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Joseph A. Konstan is a Distinguished McKnight University Professor and Distinguished University Teaching Professor in the Department of Computer Science and Engineering at the University of Minnesota , where he also serves as Associate Dean for Research of the College of Science and Engineering. His work spans human-computer interaction , recommender systems , and social computing , with significant focus on improving personalization algorithms and ethical AI applications. Education : Ph.D. in Computer Science from University of California, Berkeley (1993) M.S. in Computer Science, UC Berkeley (1990) A.B. in Computer Science, Harvard College (1987) Dr. Konstan's research addresses human-centric AI challenges, including collaborative filtering , online community dynamics , and health technology interventions . He leads the GroupLens Lab , known for developing foundational recommender systems frameworks like MovieLens. His work on organizational communication and health apps demonstrates practical applications of behavioral interventions. Recent publications analyze algorithmic fairness , user inaction patterns , and human-AI collaboration in media recommendation. He chairs the ACM Publications Board and has led major NSF grants for human-centered news recommenders . His 130+ publications include influential works on user modeling , social media ethics , and interactive learning systems . ACM Software Systems Award for GroupLens Fellow, ACM/AAAS/IEEE CHI Academy member As an advisor, Dr. Konstan has mentored 16 Ph.D. graduates including Ruoyan Kong (2023) and Max Harper (2019). He leads NSF-funded research on recommendation ethics and organizational communication . The GroupLens Research Group under Konstan explores recommender system infrastructure , user experience optimization , and health technology for School of Nursing and HealthPartners collaborations.

• Human-Computer Interaction
• Recommender Systems
• Social Computing
• +6 more

Cruz Enrique Borges Hernandez is a Professor at the Faculty of Engineering, University of Deusto, specializing in computational approaches to energy systems and urban sustainability. His research integrates data science, agent-based modeling, and behavioral analysis to address critical challenges in smart grids, energy consumption patterns, and urban mobility. His primary research interests include: Smart grid optimization and electricity demand forecasting Urban mobility modeling and 15-minute city concepts Behavioral interventions for energy efficiency in buildings Cross-generational climate change perception studies Blockchain applications for peer-to-peer energy markets His recent publications demonstrate strong trends in applying machine learning to smart meter data analysis, developing agent-based simulations for urban systems, and examining socio-technical aspects of energy transitions. Key methodological contributions include cascading models for behavioral nudges and novel approaches to electricity consumption typology derivation. As an active researcher in EU-funded projects, he bridges technical energy modeling with social science perspectives, creating policy-relevant outputs that address both engineering challenges and human behavior aspects of sustainability transitions. His work emphasizes practical implementation through platforms like GreenSoul for building energy monitoring and GTPlat for transport planning simulations.

• Smart Grids
• Energy Consumption Modeling
• Urban Mobility
• +4 more

William Currie is a Professor at the University of Michigan with dual appointments in the School for Environment and Sustainability and the College of Literature, Science, and the Arts. His research centers on ecosystem ecology in wetland and Great Lakes environments, addressing nutrient cycling dynamics, invasion processes, and anthropogenic impacts including urbanization and climate change. His primary research interests encompass wetland biogeochemistry, nutrient cycling under environmental stressors, invasion ecology of species like Typha in coastal systems, and the integration of machine learning for environmental prediction. Currie's work bridges experimental field studies, ecosystem modeling, and socio-ecological frameworks to address sustainability challenges in the Great Lakes region and continental US water systems. Analysis of his 2020-2025 publications reveals a significant shift toward computational approaches, particularly machine learning applications for water quality prediction and Great Lakes forecasting, while maintaining core experimental research on wetland nutrient dynamics. His scholarship increasingly addresses cross-cutting issues including urban stream pollution, blue carbon valuation, and the ecological consequences of infrastructure development. Currie directs the Currie Lab Group, which focuses on sustainability science through ecosystem modeling, field experimentation, and stakeholder engagement to advance understanding of environmental change in freshwater coastal systems.

