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Bri-Mathias Hodge is an Associate Professor at the University of Colorado Boulder's Department of Electrical, Computer, and Energy Engineering, while also serving as Chief Scientist at NREL's Grid Planning and Analysis Center and Associate Director of the Renewable and Sustainable Energy Institute. His career spans academic and industry roles in power systems analysis and renewables integration. Bachelor's, Master's, and PhD in Chemical Engineering from Carnegie Mellon, Åbo Akademi, and Purdue respectively His research focuses on Renewables integration , Net-zero energy systems , and Wind and solar power forecasting . Recent publications explore energy storage dispatch modeling, electric vehicle wireless charging impacts, and AI-driven grid foundation models. His 299+ research outputs (2011-2025) emphasize Renewable energy grid integration Power system forecasting AI applications in energy systems EV infrastructure impacts Carbon capture technologies Scientific recognition includes Fulbright Fellowship (2016) Five IEEE Power and Energy Society Best Paper Awards (2015-2018) Active in professional networks as Member of IEEE Transactions on Sustainable Energy Member of multiple IEEE working groups Contributor to Journal of Renewable and Sustainable Energy

• Renewables integration
• Net-zero energy systems
• Wind and solar power forecasting
• +3 more

Professor Paul D. Sclavounos is a faculty member in the Department of Mechanical Engineering at the Massachusetts Institute of Technology (MIT). He earned his B.Sc. from the National Technical University of Athens in 1977 and Ph.D. from MIT in 1981. Research Interests : Marine hydrodynamics, stochastic control, offshore wind/wave/tidal/solar energy, machine learning applications, magnetohydrodynamic propulsion systems. Notable Contributions : Development of computational tools like SWAN and SML software suites; analysis of nonlinear wave dynamics; integration of AI/ML in marine hydrodynamics. Scientific Recognition : First Prize in National Mathematics Competition (1972), Georg Weinblum Memorial Lecturer (2010-2011), Best Paper Award at OMAE 2019, AEOLOS Scientific Award (2024). Leadership : Director of the Laboratory for Ship and Platform Flows since 1985; advisory roles for US Navy, US Department of Energy, and Det Norske Veritas (DNV). Teaching : Courses in Hydrodynamics (2.016), Advanced Fluid Mechanics (2.25), and Naval Architecture (2.701).

• Marine Hydrodynamics
• Stochastic Control
• Offshore Wind Energy
• +8 more

Lei Wu is a Professor and Anson Wood Burchard Chair Professor in the Department of Electrical and Computer Engineering at Stevens Institute of Technology. He holds a B.S. (2001) and M.S. (2004) in Electrical Engineering from Xi'an Jiaotong University, and a Ph.D. (2008) in Electrical Engineering from Illinois Institute of Technology. His research focuses on power system optimization, renewable energy integration, microgrid control, and cyber-physical systems resilience. Education: B.S. Electrical Engineering, Xi'an Jiaotong University (2001) M.S. Systems Engineering, Xi'an Jiaotong University (2004) Ph.D. Electrical Engineering, Illinois Institute of Technology (2008) Research Interests: Dr. Wu's work addresses challenges in power system operations, including optimization of renewable energy integration, electricity market design, and resilient microgrid control. He develops advanced algorithms for unit commitment, stochastic modeling of renewable resources, and cyber-physical security. His research emphasizes practical applications in grid resilience, demand response, and multi-energy system coordination. Awards: Fellow of IEEE (2022) NSF CAREER Award (2013) IBM Smarter Planet Faculty Innovation Award (2011) Grants & Professional Service: He leads grants on smart grid optimization, including projects from NSF, DOE, and industry partners. He serves as Editor for IEEE Transactions on Smart Grid and other journals, and has advised numerous students on energy-related research. His work on microgrid control and cyber-physical security has been widely recognized in industry and academia. Labs & Teams: Leads the Stevens Energy Systems Lab, focusing on advanced grid technologies and interdisciplinary collaborations between power systems, AI, and cybersecurity.

