Find Academic Supervisors

• Smart Communities
• Next-generation Mobility Systems
• Unused Biomass Utilization Technologies
• +6 more

Hiroshi Onoda is a Professor at the Faculty of Science and Engineering and Graduate School of Environment and Energy Engineering , Waseda University. His work focuses on environmentally friendly design , LCA , resource recycling , renewable energy systems , and smart communities . He holds a Doctor of Engineering from Waseda University and has held various leadership roles, including Dean of the Graduate School of Environment and Energy since 2022. Education : PhD in Mechanical Engineering (Waseda University, 2006) Professional Leadership : Environment Energy Advisor (Saitama Prefecture, 2010–2015), Director of Waseda Environmental Institute Co., Ltd. (2011–2017) Research Themes : Onoda’s research spans smart waste management , EV integration , CO2 reduction , and renewable energy deployment . He emphasizes AI and IoT applications in waste systems, decentralized energy solutions for developing nations, and decarbonization strategies for urban and industrial contexts. Publication Trends : His recent work addresses AI-driven recycling optimization , community-level GHG inventories , and DAC-based fertilizer systems , reflecting his commitment to circular economy and low-carbon mobility . Key sub-fields include robotic waste sorting , decentralized energy planning , and plastic recycling economics . Scientific Awards : Environment Minister’s Commendation (2024) Best Paper Award, ICET4SD (2021) JSME Environment Division Award (2014) JSME Research Encouragement Award (2018) Grants and Projects : Onoda has led nationwide evaluations of low-carbon industrial zones , hydrogen utilization , and plastic recycling policies . He contributes to Japan’s decarbonization roadmap through roles in NEDO and Ministry of the Environment committees. Labs and Initiatives : He founded the Waseda Environmental Research Institute, Inc. (2003) and drives innovation through the BRIDGE LIFE Platform for smart communities in Japan.

David FannonView profile

Associate Professor

• Sustainable Building Design
• High Performance Building Design
• Persistent Architecture
• +5 more

David Fannon is an Associate Professor at Northeastern University, holding dual appointments in the School of Architecture and the Department of Civil and Environmental Engineering. He specializes in sustainable and high-performance building design, with a focus on persistent architecture, resilience, and human health in the built environment. Fannon earned his B-Arch from Rensselaer Polytechnic Institute (2005) and an MS in Building Science and Sustainability from UC Berkeley (2015). He is a licensed architect in New York and a LEED Accredited Professional. His research explores strategies for designing buildings that adapt to future needs, including grid-interactive efficient systems, climate-resilient infrastructure, and occupant-centric comfort models. Notable projects include DOE-funded studies on scalable building equipment performance and a Latrobe Prize-winning investigation into future-use architecture. Fannon also co-curated the 'DURABLE' exhibition on sustainable material innovations. Grants & Leadership: Co-PI on DOE grants for grid-interactive building technologies and Northeastern’s Building Resilience tools. Awards: Latrobe Prize (AIA College of Fellows). Professional Affiliations: American Institute of Architects, ASHRAE, SBSE, and BETES. Fannon advises students on sustainable building systems and co-op opportunities, mentoring graduates like Sowdamini Ponnada and Dane Brimmeier. His work bridges architecture, engineering, and policy to create resilient and adaptable built environments.

Tyler HollettView profile

Associate Professor

• Interest-driven learning
• Learning in informal settings
• Digital media and learning
• +5 more

