Andrea Bonfiglio is an Associate Professor at the Department of Naval, Electrical, Electronic and Telecommunication Engineering (DITEN) within the School of Engineering at the University of Genoa. His work focuses on power systems, smart grids, and renewable energy integration with a particular emphasis on innovative control strategies and energy storage solutions. Teaching areas: Electrical Systems, Industrial Measurements, Energy Security Key research themes: Smart distribution networks, synthetic inertia, microgrid control, vehicle-to-grid technologies, battery energy storage Recent work explores virtual energy partitioning, load flow optimization, and inertia allocation in transmission networks Contact: a.bonfiglio@unige.it His publications highlight advanced control methodologies using machine learning and sliding mode control for both transmission and distribution networks, with applications to renewable integration and grid stability challenges.
Greg Keoleian is the Peter M. Wege Endowed Professor of Sustainable Systems at the University of Michigan. He co-founded and directs the Center for Sustainable Systems and co-leads the MI Hydrogen initiative. His research focuses on advancing life cycle assessment (LCA) methodologies to evaluate the sustainability of technologies, products, and systems. Key areas include renewable energy systems (e.g., wind, solar, bioenergy), transportation decarbonization, circular economy frameworks, and food/agricultural systems. He teaches interdisciplinary graduate courses on Sustainable Energy Systems and Industrial Ecology, and co-directs the Engineering Sustainable Systems Dual Degree Program and the Rackham Graduate Certificate Program in Industry Ecology. Research interests emphasize integrating environmental, economic, and social metrics into sustainability assessments. Notable contributions include pioneering LCA models for hydrogen energy systems, vehicle lifecycle optimization, and circular economy pathways for automotive materials. His work spans global and regional scales, addressing challenges such as reducing greenhouse gas emissions, optimizing resource efficiency, and promoting sustainable urban infrastructure. Keoleian’s recent work highlights synergies between emerging technologies (e.g., wireless charging, autonomous vehicles) and sustainability goals. He collaborates with policymakers and industry leaders to translate research into actionable strategies for deep decarbonization and circular economy adoption. Initiatives like the State of Michigan Hydrogen Roadmap exemplify his focus on bridging academic research with practical implementation. His interdisciplinary approach ensures comprehensive analysis of energy systems, industrial processes, and consumer behaviors. Keoleian’s teaching and mentorship emphasize systems thinking and cross-sector collaboration. He has shaped curricula that prepare students for leadership roles in sustainable systems design, policy development, and corporate sustainability management. Ongoing projects include optimizing reusable packaging systems, evaluating food waste impacts, and modeling urban energy justice in electric vehicle deployment.
Yuvraj Agarwal is a Professor in the School of Computer Science at Carnegie Mellon University , where he leads the SYNERGY Labs . His research focuses on Systems and Networking with emphasis on Embedded Systems , Security , and Energy Efficiency in computing environments. He has been recognized with the NSF Expeditions in Computing Award for Computational Decarbonization research and multiple best paper awards. Education : PhD in Computer Science from University of California, San Diego Research Leadership : Founder/Director of SYNERGY Labs; Executive Director of NSF Expeditions in Variability (2010-2013) Research Trajectory : Recent publications highlight his work on Privacy-preserving smart classroom systems (EduSense, ClassID) IoT security labeling frameworks Audio privacy protection mechanisms Computational decarbonization of infrastructure His research combines hardware-software co-design with societal impact considerations. Scientific Recognition : NSF Expeditions in Computing Award for CoDec (2024) Ubicomp/IMWUT Distinguished Paper Award (2024) CHI Best Paper Honorable Mention (2022) Advising & Collaboration : Mentors students in IoT systems , privacy research , and green computing . Collaborates with institutions including University of Massachusetts Amherst and industry partners like Johnson Controls. Grants include NSF funding for multi-university research initiatives.
