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Gauri Joshi is an Associate Professor in the Electrical and Computer Engineering (ECE) department at Carnegie Mellon University, with affiliate appointments in the Machine Learning Department and Robotics Institute. Her work focuses on system-aware algorithms for distributed machine learning, combining optimization, probability, and coding theory to address communication and computational constraints in edge networks. MIT Ph.D. in EECS (2016) IIT Bombay B.Tech/M.Tech in Electrical Engineering (2010) Research themes include federated learning with communication efficiency, erasure coding for non-linear computations, and reinforcement learning for heterogeneous queueing systems. She leads the Optimization, Probability and Learning (OPAL) lab , affiliated with the Parallel Data Lab (PDL), CyLab, and FLAME Center. Recent publications highlight advances in: federated fine-tuning with low-rank adaptation, robust PCA for model aggregation, privacy-preserving prediction mechanisms, and adaptive reinforcement learning for job dispatching systems. Her group has received 15+ paper awards across SIGMETRICS, MobiHoc, and NeurIPS workshops. Scientific recognition includes: IEEE Goldsmith Lecturer (2025), MIT Technology Review '35 Innovators Under 35' (2022), ONR Young Investigator Award (2023), NSF CAREER (2021), and ACM SIGMETRICS Best Paper (2020). She has advised 20+ graduate students, many now at tech giants like Google, Apple, and Meta. Service contributions span program co-chair roles (MLSys 2025), associate editorships (IEEE/ACM Transactions on Networking), and workshop organization (ICML, NeurIPS). Her NSF AI-EDGE Institute leadership (2021-present) drives next-generation intelligent edge networks for robotics and aerospace applications.

• Distributed Machine Learning
• Federated Learning
• Stochastic Modeling
• +7 more

Reza Ghabcheloo is a Professor at Tampere University, affiliated with the Faculty of Engineering and Natural Sciences and the Department of Automation Technology and Mechanical Engineering. He leads the Robotics major and the international Automation Engineering program. His research focuses on autonomous mobile machines, robotics, control systems, and safety engineering, with specific interests in construction robotics, sensor fusion, and hydraulic systems. He co-leads the Autonomous Mobile Machines Group and is associated with the Robotics and Intelligent Machines Lab and the Innovative Hydraulics and Automation Lab. His research emphasizes developing autonomous systems for off-road machinery, safe control strategies, and energy-efficient automation. He has published extensively on topics such as reinforcement learning for crane control, radar-based perception, and safety architectures for autonomous systems. His work bridges robotics, control theory, and industrial automation, addressing challenges in heavy-duty machinery and real-world robotic applications. Research Group: Autonomous Mobile Machines Group Labs: Robotics and Intelligent Machines Lab, Innovative Hydraulics and Automation Lab Key Projects: Safety of automated off-road machinery, machine learning for autonomous loading, and trajectory optimization

• Robotics
• Automation Engineering
• Control Systems
• +7 more

Prof. Walter Richtering is a Universitätsprofessor at RWTH Aachen University, affiliated with JARA-SOFT and the Institute of Physical Chemistry (IPC). His research focuses on soft matter physics, colloids, and polymer chemistry with emphasis on microgels, nanogels, and their applications in biomaterials and materials science. He leads the 'Physical Chemistry of Solids' group and contributes to the CRC 985 (Functional Microgels and Microgel Systems). Key interests include quantifying softness in colloids, interfacial phenomena, and developing educational tools like AFM-based microgel experiments for undergraduate labs. Position: Professor of Physical Chemistry Affiliations: JARA-SOFT, IPC RWTH Aachen, CRC 985 Research Groups: Physical Chemistry of Solids, Polymers and Colloids His work explores structure-property relationships in soft materials, including phase behavior under non-equilibrium conditions, thermoresponsive systems, and catalytic microgel applications. Recent studies address microgel mechanics, anisotropic architectures, and filtration technologies.

