Mikael Johansson is a Professor at Kungliga Tekniska Högskolan (KTH), specializing in Control Technology . He teaches and coordinates courses such as Distributed Optimization (FEL3311) and various advanced-level degree projects in computer science, electrical engineering, and systems engineering. His research spans Control Systems , Machine Learning , and Optimization , with a focus on asynchronous algorithms, federated learning, and applications in energy systems and construction. His work includes 15 recent publications on topics like neural networks, distributed optimization, and battery technology. Notable areas of contribution are in asynchronous learning, federated learning with privacy constraints, and quasi-Newton methods for optimization. His research bridges theoretical advancements with practical applications in urban design, healthcare, and autonomous systems.
Mikael Gidlund is a Full Professor of Computer Engineering at Mid Sweden University in Sundsvall and holds an adjunct professorship at Beijing Jiaotong University, China. He serves as head of the Computer Engineering subject and program manager for the international MSc program in Computer Engineering. His academic journey includes a Ph.D. in Electrical Engineering from Mid Sweden University (2005), followed by roles at ABB Corporate Research (2008-2014) where he led wireless technologies research. Dr. Gidlund's research spans Wireless Communication, Industrial IoT, 5G/6G Networks, and Network Security . His group focuses on AI/ML for beyond-5G wireless communication, time-critical industrial applications, and IoT security. Current research themes include Future Wireless Networks (5G/6G) using AI/ML, Time-and mission-critical wireless communication, Industrial IoT, and IoT Security. His work demonstrates strong interdisciplinary connections between wireless systems, industrial automation, and security. His publication portfolio includes over 200 scientific articles and 20+ patents. Recent publications show a clear trend toward AI/ML integration in wireless systems, NOMA techniques, RIS technologies, and security solutions for industrial applications. The research output demonstrates strong international collaboration across six continents. Best Paper Award at IEEE International Conference on Industrial IT (2014) Co-author of IEEE Sweden VT-COM-IT Joint Chapter Best Student Journal Paper Award (2022) Dr. Gidlund actively mentors 6 current PhD students and has supervised 16 former PhD students who now hold positions at institutions including Ericsson, Lund University, Aalborg University, and Mid Sweden University. His research is supported by multiple active projects including IRS TransTech, NIIT, ENSURE 6G, and TRUST. He collaborates with institutions worldwide including City University of Hong Kong, Iowa State University, Kyung Hee University, and KTH Royal Institute of Technology. His research group maintains strong industry connections through projects with ABB, Ericsson, and other industrial partners, focusing on practical implementations of wireless technologies for industrial automation and critical infrastructure.
Thomas DC Little is a Professor of Electrical and Computer Engineering in the College of Engineering at Boston University. He serves as the Associate Dean for Educational Initiatives, driving the growth of the engineering master’s program and enhancing pedagogy through mobile and cloud technologies. Additionally, he is the Associate Director and Principal Investigator of the National Science Foundation Smart Lighting Engineering Research Center (LESA), a multi-institutional effort advancing visible light communication and smart lighting systems. Professor Little's research centers on ubiquitous computing and communications, with a focus on using optical cells to expand wireless data capacity for mobile devices. He pioneers ambient intelligence that enables environments to anticipate human needs. His key areas include Visible Light Communications (VLC), Optical Wireless Communications, Indoor Positioning Systems, and Smart Lighting. By integrating lighting infrastructure with communication networks, his work addresses the growing demand for wireless data and enables energy-efficient, responsive smart buildings and urban environments. Analysis of his recent publications (2019-2024) shows a strong trend toward occupancy sensing, indoor positioning, and hybrid RF/VLC networks. His team develops innovative solutions for people counting, zone-based positioning, and interference mitigation in dense optical wireless environments. There is increasing integration of machine learning for security and optimization, with applications in energy-efficient buildings and user-centric smart spaces. Scientific awards received by Professor Little include: Janetos Award for Continuous Indoor Air Quality Assessment for BU Buildings (2025) Professor Little actively mentors graduate students and postdocs, with notable advisees including Iman Abdalla (awarded Best Computer Engineering Dissertation, 2020-2021) and the MenuNav team (Societal Impact Award for a navigation app for the blind). He has secured significant research funding, including a $1M Department of Energy/ARPA-E project for occupancy sensing to reduce energy costs in commercial buildings and grants for indoor air quality sensor development. He leads the NSF Smart Lighting ERC (LESA), which develops COSSY people counting technology, sensory lighting systems, and dynamic light control applications. His team collaborates with industry and has spun off Helux Technologies, Inc. to commercialize dynamic lighting control. Current projects focus on creating safe, energy-efficient buildings through advanced sensor integration and wireless communication.
