Find Academic Supervisors

• Sustainable Energy
• Microgrid Technology
• Energy Systems
• +4 more

Nathan Johnson is an Associate Professor at Arizona State University (ASU) within the Ira A. Fulton Schools of Engineering's Polytechnic School. He directs the Laboratory for Energy And Power Solutions and the ASU-Starbucks Center for the Future of People and the Planet, while serving as Assistant Director of Research for the Global Futures Laboratory. His work focuses on sustainable development through energy decarbonization, microgrid innovation, and public-private partnerships. Ph.D. Mechanical Engineering, Iowa State University (2012) M.S. International Development & Mechanical Engineering, Iowa State University (2008, 2005) B.S. Mechanical Engineering, Iowa State University (2004) Research interests span microgrid resilience , energy-water-food nexus , grid modernization , and resource circularity , with applications in defense energy security, global energy access, and climate adaptation. His recent publications examine cascading infrastructure failures, hydrogen's role in decarbonization, and AI-driven solar panel diagnostics, reflecting interdisciplinary work in energy economics , control systems , and climate-resilient infrastructure . Over $70 million in funding includes projects like: DoD-funded microgrid resilience programs ($1.05M, 2022) World Bank climate-adaptive energy solutions in West Africa ($39.95M, 2021) NSF grants for urban resilience modeling ($3.6M, 2019) As leader of ASU's LEAPS initiative, he develops deployable energy solutions for disaster relief and underserved communities, combining hardware innovation with workforce development programs for veterans and civilians.

Luo MaiView profile

Assistant Professor

• Computer Systems
• Machine Learning Systems
• Data Management
• +3 more

Luo Mai is an Assistant Professor at the University of Edinburgh's School of Informatics , with an upcoming promotion to Associate Professor (UK Reader) in August 2025. He leads the Large-Scale Machine Learning Systems Group and co-leads the UK EPSRC Centre for Doctoral Training in Machine Learning Systems and an ARIA Project on Scaling AI Compute by 1000X . PhD in Computer Science (Imperial College London, 2018) MRes in Advanced Computing (Imperial College London, 2012) His research focuses on the intersection of computer systems , machine learning , and data management . Key contributions include award-winning systems like WaferLLM (wafer-scale LLM inference), Tenplex (elastic ML), and ServerlessLLM (serverless LLM serving), published at top venues (OSDI, SOSP, ICML, NeurIPS, JMLR). Recent publications demonstrate trends in GPU-based distributed systems , LLM optimization , and adaptive machine learning . His team has developed groundbreaking open-source projects including TensorLayer , TorchOpt , and ServerlessLLM . Awarded Microsoft Research StarTrack Scholar (2024) , secured ARIA grant (2024) with Imperial College & Cambridge University, and received Google Fellowship during PhD (2012-2016). As an educator, he designed Edinburgh's popular Machine Learning Systems course (150+ students). His group supervises multiple PhD students including Yao Fu (recognized as 2024 Rising Star in ML & Systems) and Leyang Xue .

Emiliano CasatiView profile

Lecturer

• Sustainable energy engineering
• Decarbonization of heat
• Solarization of high-temperature industrial processes
• +3 more

Dr. Emiliano Casati is a Lecturer at the Department of Energy and Process Systems Engineering within the College of Mechanical and Process Engineering at ETH Zürich. His work focuses on sustainable energy engineering, particularly in decarbonizing high-temperature industrial processes and advancing solar thermal technologies. Research Interests: Sustainable energy engineering Decarbonization of heat Solarization of high-temperature industrial processes Thermal energy storage Conceptualization and prototyping of novel energy concepts Measurement of thermodynamic properties Publications Trends: Dr. Casati's recent research spans solar thermal systems (e.g., organic Rankine cycles, thermal trapping), computational tools for heat transfer simulation (FIVER), experimental thermodynamics, and industrial decarbonization. His work bridges historical analysis with cutting-edge technical innovation. Collaborations: He collaborates with leading experts like André Bardow (ETH Zürich) and Aldo Steinfeld (emeritus, ETH Zürich), contributing to multidisciplinary projects in renewable energy and process engineering.