• Soft Matter Physics
• Colloid & Interface Science
• Polymer Chemistry
• +3 more

Lianne Lefsrud serves as Associate Professor and Risk, Innovation, and Sustainability Chair (RISC) in the Department of Chemical and Materials Engineering at the University of Alberta's Faculty of Engineering. Her interdisciplinary research bridges engineering, social sciences, and policy to transform risk management practices across energy, mining, construction, and railroading industries, directly influencing regulations, building codes, and industry operations for sustainable development. Her academic credentials include: BSc in Civil Engineering (Cooperative Program), University of Alberta (1994) MSc in Interdisciplinary Civil & Environmental Engineering and Sociology, University of Alberta (1996) PhD in Strategic Management and Organization, Alberta School of Business (2014) Dr. Lefsrud's research centers on risk management frameworks for sustainability challenges. She examines hazard identification, social license to operate, and technology adoption drivers in high-hazard industries, with emphasis on prospective risk assessment (e.g., hydrogen infrastructure design) and retrospective analysis (e.g., microplastic pollution impacts). Her work integrates circular economy principles into energy systems while addressing unintended consequences across UN Sustainable Development Goals. Recent publications (2024-2025) demonstrate heavy focus on machine learning applications for rail and construction safety, hydrogen infrastructure risk analysis, and science denial mitigation. Key patterns show cross-industry adaptation of AI for incident prediction, regulatory gap analysis for emerging energy systems, and socio-technical approaches to reconcile sustainability goals with operational realities. Scientific recognition includes: Erb Post-Doctoral Fellowship (University of Michigan) Dow Sustainability Research Fellowship (Ross School of Business) Dr. Lefsrud mentors graduate students through industry-integrated projects like her Sustainable Design course where teams generated patents and city solutions. Her research secures Alberta Innovates funding with 1:4 industrial-to-federal matching, collaborating with Suncor, Transport Canada, and Canadian Standards Association. Grants target practical implementations including railcar inspection systems and hydrogen safety protocols. She co-founded Insight Risk Systems and leads the Lefsrud Lab, prioritizing inclusive teams with under-represented groups (women, Indigenous, LGBTQ2S+, neurodiverse) to tackle 'wicked problems' in sustainability. The lab leverages interdisciplinary partnerships across engineering, computer science, psychology, and environmental sociology for real-world risk management solutions.

• Risk Management
• Sustainability
• Organizational Theory
• +5 more

Thomas Ertl is a Professor at the University of Natural Resources and Life Sciences, Vienna (BOKU), leading the Institute of Sanitary Engineering and Water Pollution Control. His research focuses on urban water systems, emphasizing sustainable drainage, climate change adaptation, and nature-based solutions. He has coordinated 55 projects, including international initiatives in Albania and Austria, addressing stormwater management, wastewater heat recovery, and sewer infrastructure resilience. Key Projects : Analysing re-activated watercourses for urban resilience (2024–2028) Resilient rainwater management in Austria (2024–2028) Assessing pollutant emissions in Albania (2024–2027) Research Themes : Building Information Modeling (BIM) in wastewater systems Uncertainty analysis under climate change Stormwater pollution and heat island mitigation Awards : 2018: Goldene Ehrennadel des ÖWAV 1993: Best student award at AGIT 93 His recent publications highlight multidisciplinary approaches to wastewater energy recovery, spatial compatibility of nature-based solutions, and prioritization of stormwater management sites. He has supervised numerous theses and contributed to media discussions on urban climate resilience, including articles in Austrian outlets like futurezone.at and Der Kurier.

• Environmental Engineering
• Water Resource Management
• Urban Hydrology
• +3 more

Dr. David Kelly is a Lecturer in the Department of Sport and Health Science at Dublin City University (DCU), within the Faculty of Science and Health. He teaches across Sport Science, Athletic Therapy, and Physical Activity programs, with a focus on Applied Sport Science. David Kelly obtained his BSc in Sport Science and Health in 2010 and a PhD in Exercise Physiology in 2014, both from DCU. His academic journey reflects a strong foundation in sport and health sciences. His research employs a multidisciplinary approach integrating physiological, nutritional, and biomechanical methodologies. Key interests include Exercise Training Specificity, Energy Demands, Nutritional Knowledge and Dietary Intake of Adolescent Team Sport Players, and Performance Profiling of elite and sub-elite athletes. His work has significant application in Gaelic games and team sports performance. The most recent articles indicate a growing trend toward data-driven athlete monitoring, including machine learning applications for performance prediction, meta-analyses of training methods, physiological comparisons in Gaelic football, athlete recovery perceptions, and nutritional behaviors. These span sports science, physiology, nutrition, and data analytics. David is actively involved in national sports organizations, serving on the Sport Science Working Group for the Gaelic Athletic Association (GAA) and the Player Welfare and Safety Committee for the Gaelic Players Association (GPA). These roles reflect his commitment to athlete welfare and performance optimization. There is no public information on specific research grants or students he has supervised. He is not listed as part-time, retired, or deceased, and there are no mentions of scientific awards in the provided text. He is associated with collaborative research networks and contributes to interdisciplinary projects, particularly in athlete performance and health. His work bridges academic research and practical application in elite sports settings.