Christopher Rycroft is a Professor and Associate Chair in the Department of Mathematics at the University of Wisconsin–Madison. He leads the Rycroft Group, which focuses on mathematical modeling and scientific computation for interdisciplinary applications in science and engineering. Prior to joining UW-Madison in summer 2022, he was a professor at Harvard University's School of Engineering and Applied Sciences from 2014-2022, and before that a Morrey Assistant Professor at UC Berkeley from 2010-2013. Professor Rycroft's research spans three main areas: numerical methods for material mechanics, data-driven discovery, and computational geometry. His group develops new computational methods while working directly with domain scientists. Key achievements include the development of the reference map technique for fluid-structure interaction, Voro++ software library for Voronoi tessellation, and novel approaches to understanding crumpling physics. His work combines traditional analysis and modeling with machine learning methods to extract scientific insights from complex data. The Rycroft Group's publication record demonstrates a strong trajectory of interdisciplinary research bridging mathematics, physics, materials science, and biology. Recent work has focused on fluid-structure interaction, computational geometry applications, mechanical metamaterials, and biological fluid dynamics. The group develops both theoretical frameworks and practical software tools that have found applications across diverse scientific domains from materials science to virology. Everett Mendelsohn Award for Excellence in Mentorship (2021) Professor Rycroft has advised numerous PhD and master's students who have gone on to postdoctoral positions at institutions including MIT, EPFL, and Cornell. His teaching includes advanced scientific computing courses that have quadrupled in enrollment during his tenure. He has secured research funding supporting his group's work on computational methods and interdisciplinary applications. The Rycroft Group consists of graduate students, postdocs, and collaborators with diverse backgrounds in applied mathematics, physics, engineering, and computer science. The group maintains active collaborations with researchers across multiple institutions and participates in centers such as the Harvard Quantitative Biology Initiative.
Koroush Shirvan is the Atlantic Richfield Career Development Professor in Energy Studies and a tenured faculty member in MIT's Department of Nuclear Science and Engineering within the School of Engineering. Joined in July 2017, he directs the Reactor Technology Course for Utility Executives and leads the Fission Materials in Extreme Environments Lab. His work bridges nuclear engineering with practical industrial applications for decarbonization. His research focuses on reactor design economics, materials testing under irradiation, nuclear safety, and boiling heat transfer. He accelerates innovations in nuclear fuels, small modular reactors, and space propulsion through multi-scale physics integration. Current projects include accident-tolerant fuels, high-temperature materials for microreactors, and AI-driven optimization of reactor systems. His approach combines experimental irradiation testing at MITR with advanced computational modeling. Recent publications reveal strong trends toward economic nuclear deployment via advanced fuel technologies and small modular reactors. AI/ML applications dominate optimization research, particularly for core reload and uncertainty quantification. Materials science under extreme conditions remains central, with growing emphasis on space nuclear applications and horizontal reactor configurations for cost reduction. His scientific recognition includes: Nuclear News 40 under 40 (2024) American Nuclear Society Landis Young Member Engineering Achievement Award (2023) American Nuclear Society Reactor Technology Award (2022) Teaching responsibilities span Sustainable Energy (22.811/081), Graduate Reactor Physics, and Nuclear Design courses. Research grants support experimental programs at MIT Reactor Lab and computational frameworks for reactor-to-repository analysis. He mentors students through senior design projects and graduate research in nuclear fuel cycles. He directs the Fission Materials in Extreme Environments Lab and co-leads MIT's Space Nuclear initiative with AeroAstro. The team conducts irradiation experiments using MITR's high-temperature hydrogen flow capabilities and advanced diagnostics for post-irradiation examination. Current thrusts include nuclear thermal rocket materials testing and fission surface power development for lunar/Mars missions.
