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Ramakrishna GokarajuView profile

Professor

• Power System Protection
• Smart Grid Applications
• Sustainable Energy Systems
• +4 more

Prof. Ramakrishna Gokaraju is a Professor and Graduate Chair in the Department of Electrical and Computer Engineering at the University of Saskatchewan. His academic journey includes roles as Assistant Professor (2003), Associate Professor (2009), and full Professor (2015). He holds a B.E. from NIT Trichy (1992), M.Sc. and Ph.D. from the University of Calgary (1996, 2000). His research focuses on power system protection, smart grids, and sustainable energy systems, including small modular reactors (SMRs) and renewable integration. He has advised 8 PhD and 25+ Master’s students, with over 80 publications in top journals/conferences. Dr. Gokaraju’s honors include the Izaak Walton Killam Memorial Scholarship (1998–2000) and the Professor of the Year Award (2008). He has held visiting roles at the University of Manitoba (2009–2010), IIT Kanpur (2018), and institutions in Australia and India. His work emphasizes high-speed digital relaying, PMU-based solutions, and transient stability protection. Current research includes wind generator modeling, SMR integration, and energy storage systems for remote communities. His technical contributions span fault location algorithms, grid resilience enhancement, and GPU-based optimization for transport systems. Ongoing projects explore hybrid energy systems combining SMRs with renewables. Lab affiliations include the Power Systems Research Group at the University of Saskatchewan, focusing on smart grid innovation and sustainable energy solutions.

Larry PileggiView profile

Professor

• Secure Integrated Circuit Hardware
• Integrated Circuits Design Methodologies
• Power Systems Simulation and Optimization
• +3 more

Larry Pileggi is the Coraluppi Head and Tanoto Professor of Electrical and Computer Engineering at Carnegie Mellon University (CMU). He is also the Department Head of CMU’s ECE Department and has held prior roles at Westinghouse Research and Development and the University of Texas at Austin. His work bridges academic research and industry innovation, with co-founding ventures like Fabbrix Inc., Extreme DA, and Pearl Street Technologies. Dr. Pileggi earned his Ph.D. in Electrical and Computer Engineering from CMU (1989), following an M.S. (1984) and B.S. (1983) in Electrical Engineering from the University of Pittsburgh. His research focuses on three core areas: secure integrated circuit hardware (mitigating supply-chain threats), integrated circuits design methodologies (supporting sub-20nm CMOS and heterogeneous technologies), and power systems simulation (developing robust grid analysis tools like SUGAR). He has been recognized with numerous awards, including the prestigious 2023 Phil Kaufman Award for contributions to electronic system design, and is an IEEE Fellow. His academic leadership includes fostering maker initiatives and interdisciplinary research programs to address future challenges in energy and computing systems. Pileggi’s advising record includes over 47 Ph.D. students, many of whom collaborate with him in industry ventures. Current and past grants support his work on resilient power grids and novel memory technologies, reflecting a commitment to both theoretical and applied research. His lab, the Pileggi Lab, develops cutting-edge solutions for energy and integrated systems, emphasizing scalable simulation, secure hardware design, and next-generation memory architectures. Collaborations span institutions like ETH Zurich and industry partners in EDA and semiconductor sectors.

Fei TengView profile

Associate Professor

• Power Systems
• Cybersecurity
• Renewable Energy Integration
• +3 more

Dr. Fei Teng is an Associate Professor in the Department of Electrical and Electronic Engineering at Imperial College London and Director of Education at the Energy Futures Lab, a pan-university hub for interdisciplinary energy research. He holds visiting positions at MINES ParisTech, PolyU Hong Kong, and KTH Sweden. His research focuses on software-defined power networks, stability-constrained optimization, cyber-resilient decision-making, and privacy-preserving data exchange in low-inertia grids. Dr. Teng has authored over 100 publications in top-tier journals and conferences, with funding from EPSRC, Innovate UK, the Royal Society, and industry partners like Hitachi and National Grid ESO. His work addresses critical challenges in grid stability, cybersecurity, and renewable energy integration. He has received prestigious awards, including the IEEE Early Career Award and Royal Society Kan Tong Po Fellowship. Research interests include high-penetration power electronics, uncertainty modeling in power systems, and data privacy in smart grids. His interdisciplinary approach integrates machine learning, quantum computing, and cyber-physical systems to enhance grid resilience and efficiency. Key contributions include frameworks for stability-constrained optimization, cyber-resilient control, and synthetic inertia from electric vehicles. He advocates for software-defined grids to revolutionize decision-making frameworks for NetZero systems.