• Power Systems
• Renewable Energy Integration
• Optimization
• +6 more

Benjamin F. Hobbs serves as the Theodore M. and Kay W. Schad Professor of Environmental Management at Johns Hopkins University, holding a primary appointment in the Department of Environmental Health and Engineering and a joint appointment in the Department of Applied Mathematics and Statistics. He is co-director of the USEPA Yale-JHU SEARCH Center and director of the NSF-funded Electric Power Innovation for a Carbon-free Society (EPICS) Center, focusing on interdisciplinary research at the intersection of energy systems, environmental management, and public health. Hobbs' educational background includes a BS from South Dakota State University (1976), an MS in Resources Management and Policy from SUNY-Syracuse (1978), and a PhD in Environmental Systems Engineering from Cornell University (1983). Prior to joining Johns Hopkins in 1995, he worked at Brookhaven and Oak Ridge National Laboratories and served as a professor at Case Western Reserve University, with additional visiting appointments at institutions including Cambridge University. His research integrates systems analysis, economics, and optimization to address critical challenges in electric utility planning, renewable energy integration, and environmental resource management. Key focus areas include solar forecasting using AI, green infrastructure for urban water management, health impacts of energy transitions, and grid reliability under high renewable penetration. His work emphasizes practical applications through engineering-economic modeling with rich technological and environmental detail. Analysis of his recent publications reveals a strong trend toward addressing grid reliability in decarbonizing systems, with increasing emphasis on market design innovations, resource adequacy under uncertainty, and storage-transmission tradeoffs. His research consistently bridges theoretical optimization with real-world policy implementation, particularly evident in his leadership of the EPICS Center's 100% renewable grid initiatives. Lifetime Achievement Award by Energy Systems Integration Group (ESIG), 2024 Fellow of the Institute of Electrical and Electronics Engineers (IEEE) Fellow of the Institute for Operations Research and Management Science (INFORMS) Hobbs advises graduate students through Johns Hopkins' interdisciplinary programs, with alumni employed as energy consultants, policy analysts, and researchers. His current grants include leadership of the NSF Global Center EPICS and co-direction of the USEPA SEARCH Center, focusing on energy-air-climate-health interactions. He chairs the Market Surveillance Committee for the California Independent System Operator and serves on editorial boards for Energy Economics and other leading energy journals. He leads the Hobbs Energy & Environment Decisions Research Group, which collaborates with institutions including IBM, National Renewable Energy Laboratory, and University of Texas at Dallas. The group participates in the Global Power Systems Transformation Consortium and Columbia-JHU Future Power Markets Forum, conducting fieldwork initially in California and the central United States.

• Electric Power Systems
• Renewable Energy Integration
• Energy Policy and Economics
• +3 more

Bing Yan is an Assistant Professor in the Department of Electrical and Microelectronic Engineering at Rochester Institute of Technology (RIT), affiliated with the Kate Gleason College of Engineering. She holds a B.S. in Information Management from Renmin University of China (2010), and M.S. and Ph.D. degrees in Electrical Engineering and Statistics from the University of Connecticut (2012–2017). Prior to RIT, she was an Assistant Research Professor at the University of Connecticut. Dr. Yan’s research focuses on power system optimization , including grid integration of renewables (wind/solar), microgrid operations, distributed energy systems, and manufacturing scheduling. She has published over 30 peer-reviewed articles and secured grants from the National Science Foundation (including a CAREER Award), Department of Energy, and industry partners like Brookhaven National Laboratory and ABB. Her work emphasizes mixed-integer linear programming and machine learning applications in energy systems. Notable contributions include stochastic unit commitment models for wind farms, voltage control via deep reinforcement learning, and multi-layer weather models for PV prediction. She advises on projects involving grid resilience, smart manufacturing, and data-driven optimization. Awards: National Science Foundation Faculty Early Career Development (CAREER) Award Multiple NSF grants, DOE grants, and industry contracts Teaching: Courses include Circuits I , Electric Power Transmission & Distribution , and Advanced Power Systems . She also mentors students through co-op programs and independent studies. Labs/Teams: Leads the Intelligent Lab of Power and Manufacturing (ILPM), focusing on multidisciplinary solutions for energy and manufacturing systems. The lab emphasizes hands-on training and innovation in smart grid technologies and sustainable energy systems.

• Power System Optimization
• Grid Integration of Renewables
• Microgrid Operation
• +3 more

Teng Wu is a Professor and Director of Graduate Studies in the Department of Civil, Structural and Environmental Engineering at the School of Engineering and Applied Sciences, University at Buffalo . His research focuses on wind engineering, hurricane risk assessment, and climate change adaptation in infrastructure systems. PhD, Civil Engineering, University of Notre Dame (2013) MS, Civil Engineering, University of Notre Dame (2012) MS, Bridge Engineering, Tongji University (2010) BS, Civil Engineering, Tongji University (2007) Minor, Financial Engineering, Fudan University (2006) Teng Wu's research spans multiple domains including Wind Engineering , Hurricane Engineering , Structural Engineering , and Climate Change Adaptation . He specializes in nonlinear aerodynamics, performance-based wind design, and computational fluid dynamics applications to infrastructure resilience. His recent publications focus on machine learning applications for storm surge prediction, wind-induced structural response analysis, and climate change-informed infrastructure recovery frameworks. Key methodologies include hierarchical deep neural networks, knowledge-enhanced models, and reinforcement learning-based control systems. Contact: tengwu@buffalo.edu | Office: 226 Ketter Hall, Buffalo, NY 14260

