Dr. Lilianna Wojtynek is a Lecturer at the Department of Logistics, Faculty of Production Engineering and Logistics, Opole University of Technology. Her academic career focuses on logistics, production engineering, and industrial safety. Current Position: Lecturer in Logistics Department: Logistics School: Faculty of Production Engineering and Logistics University: Opole University of Technology Research interests span logistics systems, quality management, and transportation safety. Key themes include: Lean methodologies (5S, supply chain optimization) Industry 4.0 applications in logistics Risk analysis in transportation and logistics Production process planning and decision modeling Articles trends emphasize industrial safety, logistics efficiency, and technology integration in transportation. Notable subfields include dynamic forklift testing, BRT systems, and hazardous material storage.
Daehyeok Kim is an Assistant Professor in the Department of Computer Science at The University of Texas at Austin, where he co-leads the UT Networked Systems Research Group and participates in the Wireless Networking and Communications Group and 6G@UT. He serves as co-PI for the LDOS NSF Expeditions in Computing project, a major initiative rethinking operating systems through AI. His educational background includes a Ph.D. in Computer Science from Carnegie Mellon University under advisors Vyas Sekar and Srinivasan Seshan, where his dissertation introduced abstractions for elastic in-network computing. He also earned B.S. and M.S. degrees in Computer Science and Engineering from POSTECH, South Korea, followed by research scientist work at KAIST prior to his Ph.D. Kim's research centers on hardware-software co-design for cloud and edge data centers, targeting speed, efficiency, and resilience. Key projects include resource management for programmable infrastructure, robust cellular network design, end-to-end network transport frameworks, and learning-directed operating systems. His work bridges computer networks, operating systems, distributed systems, and 5G/6G technologies, with emphasis on virtualized radio access networks (vRAN) and edge computing challenges. Analysis of his recent publications reveals a dominant focus on enhancing 5G/6G infrastructure reliability—particularly in virtualized RANs—through innovations in failover mechanisms, integrity protection, and latency-sensitive resource allocation. His research consistently addresses critical industry pain points like sub-second availability requirements, fronthaul security vulnerabilities, and end-to-end service-level objective (SLO) guarantees for mobile-edge applications. Notable scientific awards include: NSF CAREER Award (2025) for advancing cloud hardware efficiency Microsoft Research PhD Fellowship (2019) Bronze Award at Samsung HumanTech Paper Awards (2018) Qualcomm Innovation Awards (2016) His grant portfolio features leadership in the $10M+ LDOS NSF Expeditions project and the NSF CAREER award, both driving transformative work in AI-integrated operating systems and resilient network infrastructure. These projects demonstrate strong industry-academia collaboration with Microsoft Research, wireless vendors, and cloud providers. Kim co-leads the UT Networked Systems Research Group, which operates within the Wireless Networking and Communications Group and 6G@UT consortium. These labs maintain a 5G/6G testbed for Open RAN validation and focus on solving real-world problems in cellular infrastructure, edge computing, and network security through close partnerships with industry leaders.
Dr. Tobias Binninger is a researcher at the Institute of Energy Technologies (IET) within Forschungszentrum Jülich GmbH, Germany. His work focuses on theoretical and computational modeling of materials for electrochemical energy systems , particularly in the context of catalysts and solid-state electrolytes. His research spans topics such as electrochemical interfaces , redox reactions , quantum capacitance , and nanoparticle stability , as reflected in his publications in high-impact journals. He has contributed significantly to understanding the Oxygen Evolution Reaction (OER) mechanisms and solid-state electrolyte materials through advanced computational methods like quantum annealing and density functional theory. Recent studies highlight his focus on electrolyte correlation effects , metal-support interactions , and co-electrolysis cell design for CO 2 reduction. Despite lacking explicit details on awards or mentoring, his work addresses critical challenges in energy storage , catalyst degradation , and quantum modeling of electrochemical systems .
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 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 .
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.
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 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.
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 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.
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 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
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.
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.
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.
