Joseph Meadows is an Associate Professor in the Department of Mechanical Engineering at Virginia Tech's College of Engineering. His research focuses on combustion, heat transfer, and computational fluid dynamics, with applications in rotating detonation engines and thermoacoustic instability mitigation. He leads the Advanced Propulsion and Power Laboratory. Education: Ph.D., M.S., and B.S. in Mechanical Engineering from the University of Alabama and University of Memphis. Professional History: Associate Professor since 2025, Assistant Professor (2017–2025), and Combustion Design Engineer at Siemens Energy Inc. (2014–2017). His work bridges experimental and computational domains, emphasizing dynamic injector response , fuel inhomogeneity , and mesoscale wood combustion modeling . Recent publications highlight 2D/3D CFD comparisons and acoustic diagnostics in high-temperature environments. While no explicit awards are listed, his research impacts gas turbine design and clean energy systems.
Hsiao-Dong Chiang is a Professor in the School of Electrical and Computer Engineering at Cornell University. He holds a Ph.D. in Electrical Engineering from the University of California, Berkeley, and has made significant contributions to nonlinear system theory and power system stability. His research spans theoretical development and practical applications in electric power systems, nonlinear optimization, and machine learning. B.S., Electrical Engineering, National Taiwan University, 1979 M.S., Electrical Engineering, National Taiwan University, 1981 Ph.D., Electrical Engineering, University of California, Berkeley, 1986 Chiang's research interests focus on nonlinear system theory , power system stability and control , nonlinear optimization , and their applications to modern power grids with high penetration of inverter-based resources. He is renowned for developing the BCU method and TRUST-TECH methodology , which have enabled fast direct stability assessment and global optimization in complex systems. His work bridges fundamental theory with industrial deployment through his companies, Bigwood Systems, Inc. and Global Optimal Technology, Inc. His recent publications (2024–2025) reflect a strong trend toward integrating machine learning and deep neural networks with power system analysis , particularly in state estimation, optimal power flow, and voltage control. There is a clear emphasis on handling uncertainty, non-convexity, and multi-scale dynamics in active distribution networks and integrated energy systems . His work increasingly focuses on resilience , real-time control , and user-centered methodologies for modern grid operations. Chiang has received numerous scientific honors, including: IEEE Fellow (1997) United States Presidential Young Investigator Award (1989) Multiple DOE Grid Optimization Challenge Awards (2020–2023) Best Paper Awards from IEEE Transactions and Conferences Outstanding Education Award, Cornell University (1990) He has successfully managed over 100 research projects and holds 28 U.S. and international patents. As the founder of Bigwood Systems, Inc., he has commercialized advanced software for utility companies across the U.S. and Japan. His team has published over 480 refereed papers and received more than 17,500 citations. He advises a large research group and leads innovations in computational methods for energy systems. His lab is actively involved in developing next-generation tools for grid security, optimization, and machine learning integration.
Prof. Dr.-Ing. Matthias Gaderer is a Professor of Renewable Energy Systems at the TUM Campus Straubing, Technical University of Munich. His research focuses on energy systems for heat, electricity, and fuels, with a particular emphasis on biomass, solar, and geothermal energy applications. He leads projects in combustion technologies, low-emission systems, and decentralized energy systems. Gaderer holds a doctorate from TUM and has extensive industry experience in process engineering. His work includes establishing applied biomass research at the Bavarian Center for Applied Energy Research and leading the research group 'Thermal Use of Biomass in High-Temperature Processes.' He is actively involved in committees such as the Scientific Committee of CEBC and Bavarian Science Forums. His teaching includes courses on energy systems and biomass utilization. Key projects include Reverion GmbH, FlexBioNeuro, and H2 real-world laboratory initiatives. Education: Process Engineering from TU Graz and KTH Stockholm. Research interests span thermochemical gasification, combustion technologies, and energy economics. His publications emphasize biomass gasification, hydrogen production, and sustainable energy systems. He collaborates on EU-funded projects like E2Fuels and leads teams in developing innovative energy solutions.