• Exercise Physiology
• Sport Science
• Nutritional Science in Sports
• +10 more

Dr. Ciarán Ó Catháin is a Lecturer in the Department of Sport and Health Science within the Faculty of Science and Health. He is actively engaged in research at the intersection of sports science, exercise physiology, and nutritional health, with a strong emphasis on athlete performance and well-being. His research interests include: Sports Science and Exercise Physiology Nutritional Science in Athletics Female Athlete Health, particularly menstrual cycle and hormonal contraceptive tracking Dietary intake and culinary nutrition among athletes Resisted sprint training and performance monitoring Systematic reviews and meta-analyses in sports interventions Application of machine learning and wearable technology in sports Dr. Ó Catháin’s recent publications demonstrate a trend toward evidence synthesis (systematic reviews and meta-analyses), interdisciplinary methodologies, and a growing focus on gender-specific considerations in sports performance. His work integrates engineering concepts such as gait analysis and phase velocity with health sciences, reflecting a cross-disciplinary approach. He also explores emerging technologies like augmented reality and synthetic data generation for performance prediction. While no formal scientific awards are listed, his research has contributed to high-impact journals including Sports Medicine , Frontiers in Sports and Active Living , and Nutrition Bulletin . His h-index of 10 and 254 citations reflect a solid and growing academic influence. There is no available information regarding student supervision, grant funding, laboratory affiliations, or collaborative teams. However, his frequent co-authorship suggests active research collaboration, particularly with researchers in sports physiology and nutrition.

• Sports Science
• Exercise Physiology
• Nutritional Science in Athletics
• +14 more

Milos Nikolic is a Lecturer in Database Systems at the School of Informatics, University of Edinburgh. He is a member of the Database Group and the Laboratory for Foundations of Computer Science. Prior to joining Edinburgh, he was a Departmental Lecturer in the Department of Computer Science at the University of Oxford. He holds a PhD in Computer Science from EPFL. Research Interests: Milos Nikolic's research focuses on databases and large-scale data management, with emphasis on incremental computation, in-database learning, stream processing, and query compilation. His work explores how complex analytical queries—such as SQL, linear algebra, and machine learning tasks—can be efficiently maintained and evaluated in dynamic and distributed environments. He develops novel techniques in query optimization and compilation to enable real-time analytics over evolving data. His recent publications demonstrate a strong trend in dynamic query evaluation, particularly around conjunctive and hierarchical queries under updates, incremental view maintenance (e.g., F-IVM), and scalable processing of nested and biomedical data. His work often leverages theoretical foundations to achieve worst-case optimal performance, grounded in conjectures like the Online Matrix-Vector Multiplication (OMv) hypothesis. Scientific Awards: Best Paper Award, ICDT 2019 Advising and Grants: Milos is actively seeking PhD students to work on data management topics. While no formal list of advisees is provided, he collaborates extensively with researchers such as Dan Olteanu, Ahmet Kara, and Haozhe Zhang. His projects, including Adaptive Query Processing , Incremental Maintenance of Complex Analytics , and Declarative Data Pipelines (industry-supported), suggest ongoing grant and industry collaborations. Labs and Teams: He is a key member of the Database Group and the Laboratory for Foundations of Computer Science at the University of Edinburgh, contributing to cutting-edge research in foundational and applied database systems.