Dr. Jiaqi Gong serves as Associate Professor in Computer Science and Adjunct Associate Professor in Mechanical Engineering at The University of Alabama's College of Engineering, while directing the Alabama Center for the Advancement of Artificial Intelligence. His academic foundation includes: B.S. in Engineering, China University of Geoscience (2004) Ph.D. in Engineering, Huazhong University of Science and Technology (2010) Dr. Gong's research pioneers human-AI convergence through cyber-physical systems and smart health technologies, developing mobile/wearable platforms to enhance human perceptual, cognitive, and physical capabilities. His work spans artificial intelligence, machine learning, computer vision, and IoT with applications in healthcare, environmental monitoring, and education. The Sensor-Accelerated Intelligent Learning (SAIL) laboratory he founded drives innovation in behavior change interventions, human movement modeling, and educational data mining. Recent publications reveal strong interdisciplinary trends: healthcare AI dominates with medication adherence prediction and surgical classification systems, while environmental applications feature flood-risk communication and drought analysis. His work increasingly integrates generative AI and LLMs across domains, demonstrating methodological innovation in federated learning, knowledge graphs, and explainable storytelling frameworks. Notable recognitions include: Best Student Paper Award, IEEE/ACM Connected Health Conference (2022) Best Student Paper Award, Body Sensor Networks Conference (2019) Data Challenge Win, IEEE Biomedical Health Informatics (2018) Best Paper Award, Body Area Networks Conference (2014) Best Demonstration Award, IEEE Wireless Health Conference (2014) Dr. Gong leads significant funded projects including a $2M CDC/NIOSH grant for first responder safety and $3M NSF funding for hydrologic research. As SAIL laboratory director, he mentors students in developing clinically deployed technologies for multiple sclerosis, dementia, and mental health. Future work focuses on scaling AI applications in chronic disease management and climate resilience through the Alabama AI Center. The SAIL laboratory (founded 2017) operates as a multidisciplinary hub developing wearable/mobile systems for health applications, with active collaborations across medical clinics and engineering departments for real-world deployment of behavior change interventions and movement analysis tools.
Jonathan M. Baker is an Assistant Professor in the Department of Electrical and Computer Engineering at The University of Texas at Austin, holding the Advanced Micro Devices Chair in Computer Engineering. His research centers on quantum computer architecture with emphasis on practical quantum error correction implementation across the quantum computing stack. His educational background includes a Ph.D. in Computer Science from the University of Chicago (advised by Fred Chong) and dual B.S. degrees in Mathematics and Chemistry and Computer Science from the University of Notre Dame. Baker's research spans quantum compilation, logic synthesis, multi-radix architectures, and error mitigation for both near-term and fault-tolerant quantum systems. His work addresses critical challenges in quantum hardware-software co-design, with particular focus on optimizing quantum circuits for real-world hardware constraints and noise characteristics. Current projects emphasize qudit-based computing, neutral atom architectures, and efficient error correction implementations. His publication record shows strong focus on quantum architecture innovations, with recent work exploring qudit advantages, modular chiplet designs, and dynamic noise adaptation. Key trends include hardware-aware compilation techniques, communication optimization across quantum systems, and practical approaches to fault tolerance. Best Paper Award Runner Up, MICRO 2020 IEEE Micro Top Pick, 2020 (Virtualized Logical Qubits) IEEE Micro Top Pick, 2020 (Extending Frontier with Qutrits) IEEE Micro Top Pick, 2021 (Emerging Technologies) Best Poster Award, MICRO 2018 Baker actively mentors graduate students in quantum computing architecture research and serves on conference review committees including MICRO and ASPLOS. His teaching includes specialized quantum systems courses at UT Austin and online EdX modules covering quantum computation fundamentals and architecture. He collaborates with the Duke Quantum Center and maintains strong industry connections through the AMD Chair position, focusing on bridging academic research with practical quantum computing implementations.