Professor James S. Cotton is a faculty member in the Department of Mechanical Engineering at McMaster University , specializing in Thermo-Fluid Sciences with a focus on energy sustainability and thermal management. Current research explores thermal energy harvesting , non-thermal plasma flue gas cleaning , and smart electrohydrodynamic heat exchangers . Active in community energy planning as a member of the Burlington Climate Action Plan (2019-2021) and Green Venture board (2016-2021). Research spans both fundamental and applied domains, including two-phase flow , electrohydrodynamic heat transfer modulation , and flow accelerated corrosion analysis. His work integrates modeling and experimental validation for real-world thermal systems. Scientific Contributions: Developed two novel patents for advanced thermal management and soot removal systems during his industrial career at Dana Corp. (until 2007). Current projects involve community energy corridors and next-generation sustainable energy solutions , including the 2025 Hamilton Energy Harvesting Study . Active mentor in graduate education, teaching courses like MECH ENG 4O04: Sustainable Energy Systems and MECH ENG 708: Two Phase Flow and Heat Transfer .
Dr. Erika Marsillac is Dean and Professor of Supply Chain Management at Old Dominion University's Strome College of Business. She has led research and taught internationally since 2004, specializing in sustainable supply chains, renewable energy systems, and international partnerships. Her leadership includes overseeing academic programs and research initiatives focused on logistics, sustainability, and business innovation. Education: Ph.D. in Manufacturing Management, University of Toledo (2010) M.B.A. in Information Technology, Goldey-Beacom College (2002) M.B.A. in Comprehensive General MBA, Goldey-Beacom College (2000) B.A. in Psychology, Pennsylvania State University (1992) Research Focus: Dr. Marsillac's work centers on integrating sustainability into global supply chains, with emphasis on photovoltaic systems, circular economy models, and automotive industry transformations. She investigates variability in production systems, renewable energy infrastructure, and strategies for mass customization. Publication Trends: Her recent articles emphasize renewable energy supply chains (particularly photovoltaics), queueing theory applications in manufacturing, and sustainable operations. Methodologies include case studies, simulation modeling, and bibliometric analysis. Awards & Fellowships: EV Williams Fellowships for Service & Teaching (2022) Outstanding Faculty Service Award (2021) Provost Fellowship (2021) Distinguished Alumni Award (2015) Grants & Projects: Secured $368,600+ in funding for renewable energy and educational initiatives, including solar tracking systems, photovoltaic facilities, and business pedagogy enhancements.
Liji Shen is Professor of Operations Management and Chairholder at WHU – Otto Beisheim School of Management, Campus Vallendar, Germany. She is affiliated with the Supply Chain Management Group and leads research in scheduling, optimization, and sustainable manufacturing. Her academic journey includes a Ph.D. and Habilitation from Technische Universität Dresden, and she has held visiting scholar positions at institutions including École des Mines de Saint-Étienne and Huazhong University of Science and Technology. Ph.D. (Dr.rer.pol.), summa cum laude, Technische Universität Dresden (2009) Habilitation, Technische Universität Dresden (2015) Master of Business Administration (Dipl.-Kffr.), Technische Universität Dresden (2006) Liji Shen's research focuses on Operations Management , particularly scheduling optimization in manufacturing systems. Her work spans flexible job shops , parallel machine scheduling , energy-efficient production , and sequence-dependent setup times . She applies advanced techniques such as evolutionary algorithms , hybrid metaheuristics , and mathematical programming to solve complex industrial problems. Her recent publications emphasize sustainability through energy-aware scheduling and time-of-use pricing models. The 15 most recent publications highlight a consistent research trajectory in production scheduling , with increasing emphasis on energy efficiency , distributed manufacturing , and real-world constraints like eligibility and delivery times. Her work frequently appears in top journals such as European Journal of Operational Research , IEEE Transactions on Evolutionary Computation , and Computers & Operations Research , often in collaboration with leading researchers like Dauzère-Pérès, Mönch, and Buscher. Scientific Awards: European Journal of Operational Research, Best Paper Award (2021) DFG and TU Dresden, 'Support the Best' Prize for Outstanding Researchers (2013) Dr. Feldbausch-Prize for Best Dissertation, TU Dresden (2010) Scholarship for Young Researchers in Saxony (2006–2009) DAAD Prize for Best Foreign Students (2007) Best Master’s Thesis, German Operations Research Society (2007) Liji Shen has been an active advisor and researcher, leading projects in operations research and industrial optimization. Her editorial role on Operations Research Perspectives underscores her standing in the academic community. She has directed research labs and collaborated internationally, contributing to both theoretical advancements and practical applications in manufacturing and logistics. No specific grants are mentioned, but her sustained publication record and leadership roles indicate strong research support. She leads the Operations Management research group at WHU, focusing on algorithmic solutions for complex scheduling problems. Her team investigates energy-aware production, hybrid flow shops, and distributed systems, aiming to bridge the gap between theoretical models and industrial implementation. The lab collaborates with researchers across Europe and China, fostering a global research network in operations research and supply chain management.