Marat I. Latypov serves as Assistant Professor in the Department of Materials Science and Engineering at the University of Arizona's College of Engineering. He is also a member of the Applied Mathematics Graduate Interdisciplinary Program and leads the Materials Informatics Lab. His research spans computational materials science, sustainable alloy design, and machine learning applications for materials development. Dr. Latypov holds a PhD in Materials Science and Engineering from Pohang University of Science and Technology (POSTECH, South Korea, 2014) and a Dipl.-Ing. in Engineering Physics from Ufa State Aviation Technical University (Russia, 2011). His postdoctoral training included appointments at Georgia Tech/CNRS in France and the University of California, Santa Barbara. His research focuses on materials informatics , physics-informed machine learning , and sustainable structural alloys . Key methodologies include graph neural networks for polycrystal mechanics, vision transformers for microstructure representation, and adaptive experimental design for materials optimization. Recent work emphasizes circular economy applications through construction waste recycling and copper mine tailings valorization. Analysis of his publication record reveals strong emphasis on computational microstructure-property linkages (35% of recent work), machine learning for materials design (30%), and sustainable materials processing (25%), with growing integration of large language models for materials knowledge extraction. NSF CAREER Award (2025) : For damage control in recycled aluminum alloys ISTI Distinguished Faculty Scholar (2024) : At Los Alamos National Laboratory Novelis Hackathon First Prize (2021) : Computer vision application Acta Materialia Outstanding Reviewer (2018) Young Researcher Award (2017) : NanoSPD7 Conference Dr. Latypov advises PhD students including Herbold Fellow Zhuocheng Huang and leads projects funded by NSF and the Grantham Foundation. Current initiatives include chalcopyrite leaching optimization for copper mining and graph neural network development for fatigue prediction. His Materials Informatics Lab maintains collaborations with Los Alamos National Laboratory, MIT, and industry partners including Novelis. The lab operates at the intersection of metallurgy , machine learning , and high-performance computing , with capabilities spanning deep learning, Bayesian inference, and cloud-based computational infrastructure. Recent news highlights participation in CODAS-HEP summer school and publication of vision transformer work in Acta Materialia.
Associate Professor Hu Yunfei is affiliated with the School of New Materials and New Energy at Shenzhen University of Technology , where she leads the New Energy Systems and Smart Microgrids Laboratory . She is a member of the China Renewable Energy Society and Guangdong Solar Energy Association . PhD in Materials Processing Engineering (2005), South China University of Technology Bachelor of Engineering (2000), South China University of Technology Her research focuses on new energy systems , solar-storage direct-flexible systems , and high-efficiency photovoltaic devices , including perovskite solar cells , tandem solar cells , and transparent conductive oxides . Her work spans fundamental materials science and applied energy systems. The 15 most recent publications highlight her expertise in polycrystalline silicon thin films , transparent conductive oxides , perovskite solar cells , and optoelectronic materials . These works reflect trends in improving solar cell efficiency, stability, and manufacturing scalability. She has led projects such as the development of consumer solar power optimizers , optical performance testing for bifacial solar panels , and industrial collaborations on silicon ribbon substrates . Her projects are funded by institutions like the Norwegian Science Foundation and National Natural Science Foundation of China . At Shenzhen University of Technology, she oversees the New Energy Systems and Smart Microgrids Laboratory , integrating advanced materials and system design for renewable energy applications.