• Databases
• Data Management
• Incremental Computation
• +7 more

Dr. Jangho Park is an Assistant Professor in the Department of Industrial & Systems Engineering at Texas A&M University. His research focuses on ergonomic interventions, assistive technologies (e.g., exoskeletons), and biomechanical modeling to enhance workplace safety and human performance. He holds a Ph.D. in Occupational Ergonomics and Safety from Virginia Tech, and master's and bachelor's degrees in Biomedical Engineering from Kyung Hee University, South Korea. Education: Ph.D., Industrial and Systems Engineering (Occupational Ergonomics and Safety), Virginia Tech M.E., Biomedical Engineering, Kyung Hee University B.E., Biomedical Engineering, Kyung Hee University Research Interests: Ergonomic interventions to reduce musculoskeletal disorders Development and assessment of assistive technologies (e.g., exoskeletons) Postural control and balance recovery mechanisms Biomechanical modeling of human movement and load-bearing Effects of vibration exposure on occupational safety Research Trends: Dr. Park’s work emphasizes the integration of biomechanics, human factors, and wearable technologies. His recent studies explore how exoskeletons affect gait dynamics, postural stability, and balance recovery, while also investigating vibration-induced risks in heavy vehicle operations. Awards & Grants: No awards explicitly listed in the provided text. His grants and funding sources are omitted due to lack of explicit mention. Labs & Teams: No specific lab affiliations or collaborative teams are mentioned in the text.

• Ergonomic intervention
• Assistive technology
• Postural control assessment
• +4 more

Prof. Wenyi Yan is a Professor in the Department of Mechanical & Aerospace Engineering at Monash University. His career includes research fellowships in Europe, roles at multiple Australian universities, and leadership in over 14 Australian Research Council (ARC) grants since 2006. He has supervised 19 PhD and 5 MSc graduates, currently mentoring 12 PhD students. Education: B.Eng. (Hons) from Beijing University of Aeronautics and Astronautics (1989), M.Sc. (1992), and Ph.D. (1995) from Tsinghua University. Research focuses on material behavior under cyclic loading, railway infrastructure optimization, laser cladding repair, and additive manufacturing. Key areas include fracture mechanics, tribology, and computational modeling for rail systems. Notable projects: Development of machine learning tools for structural analysis (2025–2028), ARC Hub for Smart Process Design (2024–2029), and rail component repair using laser cladding. His work addresses UN SDGs related to sustainable infrastructure and innovation. Awards: While no specific prizes are listed, his extensive grants and publications (3 book chapters, 176 journals, 68 conferences; h-index 42) reflect his impact. Current grants total over 10 projects, emphasizing industry collaboration with Rio Tinto, ANSTO, and others.

• Mechanical Engineering
• Materials Science
• Railway Engineering
• +7 more

Assoc Prof Shuangchi He is affiliated with the Industrial Systems Engineering and Management Department at the National University of Singapore. His research focuses on operations research, stochastic modeling, queueing systems, and their applications in healthcare, transportation, and communications engineering. He holds a PhD from Georgia Institute of Technology (2011). Research interests include queueing design for service systems, diffusion approximations, patient scheduling optimization, and electric vehicle-sharing network analysis. His work bridges theoretical stochastic analysis with practical applications in logistics, healthcare management, and wireless communication systems. Recent publications highlight advancements in randomized routing strategies, on-demand ride-matching algorithms, and inpatient bed assignment models. His contributions to many-server queueing theory and doubly-selective channel estimation demonstrate expertise in both operations research and signal processing domains. Prof He collaborates on topics such as inventory management policies and MIMO channel estimation techniques, reflecting his interdisciplinary approach to solving complex system-level problems.