• Sustainability
• Environmental Science
• Ecosystem Ecology
• +5 more

Francesco Lombardi is an Assistant Professor at the Delft University of Technology (TU Delft) within the School of Technology, Policy and Management , Energy and Industry department. He specializes in computational methods for energy system design, emphasizing social justice and technical robustness. PhD in Energy Engineering from Politecnico di Milano Visiting researcher at ETH Zurich and KU Leuven His research focuses on Modelling to Generate Alternatives (MGA) methods, including the SPORES algorithm , integrated into the open-source energy framework Calliope . He leads the development of RAMP software , a stochastic model for energy demand profiles in data-scarce scenarios like remote areas and future electric-vehicle fleets. Current projects include advancing MGA methods for policy-relevant energy questions and contributing to the PowerWeb Institute , Urban Energy Institute , and Open Energy Modelling Initiative . His work spans urban-to-national scales, addressing multi-energy systems and decarbonization strategies. Notable publications include studies in Joule and Applied Energy on renewable deployment, fossil fuel elimination, and smart charging. Collaborations involve industrial and academic partners, with software like RAMP co-funded by institutions such as Reiner Lemoine Institut and University of Liège.

• Energy System Modelling
• Computational Optimization
• Stochastic Simulation
• +4 more

Prof. Dr. Uğur Atikol is a Professor of Thermodynamics, Energy Management and Building Services at Eastern Mediterranean University's Department of Mechanical Engineering within the College of Engineering. As Director of the Energy Research Center (ERC) since 2004 and former Head of Mechanical Engineering Department (2010-2016), he has established himself as a leading expert in sustainable energy implementation. A Certified Energy Auditor with extensive HVAC engineering experience, Dr. Atikol has contributed significantly to energy projects sponsored by USAID and the EU, particularly focused on improving living standards in the Turkish Cypriot community. Dr. Atikol's research expertise spans Thermodynamics, Energy Management, and Building Services , with particular emphasis on transferring clean and efficient energy technologies to developing countries. His work addresses critical challenges in sustainable energy implementation through projects like the Resource Efficiency Achievement Project (REAP) and EU-sponsored renewable energy initiatives. He recently co-chaired a working group developing a strategic plan for energy efficiency across all sectors in northern Cyprus. His scholarly output demonstrates consistent focus on practical energy solutions, with research trends showing strong emphasis on demand-side management strategies, solar energy applications, desalination technologies, and thermodynamic optimization of energy systems. The progression of his work reveals increasing sophistication in system integration and practical implementation of theoretical concepts. Certified Energy Auditor First President of Cyprus Chapter of Association of Energy Engineers (2006) Co-founder of Energy Professionals Association in northern Cyprus Dr. Atikol has successfully supervised five PhD students to completion and currently mentors three ongoing PhD projects focused on demand-side management and solar thermal technology transfer. His research has been supported by significant international projects including USAID's REAP and EU renewable energy programs, demonstrating his ability to secure and manage substantial research funding. As Director of the Energy Research Center, Dr. Atikol leads multidisciplinary teams focused on sustainable energy solutions for the region. His leadership extends to professional organizations, where he co-founded both the Cyprus Chapter of the Association of Energy Engineers and the Energy Professionals Association in northern Cyprus, significantly contributing to the development of energy professionals in the region.

• Thermodynamics
• Energy Management
• Building Services
• +6 more

Lydell Andree Wiebe is a Professor in the Department of Civil Engineering at McMaster University's Faculty of Engineering. He specializes in earthquake engineering, seismic design of steel structures, and resilient infrastructure systems. His academic credentials include a BASc (2005) and PhD (2013) in Civil Engineering from the University of Toronto, and an MSc in Earthquake Engineering (2008) from the ROSE School in Pavia, Italy. His research focuses on developing innovative structural systems such as controlled rocking braced frames and masonry walls to enhance seismic resilience. Key areas include performance-based design, structural dynamics, and risk assessment of infrastructure under seismic loads. He actively contributes to professional committees, including the CSA S16 Technical Committee (Steel Structures) and the Canadian Association for Earthquake Engineering. Dr. Wiebe's recent publications (2020–2025) emphasize seismic loss mitigation, optimization of controlled rocking systems, and machine learning applications in structural engineering. His work integrates experimental testing with advanced computational models to improve design methodologies for earthquake-resistant structures. Awards & Honors: GJ Jackson Fellowship Award (2005) HA Krentz Research Award (2015) McMaster Faculty of Engineering Teaching Excellence Award (2017) McMaster Students Union Teaching Award (2014, 2017) He teaches courses including Steel Structures , Seismic Design and Analysis , and Introduction to Civil Engineering , reflecting his commitment to education and mentorship.