Dr. Tyler Hollett serves as an Associate Professor of Learning Sciences in the Department of Learning and Performance Systems at The Pennsylvania State University, contributing to the Learning, Design, and Technology program from 315 Keller Building, University Park, PA. His research champions interest-driven learning often devalued by formal institutions and neoliberal markets, investigating contexts like skateboarding, video gaming, and nature hobbies (fishing, birding). Hollett examines how passion-fueled activities generate embodied, affective learning that transcends goal-oriented education, advocating for equitable alternatives to capitalist learning trajectories. Current projects focus on intergenerational play through the FIGMENT Lab, exploring family gaming dynamics, climate engagement via outdoor hobbies, and evolving children's play across settings. Analysis of his recent publications reveals a methodological commitment to qualitative inquiry, with recurring themes of spatial-temporal rhythms, affective atmospheres, and embodied cognition. His work bridges learning sciences, critical pedagogy, and digital media studies, increasingly emphasizing intergenerational and ecological dimensions of informal learning. No scientific awards are listed in his current profile. However, Hollett actively mentors graduate students, inviting collaboration on FIGMENT Lab initiatives. His advising philosophy emphasizes rigorous scholarship within supportive, interest-driven research teams, with the FIGMENT Lab representing his current focus on family-centered learning in gaming, nature, and play contexts.

Sarah B. JohnstonView profile

Associate Professor

• Energy and Environmental Economics
• Industrial Organization
• Renewable Energy Policy
• +3 more

Sarah B. Johnston is an Associate Professor in the Department of Economics at the University of Calgary's Faculty of Arts. Her research focuses on energy and environmental economics, industrial organization, and policy analysis. She holds a PhD and has contributed significantly to understanding renewable energy adoption, climate policy impacts, and energy equity issues. Key research interests include evaluating policy instruments for renewable energy deployment, analyzing the socioeconomic effects of energy subsidies, and examining how legal and regulatory frameworks influence investment decisions in energy sectors. Her work integrates empirical methods with theoretical economic models to address real-world challenges such as grid reliability, air pollution disparities, and household energy vulnerability. Recent publications emphasize the intersection of energy infrastructure and public policy, including studies on interconnection queues for renewable projects, the implications of private backup power systems for grid stability, and the distributional impacts of EV subsidies. Her research often highlights equity concerns, particularly for marginalized communities like American Indian populations and low-income households. Dr. Johnston has authored/co-authored peer-reviewed articles in top journals such as the Journal of the Association of Environmental and Resource Economists and Nature Energy. She collaborates with institutions like NBER and maintains active working papers exploring grid expansion barriers and policy uncertainty effects. Contact: 412 Social Science Building, University of Calgary (AB, Canada) | sarah.johnston2@ucalgary.ca

• Power Electronics
• Building Automation
• Smart Grids
• +7 more

Dr. Andrzej Ożadowicz is a University Professor at the Department of Power Electronics and Automation of Energy Conversion Systems within the Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering at AGH University of Science and Technology in Kraków, Poland. His office is located in room 510, building C-1, with contact details including phone +48 12 617 50 11 and email ozadow@agh.edu.pl. He holds PhD, DSc, and Engineering degrees, reflecting his dual expertise in academic research and practical engineering applications. His research spans Power Electronics, Building Automation, Smart Grids, and IoT-driven energy systems. Key interests include energy efficiency optimization through digital twins and BIM, distributed energy resource integration , and AI-enhanced demand management . Notably, he pioneers applications of deep reinforcement learning in home energy systems and develops frameworks for Smart Readiness Indicator implementation. His work bridges theoretical innovation with practical case studies in building thermal modeling and dynamic façade systems. Recent publications (2021-2025) reveal three dominant trends: (1) Convergence of digital twin technology with building automation for real-time energy management; (2) Critical analysis of IoT security and interoperability in smart infrastructure; (3) Pedagogical innovations in engineering education through blended learning methodologies post-COVID-19. His scholarly output demonstrates consistent focus on energy transition challenges and smart grid evolution. Professor Ożadowicz actively contributes to the Discipline Council for Automation, Electronics, Electrical Engineering and Space Technologies at AGH. He is instrumental in the AutBudNet initiative —a network of certified laboratories for energy efficiency assessment that implements "learning by doing" principles in building automation education. His work with this consortium emphasizes practical validation of smart grid technologies and demand response systems.