• Wind Engineering
• Hurricane Engineering
• Structural Engineering
• +8 more

Dr. Xingpeng Li is an Associate Professor in the Department of Electrical & Computer Engineering at the University of Houston (UH), where he has held this position since 2024, following his tenure as Assistant Professor (2018–2024). His research focuses on smart grid technologies, renewable energy integration, and optimization of power systems. He holds a Ph.D. in Electrical Engineering from Arizona State University (2017) and multiple master’s degrees in Computer Science (Georgia Tech, 2023), Industrial Engineering (ASU, 2016), and Electrical Engineering (Zhejiang University, 2013). His work emphasizes machine learning applications in power systems, including battery degradation modeling, microgrid design, and climate-resilient grid planning. He leads the RPG Lab (https://rpglab.github.io), advancing solutions for offshore renewable energy systems, hydrogen transmission, and grid cybersecurity. His research has been funded by the NSF CAREER Award (2024) and the NAS Gulf Research Program (2023). Education : Ph.D., Electrical Engineering, Arizona State University (2017) M.S., Computer Science, Georgia Institute of Technology (2023) M.S., Industrial Engineering, Arizona State University (2016) M.S., Electrical Engineering, Zhejiang University (2013) B.S., Electrical Engineering, Shandong University (2010) Dr. Li’s recent publications highlight advancements in AI-driven grid optimization, battery lifecycle modeling, and offshore microgrid planning. He has received awards such as the Early-Career Research Follow (NAS Gulf, 2023) and the IEEE Phoenix Section Student Scholarship (2016). Awards : NSF CAREER Award (2024) Early-Career Research Follow, NAS Gulf Research Program (2023) Emerging Leader, Offshore Technology Conference (2023) His teaching includes courses like ECE 6327 (Smart Grid Systems) and ECE 6379 (Power System Operations), bridging theoretical research with practical grid challenges. His lab collaborates on projects like 100% renewable offshore platforms and hydrogen energy transmission systems, addressing climate resilience and decarbonization goals.

• Power Systems
• Machine Learning
• Renewable Energy Integration
• +5 more

Taehyung Kim is an Associate Professor at the University of Michigan-Dearborn in the Department of Electrical and Computer Engineering , College of Engineering and Computer Science. His research focuses on power electronics , motor drives , and electric/hybrid power systems for vehicles and aircraft , with an emphasis on renewable energy integration and fault-tolerant control . Education Ph.D., Electrical & Computer Engineering, Texas A&M University M.S., Electrical Engineering, Korea University B.S., Electrical Engineering, Korea University His research interests include energy conversion systems, power electronics for electric vehicles, evaluation and diagnosis of AC motors, and position sensorless control of permanent magnet motors. He leads the KIM Laboratory , which explores unmanned aerial vehicles (UAVs) , battery systems , and powertrain reliability . The 15 most recent articles (2024-2021) highlight his work on hybrid UAVs , fault detection algorithms , cost-effective converters , and powertrain optimization . These publications span power electronics , renewable energy integration , and electric propulsion systems , with applications in transportation electrification and industrial power systems . Scientific Awards NSF Mid Career Advancement Award, 2023 IEEE-IAS Prize Paper Award (2nd Place), 2012 Best Paper Award, IEEE Transportation Electrification Conference, 2021 Listed in "World Top 2% Scientists" (Stanford University, 2020-2024) Listed in Marquis Who’s Who in America Technical Program Co-Chair, 2009 IEEE Vehicle Power and Propulsion Conference Prof. Kim has advised numerous PhD and Master’s students , including Feng Zhou , Sreekanthreddy Chalapala , and Sahithya Parvathareddy . He has secured significant grants from the NSF , Department of Energy , and industry partners like Ford, focusing on smart monitoring , fault identification , and energy management for electrified systems. His lab’s facilities include advanced power electronics labs and hybrid powertrain testing environments .