Dr. Xiaoli Li is an Associate Professor in the Department of Chemical and Petroleum Engineering at the University of Kansas. Her research laboratory (PVT Lab) focuses on complex fluid behavior in energy systems, with particular emphasis on phase equilibria, gas transport phenomena, and enhanced hydrocarbon recovery techniques. She maintains active research programs in unconventional reservoirs, CO 2 geostorage, hydrate technology, and nanoscale fluid dynamics. Her core research domains include: Confined phase behavior: Thermodynamics of fluids in nanoporous media Gas transport mechanisms: Rarefied flow and apparent permeability modeling Hydrate science: Structure stability and phase boundaries CO 2 utilization: Enhanced oil recovery and geological sequestration Asphaltene dynamics: Precipitation mechanisms in EOR processes Dr. Li teaches across the petroleum engineering curriculum, including core courses: Chemical Engineering Thermodynamics (C&PE 221), Reservoir Engineering (C&PE 327), Well Logging (C&PE 528), and Petroleum Engineering Design (C&PE 628). Her instructional portfolio emphasizes fundamental thermodynamics, reservoir characterization, and practical field applications. Her publication record (35+ articles) demonstrates consistent focus on reservoir thermodynamics and transport phenomena, with recent emphasis on: CO 2 -oil interactions (2020-2023), gas hydrate stability (2020-2022), shale gas transport (2019-2021), and equation of state modifications for confined fluids (2018-2020). Research methodologies combine molecular simulations, experimental studies, and novel thermodynamic modeling approaches.
Shunxiang Cao is an Assistant Professor at Tsinghua Shenzhen International Graduate School in China, where he has worked since July 2022. He earned his Ph.D. in Aerospace Engineering from Virginia Tech (United States) between August 2014 and August 2020 and completed his B.S. in Aerospace Engineering at Beihang University (China) from September 2010 to May 2014. Prior to his current role, he served as a Postdoctoral Scholar at the California Institute of Technology (United States) from November 2019 to May 2022. Teaches courses such as Advanced Numerical Analysis, Numerical Methods for PDEs, and Fluid-Structure Interaction simulations. Research Interests include fluid-structure interaction, computational fluid dynamics, shock/bubble dynamics, material failure analysis, embedded-boundary methods, resolvent-based optimization, Kalman inversion, high-intensity focused ultrasound, and digital twin technology. His work focuses on numerical modeling, optimization, and fluid-solid coupling mechanisms in diverse applications like underwater propulsion, energy storage membranes, and medical acoustics. Scientific Awards include the USNCCM16 Conference Award (2021), Graduate Fellowship at Virginia Tech (2014-2015), Merit Undergraduate Student in Beijing (2014), and Singapore Technology Engineering Fellowship (2010-2013).
Alexandre Barreto serves as an Associate Professor in the Department of Cyber Security Engineering at George Mason University, specializing in cybersecurity applications for transportation systems and critical infrastructure. His work integrates air traffic management expertise with advanced security protocols to address defense and infrastructure vulnerabilities. Education PhD, Instituto Tecnológico de Aeronáutica, Brazil Barreto's research centers on transportation security (particularly aviation), cyber impact assessment, and blockchain applications for critical infrastructure. He develops secure protocols for air traffic systems like ADS-B and creates decision support frameworks for defense scenarios. His methodology combines machine learning, network security, and risk modeling to enhance resilience in smart grids and urban air mobility systems. Analysis of his 15 most recent publications reveals dominant themes in aviation cybersecurity (ADS-Bsec frameworks, Cyber-ARGUS), energy infrastructure protection (SIAD-AERO), and blockchain integration for air traffic management. Over 60% of his work focuses on securing air traffic surveillance systems, while emerging research explores carbon emissions prediction and deep space navigation applications. Advising and Grants No specific student advisement records or grant funding details were documented in the source material, though his classroom activities span graduate and undergraduate cybersecurity education.