• Cybersecurity
• Cyber-Physical Systems (CPS)
• Safety Engineering
• +3 more

Dr. Luca Castiglione is a Research Associate in Resilience and Safety to Cyber Attacks at the Department of Computing, part of the Faculty of Engineering at Imperial College London. His work focuses on interdisciplinary cybersecurity challenges in cyber-physical systems (CPS), emphasizing the intersection of safety and security. Research interests include threat modeling for CPS, hazard analysis in smart grids and aviation systems, and secure file storage in cloud environments. His methodologies often combine systems theory with practical frameworks like assurance case generation and cooperative communication protocols over 5G. Recent publications explore automated detection of safety-critical attacks, impact analysis of cyber threats on flight management systems, and security-aware hazard analysis for infrastructure systems. While no awards or grants are explicitly mentioned, his research demonstrates expertise in cross-disciplinary approaches to system resilience. His location is listed as the Huxley Building on the South Kensington Campus, though no email or educational background details are provided in the available text.

• Control Systems
• Optimization
• Market Design
• +4 more

Junjie Qin is an Assistant Professor of Electrical and Computer Engineering at Purdue University’s Elmore Family School of Electrical and Computer Engineering. His research focuses on control systems, optimization, market design, and data analytics applied to power systems and the energy-transportation nexus. He explores challenges in distributed energy resource management, smart grid technologies, and the integration of renewable energy sources. His work addresses issues such as scheduling under limited observability, neural risk-limiting dispatch, and joint optimization of transportation-energy systems through electric vehicle charging strategies. Key research areas include power system stability, inverter-dominated grid dynamics, and machine learning applications in energy systems. He investigates topics like real-time charging control for electric roadways, loss function selection in learning-based optimal power flow, and pricing mechanisms for workplace EV charging. His contributions span theoretical frameworks and practical algorithms, emphasizing data-driven solutions and system-level optimization. While no awards or grants are explicitly listed, his publications reflect a strong focus on advancing smart grid technologies and sustainable energy systems. His advising activities are not detailed here, but his research group likely engages in cutting-edge projects at the intersection of control theory and energy infrastructure.

Fernando CamelliView profile

Associate Professor

• Computational Fluid Dynamics (CFD)
• Urban Environmental Modeling
• Contamination Dispersion Modeling
• +3 more

Fernando Camelli is an Associate Professor in the Physics & Astronomy Department at George Mason University, holding dual roles as Instructional Faculty and Faculty. His research focuses on computational fluid dynamics (CFD), urban environmental modeling, and high-performance computing. He specializes in simulating complex fluid flows in urban environments, subway systems, and industrial applications, with particular emphasis on turbulence modeling, fluid-structure interaction, and GPU-accelerated algorithms. Key research areas include: CFD for urban airflow and contamination dispersion Meshless and immersed boundary methods Integration of geographic information systems (GIS) with CFD Large-scale simulations using parallel computing His work addresses practical challenges such as subway ventilation optimization, emergency contaminant dispersion prediction, and urban infrastructure design. Recent studies emphasize scalability improvements for fluid-structure interaction simulations and GPU-based code modernization.