• Earthquake Engineering
• Seismic Design
• Steel Structures
• +2 more

Brian Karney is an Adjunct Associate Professor in the Department of Civil Engineering at McMaster University. His work focuses on hydraulic transients, water distribution systems, and energy efficiency in pipeline networks. Academic rank: Adjunct Associate Professor Institution: McMaster University Research areas: Transient flow analysis, pipeline optimization, and sustainable infrastructure Dr. Karney’s research interests bridge theoretical and applied hydraulic engineering. He investigates transient fault detection, air management in pressurized systems, and energy transformations in water networks. His work includes field testing of mobile DMA units for leakage assessment and computational modeling of surge protection strategies. Recent scholarly activity trends show a focus on transient pressure modeling (e.g., Godunov schemes for dam-break flows), air valve optimization, and value-based decision frameworks for pipe maintenance. His studies address challenges like energy dissipation in rapid filling pipelines and dynamic effects in two-phase flows. Key collaborative efforts involve international conferences (IAHR, ASCE) and interdisciplinary projects on climate adaptation, water quality, and infrastructure resilience. While no formal awards are listed, his publications span 30+ years of influential contributions to hydraulic transient theory and practice.

• Hydraulic Transients
• Water Distribution Systems
• Pipeline Optimization
• +3 more

Olof Samuelsson is a Professor at the School of Engineering (Lund University), serving as Director of Third Cycle Studies and Coordinator for the LTH Profile Area: The Energy Transition. His work focuses on modernizing power systems to support renewable energy integration and electromobility infrastructure. Division for Industrial Electrical Engineering and Automation UN SDG: Clean Energy & Climate Action Research Themes: Grid Capacity, Reliable Power Supply, Blackstart Operations His research interests span power systems analysis , electrical machines , power electronics , and smart grid automation , with a focus on enabling renewable energy integration and electric transport networks. Key subtopics include: Wind/solar grid integration Electric vehicle charging impacts System integrity protection schemes Probabilistic grid modeling Space weather resilience Recent Scientific Trends His research group analyzes 15+ publications since 2023, emphasizing: Electrified transport grid impacts (2025) Renewable energy congestion management (2023) Probabilistic modeling of sub-transmission systems System integrity schemes across Nordic grids Awards : IEEE PES Chapter Outstanding Engineer (2017) Projects : Leads SPS4SE (2023–2026) and co-leads VINST (2020–2023) with the Swedish Energy Agency.

• Electric Power Systems
• Smart Grids
• Renewable Energy Integration
• +4 more

Lloyd Chapman serves as a Lecturer in the School of Mathematical Sciences within Lancaster University's Faculty of Science and Technology. His research bridges statistical methodology and infectious disease dynamics, with emphasis on epidemic modeling and public health applications. His primary research interests include: Bayesian inference methods for epidemic models Spatiotemporal modeling of infectious diseases Individual-level disease transmission modeling Computational statistics for public health Dr. Chapman's publication portfolio demonstrates consistent focus on neglected tropical diseases (particularly leishmaniasis) and pandemic influenza/COVID-19 modeling. His work frequently employs advanced statistical techniques including data augmentation MCMC and particle MCMC to address complex transmission dynamics. Recent publications show increasing emphasis on asymptomatic infection reservoirs and spatial heterogeneity in disease transmission. As a supervisor within the STOR-i Centre for Doctoral Training, he mentors PhD students including James Neill and Lanya Yang in biostatistics and computational statistics. Current projects include "Modelling and inference of seasonal flu transmission to optimise flu vaccination" (2024-2026). He actively contributes to the Bayesian and Computational Statistics research group and the Biostatistics team.