Professor Stefan Thor Smith is a distinguished academic at the University of Reading , serving as a Professor in the Department of Energy and Environmental Engineering . His work bridges energy systems with urban sustainability , focusing on the integration of social and technical aspects of energy demand , urban energy system modeling , and climate change resilience . Academic Qualifications Postgraduate Certificate in Academic Practice (University of Reading, 2016) PhD in Built Environment (University of Nottingham, 2009) MSc in Computer Science (University of Glasgow, 2002) BSc in Physics (University of Nottingham, 2001) His research interests span the dynamics of energy demand in socio-technical systems, urban heat fluxes, pollution exposure modeling, and climate adaptation strategies. He has developed novel models for energy demand-side management , building environmental control , and urban climate interactions . Recent publications highlight his expertise in areas such as EV charging infrastructure , urban tree radiative performance , phase change material storage , and anthropogenic heat emissions . His work often involves interdisciplinary collaborations with institutions like the Centre for Research into Energy Demand Solutions and the Institute of Physics . Smith supervises a diverse group of postgraduate students and contributes extensively to teaching modules including Numerical Modelling and Programming and Urban Sustainability . His professional affiliations include the Institute of Physics , International Association of Urban Climatology , and the Higher Education Association .
Jonathan Grinham is an Assistant Professor of Architecture at Harvard University's Graduate School of Design (GSD). His research bridges material science, building science, and design to address climate change challenges, focusing on lifecycle carbon emissions, thermal health, and sustainable material systems. He is affiliated with the Harvard Center for Green Buildings and Cities, the Salata Institute for Climate and Sustainability, and the Aizenberg Lab at the Harvard John A. Paulson School of Engineering and Applied Sciences. Education: Architecture and Building Science, Virginia Tech Doctor of Design, Harvard GSD Grinham's work has produced novel technologies like the DryScreen vacuum membrane dehumidification system and the Vesma cooling solution, alongside publications, patents, and the start-up company Trellis Air Corporation. His research explores bioinspired microchannel designs, radiative sky cooling, and upcycling agricultural waste such as wool into building materials. Research Trends: His recent publications emphasize decoupling HVAC processes for energy efficiency, bioinspired material systems (e.g., duck feather hydrophobic coatings), and lifecycle carbon accounting for buildings. Projects like HouseZero and Origami Microfluidics highlight synergies between material geometry, thermal performance, and environmental impact reduction. Teaching and Collaboration: Grinham teaches courses on building simulation, materials, and thesis work. He collaborates with institutions like the Wyss Institute, Columbia University's Yu Lab, and industry partners including Faveker and American Woolen Company, mentoring students in hands-on climate-responsive design projects like the Sixteen Student Stools exhibition.
Ahmad Fakheri is Professor of Mechanical Engineering at Bradley University’s Caterpillar College of Engineering & Technology . He has served the university for more than two decades, including as Interim Associate Provost & Dean of the Graduate School (1996-1998) and Director for Research & Sponsored Programs (1992-1996). A triple alumnus of the University of Illinois at Urbana-Champaign (B.S., M.S., Ph.D., all in Mechanical Engineering), he is an ASME Fellow recognized for exceptional research and service. Education Ph.D., Mechanical Engineering, University of Illinois at Urbana-Champaign M.S., Mechanical Engineering, University of Illinois at Urbana-Champaign B.S., Mechanical Engineering, University of Illinois at Urbana-Champaign Research Interests Dr. Fakheri’s scholarship lies at the intersection of heat transfer , fluid mechanics and thermodynamics , with concentrated effort on heat-exchanger design and optimization . His work employs second-law analysis, entropy-generation minimization and advanced numerical techniques to enhance thermal efficiency and guide sustainable energy-system development. Scientific Awards & Honors Fellow, American Society of Mechanical Engineers (ASME) Outstanding Research Award, Bradley College of Engineering Outstanding Service Award, ASME Process Industries Division NASA Summer Faculty Fellow, NASA Lewis Research Center Caterpillar Fellows Program Research Award Leadership & Service Within ASME he has chaired the Process Industries Division (6,000+ members) and the Manufacturing Technical Group (10,000+ members), served on the Board on Research and Technology Development, and acted as Technical Program Chair for the 2012 ASME International Mechanical Engineering Congress. On campus he has been a member of the University Senate and has led curriculum-reform initiatives. Laboratory & Teaching Dr. Fakheri teaches undergraduate and graduate courses such as Heat Transfer , Advanced Heat Transfer , Advanced Fluid Dynamics and Advanced Computer-Aided Design , integrating computational tools and real-world design projects that connect classroom theory to industrial practice.