• Corporate Finance
• Corporate Social Responsibility
• Happiness Economics
• +3 more

Leonardo Becchetti is a Full Professor at the University of Rome Tor Vergata's Department of Economics and Finance, teaching Microeconomics and Topics in Applied Economics for the 2025-2026 academic year. Based in room P2 S55, he maintains an active research profile with email contact becchetti@economia.uniroma2.it. His research centers on Corporate Finance, Corporate Social Responsibility, and Happiness Economics, extending to Sustainable Development and Ecological Transition. He investigates how economic structures influence well-being through relational goods, generativity, and sustainability frameworks, employing game-theoretic and empirical methodologies to analyze climate action, AI impacts, and cooperative behavior. Analysis of his 2024-2025 publications reveals intensifying focus on ecological transition mechanisms, including renewable energy communities, circular economy governance, and sustainable investment models. His work increasingly integrates climate economics with behavioral insights, examining conditional cooperation in environmental actions and AI's disruption of labor markets. No scientific awards or student advising information is publicly documented. He participates in departmental research initiatives including DEF Seminars and ROBO Seminars, contributing to the university's research centers on economic and social impact.

Margaret GarciaView profile

Associate Professor

• Water Resource Management
• Urban Infrastructure
• Watershed Hydrology
• +6 more

Margaret Garcia is an Associate Professor at the School of Sustainable Engineering and the Built Environment , Arizona State University (ASU). She is affiliated with multiple research centers, including the Center for Behavior, Institutions and the Environment (CBIE) , Central Arizona-Phoenix Long Term Ecological Research , Earth Systems Science for the Anthropocene , Water Institute , and Global Futures Scientists and Scholars . Education: Ph.D., Civil and Environmental Engineering, Tufts University (2017) M.S., Civil and Environmental Engineering, University of California-Los Angeles B.S., Civil and Environmental Engineering and B.A., International Studies, Lafayette College (2004) Her research focuses on the sustainability and resilience of urban water systems , using systems analysis to study feedbacks in coupled human-hydrological systems . Key themes include reservoir operations , adaptive infrastructure , water policy , and real-time flood monitoring . Recent work explores equity in water management , institutional dynamics , and green infrastructure optimization . Her 15 most recent publications span topics in socio-hydrology , water policy analysis , climate change adaptation , and urban flood modeling , with applications to the Western Water Network , Colorado River Basin , and transboundary regions like Ambos Nogales. Collaborative projects include NSF-funded initiatives on adaptive reservoir operations , cross-scale interactions , and community-based flood awareness . Scientific Awards: NSF CAREER Grant 1942370 (2020) She mentors students in Ph.D. programs (e.g., Ashish Shrestha , Behshad Mohajer ) and Master’s programs (e.g., Dillon Nys , Krista Lawless ). Her teaching includes graduate courses on research, reading, and thesis advising, alongside undergraduate hydrology classes.

• Chemical Engineering
• Energy Storage Materials
• Lithium-ion Battery Manufacturing
• +4 more

Dr. Yeshui Zhang is a Lecturer at the School of Engineering, University of Aberdeen, UK, since December 2021. Previously, she held a Faraday Institution Research Fellowship at University College London (2018–2021). University of Birmingham (BSc Environmental Management, 2012) University of Sheffield (MSc Energy and Environmental Engineering, 2013) University of Leeds (PhD Chemical and Process Engineering, 2017) Her research spans chemical and environmental engineering, focusing on: Energy storage materials (e.g., lithium-ion batteries) Pyrolysis-catalysis of waste materials High-temperature quartz crystal microbalance applications Carbon nanotubes synthesis Circular economy strategies for plastics Recent publications emphasize catalytic waste valorization for hydrogen-rich syngas, biomass pyrolysis mechanisms, and hybrid-functional catalyst design. She serves as Associate Editor for Carbon Capture Science & Technology and contributes to standards in battery manufacturing. Emerging Investigator Award, IChemE 2022 IAAM Young Scientist Medal 2022 Best Paper Award, 21st CCSSTA 2020 Dr. Zhang supervises PhD students in chemical engineering and leads the Meston Lab 155 at Aberdeen. Her work bridges academic research with industrial applications through memberships in the Royal Society of Chemistry and IChemE.