Tim Baarslag is a Senior Researcher and leader of the Intelligent and Autonomous Systems group at CWI (Centrum Wiskunde & Informatica), a Part-Time Professor of Mathematics of Cooperative AI at Eindhoven University of Technology (TU/e), and an Associate Professor at Utrecht University. Additionally, he holds visiting roles as a Scholar at MIT, Associate Professor at Nagoya University of Technology, and Fellow at the University of Southampton. His research focuses on enabling autonomous systems to collaborate through joint decision-making, with applications in smart energy trading, the Internet of Things, and autonomous vehicles. Education: MSc in Mathematics (cum laude), Utrecht University BSc in Computer Science (cum laude), Utrecht University PhD in Automated Negotiation, Delft University of Technology (2014, cum laude) Tim Baarslag investigates foundational theories for cooperative artificial intelligence, particularly in automated negotiation. His work includes developing algorithms for multi-deal coordination, optimizing bidding strategies with reservation values, and creating frameworks like Genius and NegoLog to evaluate automated negotiators. He explores how AI can balance efficiency and fairness in complex, real-world scenarios such as procurement and energy trading. Recent research trends highlight his development of NegoLog, a Python-based negotiation framework with advanced analytics, and his work on multi-deal negotiation protocols. He also investigates preference uncertainty in user-agent interactions and designs optimal concession strategies for risk-seeking agents with high reservation values. Scientific Awards: Cor Baayen Young Researcher Award Academic Pioneer by Elsevier Young Talent by The Financial Daily Science Talent by New Scientist Tim Baarslag leads the Intelligent and Autonomous Systems group at CWI and organizes the International Automated Negotiating Agent Competition. He is involved in the ACM Future of Computing Academy, The Young Academy, and the Netherlands Academy of Engineering. His work is supported by the NWO Vidi grant COMBINE, focusing on coordinating multi-deal bilateral negotiations. Labs & Teams: Intelligent and Autonomous Systems group, CWI EAISI and Combinatorial Optimization groups, TU/e ACM Future of Computing Academy The Young Academy Netherlands Academy of Engineering
Kwanghee Jeong is a Research Fellow at the University of Western Australia , affiliated with the Fluid Science and Resources research group within the School of Engineering and Chemical Engineering Department . His work focuses on energy transport, decarbonisation technologies, and flow assurance. Education: PhD in Chemical Engineering (UWA, 2020), BSc in Mechanical Engineering (Dongguk University, 2014) Research Themes include: Flow Assurance for hydrogen, CO2, and natural gas pipelines Carbon Capture & Emissions Management (MOFs, Raman spectroscopy) Cryogenic Hydrogen Process Engineering (liquefaction, boil-off gas) Cold Energy Utilisation and Waste Heat Recovery Hydrate Formation Kinetics via Acoustic Levitation Article Trends reflect expertise in: Using Raman spectroscopy for real-time adsorption and phase transition analysis Developing Joule-Thomson loops to simulate pipeline conditions Optimizing Metal-Organic Frameworks for GHG separation Advancing hydrogen liquefaction efficiency through catalysis Addressing microplastics and hydrate nucleation via spectroscopic methods Scientific Awards : Best Poster Award (2023) - Natural Gas UWA Travel Award (2017) ARC PhD Scholarship (2016) He contributes to UN Sustainable Development Goals via decarbonisation research and has collaborated with Chevron, Woodside Energy, and Curtin University. His technical skills include Aspen HYSYS, OLGA simulations, HAZOP studies, and Differential Scanning Calorimetry (DSC).
Prof. Dr. Jürgen Biela serves as Full Professor at ETH Zurich within the Department of Information Technology and Electrical Engineering, where he leads the Laboratory for High Power Electronic Systems. His academic career at ETH Zurich has progressed from doctoral studies to his current position as head of his research laboratory, with significant contributions to power electronics research and education. Biela earned his diploma with honors from Friedrich-Alexander University in Erlangen, Germany in 2000 and completed his Ph.D. at ETH Zurich in 2005, both in electrical engineering. His educational background includes specialized work on resonant DC-link inverters at Strathclyde University and active control of series connected IGCTs at the Technical University of Munich. His research program focuses on multi-physics modeling, design and optimization of power electronic systems , with particular emphasis on applications for future energy distribution and transmission, pulsed power systems, and advanced medium voltage power electronics based on novel semiconductor technologies like silicon carbide (SiC). He also investigates integrated passive components for ultra-compact and ultra-efficient high-power converter systems, pushing the boundaries of power density and efficiency in electronic power conversion. Analysis of his recent publications reveals strong trends in high-frequency power conversion , with significant work on transformer and inductor design, insulation systems for medium-frequency applications, thermal management of power components, and advanced modeling techniques for electromagnetic phenomena. His research bridges fundamental electromagnetic theory with practical engineering applications, particularly in high-voltage and high-power scenarios where traditional approaches face limitations. As a prolific researcher, Biela has published over 85 journal papers and 210 conference papers while holding more than 35 patents. He serves as an Associate Editor for the IEEE Transactions on Power Electronics and regularly reviews for leading journals and conferences in the field. His work demonstrates consistent contributions to advancing power electronic systems through rigorous theoretical analysis combined with practical implementation. Biela has supervised numerous doctoral and master's students, with recent publications indicating active mentorship of researchers working on advanced power electronic components and systems. His laboratory at ETH Zurich serves as a hub for innovation in high-power electronics, with connections to industry research projects that translate theoretical advances into practical applications. Current research directions include developing cost-effective alternatives to traditional components like Litz wire, improving insulation systems for high-voltage applications, and creating more accurate models for predicting thermal and electromagnetic behavior in power electronic systems.