N.K. Anand is a Distinguished Professor of Mechanical Engineering at Texas A&M University, holding the James J. Cain III Regents Professorship. He leads research in advanced computational methods and thermal-hydraulic systems, with affiliations to Multidisciplinary Engineering and Nuclear Engineering programs. His work focuses on physics-informed machine learning, finite volume methods, and aerosol transport in nuclear reactor contexts. Education: PhD (Mechanical Engineering, Purdue University, 1983), M.S. (Kansas State University, 1979), and B.E. (Bangalore University, 1978). Awards include the ASME James Harry Potter Gold Medal (2020) and multiple teaching/administrative excellence awards from Texas A&M. Research emphasizes fluid dynamics modeling (e.g., PINNs for periodic flows, turbulent deposition studies), heat pipe systems, and nuclear reactor thermal-hydraulics. His Versatile Test Reactor (VTR) contributions include cartridge loop designs and aerosol transport experiments. Active in high-temperature reactor safety, with facilities studying pebble beds, helical coil exchangers, and HTGR upper plenum dynamics. Publications span physics-informed ML applications, finite volume techniques, and nuclear thermal systems. Grants supported development of advanced CFD tools and reactor safety infrastructure. His lab collaborates on international nuclear energy projects and emerging AI-driven simulation methodologies.
Thomas Gray is an Assistant Professor in the Mechanical Engineering Department at Texas A&M University, affiliated with the Mike J. Walker ’66 Department. His research focuses on Human Strength Amplification, Wearable Robotics, and Control Systems, with a particular emphasis on exoskeleton design and biomechanical interaction. He leads the HERC Lab, aiming to advance direct control paradigms for physically interactive robots. Educational Background : Ph.D., Mechanical Engineering, University of Texas at Austin (2019) B.S., Engineering: Robotics, Olin College of Engineering (2012) Research Interests : Gray’s work centers on enhancing human performance through advanced robotic systems. Key areas include: Development of wearable devices for strength amplification and fatigue mitigation Design of series-elastic actuators and force/torque feedback mechanisms System identification for robust control in dynamic environments Optimization of mechanical impedance rendering for natural human-robot interaction Awards & Recognition : IEEE ICRA Best Manipulation Paper Award (2017) IJHR Best Paper Award (2016) NASA Space Technology Research Fellowship (2015) DARPA Virtual Robotics Challenge Winner (Team IHMC, 2013) Grants & Advising : Gray has secured significant funding for his research, including grants from NASA and DARPA. He advises students in robotics and control systems, though specific student names are not listed. Labs & Teams : He directs the Human-Empowering Robotics and Control (HERC) Lab, which explores next-generation robotics for human augmentation and direct control methodologies.
Prof. Catherine O'Sullivan is a Professor of Particulate Soil Mechanics at Imperial College London's Department of Civil and Environmental Engineering, part of the Faculty of Engineering. She leads the Geotechnics Section and serves as Editor-in-Chief of the ASCE Journal of Geotechnical and Geoenvironmental Engineering. Her research focuses on particulate soil mechanics, employing Discrete Element Modelling (DEM) and micro-CT imaging to study sand behavior, reservoir sandstones, and internal erosion. Notable recognitions include the 2016 Shamsher Prakash Research Award and the 2021 President’s Teaching Innovation Award. Education : PhD in Civil Engineering, University of California, Berkeley (2002) MEngSc in Civil Engineering, University College Cork (Ireland) BEng (Civil Engineering), University College Cork (Ireland) Research Interests : Prof. O'Sullivan's work integrates computational and experimental methods to explore granular material behavior. Key areas include DEM validation, μCT analysis, and pore network modeling. Her group collaborates across disciplines, involving physicists and mechanical engineers alongside civil engineers. Awards & Recognition : 2015 Geotechnique Lecture Student Choice Supervision Award (nominated twice) 2023 Alert Geomechanics Special Lecture Advising & Grants : She supports PhD and postdoctoral researchers through Imperial scholarships and fellowships. Her students often explore particulate soil behavior, with many securing prestigious awards. Labs & Teams : Leads the Geotechnics Section at Imperial, fostering interdisciplinary research in geomechanics and computational modeling.