• Power Electronics
• Motor Drives
• Automotive Engineering
• +3 more

Gabriel Chan is an Associate Professor at the University of Minnesota's Humphrey School of Public Affairs , affiliated with the Science, Technology, and Environmental Policy (STEP) Area. He co-directs the Center for Science, Technology, and Environmental Policy and the Electric Cooperative Innovation Center , with a focus on equitable energy transitions. Ph.D. in Public Policy (Harvard, 2015) B.S. in Earth, Atmospheric, and Planetary Science and Political Science (MIT, 2009) His research blends economic methods with social science and technical knowledge to address climate change and energy policy, particularly in distributed energy resource deployment , community solar , and electric cooperative governance . Recent work explores policy frameworks for integrating renewable energy into municipal utilities and mitigating climate impacts globally. Publications highlight trends in equitable solar deployment , barriers to dynamic electricity pricing , and zero-carbon commitments . While no explicit scientific awards are listed, his leadership in energy policy research and engagement with institutions like the Institute on the Environment underscores his influence. Chan actively mentors graduate students and has led projects on energy efficiency, rural poverty reduction through solar, and international climate agreements. His lab website and media commentary (e.g., IPCC report analysis) reflect ongoing contributions to climate policy discourse.

• Energy Policy
• Climate Change Mitigation
• Sustainable Development
• +4 more

Dilek Uz serves as Assistant Professor of Economics at the University of Nevada, Reno, where she teaches Advanced Microeconomics and Natural Resource and Environmental Economics with emphasis on energy resources. Her academic profile includes research positions at UC Berkeley, the World Bank, and Nevada State Demographer's Office. Her educational credentials feature: Ph.D. in Agricultural and Resource Economics, University of California, Berkeley (2016) M.S. in Statistics, University of Nevada, Reno (2010) M.S. in Economics, University of Nevada, Reno (2008) B.S. in Business Administration, Middle East Technical University, Ankara, Turkey (2003) Dr. Uz's research program centers on empirical analysis of environmental and energy economics, with particular focus on renewable energy integration, water resource management, and climate policy impacts. Her methodological approach combines econometric modeling with policy-relevant case studies spanning both developed and developing economies, especially examining energy-water nexus challenges under climate change scenarios. Her publication trajectory from 2016-2024 reveals expanding expertise in energy transition economics, with recent work analyzing solar adoption behavior, rural electrification challenges under depopulation, and firm-level responses to renewable intermittency. Key journals include Sustainability , Energy Economics , and American Journal of Agricultural Economics , with increasing emphasis on developing economy contexts like Turkey. Her scholarly recognition includes: Outstanding Graduate Student Instructor Award, UC Berkeley (Spring 2016) Graduate Division Summer Grant, UC Berkeley (2015) Dr. Uz's professional activities demonstrate strong integration of research and teaching, with World Bank consultancy experience directly informing her classroom instruction on resource economics. Her research trajectory shows progression from California energy crisis analysis to broader climate-resilient infrastructure studies, supported by consistent publication output in high-impact environmental economics journals.

• Environmental Economics
• Natural Resource Economics
• Energy Economics
• +3 more

Dr. Edmund Spencer is an Associate Professor in the Department of Electrical and Computer Engineering at the University of South Alabama , with research focused on space plasma physics and space weather . He designs advanced instruments for space science, develops theoretical frameworks for plasma characterization, and applies stochastic optimization algorithms to complex systems. Ph.D. Electrical and Computer Engineering, University of Texas at Austin M.S. Electrical and Computer Engineering, University of Texas at Austin B.S. Electrical and Electronics Engineering, University of Leicester, UK His work bridges space instrumentation with nonlinear magnetospheric dynamics , particularly in geomagnetic substorms and solar wind-earth magnetosphere interactions . Current projects include onboard space weather modules for satellites and advanced antenna systems for CubeSats . Recent research trends from his 15 most recent publications (2019-2025) include: Development of time-domain impedance probes for ionospheric electron density measurements Applications of machine learning in substorm prediction Hybrid physics-black-box modeling for Dst index forecasting Advanced antenna designs for small satellites 3D Particle-in-Cell simulations for RF instruments Collisional effects in plasma probe measurements Scientific contributions include: NSF CAREER Award (2013) for RF impedance probe development Key role in NASA's USIP CubeSat missions (e.g., JAGSAT I) Leveraging WINDMI model for substorm dynamics analysis He teaches graduate and undergraduate courses in electromagnetics and stochastic processes , contributing to the department's space science integration in engineering education.