Julian ShunView profile

Associate Professor

• Parallel Computing
• High-Performance Computing
• Graph Analytics
• +7 more

Julian Shun is an Associate Professor at the Massachusetts Institute of Technology (MIT) in the Department of Electrical Engineering and Computer Science (EECS) and a principal investigator in the Computer Science and Artificial Intelligence Laboratory (CSAIL). Previously, he was a Miller Research Fellow at UC Berkeley and earned his Ph.D. from Carnegie Mellon University under Guy Blelloch. His research focuses on parallel and high-performance computing, with emphasis on graph analytics, spatial/graph clustering, and dynamic algorithms. He designs algorithms with theoretical guarantees and empirical efficiency, along with high-level programming frameworks to simplify parallel code development. His work spans cache-oblivious, external-memory, and streaming graph algorithms, addressing scalability and performance across diverse computational architectures. Julien's recent publications highlight advancements in parallel graph traversal, dynamic connectivity, and approximation algorithms for centrality metrics. His research also explores domain-specific languages like GraphIt for graph analytics and frameworks such as Julienne for work-efficient bucketing. Scientific Awards: Miller Research Fellow at UC Berkeley He has taught graduate-level courses at MIT, including 6.506 (Algorithm Engineering) and 6.886 (Graph Analytics), emphasizing theoretical foundations, experimental analysis, and open-ended research projects.

Yang FanView profile

Associate Professor

• Magnetic Functional Materials
• Silicon-Carbon Anode Materials
• Functional Coating Materials
• +3 more

Yang Fan is an Associate Professor at the Shenzhen University of Technology, currently serving as Deputy Director of the Shenzhen Key Laboratory of Marine Energy and Environmental Safety and Deputy Director of the Center for Frontier Science and Engineering Applications of Surfaces and Interfaces. He is a recipient of the Shenzhen 'Peacock Plan' Overseas High-Level Talent Program and Pingshan District Second Prize in the 2020 Shenzhen Innovation and Entrepreneurship Competition. Educational Background: Bachelor in Materials Science (2006), Huazhong University of Science and Technology Master in Materials Science (2009), University of Alberta PhD in Chemical Engineering (2015), University of Alberta Research Interests: Focuses on magnetic functional materials, silicon-carbon anode materials for lithium-ion batteries, and superhydrophobic coatings. His work on oil-water emulsion stability mechanisms and nanosilver composite applications has been recognized by major energy companies. Prominent Research Trends: Publications highlight advancements in energy storage materials (e.g., potassium-ion battery anodes), functional coatings for water treatment, and innovative carbon encapsulation strategies for silicon nanoparticles in batteries. Scientific Awards: Shenzhen 'Peacock Plan' Overseas High-Level Talent Program Nanshan District Pilot Talent Guangdong Province Yuyue Card 2019 Guangdong Provincial University Achievement Transformation Competition - First Place in Environmental Protection and New Materials 2020 Shenzhen Innovation and Entrepreneurship Competition - Third Place in Finals Grants & Projects: Currently leads the Shenzhen Key Laboratory of Marine Energy and Environmental Safety (5000k RMB, 2021-2023) and co-leads the Shenzhen University of Technology's Center for Surface and Interface Science (10,000k RMB, 2021-2023). Previously contributed to NSERC-funded projects in Canada and Guangdong's leading talent program. Labs & Teams: Associated with the Shenzhen Key Laboratory of Marine Energy and Environmental Safety and the Center for Surface and Interface Science and Applied Engineering at Shenzhen University of Technology.

• Total Productive Maintenance
• Artificial Intelligence
• Multi-Criteria Decision Making
• +3 more

Ebru Turanoglu Bekar is a Senior Lecturer at the Department of Industrial and Materials Science, Chalmers University of Technology, specializing in Smart Maintenance and Production Systems. She contributes to the Production Service Systems & Maintenance research group. Research Interests: Total Productive Maintenance (TPM), Artificial Intelligence applications in manufacturing, Multi-Criteria Decision Making, Performance Measurement systems Recent Focus: Development of data-driven algorithms for predictive maintenance, integration of digital twins in industrial contexts Key Projects: Factory SensAI (2025–2028) - Data integration for AI in manufacturing Trustworthy Predictive Maintenance TPdM (2022–2025)