• Stochastic programming
• Two-phase and multi-phase models
• Scenario generation and reduction
• +9 more

Trine Krogh Boomsma is a Professor in the Department of Insurance and Economics at the University of Copenhagen's Department of Mathematical Sciences. Her research focuses on optimization under uncertainty with significant applications in energy systems, particularly electricity markets, renewable energy investments, and power system planning. PhD in Mathematics-Economics, Aarhus University (2003-2007) Visiting PhD at University of Duisburg-Essen (2004) Academic career includes positions at Risø National Laboratory for Renewable Energy and Imperial College London Her work spans stochastic programming, real options analysis, and dynamic programming to address energy sector challenges. Key areas include support schemes for renewables, market risk modeling, and operational optimization of hybrid conventional-renewable systems. Recent research explores policy impacts on investment decisions and advanced scenario generation techniques. Major publications (2012-2020) cover renewable energy policy frameworks, power plant valuation models, and sequential market bidding strategies. These works emphasize electricity market dynamics, investment risk quantification, and robust planning under uncertainty. She teaches linear programming, integer programming, and stochastic programming applications in operational analysis, contributing to energy economics education at the department.

Jacob BrouwerView profile

Professor

• Fuel Cell Technology
• Hydrogen Energy
• Renewable Energy Systems
• +7 more

Professor Jacob "Jack" Brouwer serves as a Professor and Chancellor's Fellow at the University of California, Irvine's Samueli School of Engineering. He holds primary appointment in Mechanical and Aerospace Engineering with joint appointments in Chemical and Biomolecular Engineering and Civil and Environmental Engineering. As Director of the Clean Energy Institute and former Associate Director of the National Fuel Cell Research Center (NFCRC), he leads critical research initiatives in sustainable energy technologies. Dr. Brouwer earned his Ph.D. in Mechanical Engineering from MIT in 1993, following B.S. and M.S. degrees in Mechanical Engineering from UCI. His research focuses on high-temperature electrochemical dynamics, hydrogen energy systems, and integrated energy conversion technologies. He has pioneered work in fuel cell systems analysis, novel solid oxide fuel cell materials, and life cycle assessments of clean energy technologies. His research integrates mass, energy, and momentum conservation principles with chemical and electrochemical reaction engineering. In August 2011, Professor Brouwer led the development of an innovative fuel cell generator system in collaboration with the Orange County Sanitation District, FuelCell Energy, Inc., and Air Products. This groundbreaking technology converts wastewater digester gases into hydrogen for zero-emission vehicle fuel, electricity, and heat production, representing a significant advancement in clean energy infrastructure. International Who's Who of Professionals, Honored Member (2006) National Academy of Engineering, Invited Lecturer (2004) UC Irvine Chancellor's Fellow (2022) U.C. Regents Fellowship Recipient (1987-1988) Summa Cum Laude, UCI (1987) As Director of the Clean Energy Institute, Professor Brouwer oversees extensive research operations including external relations, project management, and supervision of technical and administrative staff. His leadership extends to curriculum development and instruction in fuel cell science and technology. He works collaboratively with Professor Scott Samuelsen and colleagues across engineering disciplines, demonstrating exceptional expertise in fuel cells and advanced alternative energy conversion devices. His laboratory facilities include the 221 Engineering Lab Facility where experimental and simulation capabilities for advanced power technologies are developed.

Gabriela HugView profile

Professor

• Electric Power Systems
• Sustainable Energy
• Control Systems
• +3 more

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)

Malcolm McCullochView profile

Professor

• Renewable Energy Integration
• Electric Vehicle Powertrains
• Demand Side Management
• +5 more

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.

Yannis PaschalidisView profile

Professor

• Optimization
• Control Systems
• Stochastic Systems
• +8 more

Yannis Paschalidis is a Distinguished Professor at Boston University with appointments in Electrical and Computer Engineering, Systems Engineering, Biomedical Engineering, and Computing & Data Sciences. He serves as Director of the Rafik B. Hariri Institute for Computing and Computational Science & Engineering. He holds a PhD (1996) and MS (1993) in Electrical Engineering and Computer Science from MIT, and a Diploma (1991) from the National Technical University of Athens. His interdisciplinary research spans optimization, control systems, machine learning, and data science with applications in healthcare, autonomous systems, and networks. Key focus areas include developing algorithms for autonomous navigation, healthcare analytics for clinical decision support, energy demand optimization, and computational biology for protein interaction modeling. Recent publications demonstrate strong focus on AI robustness (adversarial defenses, distributional robustness), healthcare applications (cognitive impairment detection, epidemic control), and sustainable systems (power networks, ecological forecasting). Methodological innovations center on reinforcement learning, distributionally robust optimization, and geometric analysis of classical algorithms. CAREER Award (NSF) IEEE Fellow (2014) IFAC Fellow (2022) IBM/IEEE Smarter Planet Award IEEE Computer Society Crowd Sourcing Prize IMIA Best Paper Award Charles DeLisi Award (2020) Distinguished Professor of Engineering As primary advisor to 35 PhD graduates, he leads the Network Optimization & Control (NOC) Lab. His research is funded by NSF, NIH, DoD, ARPA-E, and industry partners, including major grants on Neuro-Autonomy (ONR MURI), pandemic preparedness (ARPA-E NewRAMP), and healthcare AI (NIH QuBBD). He directs the Network Optimization & Control Lab focusing on optimization, learning, and control for autonomous systems, healthcare, and networks. The lab develops fundamental methodologies with applications in robotics, computational medicine, and infrastructure systems.

