sweden. She joined the department in January 2021 and holds a prestigious WASP (Wallenberg AI, Autonomous Systems and Software Program) professorship. Her research focuses on the analysis and control of large-scale networked systems, with applications in distributed electric power networks and socio-epidemiological networks. She is actively involved in multiple research projects, supervises several PhD students, and contributes to major academic events in control theory. Education: Ph.D. in Electrical Engineering, KTH Royal Institute of Technology (2019) M.Sc. in Engineering Physics, KTH Royal Institute of Technology (2013) B.Sc. in Engineering Physics, KTH Royal Institute of Technology (2011) Emma Tegling's research centers on the fundamental limitations of distributed control, particularly in large-scale and non-normal network systems. Her work addresses critical challenges in vehicular formations, power grids, and social networks. She develops scalable control designs, consensus protocols, and optimal control strategies for complex networked environments. Her recent publications highlight breakthroughs in string stability, transient performance, and distributed optimization. The trend in her articles shows a strong focus on mathematical control theory, network dynamics, and real-world applications in socio-technical systems. Scientific Awards: WASP professorship (Wallenberg AI, Autonomous Systems and Software Program) Emma Tegling leads and co-leads several significant research grants, including WASP NEST: Learning in Networks and Dynamics of Complex Socio-Technological Network Systems. She actively supervises PhD students such as Jonas Hansson and David Ohlin, whose work has led to novel consensus protocols and optimal control formulations. Her academic leadership extends to organizing the European Control Conference and co-organizing interdisciplinary workshops on power and democracy in modern societies. She is also involved in public engagement and academic service through supervision and project coordination. Emma Tegling is a key member of the Department of Automatic Control at Lund University, contributing to research teams focused on networked systems, control theory, and AI integration. She collaborates extensively within ELLIIT (the Linköping-Lund initiative on IT and mobile communication) and participates in cross-disciplinary labs working on AI, digitalization, and natural/artificial cognition. Her work is aligned with UN Sustainable Development Goals related to sustainable energy and resilient infrastructure.
Dr. Huadong Mo is a Senior Lecturer at the School of Systems and Computing, University of New South Wales (UNSW) Canberra, Australia. He holds a B.E. degree in automation from the University of Science and Technology of China (2012) and a Ph.D. in systems engineering and engineering management from the City University of Hong Kong (2016). Prior to his current position, he was a research associate at ETH Zurich's Reliability and Risk Engineering Lab (2016-2019) and a Lecturer at UNSW Canberra (2019-2021). Dr. Mo's educational background includes a strong foundation in systems engineering with international experience across China, Switzerland, and Australia. His career trajectory demonstrates a progression from academic research to faculty positions with increasing responsibilities in teaching and research leadership. His research focuses on enhancing the resilience, performance, and security of complex systems using learning-based algorithms, primarily in power and energy systems, cyber-physical systems, and manufacturing systems. He applies data analytics to understand system evolution under uncertainties, with particular emphasis on prognostics and health management, sustainable transportation, robust operation of power systems under extreme events, and reinforcement learning-based asset management. His work bridges theoretical advances with practical applications in critical infrastructure. Analysis of Dr. Mo's recent publications reveals a strong focus on energy systems, particularly in the integration of machine learning with power grid management, battery storage systems, and resilience against cyber threats. His research shows a clear trajectory toward increasingly complex system integration, with growing emphasis on multi-vector energy communities, cross-domain prediction, and uncertainty-aware energy management. The interdisciplinary nature of his work spans electrical engineering, computer science, and operations research. 2024 IEEE SMC Early Career Award 2023 Visiting Research Fellowship (Jean d'Alembert Pour Fellowship) Gold Medal in 2024 China International College Student Innovation Competition (as supervisor) Arc PGC Supervisor Award (2021) IEEE SMC Outstanding Chapter Award (2021) Alumni Achievement Award from City University of Hong Kong (2019) Dr. Mo actively supervises numerous HDR students working on cutting-edge research topics including battery health monitoring, quantum control, reinforcement learning for power systems, and explainable AI for energy management. He leads multiple significant research grants totaling over 3 million AUD, including projects funded by ARC, Energy Innovation Fund, and international collaborations with institutions like ETH Zurich, Cambridge, and Tsinghua University. His research group maintains strong international connections, facilitating student exchanges and collaborative research. As Postgraduate Course Coordinator of Systems Engineering and Chair of IEEE SMC ACT Chapter, Dr. Mo plays a significant role in academic leadership and professional community building. His research team collaborates with industry partners on practical implementations of their theoretical work, particularly in the energy sector.