Professor D Graham J Shipley is the Professor of Ancient History at the University of Leicester's School of Archaeology and Ancient History since 2002. His research focuses on Hellenistic and Classical antiquity, particularly on political landscapes, environmental studies, and urban planning. He holds a D.Litt. from the University of Oxford (2020) and is a Senior Fellow of the Higher Education Academy (2014). Education: Graduated in Classics from Oxford University. Academic roles include serving on the Oxford Classical Texts Committee and the UK Education Honours Committee. Previously chaired the Council of University Classical Departments and convened the Dorothy Buchan Memorial lectures. Research interests emphasize ancient geography, socio-political structures, and environmental interactions. His work spans studies of Sparta, Greek urban planning, and the cultural impact of Hellenistic expansion. Recent publications examine Pseudo-Skylax's geographical texts and post-Alexandrian political dynamics. Scientific Awards: Senior Fellow of the Higher Education Academy (2014) D.Litt. (Doctor of Letters) from University of Oxford (2020) Advising and Grants: No specific advisees listed, but supervises research in ancient history and archaeology. Active in collaborative projects such as the Laconia Survey. Grants have supported archaeological fieldwork and publication initiatives. Labs/Teams: Collaborates with the Oxford Classical Texts Committee and has led interdisciplinary teams in regional archaeological surveys.
Qing Li is an Associate Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University (CMU), part of the College of Engineering. He holds a B.E. in Electronics Engineering from Tsinghua University (2006) and a Ph.D. in Electrical and Computer Engineering from Georgia Institute of Technology (2013). Prior to CMU, he worked as a postdoctoral researcher at the National Institute of Standards and Technology (NIST), where he developed quantum frequency conversion and microresonator-based optical systems. His research focuses on light-matter interactions in integrated photonics, emphasizing nonlinear optics and quantum information processing. He has pioneered silicon carbide and aluminum nitride platforms for chip-scale quantum technologies and optical metrology. Dr. Li has been recognized with prestigious awards including the Darpa Young Faculty Award (2019), OSA Paul F. Forman Team Engineering Excellence Award (2020), and Sigma Xi Best Ph.D. Thesis Award (Georgia Tech). His work bridges classical and quantum information systems, with applications in secure communication, atomic systems interrogation, and high-precision frequency synthesis. He actively contributes to the Pittsburgh Quantum Institute (PQI), advancing regional quantum engineering initiatives. His research group’s key projects include developing compact optical frequency synthesizers, soliton microcombs for communication grids, and entangled photon pair sources for quantum networks. Grants and collaborations support his exploration of novel photonic materials and devices, targeting advancements in both fundamental science and applied technologies.
Mehrdad Ehsani is a Robert M. Kennedy Endowed Professor of Electrical Engineering at Texas A&M University, leading the Power Electronics and Motor Drives Laboratory. He holds a Ph.D. from the University of Wisconsin-Madison and has over four decades of expertise in power electronics, electric/hybrid vehicles, and energy systems. His research focuses on sustainable energy, advanced power conversion, and vehicle electrification. Educational Background: Ph.D., Electrical Engineering, University of Wisconsin-Madison (1981) M.S., Electrical Engineering, University of Texas at Austin (1974) B.S., Electrical Engineering, University of Texas at Austin (1973) Research Interests: Sustainable power systems, electric/hybrid vehicles, energy storage, power electronics, and aerospace power systems. His work emphasizes practical applications, such as transmotor technology for energy efficiency and grid-interactive buildings. Awards & Recognition: Life Fellow of IEEE SAE Fellow (2005) IEEE Vehicular Technology Society Avant Garde Award (2001) Recipient of multiple Prize Paper Awards (IEEE-IAS) Advising & Grants: Director of Advanced Vehicle Systems Research Program. His lab collaborates with industry on patents, including over 30 granted/pending patents, and advises on sustainable transportation technologies. He has consulted for over 60 companies and government agencies. Labs & Teams: Founder and director of the Power Electronics & Motor Drives Lab, focusing on electric vehicle propulsion, renewable energy integration, and advanced control systems.