• Space Plasma Physics
• Space Weather
• Radio Frequency Instrumentation
• +3 more

Joshua Smith is a Professor at Loyola University Maryland's School of Education, where he served as Dean from 2012-2021. He was a Visiting Professor at National Chengchi University in Taiwan from 2021-2023, teaching international higher education and design thinking. Education: Ph.D. in Educational Psychology and Methodology (University at Albany, 2002) M.S. in Educational Psychology and Statistics (University at Albany) B.A. Cum Laude in U.S. History with a minor in Sociology (University at Albany) His research focuses on educational transitions (middle school to high school, high school to college), student engagement, and organizational effectiveness. He collaborates with schools and community organizations to design and evaluate educational programs. Recent scholarship trends highlight his work in post-pandemic higher education innovation (e.g., student agency, design thinking), trauma-informed care in educational settings, international collaboration in education, and computational methods in interdisciplinary fields like renewable energy and environmental policy. No scientific awards or honors were explicitly mentioned in the text. Joshua Smith has advised academic programs and partnerships but no formal advisees or grants are listed in the provided data. His affiliations include Loyola University Maryland and National Chengchi University (visiting role).

• Educational Psychology
• Statistics
• Methodology
• +7 more

Delores Knipp is a Research Professor in the Aerospace Engineering Sciences Department at the University of Colorado Boulder. She is affiliated with the Colorado Center for Astrodynamics Research (CCAR) and the Space Weather Technology, Research, and Education Center. Previously, she served as Editor-in-Chief of the American Geophysical Union's Space Weather Journal and Visiting Professor at CU Boulder. Her professional experience includes roles as Professor of Physics at the U.S. Air Force Academy and Senior Research Associate positions at NOAA and the National Center for Atmospheric Research. Knipp's research focuses on space environment dynamics, solar-terrestrial coupling, and space weather education. She holds a Ph.D. in Atmospheric Science from UCLA (1989) and earlier degrees from the University of Missouri. Her research interests encompass ionospheric responses to geomagnetic storms, satellite drag modeling, and space weather impacts on infrastructure. Notable awards include the International Baron Marcel Nicolet Medal (2019) and Fellow of the American Meteorological Society (2019). Knipp has contributed to major initiatives such as the Space Weather Advisory Group and pioneered data-driven approaches to understanding geomagnetically induced currents (GICs). Recent work includes analyzing extreme historical space weather events (e.g., 1872 and 1972 storms) and applying machine learning to identify superstorm signatures. She emphasizes interdisciplinary collaboration, bridging academic research with operational needs for satellite drag models and space weather benchmarks.

• Space Weather
• Ionospheric Physics
• Solar Wind-Geospace Coupling
• +3 more

William F. Holmgren is an Assistant Research Professor at the University of Arizona, affiliated with the Power Forecasting Group and the Institute for Energy Solutions. His expertise centers on solar and wind power forecasting using regional weather models, satellite imagery, and ground sensors, alongside open-source software development for renewable energy applications. He holds a PhD in Physics from the University of Arizona (2013). Holmgren’s research emphasizes improving solar irradiance forecasts through advanced modeling, data assimilation, and tool development, notably contributing to projects like pvlib Python and the Solar Forecast Arbiter. His work integrates interdisciplinary approaches, combining atmospheric science with software engineering to address challenges in renewable energy systems. Key contributions include optimizing photovoltaic (PV) system modeling, enhancing satellite-derived irradiance algorithms, and developing frameworks for forecast evaluation. Holmgren is actively involved in community-driven open-source initiatives to advance solar energy research and operational forecasting tools.

• Solar Power Forecasting
• Renewable Energy Systems
• Weather Modeling
• +7 more

Dr. Jie Zhang is a Professor in the Department of Mechanical Engineering at the University of Texas at Dallas (UTD), affiliated with Electrical and Computer Engineering and the Center for Wind Energy. He holds a Ph.D. in Mechanical Engineering from Rensselaer Polytechnic Institute (2012), and M.S. and B.S. from Huazhong University of Science & Technology (2008, 2006). Before joining UTD in 2015, he was a Research Engineer and Postdoctoral Researcher at the National Renewable Energy Laboratory (2012–2015). His research focuses on sustainable energy systems, including renewable integration, grid resilience, and AI-driven optimization. Notable projects include using Navy ships for emergency power, hydrogen systems in Texas, and generative AI for EV cybersecurity. His lab, the Design and Optimization of Energy Systems (DOES), has secured grants from DOE, NSF, and industry partners. Dr. Zhang has authored over 100 peer-reviewed publications and received awards such as the ONR Young Investigator Award (2020), ASME Design Automation Young Investigator Award, and 16 best paper awards. He leads a team of ~15 graduate/undergraduate students and postdocs, with alumni in academia and industry. Recent achievements include a 2025 UTD Faculty Research Award, promotion to Full Professor (2025), and a $3.5M DOE grant for EV cybersecurity research. His work bridges engineering, AI, and policy to address energy challenges like decarbonization and grid resilience.

• Multidisciplinary Design Optimization
• Complex Engineered Systems
• Big Data Analytics
• +7 more