Daniel ValleroView profile

Adjunct Professor

• Environmental Engineering
• Air Pollution
• Climate Change
• +5 more

Daniel Vallero is an Adjunct Professor in the Department of Civil and Environmental Engineering at Duke University . He holds a Ph.D. from Duke (2000) , an M.S. from the University of Kansas (1996) , and a B.A. from Southern Illinois University (1974) . His career spans environmental engineering, exposure assessment, and climate change adaptation, with affiliations including North Carolina Central University (2012-2013) as Associate Professor. Education B.A., Southern Illinois University, 1974 M.S., University of Kansas, 1996 Ph.D., Duke University, 2000 Key Research Areas Environmental systems science Air pollution modeling and control Hazardous waste bioremediation Climate change governance Exposure-based chemical prioritization Biogeochemical cycling under climate stress Publication Trends Focus on PFAS exposure pathways , climate adaptation strategies , and pollutant fate in ecosystems Recent work includes high-throughput exposure models and environmental justice in global warming Scientific Awards Federal Honor Awards (2025) from the U.S. EPA Jeffrey B. Taub Award (1999) at Duke University Notable Contributions Authored Air Pollution Calculations and Environmental Systems Science Developed exposure prioritization tools like Ex Priori Post-9/11 environmental contamination studies in New York City

• Coding Theory
• Network Coding
• Information Theory
• +4 more

Chih-Chun Wang is a Professor at the Elmore Family School of Electrical and Computer Engineering , Purdue University, with additional leadership roles as Associate Head for Facilities, Planning, and Staff. He earned his Ph.D. in Information Sciences and Systems from Princeton University in 2005, following an M.S. (2002) and B.S. (1999) in Electrical Engineering from Princeton and National Taiwan University, respectively. Research Interests: His work spans Network coding (graph-theoretic capacity, wireless network coding, feedback mechanisms) Coding theory (LDPC codes, Reed-Solomon decoding, iterative algorithms) Information theory (multi-user detection, network information theory) Signal processing (turbo equalization, space-time codes) Control theory (optimal stopping theory) Scientific Contributions: He has published extensively on Age-of-Information (AoI) minimization, low-latency coding, and multi-hop relay optimization. His research trends include Integrating machine learning with network coding Wireless security for Beyond-5G systems Distributed storage networks with intelligent helper selection Delay-constrained communication protocols Awards: Recognized as an IEEE Fellow in 2024 for contributions to network coding and information theory. Teaching: He teaches undergraduate courses like ECE301: Signals and Systems and graduate courses such as ECE639: Error Control Coding , with a focus on iterative decoding, LDPC codes, and network information theory. Advising: Supervised 15+ Ph.D. students, including current advisees Pin-Wen Su (delay-oriented coding), Wonjun Lee (cyber-physical systems), and Giles Bischoff (low-latency systems). Former students hold prominent roles at institutions like Google, Meta, and Intel.

• Modelling and Control of Electrical and Electromechanical Systems
• HVDC Systems and DC Grids
• High Power AC/DC and DC/DC Converters
• +3 more

Dr. Aliakbar Jamshidi Far is a Lecturer at the School of Engineering, University of Aberdeen, since December 2017. Previously, he served as a Research Fellow at the Aberdeen HVDC Centre (2012-2017) and as an Assistant Professor at the Iranian Research Organization for Science and Technology (2008-2012). Dr. Jamshidi Far holds a PhD in Electrical Engineering from AmirKabir University (2008), an MSc from Iran University of Science and Technology (1996), and a BSc from Sharif University of Technology (1992). He is an IET Chartered Engineer, Senior Member of IEEE, and member of CIGRE Working Group B4.76. His research focuses on Modeling and control of HVDC systems and DC grids High-power AC/DC and DC/DC converters Hybrid DC circuit breakers Ultrasound applications in Oil & Gas Renewable energy integration Recent publications highlight trends in Modular Multilevel Converters (MMC) for DC grids Flux Switching Machine optimization Ultrasound-based scale removal technology Wave energy for remote islands Smart microgrids for Indonesia and Nigeria Advanced DC circuit breaker designs Dr. Jamshidi Far has secured significant funding including £204k from the Oil & Gas Technology Centre (2019-2021, Co-PI) £42k Consultancy from BP PLC (2019-2020, PI) EU Horizon 2020 PROMOTion Project (2016-2017, Research Fellow) SSE-funded DC converter research (2015-2016, Research Fellow) ERC-funded DC systems modeling (2012-2014, Research Fellow) Teaching responsibilities include Undergraduate: EE3579 - Electrical and Electronic Engineering Design Postgraduate: EG551K/55M5 - Renewable Energy Integration to Grid (Coordinator) EG503V/503W - Solar Energy (Coordinator) EG501H/504B - Electrical Systems for Renewable Energy (Coordinator) He supervises MEng/BEng and MSc students in Renewable Energy, Oil & Gas, and Subsea programs.