Heikki Remes serves as Associate Professor in the Department of Energy and Mechanical Engineering at Aalto University's School of Engineering, where he investigates high-performance steel structures for marine environments with emphasis on lightweight ship designs using advanced materials and manufacturing techniques. His research integrates fundamental fatigue and fracture mechanics with practical structural challenges, spanning from crystal-level material behavior to continuum-scale modeling. Key focus areas include welded joint integrity, additive manufacturing defects, and computational analysis of marine structures under extreme conditions. Recent publications reveal strong trends in fatigue assessment methodologies for complex welded geometries, experimental validation of distortion effects, and AI-enhanced damage prediction systems, reflecting his commitment to bridging theoretical mechanics with shipbuilding applications. Scientific Awards: Aalto Education Impact Award (2018) for establishing Marine Technology study programs SNAME Honorable Mention for 2018 Vice Admiral E. L. Cochrane Award Teaching Award of Aalto School of Engineering (2012) for educational tools No specific student advising or grant information appears in available sources, though his active publication record indicates ongoing research leadership. He contributes significantly to the Marine and Arctic Technology research group, driving projects on structural integrity assessment and advanced manufacturing solutions for next-generation marine vessels.
Hamidreza Karami is an Associate Professor in the School of Petroleum and Geological Engineering at the University of Oklahoma. His research focuses on multiphase flow, production engineering, artificial lift, and flow assurance, with applications in unconventional wells, geothermal systems, and hydrogen transportation. BSc, Petroleum Engineering, Sharif University of Technology (2009) MSc, Petroleum Engineering, The University of Tulsa (2011) PhD, Petroleum Engineering, The University of Tulsa (2015) Karami's work combines experimental and computational fluid dynamics (CFD) with machine learning to address challenges in gas lift, downhole separators, well cleanout, and leak detection. Recent publications emphasize data-driven modeling of multiphase flow systems and optimization of artificial lift methods. His lab at the University of Oklahoma investigates advanced technologies for flow assurance, including paraffin and asphaltene deposition, foam lifting, and surfactant applications. Collaborative projects involve Tulsa University Fluid Flow Projects (TUFFP) and industry stakeholders.
Amir Bahadori serves as Professor and Nuclear Engineering Program Director in the Department of Mechanical and Nuclear Engineering at Kansas State University's Carl R. Ice College of Engineering, holding the Hal and Mary Siegele Professorship in Engineering. He directs the Radiological Engineering Analysis Laboratory (REAL) and established the Institute for Radiation Health Studies (IRHS) in 2024, focusing on radiation protection, space radiation environments, and radiation health effects. His educational background includes: Ph.D. in Biomedical Engineering, University of Florida (2012) M.S. in Nuclear Engineering Sciences, University of Florida (2010) B.S. in Mechanical Engineering and Mathematics, Kansas State University (2008) Bahadori's research spans radiation transport modeling, dosimetry, and risk assessment with applications in space exploration, medical physics, and radiation epidemiology. He develops computational frameworks for radiation exposure scenarios and biological response prediction, emphasizing space radiation protection for Artemis missions and chronic exposure studies through the Million Person Study collaboration. Analysis of his recent publications reveals dominant themes in space radiation measurement (Artemis missions), radiation epidemiology (Million Person Study innovations), and advanced detection systems (miniaturized neutron spectrometers). His work increasingly integrates big data approaches for radiation risk assessment and electrostatic shielding concepts for deep-space exploration. His scientific recognition includes: NASA Graduate Student Research Fellowship (2009) Certified Health Physicist designation Big 12 faculty fellowship (2022-2023) NCRP council election (2024) Two USPTO patents Bahadori secures substantial research funding from NASA for space radiation instrumentation, Department of Energy projects via the Kansas City National Security Campus, and collaborative epidemiological studies. He mentors nuclear engineering graduate students while leading interdisciplinary teams developing radiation protection solutions for aerospace and medical applications. His laboratory infrastructure includes the REAL with Beocat high-performance computing resources, radiation detectors, and a 3D printer, plus the IRHS with a Precision X-ray XRad320 irradiator and radon chamber. These facilities support collaborations across K-State colleges and external organizations for radiation health effect studies.
