Prof. Gabriela Hug is a Full Professor at ETH Zurich's Department of Information Technology and Electrical Engineering, serving as Deputy Head of the Department and Deputy Head of the Power Systems and High Voltage Lab. She leads the Energy Science Center (ESC) and holds adjunct roles at Carnegie Mellon University. Her research focuses on modeling, control, and optimization of electric power systems for sustainable energy transitions. Education: PhD in Information Technology and Electrical Engineering, ETH Zurich (2004–2008) MSc in Information Technology and Electrical Engineering, ETH Zurich (1999–2004) Research Interests: Her work addresses challenges in smart grid integration, renewable energy systems, and advanced control strategies. Key areas include vehicle-to-grid technologies, distribution network optimization, and energy storage system planning. She emphasizes data-driven approaches and collaborative frameworks for grid resilience and flexibility. Key Achievements: Recipient of the 2019 ALEA Award (ETH Zurich) NSF Career Award (2013) IEEE Outstanding Young Engineer Award (2013) Leadership & Roles: Co-Director, NCCR Automation (Swiss National Centre of Competence in Research) Board Chair, Energy Science Center (ESC) Adjunct Faculty, Carnegie Mellon University Labs & Teams: Power Systems Laboratory (ETH Zurich) Energy Science Center (multi-disciplinary research hub)
Ana Klimovic is an Assistant Professor at the Department of Computer Science, ETH Zürich, and Deputy Head of the Institute for Computing Platforms. She leads the Efficient Architectures and Systems Lab (EASL) and focuses on optimizing cloud computing performance and resource efficiency. Education: Ph.D. in Electrical Engineering (Stanford University), M.S. in Electrical Engineering (Stanford), B.A.Sc. in Engineering Science (University of Toronto) Previous Roles: Research Scientist at Google Brain Her research spans cloud computing, operating systems, distributed systems, and their intersection with machine learning. Key areas include cloud-native programming models, elastic storage, GPU sharing, and data pipeline optimization. The 2025-2024 articles highlight trends in serverless computing, large language model (LLM) serving, GPU optimization, and data-centric ML systems. Themes include elasticity, resource multiplexing, heterogeneous computing, and infrastructure for AI/ML workloads. Scientific Awards: Microsoft Research PhD Fellowship, Stanford Graduate Fellowship She has led research projects on ephemeral storage, distributed training automation, and cost-efficient ML preprocessing, with grants from Microsoft Research and Stanford.
Prof. Dr. Björn Corzilius is a University Professor (W2) of Physical Chemistry at the University of Rostock, Germany, leading the Corzilius group. His research focuses on solid-state NMR spectroscopy, dynamic nuclear polarization (DNP), and applications in biomolecules and materials. He holds affiliations with the Leibniz Institute for Catalysis (LIKAT) and serves on multiple academic boards, including the transregional Collaborative Research Center TRR 386 and the journal Magnetic Resonance . Education: 1999: Studies of Chemistry, TU Darmstadt 2005: Diploma in Physical Chemistry (TU Darmstadt) 2008: Ph.D. in Physical Chemistry (TU Darmstadt) Research Interests: Solid-state NMR, DNP for sensitivity enhancement, paramagnetic metal ions, biomolecular dynamics, and method development. His work bridges theoretical and experimental approaches to advance structural and functional studies of complex systems like proteins, nucleic acids, and catalytic materials. Recent Article Trends: Focus on DNP applications in biomolecular interfaces, novel polarizing agents (e.g., Gd(III) complexes), and methodological advancements like serial polarization transfer and electron-decoupled DNP. Contributions span inorganic chemistry, materials science, and biophysical systems. Awards: Emmy Noether Fellowship (2012) Felix Bloch Lecture (2016) Regitze M. Vold Memorial Prize (2017) Best Ph.D. Supervision (2018) Grants & Labs: Principal Investigator of the Emmy Noether Group (2013–2019), now leading the DNP research team at the University of Rostock. Collaborates closely with LIKAT on catalytic and materials projects. His group actively develops open-access publishing platforms like Magnetic Resonance and hosts international conferences. Labs/Teams: The Corzilius group at the Institute of Chemistry (Rostock) specializes in NMR method development and applications. Associated with LIKAT for interdisciplinary catalysis research.