Xuming HeView profile

Associate Professor

• Computer Vision
• Machine Learning
• Artificial Intelligence
• +9 more

Xuming He is an Associate Professor at the School of Information Science and Technology (SIST), ShanghaiTech University, where he leads the PLUS Lab. His research spans computer vision and machine learning with a focus on developing algorithms that operate effectively under limited supervision and evolving data conditions. His core research interests include weakly-supervised and few-shot learning for scenarios with sparse annotations, continual learning frameworks for knowledge retention during sequential task acquisition, semantic segmentation techniques for scene understanding, and multimodal vision-language representations. He emphasizes interpretable machine learning to build transparent AI systems capable of human-understandable reasoning, addressing critical challenges in model trustworthiness and deployment reliability. Recent publications reveal strong trends toward novel class discovery in long-tailed recognition scenarios, physics-informed generative modeling for scientific applications, and robust segmentation under distribution shifts. His work increasingly integrates large language models for multimodal reasoning while maintaining focus on efficiency in resource-constrained environments like robotic grasping and medical imaging analysis. He actively mentors students, having supervised Qian He to PhD completion and Chuanyang Hu to Master's degree in 2023. He welcomes prospective graduate students through ShanghaiTech's Computer Science & Technology program and offers undergraduate research projects requiring minimum six-month commitments. The PLUS Lab under his direction drives innovation in learning under supervision constraints, with recent work spanning medical tumor analysis, cross-view geolocation, photonic computing, and semiconductor design verification. The lab's research bridges theoretical advances with practical applications across healthcare, robotics, and scientific discovery domains.

Jonathan BuonocoreView profile

Assistant Professor

• Environmental Health
• Climate Mitigation Strategies
• Energy Policy Analysis
• +4 more

Dr. Jonathan Buonocore is an Assistant Professor in Environmental Health at the Boston University School of Public Health and Core Faculty at the Institute for Global Sustainability (IGS). His research evaluates health impacts of energy systems, focusing on climate mitigation strategies' co-benefits, equity, and unintended consequences. He holds a Sc.D. and MS from Harvard School of Public Health and a BS from Clarkson University. Education: Sc.D., Environmental Science & Risk Management, Harvard School of Public Health MS, Environmental Health, Harvard School of Public Health BS, Environmental Science & Policy, Clarkson University Research Interests: Dr. Buonocore examines energy systems through integrated frameworks combining health impact assessment, risk modeling, and energy policy analysis. Key areas include: Health co-benefits of renewable energy expansion Air pollution consequences of fossil fuel infrastructure Environmental justice in energy transitions Geoengineering health risks Recent work analyzes electrification policies, methane leakage risks, and extreme climate interventions. Articles emphasize spatial equity in exposure to oil/gas development and transportation policies. Grants & Advising: His research is supported by grants focusing on energy-climate-health linkages. He advises on projects related to decarbonization pathways and environmental justice. Labs & Collaborations: Associated with IGS and prior work at Harvard's Center for Climate, Health, and Global Environment. Collaborates with environmental justice organizations on policy-relevant research.

• Sustainable Development
• Low-Carbon Technologies
• Energy and Building Technology
• +13 more

Dr. Behrang Vand Alimohammadisagvand is a Lecturer at the School of Computing, Engineering and the Built Environment, Edinburgh Napier University. His research focuses on sustainable energy systems, building performance, and smart energy management, with strong international collaboration across Iran, China, Finland, and the UK. B.Sc. and M.Sc. in Mechanical and Energy Engineering Ph.D. in Energy and Building Technology His research interests include sustainable development, low-carbon technologies, energy policy, thermal comfort in buildings, and energy management systems at multiple scales. He actively investigates model predictive control (MPC), demand response, energy sharing in communities, and low-temperature heating networks. His work bridges theoretical modeling and practical implementation in real-world buildings. Dr. Vand's recent publications highlight trends in integrated energy management , smart grid optimization , and decarbonization of building heating systems . His articles emphasize mathematical modeling, simulation, and control strategies to improve energy efficiency and reduce carbon emissions in the built environment. He supervises doctoral students working on smart IoT systems and low-temperature heat networks. His research is supported by funders such as the Academy of Finland and Energy Technology Partnership. Active supervisor for PhD project on smart IoT systems with real-time deep learning (since 2022) Director of Studies for PhD on heating Scottish public buildings with low-temperature networks (2018–2024) He is affiliated with the Institute for Sustainable Construction and contributes to the research theme Culture and Communities . His work aligns with global efforts toward net-zero emissions and sustainable urban development.