• Bayesian inference
• epidemic models
• spatiotemporal modelling
• +4 more

Dr Alex Gibberd is a Senior Lecturer (equivalent to Associate Professor) in Statistics within the School of Mathematical Sciences at Lancaster University. He has been a faculty member since 2018, following postdoctoral research at Imperial College London and a PhD in Statistics from University College London (UCL) in 2017. He also holds an MPhys in Astrophysics from the University of St Andrews (2012). Education: PhD in Statistics, University College London (2017) MPhys in Astrophysics, University of St Andrews (2012) Research Interests: Dr Gibberd's research focuses on high-dimensional time-series analysis, with methodological contributions in statistical modeling under non-stationarity and high-dimensionality. His work spans both theoretical developments and practical applications, particularly in neuroscience and finance. Key areas include: Sparse dynamic factor models and regularized estimation techniques Spectral analysis and locally-stationary wavelet models Optimization algorithms for model selection in high-dimensional settings Applications in brain connectivity analysis and economic forecasting Research Themes: His recent publications demonstrate a strong focus on developing interpretable statistical methods for complex systems. These include advances in principal component analysis with joint rank and covariance estimation, sparse dynamic factor models, and regularized spectral estimation for high-dimensional point processes. The applications range from neural connectivity modeling to energy efficiency policy analysis. Grants & Funding: Research in Paris Grant (2024) Support of Collaborative Research with Dr S. Roy at University of Bath (2021) Model Selection for High-Dimensional Temporal Disaggregation in Official Statistics (2021-2023) Reducing End Use Energy Demand in Commercial Settings Through Digital Innovation (2021-2025) Wavelet Methods for Dependency Analysis in Multivariate Time Series (2020) STOR-i: Information Fusion for Non-homogeneous Panel and Time-series Data (2019-2025) PhD Supervision & Students: Dr Gibberd supervises PhD students at the intersection of high-dimensional statistics and time-series analysis. Current students include Carla Pinkney (STOR-i CDT), Ziyan Zhao, and Kai Zheng (Centre for Marketing Analytics & Forecasting). Research Affiliations: STOR-i Centre for Doctoral Training Centre for Marketing Analytics & Forecasting Changepoints and Time Series Research Group Data Science Institute - Foundations Social and Economic Statistics Group

• High-dimensional time-series analysis
• Statistical modeling under non-stationarity
• Sparse dynamic factor models
• +3 more

Dr. Philipp Kuhn is a Researcher at the Chair of Renewable and Sustainable Energy Systems at the Technical University of Munich (TUM) , with a focus on energy system modeling and optimization. His work addresses critical challenges in renewable energy integration, hydrogen/synfuel economics, and grid stability. Research Focus: Energy storage valuation through linear programming dual solutions Dynamic primary energy factor methodology for renewable systems Hydrogen's role in sector coupling and long-term energy systems Building-grid interaction models for demand response Geothermal energy flexibility for combined heat/power production Publication Trends: Recent work (2023) examines international synfuel trade routes and socio-technical modeling parameters, while 2017-2020 studies focused on Bavarian energy scenarios and geothermal applications. Earlier work (2013-2015) developed storage expansion models and demand-side management frameworks.

• Energy System Modeling
• Renewable Energy Integration
• Energy Storage Technologies
• +5 more

Stephan Baur is a researcher at the Chair of Renewable and Sustainable Energy Systems at the Technical University of Munich (TUM), based in room 5414.02.018 at Lichtenbergstr. 4a, 85748 Garching bei München. He offers consultation hours by appointment and maintains an active research profile focused on practical renewable energy solutions for developing contexts, particularly through the Laboratory for Sustainable Energy Systems (SES Lab). Baur completed his physics diploma studies at the University of Augsburg, where he conducted his thesis on "Energy supply in high mountain huts - optimization, dimensioning and maintenance of storage batteries" at the Chair of Experimental Plasma Physics. Prior to his position at TUM, he worked as a teacher at Geretsried Gymnasium teaching Mathematics, Physics and Computer Science, which informs his current educational focus. His primary research interests include sustainable energy systems in developing and emerging countries, island systems, small hydropower plants (micro-hydro), and the cultural, social and economic framework conditions of energy supply in these regions. Baur's work consistently bridges theoretical energy concepts with practical implementation challenges in resource-constrained environments. Analysis of Baur's publication record reveals a clear evolution from early work on battery systems for mountain huts (2006-2007) to Nepal-focused micro-hydro projects (2018-2020), and most recently to educational applications of solar energy systems (2021-2024). His research demonstrates increasing emphasis on making renewable energy concepts accessible through hands-on learning experiences. Baur actively participates in interdisciplinary projects connecting school and university teaching with sustainable energy production in developing countries. His collaborations with researchers including Michael Erhart, Michael Penk, and Anurag Mohapatra demonstrate a team-based approach to addressing energy challenges in diverse contexts. He is a key contributor to the Laboratory for Sustainable Energy Systems (SES Lab), where theoretical concepts are transformed into practical implementations, particularly focusing on contexts where conventional energy infrastructure is limited or unavailable. His work on simple measurement techniques for electricity demand in developing countries represents an important methodological contribution to the field.