Dr. K. Max Zhang is a Professor in the Sibley School of Mechanical and Aerospace Engineering at Cornell University. He is the director of the Energy and the Environment Research Laboratory (EERL) and a fellow at the Atkinson Center for a Sustainable Future. His research is deeply interdisciplinary, focusing on sustainable energy systems, air quality, and environmental justice, with significant impacts on policy and community development in New York and beyond. Ph.D., Mechanical Engineering, University of California-Davis, 2004 B.S., Thermal Engineering, Tianjin University, 1998 B.A., English Language, Tianjin University, 1998 Dr. Zhang’s research centers on the integration of energy and environmental systems. He investigates air pollution dynamics using advanced numerical models like CTAG, with applications in near-source pollution, indoor air quality, and environmental justice. His work on renewable energy systems includes designing sustainable solar farms and managing distributed energy resources such as heat pumps to enhance grid flexibility. He also leads a pioneering initiative to create the first statewide public IoT network in the U.S., enabling hyperlocal weather forecasting and microclimate monitoring. His recent publications reflect a strong trend toward agrivoltaics, peer-to-peer energy markets, and IoT-based environmental monitoring. These works demonstrate a consistent focus on data-driven modeling, community-scale energy solutions, and the integration of social considerations into technical systems. The keywords across his articles highlight expertise in sustainability, machine learning, air quality, and energy transition. Cornell Town-Gown Achievement Award (2022) Engaged Scholar Prize, Cornell University (2017) People's Choice Sign of Sustainability Award, Sustainable Tompkins (2016) Scientific and Technological Achievement Award, Environmental Protection Agency (2015) Fellow of the American Society of Mechanical Engineers Dr. Zhang is actively involved in mentoring students and securing research grants from agencies such as the National Science Foundation (NSF) and the New York State Energy Research and Development Authority (NYSERDA). His projects often involve interdisciplinary collaboration across eight Cornell colleges and 16 academic departments. He has led initiatives such as the Cornell Atkinson Academic Venture Fund projects and the development of a county-level energy roadmap for Tompkins County. He also teaches courses in engineering thermodynamics, future energy systems, and air quality, emphasizing experiential and community-based learning. Dr. Zhang leads the Energy and the Environment Research Laboratory (EERL) and collaborates with the Atkinson Center for a Sustainable Future. His lab functions as a hub for innovation in sustainable communities, combining advanced modeling with real-world applications. Through partnerships with community organizations, government agencies, and industry, his team develops science-driven solutions to urban and rural sustainability challenges.
Dr. Gloria Milena Monsalve Bravo is an Advanced Queensland Industry Research Fellow and lecturer at The University of Queensland's School of Chemical Engineering, where she develops novel multiscale simulation techniques combining molecular simulations with macroscopic physics-based modeling to solve complex energy and environmental problems. Her interdisciplinary work bridges applied mathematics and engineering to improve understanding of phenomena in complex systems across chemical, biomedical, and ecological applications. Her research focuses on: Multiscale simulation techniques for complex systems Molecular simulations coupled with macroscopic modeling Gas permeation and separation in mixed-matrix membranes Uncertainty and sensitivity analysis in mathematical models Applied mathematics for engineering problems Dr. Monsalve Bravo's publication record demonstrates a strong trajectory in membrane technology and computational modeling. Her recent work has advanced understanding of gas transport in novel membrane materials, particularly mixed-matrix membranes, with applications in carbon capture and hydrogen storage. She has made significant contributions to theoretical frameworks for modeling permeation in finite-sized composite systems and developed Bayesian approaches for analyzing parameter uncertainty in sorption predictions. Her research bridges fundamental science with practical applications in energy and environmental engineering. Her scientific contributions have been recognized through research funding including: ARC Research Hub for Value-Added Processing of Underutilised Carbon Wastes (2024-2029) Tailor-made composite membranes for greenhouse gas capture (2023-2026) through Advance Queensland Industry Research Fellowships Dr. Monsalve Bravo actively mentors PhD students on cutting-edge projects related to membrane technology, catalyst development, and waste conversion. She collaborates extensively across disciplines, as evidenced by her diverse publication record spanning chemical engineering, materials science, and environmental applications.