Madison Lore is an incoming Assistant Professor in the Department of City and Regional Planning at Cornell University's College of Architecture, Art, and Planning, beginning her tenure in January 2026. Her interdisciplinary research integrates urban planning, data science, and sustainability, focusing on how large-scale data and information environments shape public behaviors and perceptions around sustainable transitions in housing, transportation, and energy systems. She holds a Ph.D. from the School of Community and Regional Planning at the University of British Columbia, a Master's in Applied Mathematics, and a dual Bachelor's in Mathematics and Physics from Rensselaer Polytechnic Institute. Her academic journey reflects a strong technical foundation applied to pressing urban challenges. Madison’s research interests span urban data science, machine learning, infrastructure and land use planning, social policy, and sustainable transportation. She investigates how algorithmic and data-driven methods can be used responsibly to uncover social norms, institutional influences, and individual support for sustainable policies, particularly in contexts of information overload. Her recent publications demonstrate a strong trajectory in applying hybrid deep learning and natural language processing to urban text data, evaluating equity in public mobility, and modeling transportation preferences through digital footprints. These works reflect a consistent theme: leveraging data analytics to promote equitable and sustainable urban futures. Vanier Canada Graduate Scholarship (2023–2026) Bombardier Sustainable Transportation Fellowship (2022) The Bill and Nancy Siegmann Applied Mathematical Modeling Prize (2018) Leonhard Euler Award for Excellence in Mathematical Modeling (2016) Climate Social Science Network Grant on Big Oil’s Climate Disinformation (2024) Madison has presented her work at major conferences including the Association of Collegiate Schools of Planning, the International Conference on Travel Behavior Research, and the American Planning Association National Conference. While no formal advisees are listed, her role as an incoming assistant professor suggests future mentorship of graduate students in urban planning and data analytics. She is affiliated with the PLACE Lab and brings expertise from prior work in nuclear physics and applied mathematics into her current urban sustainability research.
Professor Steve Simpson is a leading marine biologist and fish ecologist at the University of Exeter's Biosciences department. He serves as Professor of Marine Biology & Global Change and leads a dynamic research group focused on understanding marine ecosystems, particularly in the context of climate change and human impacts. His work has been prominently featured in Blue Planet II and he actively engages with industry, policy makers, and the public through media appearances and outreach activities. Education PhD, University of York, UK (2000-2004) MRes Marine & Coastal Ecology & Environmental Management, University of York, UK (1998-1999) BSc Marine Biology (Hons), University of Liverpool, UK (1995-1998) Professor Simpson's research centers on the behavior of coral reef fishes, bioacoustics, and the effects of climate change on marine ecosystems. His approach uniquely combines fieldwork in remote environments with laboratory experiments, data-mining, and computer modeling. He has pioneered new methods for listening to ocean soundscapes and understanding fish communication, revealing how anthropogenic noise disrupts natural behaviors and ecological processes. His work on climate change impacts examines shifting fish distributions and their implications for fisheries management and conservation. Analysis of Simpson's recent publications reveals two dominant research themes: the impacts of anthropogenic noise on marine life and climate change effects on fisheries. His work demonstrates how underwater noise from boats and industrial activities impairs fish hearing, disrupts predator-prey relationships, and affects reproductive success. Simultaneously, his climate change research tracks how warming seas are altering fish distributions, creating 'mackerel wars' and requiring fisheries adaptation. These research strands converge in his innovative work on developing solutions like bubble curtains to mitigate noise impacts. Scientific Awards FSBI Medal (2016) NERC Knowledge Exchange Fellowship (2011-2014) NERC Postdoctoral Research Fellowship (2004-2007) Royal Society International Fellow (2007-2008) EPHE Postdoctoral Fellow (2007-2008) Professor Simpson leads a thriving research group of approximately 10 postdocs, PhD, and Masters students. His grant portfolio includes major NERC funding for projects on marine noise impacts and climate change effects on fisheries. He has developed strong industry partnerships through a Knowledge Exchange Fellowship, working with Cefas, the Met Office, Sustainable Marine Energy Ltd, and HR Wallingford Ltd. His research has directly informed policy through contributions to Marine Climate Change Impacts Partnership reports and presentations to European Parliament. Simpson has also created innovative knowledge exchange initiatives including the 'Vision of Sustainable Fisheries in 2050' thinktank. Simpson has developed specialized research infrastructure including a mobile lab with Ecocean in Montpellier for assessing marine noise impacts, and has conducted large-scale acoustic experiments in dry docks. His work on underwater acoustics was prominently featured in Blue Planet II, and he maintains active engagement with media through TEDx talks, BBC appearances, and public lectures to schools and community groups. He serves on the International Quiet Ocean Experiment Science Committee, helping shape global research on ocean noise.