• Sustainable energy systems in developing countries
• Small hydropower plants
• Island energy systems
• +4 more

Liangliang Lu is a Postdoctoral Researcher at the Department of Energy and Mechanical Engineering , Aalto University. Their research focuses on Marine and Arctic Technology , with significant contributions to understanding ice mechanics, ship performance in polar conditions, and maritime risk assessment. Specializes in Arctic and Antarctic navigation Develops Bayesian networks for oil spill risk modeling Engages in collaborative polar research projects Research interests span ice-induced ship hull loads , winter navigation systems , and oil spill response effectiveness . Their work combines computational modeling , field measurements , and data analytics to improve maritime safety in extreme environments. Recent publications emphasize CFD/FSI/AI integration , real-time conflict probability ranking , and flexural strength analysis of freshwater ice. Collaborations with experts in naval architecture and polar logistics appear frequently. Active in polar research groups, Lu contributes to developing decision-support tools for ice-covered operations and participates in international conferences like POAC and IAHR Symposiums.

• Marine Technology
• Arctic Engineering
• Risk Management
• +3 more

Gunnar Stefansson is an Associate Professor at Chalmers University of Technology, affiliated with the Faculty of Engineering and Department of Service Management and Logistics. His work focuses on adaptive port planning, freight transportation innovation, and system dynamics modeling. Research Themes: Logistics management, blockchain adoption in export logistics, sustainable supply chains, intermodal transportation, and stakeholder prioritization in port planning. Methodologies: Bayesian estimation, fuzzy logic, group model building, and lean principles applied to freight operations. Geographic Scope: Primarily Iceland and Sweden, with case studies on the Port of Isafjordur and West Sweden export companies. His publications (2015-2024) span adaptive port planning, interoperability challenges, and smart transportation systems. Key subfields include automated loading/unloading, RFID applications, temperature alert criteria, and freight intelligent transportation systems. Notable contributions include: Frameworks for port throughput forecasting and stakeholder classification Models for adaptive planning in multi-purpose ports Studies on blockchain technology adoption and autonomous vehicle integration

• Logistics Management
• Supply Chain Management
• Port Planning and Operations
• +6 more

Dr. Olivia Halabicky is an Assistant Professor at the University of Michigan with dual appointments in the School of Nursing and School of Public Health, specifically in the Department of Nutritional Sciences and Department of Health Behavior and Clinical Sciences. Her research focuses on children's environmental health, examining how early life exposures to toxicants, adversity, and nutrition shape neurodevelopment and health trajectories. Dr. Halabicky earned her PhD in Nursing from the University of Pennsylvania (2021), MSc in Nursing with focus on Child Health and Wellbeing from Trinity College Dublin (2018), and BSN from Saginaw Valley State University (2015). Her research program investigates how environmental exposures at sensitive developmental periods influence health disparities, with particular emphasis on lead exposure and its effects on neurodevelopment, physiological stress responses, and long-term health outcomes. She employs interdisciplinary methods from nursing, environmental epidemiology, and developmental sciences, primarily working within the ELEMENT cohort, a Mexican birth cohort followed for over 30 years. Analysis of Dr. Halabicky's publication record reveals a strong focus on environmental toxicants, particularly lead exposure, and their impacts on child development across multiple domains including neurocognitive function, physiological stress markers, sleep patterns, and cardiovascular health. Her work consistently examines how social factors like parental education modify these exposure-outcome relationships, highlighting the intersection of environmental and social determinants of health. Scholar, Michigan Program for Advancing Cultural Transformation (M-PACT), University of Michigan, 2024 Center Scientist, Michigan Lifestage Environmental Exposures and Disease (M-LEEaD) Center, 2024-2025 Award, Rising Star, Rho Chapter Sigma Theta Tau International, 2023 Fellow, Early Career Interdisciplinary Scholars, Society for Research in Child Development, 2023 Future of Nursing Scholar, Robert Wood Johnson Foundation, 2018-2021 Award, Young Alumni, Saginaw Valley State University, 2018 Dr. Halabicky serves as Principal Investigator on multiple research grants including a Center Scientist Award from the Michigan Lifestage Environmental Exposures and Disease (M-LEEaD) Center and a National Institute of Nursing Research grant (L30 NR020943) examining early life lead and psychosocial co-exposures on adolescent physiological stress. While she is not currently accepting new PhD students, she has extensive teaching and mentorship experience in both nursing and public health programs, delivering guest lectures on environmental exposures and child health. Her professional affiliations include the Center for Global Health Equity at the University of Michigan, Society for Pediatric and Perinatal Epidemiologic Research, Alliance of Nurses for Healthy Environments, International Society for Environmental Epidemiology, Society for Research in Child Development, Midwest Nursing Research Society, and Sigma Theta Tau International.

• Environmental Exposures
• Child Health and Neurodevelopment
• Global Health Equity
• +6 more