Malcolm McCulloch serves as Professor of Energy Systems and Group Leader of the Energy and Power Group within the Department of Engineering Science at the University of Oxford. He also holds the position of Co-Director for the Oxford Martin Programme on Integrating Renewable Energy and maintains affiliation with Christ Church college. His research spans four primary domains: domestic energy systems, electric vehicle technology, renewable generation, and energy solutions for developing regions. McCulloch's research focuses on practical energy transition challenges. His domestic energy work develops user-centric demand side management technologies and behavior change interventions, leading to the spin-out Intelligent Sustainable Energy (now Navetas Energy Management). In transportation, he pioneered the Morgan LifeCar hydrogen sports car project, resulting in high-efficiency motors and the Oxford Yasa Motors spin-out. His renewable generation research includes lightweight tidal turbines through Kepler Energy, while his Energy for Development work creates nano/micro grid solutions for distributed electrification. Analysis of his recent publications reveals a strong emphasis on integrating variable renewables through innovative market mechanisms, grid flexibility solutions, and electric vehicle integration. His work consistently addresses the technical and economic barriers to decarbonization, with increasing focus on peer-to-peer energy trading, thermal storage, and climate-resilient cooling solutions since 2020. McCulloch previously served as Co-Director of the Institute for Carbon and Energy Reduction in Transport (2008-2013) under the Oxford Martin School. His leadership extends to creating the Integrated Transport Network for Oxford and developing practical applications through multiple successful spin-out companies that bridge academic research and commercial implementation.
Nils Fleischhacker is an Assistant Professor for Cryptography at Ruhr University Bochum, where he leads the Theoretical Cryptography group within the Faculty of Computer Science. His research focuses on foundational aspects of cryptography with particular emphasis on zero-knowledge proofs, digital signatures, and secure computation. Prior to joining Ruhr University, he held postdoctoral positions at Johns Hopkins University and Carnegie Mellon University. Dr. Fleischhacker received his PhD in Computer Science from Saarland University in February 2017, advised by Dominique Schröder. During his doctoral studies, he was a research intern at Microsoft Research with Chris Brzuska and a research visitor at the University of Maryland, College Park with Jonathan Katz and Dana Dachman-Soled. His research spans theoretical cryptography with significant contributions to zero-knowledge proofs, multi-signature schemes, property-preserving hash functions, and security proofs for cryptographic primitives. Fleischhacker's work often addresses fundamental questions about the limits and possibilities of cryptographic constructions, with particular attention to black-box separations and lower bounds. His recent publications demonstrate a strong focus on lattice-based cryptography and post-quantum secure protocols. Fleischhacker's publications over the past five years reveal a consistent research trajectory focused on improving the efficiency and security of cryptographic primitives, with particular emphasis on signature schemes, zero-knowledge protocols, and secure computation frameworks. His work frequently appears in top-tier cryptography venues including CRYPTO, EUROCRYPT, and CCS. Dr. Fleischhacker actively mentors PhD students, with numerous successful graduations spanning from 2010 to 2024. His former PhD students include Önder Askin (2024), Floyd Zweydinger (2023), and Lars Schlieper (2022), among others. His research is supported through various academic channels and collaborations. He is affiliated with several prominent research organizations including the Horst Görtz Institute (HGI) for Information Security, the DFG Excellence Cluster CASA, the EU Marie Curie Network QSI, and the International Association for Cryptologic Research (IACR). These affiliations provide a strong institutional framework for his theoretical cryptography research.