• Operations Research
• Queueing Systems
• Stochastic Modeling
• +5 more

Izabela Krejtz is a Professor at SWPS University in Warsaw, affiliated with the Institute of Psychology, Faculty of Psychology, and Department of Clinical Psychology. She leads research at the Eye-Tracking Research Center within the Interdisciplinary Center for Applied Cognitive Studies, specializing in cognitive psychology and eye-tracking methodologies. Her research focuses on identifying factors that determine individual psychological well-being through ecological momentary assessments and new technologies. She conducts studies on cognitive biases among various populations including deaf individuals and those with depression, and investigates the effectiveness of online attention and gratitude training interventions. Her work bridges clinical psychology with innovative technological approaches to understanding human cognition and emotion. Dr. Krejtz's recent publications demonstrate a strong focus on applying eye-tracking technology across diverse domains including accessibility research, educational psychology, clinical assessment, and human factors. Her work shows a consistent pattern of translating laboratory findings to real-world applications while maintaining rigorous scientific methodology. Grants from the Foundation for Polish Science Grants from the National Science Centre As a research supervisor, she mentors PhD students and leads multiple research projects including studies on menstrual cycle effects on cognition, gratitude interventions for women with breast cancer and depression, and the relationship between musical training and reading ability in children. Her work has significant implications for clinical practice and psychological interventions. She directs the Eye-Tracking Research Center, which is part of the Interdisciplinary Center for Applied Cognitive Studies, where her team conducts cutting-edge research using eye-tracking technology to investigate cognitive processes in naturalistic settings across diverse populations including clinical groups, children, and specialized professionals.

• Cognitive Psychology
• Eye-Tracking Research
• Psychological Well-Being
• +6 more

Pia Lindh is an Associate Professor at the Department of Electrical Engineering within LUT School of Energy Systems at Lappeenranta-Lahti University of Technology LUT. She holds an M.Sc. (1998) and D.Sc. (2004) in electrical engineering from LUT. Her research focuses on electric motors, electric drives, thermal management of electrical machines, and sustainable energy technologies. She has been actively involved in multidisciplinary projects addressing traction motor design for hybrid vehicles and energy efficiency improvements in industrial applications. Her publications emphasize advancements in permanent magnet machines, cooling systems, and high-speed motor technologies. Notable works include studies on rotor eddy-current losses reduction, hybrid cooling methods for vehicle motors, and thermal modeling of high-speed induction machines. Lindh collaborates with industry partners to bridge theoretical research with practical applications in transportation and renewable energy sectors. While her work spans over 30 peer-reviewed articles and conference papers, her research trends highlight innovations in motor design, thermal optimization, and sustainable energy systems. She has contributed to international journals like IEEE Transactions on Industrial Electronics and Applied Thermal Engineering, reflecting her expertise in electromechanical systems and energy conversion.

• Electrical Engineering
• Electric Motors and Drives
• Power Electronics
• +3 more

Ibrahim Eke serves as an Associate Professor in the Department of Electrical and Electronic Engineering within the Faculty of Engineering and Natural Sciences. His academic work centers on advancing power system stability and optimization through innovative computational methods, with primary affiliations spanning electrical engineering research and education. Professor Eke's research spans critical areas of electrical power engineering including economic load dispatch, load frequency control, voltage stability, and renewable energy integration. He specializes in developing heuristic optimization algorithms such as Electric Fish Optimization, Chaotic Particle Swarm, and Vortex Search to solve complex power system problems involving time delays, multi-area networks, and renewable integration challenges. His methodology consistently bridges theoretical algorithm development with practical power grid applications. Analysis of his 15 most recent publications (2020-2024) reveals three dominant research trajectories: (1) Mitigation of communication time delays in load frequency control using fractional-order PID controllers and neural networks, (2) Development of hybrid optimization techniques (Taguchi-Vortex, Chaotic PSO) for combined heat-power economic dispatch, and (3) Integration of electric vehicles and energy storage systems into frequency regulation frameworks. His work demonstrates increasing focus on renewable-heavy grid stability amid evolving power system architectures.

• Power Systems
• Optimization Algorithms
• Load Frequency Control
• +4 more

Dr. Steffen Dirkes is the Acting Group Lead for System Research at the Institute of Energy Technologies (IET), Research Center Jülich GmbH . His work focuses on electrochemical energy systems, particularly proton exchange membrane (PEM) fuel cell technologies for sustainable mobility and industrial applications. His research interests span Fuel Cell Technology Green Hydrogen Energy Systems Optimization Computational Modeling Hydrogen Mobility Sustainable Energy . He specializes in predictive maintenance, dynamic system modeling, and energy-water nexus solutions. Dr. Dirkes has contributed to 12 publications (2019–2025) on topics like DryHy project for water-positive hydrogen carriers, lifetime management frameworks for fuel cells, and adaptive energy management strategies for hybrid railway systems. His work combines advanced simulation techniques with real-world validation in transportation and heavy-duty applications.

• Fuel Cell Technology
• Green Hydrogen
• Energy Systems
• +3 more