• Sustainable Bioenergy
• Circular Economy
• Energy Conversion Systems
• +4 more

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.

Mahdi KhodayarView profile

Assistant Professor

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +4 more

Mahdi Khodayar is an Assistant Professor of Computer Science at the University of Tulsa . He holds a Ph.D. in Electrical Engineering from Southern Methodist University (2020) and M.Sc./B.S. degrees in Artificial Intelligence and Software Engineering from K.N. Toosi University of Technology (2015, 2013). His research focuses on AI and machine learning applications in power systems, transportation systems, computer vision, and spatiotemporal pattern recognition. B.Sc. in Computer Engineering (2013), K.N. Toosi University of Technology M.Sc. in Artificial Intelligence (2015), K.N. Toosi University of Technology Ph.D. in Electrical Engineering (2020), Southern Methodist University Khodayar’s research bridges deep learning with energy systems , including fault detection in power grids, renewable energy forecasting, and traffic scene understanding. His work leverages graph neural networks , reinforcement learning , and generative models for robust spatiotemporal analysis. Recent publications highlight his focus on graph-based architectures for power systems, hybrid deep reinforcement learning in energy forecasting, and unsupervised domain adaptation in remote sensing. His work integrates physics-informed modeling with probabilistic frameworks . Scientific Awards : NSF ECCS Division Funding (2022) US DOT FHWA Grant (2023) Zelimir Schmidt Award for Early Career Research (2023) Honors Student Award (2015), K.N. Toosi University Khodayar has been funded by the NSF , US Department of Transportation , and the TU Cyber Fellows program . He serves as an associate editor for IEEE Transactions on Transportation Electrification and other journals.

• Energy Systems Modelling
• Multi-energy Systems Integration
• Renewable Energy Integration
• +4 more

Goran Strbac is a Professor of Energy Systems at Imperial College London's Faculty of Engineering, holding the Chair in Electrical Energy Systems. He leads the Department of Electrical and Electronic Engineering and directs the joint Imperial-Tsinghua Research Centre on Intelligent Power and Energy Systems. His roles include IPCC WG 3 Leading Author, OFGEM RIIO-2 Challenging Group Member, and member of multiple EU energy platforms. Strbac's research focuses on multi-energy systems integration, energy market design, renewable integration, distributed energy resources, and grid resilience. Notable contributions include whole-energy system modeling across operation and investment scales, market mechanisms for flexibility services, and security assessments for low-carbon infrastructure. His work emphasizes resilience and decarbonization, with over 500 publications and 4 co-authored books. He advises governments and regulatory bodies on energy policy, including contributions to UK Smart System Forum and European Technology and Innovation Platforms. His recent articles explore AI-driven grid optimization, hydrogen integration, and transactive energy systems. Strbac leads major initiatives like the UK Centre for Grid Scale Energy Storage and chairs resilience-focused research clusters. His research bridges academia and industry, informing policy through rigorous systems analysis and innovative modeling frameworks.

Colin JonesView profile

Associate Professor

• Optimal Control
• Model Predictive Control
• Optimization
• +6 more

Colin Jones is an Associate Professor at the École Polytechnique Fédérale de Lausanne (EPFL) in the Automatic Control Laboratory, School of Engineering. He earned his BASc and MASc in Electrical Engineering and Mathematics from the University of British Columbia (1994-2002) and a PhD in Control Theory from the University of Cambridge (2002-2005). Prior to EPFL, he was an assistant professor there and a senior researcher at ETH Zürich. Current role: Director of the Robotics, Control, and Intelligent Systems Doctoral Program at EPFL Research focus: Optimization-based and model predictive control (MPC) for renewable energy systems, green energy management, and data-driven control methods His recent work (2023-2025) spans high-speed predictive control , smart grid optimization , and physically consistent neural networks , with applications to buildings, hovercrafts, and power systems. He has secured an ERC Starting Grant for his research on optimal control of building networks. Publications include over 200 papers in journals like Automatica , IEEE Transactions , and Energy and Buildings . Notable article trends include distributed optimization , data privacy in energy systems , and nonlinear MPC for autonomous vehicles . Scientific Awards : ERC Starting Grant for optimal control of building networks Advising : Supervises 10 current PhD students and has advised 19 past PhD students, including Alessandretti Andrea and Diwale Sanket Sanjay. Grants and projects emphasize smart energy systems , predictive demand response , and nonlinear control .