Prof. Alois Christian Knoll is a full professor at the Technical University of Munich (TUM) in the School of Computation, Information and Technology. His academic career includes roles at Bielefeld University and leadership in major EU initiatives like the Human Brain Project and ECHORD++. He specializes in robotics, AI, and autonomous systems, with a focus on medical robotics, sensor-based systems, and neuromorphic engineering. Knoll has supervised over 100 doctoral theses and authored/co-authored over 1,000 publications. Education: Diploma in Electrical Engineering (University of Stuttgart, 1985); PhD in Computer Science (Technical University of Berlin, 1988); Habilitation (TU Berlin, 1993). He has been at TUM since 2001, leading the Robotics, AI, and Real-Time Systems department. Research interests span autonomous systems, neuro-IT integration, and traffic simulation. Key projects include fortiss (Bavarian State Institute for Computer Science) and TUM-CREATE (Singapore collaboration). Awards include IEEE Fellow, University of Tokyo Fellow, and the Carl-Ramsauer-Prize (1990). Current roles include editorships in robotics journals, leadership in EU flagship projects, and teaching across multiple programs. His work bridges computer science, neuroscience, and engineering, with applications in healthcare, automotive systems, and urban mobility.
Giuseppe Ateniese is a Professor and Eminent Scholar in Cybersecurity at George Mason University, affiliated with the Department of Computer Science and Cyber Security Engineering. Formerly, he held the Farber Endowed Chair and chaired the Department of Computer Science at Stevens Institute of Technology. His research focuses on cloud security, applied cryptography, blockchain technology, and AI-driven cybersecurity solutions. He has received prestigious awards including the NSF CAREER Award and Google/IBM Faculty Awards. AIFurther, he teaches courses on blockchains, cryptography fundamentals, and cryptofinance. His work includes pioneering contributions to rewritable blockchains, password cracking via AI (e.g., PassGAN), and secure decentralized systems. Education: PhD in Computer Science, University of Genoa (2000) Laurea (M.Sc.), University of Salerno (1995) Master of Engineering (Honoris Causa), Stevens Institute of Technology (2020) Research Interests: Ateniese’s work bridges theoretical and applied cryptography, with emphasis on blockchain scalability, privacy-preserving machine learning, and secure data storage. He has developed foundational techniques like proxy re-cryptography and accountable storage systems. His recent efforts address AI’s dual role as both a cybersecurity tool and threat vector, including AI-based password cracking and defense strategies against LLM-driven attacks. Awards: NSF CAREER Award (for privacy/security research) Google Faculty Research Award (cloud security) IBM Faculty Award IEEE CISTC Technical Recognition Award Teaching & Labs: He teaches advanced courses on blockchains (CS695), cryptography fundamentals (CYSE/ECE476), and introductory cryptography (CS487/587). His research team focuses on cryptographic protocols, decentralized systems, and AI-security intersections. Collaborations include projects with Accenture on editable blockchain prototypes and NSF-funded work on password security.
Mika Järvinen serves as Associate Professor in the Department of Energy and Mechanical Engineering at Aalto University, leveraging fundamental sciences—physics, thermodynamics, chemistry, and numerical modeling—to address cross-sector energy challenges. His research spans sustainable bioenergy and inter-linked circular economy systems integrating energy, materials, and environmental considerations across biomass, pulp/paper, metallurgy, and waste-to-energy industries. His expertise centers on sustainable bioenergy and circular economy frameworks, utilizing numerical modeling to optimize combustion engineering and metallurgical processes. By maintaining diverse industrial engagement, he ensures research continuity during economic fluctuations while advancing black liquor spraying technologies and energy-material-environment synergies. This approach enables flexible, physics-based solutions for complex industrial energy conversion problems. Professor Järvinen's 2025 publications reveal a cohesive focus on renewable energy systems operating within planetary boundaries, spanning carbon capture (calcium looping), low-temperature heat engines, and comprehensive textbook development. His work integrates solar, wind, bioenergy, and storage technologies into holistic frameworks that balance technical innovation with ecological constraints, emphasizing system-level sustainability over isolated component optimization. His scientific recognition includes: Best Dissertation Award (2002) from Helsinki University of Technology's Department of Machine Technology for research on black liquor droplet conversion Resonate Award (2015) from Caltech University's Resnick Institute As lead of the Energy Conversion and Systems research group, he directs projects bridging fundamental modeling with industrial applications while developing educational resources for next-generation energy engineers. His laboratory work emphasizes experimental validation of numerical models across combustion, metallurgical, and biomass conversion processes.