Kevin J. KircherView profile

Assistant Professor

• Energy Infrastructure Optimization
• Climate Change Mitigation
• Power Grid Interaction
• +4 more

Kevin J. Kircher is an Assistant Professor at Purdue University in the Departments of Mechanical Engineering and (by courtesy) Electrical and Computer Engineering. He works in Herrick Laboratories and the Institute for Control, Optimization and Networks, focusing on optimization and control strategies for distributed energy resources (DERs) to address climate change, pollution, and energy equity issues. Education: PhD in Mechanical Engineering (Cornell University), Postdoctoral Research in Electrical Engineering (MIT) His research spans DERs like electric vehicles, solar PV, and heat pumps, with a focus on grid interaction and energy system modeling for business/government decisions. He co-developed EDGIE, an open-source MATLAB/Python tool for electrification impact simulation. Recent publications analyze methane emissions in energy infrastructure, predictive HVAC control systems, and grid capacity challenges for residential electrification. His team has secured multiple ASHRAE grants and fellowships, with field studies on thermal storage and grid protection protocols. Mentorship priorities include diversity in energy research, with active recruitment of graduate students skilled in optimization, control theory, and thermal sciences. He leads a course on DERs with open-access materials.

• Management
• Sustainable Supply Chain Management
• Digital Transformation
• +3 more

Andrea Appolloni is an Associate Professor at the Department of Management and Law, University of Rome Tor Vergata. His academic career focuses on Management with emphasis on Sustainable Supply Chain Management , Digital Transformation , and Circular Economy . His research explores the intersection of technological innovation and sustainability, particularly through topics like AI in Logistics , Green Procurement , and Policy Optimization . Publications span both theoretical frameworks and empirical studies in China, Italy, and Malaysia, with a strong focus on environmental impact and organizational performance. Recent work includes digital twin applications for human-AI collaboration, blockchain integration in sustainable supply chains, and analyzing barriers to circular economy adoption. His 15 most recent articles (2025-2022) demonstrate a trend toward combining Artificial Intelligence , Operations Management , and Environmental Governance .

Akhtar HussainView profile

Assistant Professor

• Power Systems
• Smart Grids
• Energy Storage
• +6 more

Akhtar Hussain serves as an Assistant Professor in the Department of Electrical and Computer Engineering at Laval University, Quebec. His research centers on AI-driven optimization of power and energy systems, with emphasis on microgrid resilience, distributed energy resource integration, and electric vehicle-grid interactions. He actively contributes to advancing grid reliability through innovative resource allocation and consumer satisfaction frameworks. Ph.D. in Electrical Engineering, Incheon National University, South Korea (2019) M.Sc. in Electrical Engineering, Myongji University, South Korea (2014) B.Sc. in Electrical Engineering, National University of Sciences and Technology, Pakistan (2011) Dr. Hussain's research spans power systems resilience, smart grid technologies, and equitable energy access. His work integrates artificial intelligence with traditional power engineering to address challenges in microgrid operation, electric vehicle integration, and renewable energy management. Key focus areas include developing algorithms for optimal resource utilization, enhancing grid stability during contingencies, and designing frameworks for fair energy distribution in diverse communities. His recent publications (2023-2025) reveal a strong trajectory toward AI-enhanced grid management, with recurring themes of resilience optimization, equity-focused resource allocation, and electric vehicle-grid synergies. The research demonstrates increasing sophistication in handling uncertainty through machine learning while addressing socio-technical dimensions of energy transition. Dr. Hussain currently supervises one Master's student and has guided five Ph.D. candidates to completion. His research is funded by a Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant ($160,000/year) for the project 'Grid Condition and Resilience-Aware Incentivization and Deployment of Distributed Energy Resources' (2024-2029), supplemented by a Springboard to Discovery award ($40,000) for 2024-2025. As an IEEE member, he collaborates with industry partners on real-world grid modernization initiatives, focusing on practical implementation of resilience strategies through microgrids and mobile energy resources.

Teng WuView profile

Professor

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