Michael BaldeaView profile

Associate Professor

• Process Systems Engineering
• Energy Systems
• Nonlinear Optimization
• +3 more

Michael Baldea is an Associate Professor in the Department of Chemical Engineering at the University of Texas at Austin . He holds a Ph.D. in Chemical Engineering from the University of Minnesota (2006), with prior degrees from 'Babeş-Bolyai' University in Romania (M.Sc. 2001, Diploma 2000). His research group develops theoretical and computational methods for Process and Energy Systems Engineering , focusing on integrated decision-making, performance optimization, and process intensification with industrial validation. Education: Ph.D., Chemical Engineering, University of Minnesota (2006) M.Sc., Interface Process Engineering, 'Babeş-Bolyai' University (2001) Diploma, Chemical Engineering, 'Babeş-Bolyai' University (2000) Research Thrusts: Integrated decision-making in chemical/energy supply chains Process performance monitoring and optimization Process integration and intensification Key applications include grid-responsive chemical plants, intensified distillation/column designs, and renewable energy integration for building systems. Scientific Awards: Frank A. Liddell, Jr. Fellowship NSF CAREER Award (2015-2020) Moncrief Grand Challenges Faculty Award (2014) AIChE Outstanding Young Researcher Award (2017) Implementation : His group has translated research into commercial tools through partnerships with industrial test beds and is working to integrate methods into commercial simulators. They explore predictive approaches for building energy management and strategic capital investment analysis in next-generation energy systems.

Jose Miguel AbitoView profile

Associate Professor

• Industrial Organization
• Regulation
• Environmental Economics
• +3 more

Jose Miguel Abito ("Mike") is an Associate Professor in the Department of Economics at The Ohio State University (OSU), serving as Director of Undergraduate Studies. He holds a PhD from Northwestern University, with prior roles including Assistant Professor at the Wharton School, University of Pennsylvania, where he won a teaching award. His research focuses on applied microeconomics, particularly industrial organization, regulation, and environmental economics. He examines topics such as regulatory incentives, consumer misinformation effects, and antitrust methodologies in sectors like electricity, extended warranties, and infant formula. Education: PhD in Economics from Northwestern University (Evanston, IL), graduate studies in Econometrics and Mathematical Economics at Toulouse, France, and undergraduate studies in Singapore. Research Interests: Mike explores how regulatory frameworks impact market efficiency, consumer welfare, and firm behavior. Recent work analyzes renewable energy market design, electricity procurement dynamics, and demand spillovers in welfare programs like WIC. His methodologies bridge theoretical models and empirical analysis to address complex policy questions. Professional Activities: Currently serves as a University Senator (2023-2026), member of the Salmon P. Chase Center Academic Advisory Committee, and faculty advisor for the Quantitative Finance Club at OSU. Previously involved in inclusive teaching initiatives at Wharton. Awards: Recognized with a teaching award during his tenure at Wharton School. Grants & Advising: Advises on projects related to infant formula markets, wage dynamics, and environmental policy. Engaged in collaborative research on green jobs, regulatory auditing frameworks, and productivity analysis.

Mohsen GhafouriView profile

Associate Professor

• Smart Grid Security
• Cyber-Physical Systems Security
• Wide Area Monitoring Systems (WAMS)
• +5 more

Mohsen Ghafouri is an Associate Professor at the Concordia Institute for Information Systems Engineering (Concordia University). His research focuses on cybersecurity, smart grids, and cyber-physical systems with emphasis on securing energy infrastructure against cyber-attacks. Key areas include detection and mitigation of false data injection attacks, grid resilience against load-altering threats, and secure transactive energy markets. Research interests include wide-area monitoring systems (WAMS), microgrid control, and integration of renewable energy sources. He has developed frameworks for real-time anomaly detection in power systems, blockchain-based security solutions, and machine learning approaches for cyber threat identification. His work addresses vulnerabilities in smart grid components like IEC 61850 substations and EV ecosystems. Recent publications (2024-2025) highlight advancements in securing FACTS controllers, EV charging systems, and distributed energy resources. He has proposed novel mitigation strategies using reinforcement learning, graph neural networks, and federated learning. No scientific awards or grant details are provided in the source text. No advising relationships or lab affiliations are explicitly stated.