Steven I-Jy Chien serves as Professor and Director of the Transportation Program within the Department of Civil and Environmental Engineering at the New Jersey Institute of Technology (NJIT). His career spans academia, government, and industry with significant contributions to transportation engineering research and practice. His educational credentials include: Ph.D. in Civil and Environmental Engineering from University of Maryland-College Park (1995) M.S. in Civil and Environmental Engineering from University of Maryland-College Park (1991) B.S. in Civil Engineering from Tamkang University (1983) Professor Chien's research focuses on transportation system resilience, sustainable transit operations, and advanced traffic modeling. His work addresses critical challenges in urban rail networks, demand-responsive transit services, and energy-efficient transportation systems. He employs sophisticated computational methods including genetic algorithms, machine learning, and Bayesian approaches to solve complex transportation problems involving network vulnerability, passenger behavior, and infrastructure optimization under uncertainty. Analysis of his recent publications reveals strong emphasis on transportation resilience against cascading failures, sustainable operations for electric transit systems, and pandemic-responsive aviation scheduling. His research spans diverse geographic contexts including major Chinese metropolitan areas and U.S. transportation networks, demonstrating global applicability of his methodologies. His professional recognition includes: 2024 Keynote Speaker at Union-Tech Lecture, National Taiwan Ocean University 2022 Keynote Speaker at International Conference of Chinese Institute of Transportation 2022 Best Poster Award from New Jersey Department of Transportation Professor Chien has secured research funding from federal agencies including the Federal Highway Administration (FHWA) where he contributed to CORSIM traffic simulation software development. His industry experience with China Engineering Consultants Inc. and Information Dynamic Inc. informs his practical approach to transportation challenges. As Transportation Program Director, he oversees curriculum development and industry partnerships that prepare students for transportation sector careers. He maintains active collaboration with transportation agencies globally, particularly through his leadership in the Transportation Program at NJIT which serves as a hub for innovation in urban mobility solutions.
Vijay Raghunathan is a Professor in the Department of Electrical and Computer Engineering at Purdue University's College of Engineering. His work focuses on hardware and software architectures for embedded systems, wireless sensors for IoT, and wearable/implantable electronics with emphasis on low power design, energy harvesting, emerging memory technologies, and secure system design. Academic Rank: Professor Department: Electrical and Computer Engineering University: Purdue University Research Focus: Energy-efficient embedded systems, IoT, wearable devices His research explores low power design at both board-level and system-on-chip scales, micro-scale energy harvesting , and reliable/secure system design for medical devices. Recent work focuses on Processing-in-Sensor/Memory for battery-free AIoT devices, state space models for neural processing units, and security coprocessor integration in autonomous systems. Analysis of his publications reveals trends in energy-efficient neural network acceleration , approximate computing for edge inference , and compute-in-memory architectures . Key subfields include collaborative edge-cloud partitioning , sparse DNN accelerators , and security frameworks for medical devices. Vijay's work also addresses energy-accuracy tradeoffs in multimodal cognitive systems and intermittent computing using non-volatile memory technologies. His contributions span from microcontroller energy management to security protocols for implantable electronics.
Jennifer Wilcox is the Presidential Distinguished Professor of Chemical Engineering and Energy Policy at the University of Pennsylvania's School of Engineering and Applied Science. She holds the James H. Manning Chair and directs the Clean Energy Conversions Lab, which focuses on carbon management strategies to mitigate climate change. Wilcox also served as Principal Deputy Assistant Secretary of Fossil Energy and Carbon Management at the U.S. Department of Energy from January 2021. Her research spans carbon capture, utilization, and storage (CCUS), direct air capture (DAC), mineral carbonization, life cycle assessment, and techno-economic analysis of carbon management technologies. Wilcox's work examines both mitigation and adaptation strategies to minimize negative climate impacts associated with society's dependence on fossil fuels. She takes a multi-perspective approach that includes experimental work, materials characterization, geo-spatial analyses, systems modeling, and techno-economic analysis while considering environmental and social contexts. Wilcox's research has been featured in major publications including the first textbook on Carbon Capture and Storage, the California Getting to Neutral report, the CDR primer, Greenhouse Gas Removal Technologies, the State of CDR Volume 2, and the Roads to Removal report. Her work has received recognition including the DOE Secretary's Achievement Award for contributions to the Getting to Neutral report. Secretary's Achievement Award for work on the Getting to Neutral Report Principal Deputy Assistant Secretary of Fossil Energy and Carbon Management (2021) Author of the first textbook on Carbon Capture and Storage Lead contributor to the California Getting to Neutral report Co-author of the CDR primer with nearly 40 subject matter experts Wilcox mentors several PhD candidates and research associates including Maxwell Pisciotta, Shelvey Swett, Hélène Pilorgé, Shrey Patel, Aline Uwase, Katherine Vaz Gomes, and Abby Lunstrum. Her lab examines various carbon management strategies from technology development to deployment optimization, with a focus on maximizing climate change mitigation while minimizing adverse social and environmental impacts. The Clean Energy Conversions Lab tracks public funding for carbon management projects across the United States and analyzes lessons from recent legislation like the Bipartisan Infrastructure Law and Inflation Reduction Act to identify opportunities for carbon management.