Dr. Beibei Ren is an Assistant Professor in the Department of Mechanical Engineering at Texas Tech University. She earned her Ph.D. in Electrical and Computer Engineering from the National University of Singapore (NUS) in 2010, followed by postdoctoral work at UCSD and a research fellowship at NUS. Education: Ph.D. in Electrical and Computer Engineering (NUS, 2010) Previous Positions: Postdoctoral Scholar (UCSD, 2010-2013), Research Fellow (NUS, 2009-2010) Her research focuses on dynamic systems and control with applications in renewable energy integration, microgrids, UAVs, MEMS, marine systems, and manufacturing. At Texas Tech, she directs the Dynamic Intelligent Systems, Control and Optimization (DISCO) Group , emphasizing robust control strategies for uncertain systems. The 15 most recent publications highlight her expertise in uncertainty and disturbance estimator (UDE)-based control , with applications in smart grid technologies, wind and solar energy systems, quadrotor robotics, and power electronics. Her work bridges theoretical control theory with practical implementations in renewable energy and autonomous systems. STEM Outreach: Actively promotes diversity in engineering through Texas Tech's STEM CORE programs.
Surya Ganguli is an Associate Professor in the Department of Applied Physics at Stanford University, with courtesy appointments in Neurobiology and Electrical Engineering. He serves as Senior Fellow at the Stanford Institute for Human-Centered AI and is affiliated with the Stanford Neuroscience Institute , Bio-X , and Wu Tsai Neurosciences Institute . His research spans theoretical neuroscience, machine learning, and statistical mechanics. Ph.D. , UC Berkeley, Theoretical Physics (2004) M.A. , UC Berkeley, Physics (2000) M.A. , UC Berkeley, Mathematics (2004) M.Eng. , MIT, Electrical Engineering and Computer Science (1998) B.S. , MIT, Physics (1998) B.S. , MIT, Mathematics (1998) B.S. , MIT, Electrical Engineering and Computer Science (1998) His lab explores how higher-level cognitive phenomena emerge from neural network dynamics, focusing on perception, memory, attention, and decision-making . Research themes include statistical mechanics of learning , neural representational geometry , and biologically plausible learning rules . Current work examines nonlinear interactions in neural networks through the Schmidt Science Polymath Award (2023). Key article trends reveal expertise in neural coding limits (2022 Nature), synaptic plasticity models (2022 Neural Computation), and deep learning theory (2022 NeurIPS publications). His 2019 Annual Review chapter on statistical mechanics of deep learning established foundational insights into network criticality. Scientific Awards : NSF Career Award (2019) Simons Foundation Investigator (2016) McKnight Scholar Award (2015) James S. McDonnell Foundation Scholar (2014) Sloan Research Fellow (2013) As advisor, he mentors 10+ doctoral students across Applied Physics, Neurosciences, and Computer Science, including Vamshi Balanaga and Mason Kamb. His lab collaborates with experimental teams at Stanford and beyond, supported by grants from NSF , Simons Foundation , and Swartz Foundation . The Neural Dynamics & Computation Lab unites physicists, mathematicians, and neuroscientists to decode cognition through interdisciplinary methods.