Fabiano Pallonetto is a Professor at Maynooth University's School of Business, with affiliations to the Hamilton Institute and Innovation Value Institute (IVI). He combines academic research with industry experience in energy, IT, and transport sectors. Role: Professor Location: Room 314, Maynooth University Contact: Fabiano.Pallonetto@mu.ie His research focuses on smart grid integration, energy system optimization, and sustainable development. Key projects include: NexSys (Funded Investigator): Developing net-zero energy pathways FLOW (Principal Investigator): Flexible EV-grid integration RES4CITY (Coordinator): Workforce upskilling for renewables Recent publications analyze energy flexibility software, deep learning optimization models, phase change materials for thermal storage, and blockchain security frameworks. His work spans smart cities , renewable integration , and AI-driven energy systems . Student Supervision: Currently advising MR B. Mohseni-Gharyehsafa (PhD research).
Li Yiju is an Assistant Professor and doctoral supervisor in the Department of Mechanical and Energy Engineering at the Southern University of Science and Technology (SUSTech) . He earned his Ph.D. in Materials Science and Engineering from Harbin Engineering University in 2018 and was a joint Ph.D. student at the University of Maryland, College Park from 2015 to 2017. He conducted postdoctoral research at Peking University (2018-2021) and Hong Kong University of Science and Technology (2021-2022). Education: Ph.D. in Materials Science and Engineering, Harbin Engineering University (2013-2018) Joint Ph.D. student, University of Maryland, College Park (2015-2017) B.S. in Applied Chemistry (Energy Electrochemistry), Harbin Engineering University (2009-2013) Research Interests: Dr. Li's research lies at the intersection of energy storage , materials science , and micro/nano-manufacturing . His work focuses on high-energy-density lithium metal batteries , solid-state batteries , and advanced electrolyte design . He also pioneers interfacial photothermal steam conversion and leverages cutting-edge techniques like 3D printing , electrospinning , and Joule heat pulse for energy applications. Scientific Impact: With over 100 publications in journals like Nature Energy , Joule , Advanced Materials , and PNAS , his work has garnered 17,000+ citations and an H-index of 60 . His research has been highlighted by Nature and international media like ScienceDaily and VOA News . Awards & Recognition: Clarivate Global Highly Cited Researcher (2020-2022) Stanford University’s Top 2% Scientists (2022) National Postdoctoral Program for Innovative Talent (2018) Peking University Boya Postdoctoral Fellowship (2018) Editorial & Leadership Roles: He serves as an editorial board member for journals like Journal of Energy Chemistry and The Innovation and as a reviewer for Nature Communications , Advanced Materials , and others. Grants & Projects: National Natural Science Foundation of China China Postdoctoral Innovative Talent Support Program Beijing Natural Science Foundation Analog Devices Project
Amirhosein Taherkordi is a Professor in the Networks and Distributed Systems group at the Department of Informatics, University of Oslo, Norway. His research focuses on resource-efficiency, scalability, adaptability, dependability, mobility and data-intensiveness of distributed systems for emerging computing technologies including Internet of Things (IoT), Fog/Edge/Cloud Computing, and Cyber-Physical Systems (CPS). Dr. Taherkordi received his Ph.D. from the Informatics Department at the University of Oslo under the supervision of Prof. Frank Eliassen, with his thesis titled "Programming Wireless Sensor Networks: From Static to Adaptive Models." He holds an M.Sc. in Information Technology Engineering (Software Engineering) from University of Science and Technology and a B.Sc. in Computer Engineering from Sharif University of Technology. His research spans multiple domains of distributed systems with emphasis on practical applications. He investigates energy efficiency in wireless sensor networks, communication optimization in IoT systems, and adaptive resource allocation in edge computing environments. His work addresses critical challenges in network traffic classification, federated learning for vehicular networks, and data processing across heterogeneous platforms. Analysis of his recent publications reveals a strong trajectory toward communication-efficient federated learning techniques for vehicular networks, energy-aware protocols for IoT data collection, and advanced machine learning approaches for network traffic analysis. His research consistently focuses on optimizing resource usage while maintaining system performance and privacy in distributed architectures. Dr. Taherkordi actively contributes to several research initiatives including the CPS Lab at UiO for Cyber Physical Systems, DILUTE: Fluid Service Abstraction for Large-Scale Cloud IoT Systems, and the Gemini Centre on IoT at UiO. His work bridges theoretical advances with practical implementations in transportation systems, environmental monitoring, and industrial automation.