Vladimir Zhdankin is an Assistant Professor of Physics at the University of Wisconsin-Madison , where he leads the Zhdankin Group. He received his Ph.D. and B.S. in Physics from UW-Madison in 2015 and 2011, respectively. His career includes postdoctoral appointments as a NASA Einstein Postdoctoral Fellow (2018-2021) and Flatiron Research Fellow (2021-2023). Research Interests : Theoretical and computational plasma physics Relativistic plasma turbulence and instabilities Nonthermal particle acceleration and radiative processes Nonequilibrium statistical mechanics of collisionless plasmas Coherent structures in astrophysical systems Scientific Awards : NASA Einstein Postdoctoral Fellowship Flatiron Research Fellowship Advising & Collaborations : Current group members: Braden Buck, Miguel Castelan Tanner, Petr Ugarov, Cristian Vega (joint with Prof. Rogerio Jorge), Louis Henderson Collaborators: Dmitri Uzdensky, Matthew Kunz, Alexander Philippov, Stanislav Boldyrev
Professor Francesco Poletti is a Professorial Fellow-Research at the University of Southampton's Optoelectronics Research Centre (ORC), specializing in advanced optical fiber technologies. He leads multiple high-impact research projects funded by prestigious organizations including EPSRC, the European Union, Royal Society, and industry partners like Microsoft Corporation. His research focuses on: Hollow Core Optical Fibres design and fabrication Optical Communications for high capacity and low latency systems Novel active and passive optical fibres Applications of hollow core optical fibres Optical fibre guidance mechanisms Professor Poletti's recent publications demonstrate leadership in hollow core fiber technology, with significant advancements in manufacturing techniques, optical performance, and practical applications. His 2024-2025 publications show particular emphasis on improving fiber compatibility with existing infrastructure, developing mid-infrared capabilities, enhancing laser integration, and creating novel sensing applications. His scientific recognition includes a prestigious Royal Society Fellowship. Current major projects include FASTNET (revolutionary hollow core low-latency fibres), research contracts with Microsoft, and EU-funded initiatives like WISDOM and EMPRESS. Professor Poletti actively supervises PhD students and accepts new applications, currently mentoring Rene Andres Reynolds Hamel, Mahmudur Rahman, Amalie Gjelsvik, and Chiang Ping Saw. His research group is a core component of the Hollow Core Fibre and Fibres and Communications research teams at the ORC.
Dr Ian Davidson is a Senior Research Fellow at the Optoelectronics Research Centre (ORC), University of Southampton, Faculty of Engineering and Physical Sciences. He is a key researcher in the Hollow-Core Fibre group, focusing on advanced optical fibre fabrication, characterization, and application in photonic systems. His research interests include: Hollow-Core Fibre Technology Micro-Structured Optical Fibres Photonics and Quantum Optics Semiconductor Deposition and Integrated Optics Optical Fibre Sensing and Raman Spectroscopy Fibre-Based Gas Dynamics and Pressure Sensing Dr Davidson's recent publications (2022–2025) demonstrate a strong trend in developing next-generation hollow-core fibres with enhanced stability, reduced loss, and novel functionalities for applications in sensing, spectroscopy, and laser delivery. His work spans high-impact journals such as Science Advances , Optics Express , ACS Photonics , and IEEE Journal of Selected Topics in Quantum Electronics , reflecting his leadership in the field of optical fibre innovation. He currently supervises PhD students Elizaveta Elistratova and Abhishek Vijayakumar, contributing to training the next generation of photonics researchers. No scientific awards or prizes are currently listed in the provided text. Dr Davidson collaborates extensively within the ORC and with external partners on projects involving fibre fabrication, gas dynamics, and photonic device integration. He has no listed teaching responsibilities, but his research supervision plays a central role in academic mentorship. He is affiliated with advanced research infrastructure at the Optoelectronics Research Centre, a world-leading institute in photonics.
Jason Ostanek is an Assistant Professor at Purdue University's School of Engineering Technology and Environmental and Ecological Engineering. He directs the Applied Thermofluids Laboratory and Powertrain Technology Laboratory, focusing on battery safety and thermal management systems. Ph.D. in Mechanical Engineering from Penn State M.S. in Mechanical Engineering from Penn State B.S. in Mechanical Engineering from Virginia Tech His research explores energy storage systems, thermal runaway phenomena, heat transfer mechanisms in Li-ion batteries, fluid dynamics, and internal combustion engine thermal management. He has developed analytical models for battery degradation, thermal abuse simulations, and innovative cooling strategies for large-scale energy systems. Key publication trends show expertise in: Li-ion battery thermal runaway modeling Heat transfer in confined geometries Thermal management for energy storage systems Renewable energy forecasting Computational fluid dynamics applications Scientific awards include: 2020 Purdue Teaching Academy's Award for Exceptional Teaching and Instructional Support during the COVID-19 Pandemic 2020 SOET Outstanding Faculty in Engagement 2019 SOET Outstanding Faculty in Discovery 2015 NAVSEA Commander’s Award for Innovation 2013 ASME IGTI Young Engineer Travel Award 2007 DOD SMART Fellowship Recipient As director of Purdue's Applied Thermofluids Laboratory, he leads research on battery safety mechanisms, combustion dynamics, and thermal systems optimization. His work spans fundamental and applied research with industrial collaborators.