• Ocean Renewable Energy
• Robotics
• Biomechanics
• +2 more

Dr. Boyin Ding is an Associate Professor at the University of Adelaide , serving as Academic Director at Haide College and researcher in the Mechanical Engineering department within the Faculty of Sciences, Engineering and Technology. He leads the Wave Energy Research initiative established in 2014, while also contributing to Robotics and Biomechanics through his work with the Flinders Medical Device Research Institute. Research Areas: Ocean Wave Energy Harvesting Control Systems for Renewable Energy 6DOF Robotic Testing Spine Biomechanics Transnational Education Programs Key Collaborations: Australia-China Joint Research Centre for Offshore Wind & Wave Energy Acoustics, Vibration and Control Research Group Scientific Awards: Australian Endeavour Fellowship Malcolm Kinnaird Engineering Excellence Award (2012) His recent publications focus on hybrid offshore energy systems, nonlinear hydrodynamics in wave energy converters, and biomechanical testing technologies. He has developed control algorithms for floating offshore wind-wave systems and pioneered 6DOF robotic platforms for medical applications. As an eligible PhD supervisor, he actively collaborates with global industries and academic institutions.

Roberto ZaninoView profile

Professor

• Computational fluid dynamics
• Nuclear fusion
• Concentrated solar power
• +5 more

Roberto Zanino is a Full Professor of Nuclear Engineering at the Department of Energy (DENERG) of the Polytechnic of Turin, Italy. He serves as Advisor to the Rector for relations with European and international university networks and for the UniTe project, Undergraduate Research Opportunities Coordinator, and Project management functions of PoliToArgentina. He is also Scientific Advisor for the Partnership Agreement with NEWCLEO. Dr. Zanino earned his Laurea cum laude in Nuclear Engineering from Politecnico di Torino in 1984 and his Ph.D. in Energetics in 1989. His academic progression includes Assistant Professor (1990-91), Associate Professor (1992-2000), and Professor (2001-present). He previously served as Director of Alta Scuola Politecnica (2007-2010) and Head of the Graduate Program in Energetics (2011-present). His research spans computational fluid dynamics, concentrated solar power, controlled thermonuclear fusion, Generation IV nuclear fission reactors, and plasma physics. His work focuses on thermal-hydraulic analysis of liquid metal systems, superconducting magnet design for fusion applications, and concentrated solar power optimization. His recent publications demonstrate strong expertise in coupling computational tools for nuclear applications, particularly in CFD-system code integration for liquid metal systems and fusion magnet analysis. Dr. Zanino has received recognition as an IEEE Senior Member (2012) and has supervised numerous doctoral students working on topics including thermal-hydraulic analysis of heavy liquid metal systems, superconducting magnet simulation for fusion applications, and concentrated solar power modeling. He has extensive international experience, having worked at Max-Planck-Institut für Plasmaphysik, Massachusetts Institute of Technology, and University of Illinois at Chicago. He is actively involved in major fusion projects including ITER, DTT (Divertor Tokamak Test facility), and EUROfusion. His teaching portfolio includes Computational Heat and Mass Transfer, Nuclear Fusion Reactor Engineering, Solar Thermal Technologies, and Computational Thermal Fluid Dynamics at both master's and doctoral levels.

• Food Engineering
• Thermal Engineering
• Biophysics
• +3 more

Thijs Defraeye is a Senior Scientist at Empa (Swiss Federal Laboratories for Materials Science and Technology) and Adjunct Professor at Dalhousie University. He holds a PhD in Building Physics from KU Leuven (2011) and a Master's in Civil Engineering (2006). His work focuses on optimizing food supply chains through multiphysics simulations and digital twins, addressing challenges in refrigerated transport, postharvest quality preservation, and energy-efficient food processing. He leads the SimBioSys group, developing solutions for perishable goods logistics and electrohydrodynamic technologies. Research interests include: Biophysics of food systems Digital twin applications in agriculture Electrohydrodynamic drying Thermal management in cold chains Sustainable food technologies Recent work emphasizes reducing food loss through physics-based modeling of refrigerated containers, ventilated packaging optimization, and scalable evaporative cooling systems. His studies bridge engineering principles with biological processes, aiming to enhance global food security and environmental sustainability.