Professor Omer Rana serves as Professor of Performance Engineering and International Dean for the Middle East at Cardiff University's School of Computer Science and Informatics. He also holds the prestigious position of Cross-Council Research Director for the UK National Edge AI Hub, demonstrating his leadership in national research initiatives. Previously, he led the Complex Systems research group and served as Dean of International for the Physical Sciences and Engineering College at Cardiff University. Professor Rana is a Fellow of both the Learned Society of Wales and the Higher Education Academy, and serves on the Advisory Board of the Welsh Ethnic Minority Professors Initiative (WEMPI). His research expertise centers on the intersection of intelligent systems and high performance distributed computing, with particular focus on applying intelligent techniques to resource management in distributed systems. His scholarly contributions span edge computing, cloud computing, Internet of Things (IoT), artificial intelligence, cybersecurity, federated learning, privacy-preserving systems, and sustainable computing. Professor Rana has published extensively in top-tier journals and conferences, with recent work emphasizing practical applications in industrial automation, smart buildings, and sustainable computing solutions. Professor Rana's publication record demonstrates consistent leadership in edge computing and distributed systems research, with a growing emphasis on practical implementations across diverse application domains. His work bridges theoretical computer science with real-world technological challenges, particularly in industrial automation, smart environments, and sustainable infrastructure. Fellow of the Learned Society of Wales Fellow of the Higher Education Academy Professor Rana actively supervises postgraduate students and has secured significant research funding for projects related to edge computing, IoT, and distributed systems. His international collaborations span Europe, Asia, and the Middle East, reflecting his global influence in the field. He serves as a sought-after keynote speaker, workshop chair, and panel moderator at major international conferences including IEEE/ACM Utility and Cloud Computing (UCC) and IEEE Edge Computing. He leads multiple research initiatives, most notably as Cross-Council Research Director for the UK National Edge AI Hub, where he shapes national research directions in edge computing and AI. His work has practical applications across industrial automation, smart building management, electric vehicle infrastructure, and sustainable computing solutions.
Nedim Pervan is a Full Professor at the Faculty of Mechanical Engineering, University of Sarajevo, Bosnia and Herzegovina. His academic position focuses on mechanical engineering with emphasis on product design, structural analysis, and biomechanical applications. He maintains an active research profile with numerous publications and collaborations across various engineering disciplines, with office hours every workday from 09:00 to 10:00 in room 314. Professor Pervan's research interests span multiple domains of mechanical engineering. He has made significant contributions to additive manufacturing, particularly in polymer gear production and analysis. His work explores mechanical properties, failure mechanisms, and service life of polymer gears manufactured through additive processes. Additionally, he has conducted extensive research on external fixation devices used in orthopedic treatments, analyzing their biomechanical characteristics and structural stability under various loading conditions. His expertise extends to finite element analysis, structural optimization, and the application of 3D scanning technologies within Industry 4.0 contexts. His research demonstrates a strong connection between theoretical engineering principles and practical applications across automotive, medical devices, and manufacturing industries. His recent publication record reveals a strong trend toward interdisciplinary research bridging mechanical engineering with biomedical applications and advanced manufacturing technologies. A significant portion of his work focuses on polymer gears and additive manufacturing, examining material properties and performance characteristics. Another substantial research stream involves biomechanical engineering, particularly the analysis of external fixation devices. His publications demonstrate a methodological approach combining experimental testing with finite element analysis. More recently, his research has expanded into 3D scanning applications in manufacturing and the electrification of transportation systems in Bosnia and Herzegovina. Professor Pervan has been involved in numerous research projects that have advanced the capabilities of the Faculty of Mechanical Engineering. These include the "Integrated Intelligent CAD System for Interactive Design, Analysis and Prototyping of Compression and Torsion Springs" (2022), "Opremanje Laboratorije za razvoj i dizajn proizvoda" (2020), and "Modernizacija Laboratorije za ispitivanje mašinskih konstrukcija" (2019-2020). These projects have focused on developing advanced laboratory facilities, intelligent CAD systems, and equipment for mechanical design and analysis, with several specifically targeting 3D scanning technology implementation. His collaborative work extends across multiple research teams within the Department of Mechanical Constructions at the University of Sarajevo. He frequently collaborates with researchers including Adis Muminović, Elmedin Mešić, and Muamer Delić on projects related to additive manufacturing, biomechanical engineering, and structural analysis. His research group appears actively involved in both theoretical and applied engineering research with practical industrial and medical applications, contributing significantly to Bosnia and Herzegovina's engineering research landscape.