Dr. John O. Miller is an Associate Professor of Operations Research in the Department of Operational Sciences at the Air Force Institute of Technology (AFIT), where he has served since 1997 in roles including Military and Civilian Deputy Department Head and Director of the Center for Operational Analysis. A retired U.S. Air Force Lieutenant Colonel, he combines more than three decades of military experience with scholarly expertise in simulation modeling, defense logistics, and operations research. Education: Ph.D. in Industrial Engineering, The Ohio State University, 1997 M.S. in Operations Research, Air Force Institute of Technology, 1987 M.B.A., University of Missouri at Columbia, 1983 B.S. in Biology, United States Air Force Academy, 1980 Dr. Miller’s research focuses on the development and application of simulation methodologies—especially agent-based and discrete-event modeling—to military logistics, weapon system evaluation, and combat readiness. His work often integrates multivariate statistics, experimental design, and optimization techniques to address Air Force and Department of Defense challenges such as sortie generation, munitions supply chains, and directed-energy weapon assessment. Across more than 40 refereed articles, recent publications demonstrate a sustained emphasis on: Metamodeling of large-scale simulations using dynamic Bayesian networks and bootstrapping Agent-based exploration of air-to-air missile concepts and aircraft maintenance manpower Statistical evaluation of pattern-recognition and automatic-target-recognition algorithms Logistics degradation modeling for bomber fleets and brigade combat teams These contributions underscore his leadership in military simulation and defense-focused operations research. Scientific & Teaching Honors: AFIT Instructor of the Quarter, 2005 Tau Beta Pi Engineering Honor Society (Alumnus Member), 2001 AFIT Student Chapter ORSA Outstanding OR Educator, 1999 MORS Barchi Prize Nominee, 1998 Alpha Pi Mu & Omega Rho Honor Societies USAFA Department Instructor of the Year, 1993 Dr. Miller has advised numerous M.S. and Ph.D. students whose dissertations and theses advance simulation optimization, military logistics, and combat modeling. His teaching interests span simulation modeling and analysis, design of experiments, probability and statistics, and operations research methods for defense applications. He maintains active professional memberships in INFORMS, the Military Operations Research Society, and the Air Force Association, and he frequently presents at both invited and organized conferences, fostering collaboration among military, academic, and industry analysts.
Jennifer Schaefer is an Associate Professor at the Department of Chemical & Biomolecular Engineering at the University of Notre Dame. She is affiliated with the McCourtney Hall of Molecular Science & Engineering and focuses on ion transport and electrochemical processes for sustainable energy applications. Ph.D. in Chemical Engineering from Cornell University (2014) M.Eng. and B.Ch.E. in Chemical Engineering from Widener University (2008) B.S. in Chemistry from Widener University (2008) Her research develops novel polymer materials and membranes for advanced electrochemical energy storage and generation devices, emphasizing safety, sustainability, and performance. Key areas include polymer electrolytes, ion transport mechanisms, and energy storage systems for batteries. Her publications from 2020 demonstrate expertise in single-ion conductors, gel electrolytes, and multivalent cation batteries (Li+, Na+, K+, Ca2+). These works explore polymer chemistry effects, solvent interactions, and interface engineering. Burns Award for outstanding doctoral student mentorship (2024) Catherine F. Pieronek Women in Engineering Impact Award (2021) As a faculty member, Schaefer contributes to Notre Dame's energy research initiatives and leads the Schaefer Research Group, which aligns with the university's focus on sustainable technologies.