Jian Huang is an Associate Professor of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign (UIUC), holding a 100% appointment since August 2024. He is also an affiliated Associate Professor in Computer Science and serves as the Y. T. Lo Faculty Fellow in ECE. Huang leads the Systems Platform Research Group and received his Ph.D. in Computer Science from Georgia Institute of Technology in August 2017, where his dissertation earned the College of Computing Dissertation Award. His research focuses on Computer Architecture, Memory and Storage Systems, AI Infrastructure, Distributed Systems, and Systems Security . Huang has pioneered work in sustainable AI infrastructures, modular data centers, neural processing unit virtualization, and ransomware-aware storage systems. His research has been featured in top-tier conferences including ISCA, MICRO, ASPLOS, OSDI, SOSP, and USENIX ATC, with over 50 publications and multiple patents issued worldwide. Huang's research has significant industry impact, with some work transferred into products and featured in popular media outlets including ACM CACM, TechXplore, and Science Daily. His work on non-volatile memory and storage systems has received extensive coverage, with some projects generating over 50 media reports. Among his notable achievements are the ACM SIGMICRO Early Career Award, NSF CAREER Award, IEEE Micro Top Picks (three times), USENIX Best Paper Award, and the MICRO Best Paper Runner Up in 2024. He has secured over $4.01M in grants ($11.12M with collaborators) from NSF, DARPA, Army Research Office, and industry partners. ACM SIGMICRO Early Career Award NSF CAREER Award IEEE Micro Top Picks (three times) USENIX Best Paper Award MICRO Best Paper Runner Up (2024) Google Faculty Research Award NetApp Faculty Fellowship Award Huang actively contributes to the academic community as program co-chair of NVMW'23 and organizer of HotInfra'23. He currently advises 12 Ph.D. students, 1 master student, and multiple undergraduates. His teaching innovations include developing ECE522: Emerging Memory/Storage System and revising ECE511: Computer Architecture with cutting-edge content.
Professor Jiyuan Tu is a Professor in the Department of Mechanical and Automotive Engineering at RMIT University's School of Engineering. He specializes in computational fluid dynamics (CFD), multiphase flows, and their applications in renewable/nuclear energy, biomedical engineering, and built environment systems. His research has led to over 500 peer-reviewed articles, 9 books, and $10M+ in ARC grants. He has supervised over 50 postgraduate students and received prestigious awards such as the RMIT Research Excellence Award (2012) and Fulbright Senior Scholar Award (2008). Research interests include CFD modelling of bioaerosol transport, drug delivery systems, and thermal energy storage. He pioneered numerical models for multiphase flows, contributing to software implementations in industries. Notable works include books on CFD and multiphase flow analysis, and leadership in international conferences like COBEE 2018. He holds honorary professorships at Tsinghua University and is Editor-in-Chief of the Experimental and Computational of Multiphase Flow journal. Industry experience includes roles at ANSTO (1996-2001). Awards span fellowships from JSPS, KOSEF, and Fulbright programs. Grants include ARC Discovery, Linkage, and LIEF projects. His work ranks him among the world’s top researchers in pebble bed reactors and airborne infection studies (SciVal 2016-2025).
