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Jonathan BellView profile

Associate Professor

• Software Engineering
• Programming Languages
• Continuous Integration
• +5 more

Jonathan Bell is an Associate Professor at Northeastern University in the Khoury College of Computer Sciences , with prior appointments at George Mason University. His research spans Software Engineering , Program Analysis , and Ethics of Artificial Intelligence . PhD in Computer Science from Columbia University (2011) Recipient of the 2020 Dahl-Nygaard Junior Researcher Prize and NSF CAREER award His research focuses on: Resolving flaky tests in Continuous Integration systems Advancing dynamic taint tracking (e.g., Phosphor ) Formalizing software supply chain vulnerabilities Addressing ethical dimensions in automated decision-making Recent publications span flaky test prediction, semantic versioning analysis, and ethics of opaque AI systems. He co-founded the Clowdr open source project and a related startup. Awards include: 2020 Dahl-Nygaard Junior Researcher Prize 2025 NSF CAREER award 2019 GMU Teacher of Distinction award He advises PhD students like Liam DeVoe and Katherine Hough, and serves on committees for conferences such as ICSE , PLDI , and ASE . Contact: j.bell@northeastern.edu | jon@jonbell.net

Lina von SydowView profile

Professor

• Computational Science
• Computational Finance
• Ice Sheet Modeling
• +2 more

Lina von Sydow is a Professor in Computational Science at Uppsala University's Department of Information Technology. She serves as Section Dean for the Mathematical-Computer Science Section since July 2023. Her academic journey includes becoming an Associate Professor in 2000, Senior Lecturer since 1997, and leading the Department of Information Technology from 2018 to 2023. PhD in Domain Decomposition Methods (1995, Uppsala University) Postdoctoral Fellow at Oxford University (1996-1997) Her research spans computational science with dual focuses on Computational Finance and Ice Sheet Modeling . In finance, she develops numerical methods for option pricing using PDEs, radial basis functions, and stochastic volatility models. In climate science, she contributes to ice sheet dynamics through full Stokes models and adaptive time-stepping approaches, particularly in simulating grounding line migration. Recent publications (2025) address gender disparities in IT education, including comparative analysis of admission trends and intervention studies to boost female enrollment. Earlier works (2020-2015) focus on high-order finite difference methods for financial derivatives, BENCHOP benchmarking projects, and preconditioning techniques for PDEs. Scientific awards include Excellent Teacher (2013) She actively collaborates on educational reforms, co-authoring studies like Gender-aware course reform in Scientific Computing (2013). Her leadership roles include Head of Department (2018-2023) and Section Dean (2023-present), influencing academic governance and interdisciplinary research. Labs and teams: Works with Uppsala University's Computational Science group, Elmer/ICE project collaborators (e.g., Per Lötstedt, Gong Cheng), and international partners in numerical finance and climate modeling.

• Physics of Climate
• Climate Dynamics
• Turbulence
• +9 more

Peter D. Ditlevsen is a Professor at the Niels Bohr Institute , University of Copenhagen, specializing in Physics of Ice, Climate and Earth (PICE) . With a background in theoretical physics, he transitioned to climate dynamics and turbulence. Dr. Scient (2004), University of Copenhagen PhD (1991), Technical University of Denmark Research Interests : Focuses on Tipping Points in the Earth System , especially AMOC collapse , using stochastic dynamical systems , alpha-stable processes , and nonlinear climate modeling . His work bridges climate physics , dynamical meteorology , and time series analysis . Recent Publications : 2025 work on ice-core-based Dansgaard–Oeschger event modeling , 2024 studies on AMOC multistability and complex system predictability , and 2023 Nature Communications paper on AMOC collapse early warning (cited 4000+ times in media). Scientific Leadership : Leads CriticalEarth H2020 (2021-24) and contributed to TiPES (2019-23). Holds Carlsberg Fellowship and Ole Rømer Prize . Outreach : Produces weekly climate science podcast with David Trads, delivers 4-6 public lectures/year, and has appeared in 40+ media outlets. Teaches Electrodynamics , Thermodynamics , and Turbulence courses.

Michael NothnagelView profile

Professor

• Statistical Genetics
• Genetic Epidemiology
• Population Genetics
• +5 more

Michael Nothnagel is a Professor at the University of Cologne, where he leads the Department of Statistical Genetics and Bioinformatics within the Cologne Center for Genomics (CCG). His work spans statistical genetics, genetic epidemiology, and forensic genetics, focusing on methodological development and large-scale genomic data analysis. His research interests encompass theoretical and applied statistical genetics, with emphasis on human genetic diversity, disease etiology, and forensic applications. Key areas include Y-chromosomal phylogeography, genome-wide association studies for complex diseases, development of statistical methods for variant interpretation, and forensic marker optimization. His group leverages next-generation sequencing data and specialized forensic markers to address questions in population history, disease mechanisms, and identification systems. Recent publications reveal a strong focus on computational approaches to genetic analysis, including spatial frequency interpolation for haplogroup mapping, polygenic risk score applications for behavioral traits, and advanced methods for variant classification. His work demonstrates consistent integration of statistical theory with practical applications in medical and forensic genetics, often through international collaborations like the VISAGE Consortium. Nothnagel maintains active involvement in the Cologne Center for Genomics, contributing to seminars and collaborative projects including the upcoming 34th International Genetic Epidemiology Society meeting. His research group operates at the intersection of computational biology and medicine, with particular strengths in handling complex genomic datasets and developing novel analytical frameworks for genetic epidemiology.

• Indoor Air Quality
• Healthy Buildings
• Exposure Assessment
• +3 more

Joseph G. Allen is an Associate Professor at Harvard T.H. Chan School of Public Health, where he directs the Harvard Healthy Buildings Program and serves as Deputy Director of the Harvard Education and Research Center for Occupational Safety & Health . He holds leadership roles in major public health initiatives including as Commissioner for The Lancet COVID-19 Commission and Scientific Advisor to the White House (2022-2024). His work bridges environmental health, building science, and public policy to advance human health in indoor environments. Education: D.Sc. in Exposure Assessment, Environmental Epidemiology & Biostatistics – Boston University MPH in Environmental Health – Boston University BS in Biology – Boston College Certified Industrial Hygienist (CIH) Research Focus: Dr. Allen's work centers on indoor environmental quality and its impact on human health. His research examines: 1) Airborne pathogen transmission mitigation strategies, 2) Chemical exposure pathways in built environments, 3) Climate-resilient building design, and 4) Global health equity in environmental interventions. His studies employ field measurements, computational modeling, and epidemiological approaches to develop evidence-based building standards. Publications: His recent 15 publications demonstrate consistent focus on air quality interventions, chemical exposure assessment, and health-focused building design. Key themes include pandemic-responsive ventilation standards, PFAS contamination mitigation, global health equity in environmental interventions, and technological innovations in exposure monitoring. His work appears in both scientific journals and policy-oriented outlets like Harvard Business Review. Awards & Leadership: Scientific Advisor to White House & Massachusetts Governor Chair of Lancet COVID-19 Task Force for Safe Work/Schools/Travel Co-Chair of Harvard Sustainability Committee's 2050 Subcommittee Program Direction: As Director of the Harvard Healthy Buildings Program, Dr. Allen leads interdisciplinary research translating building science into public health practice. The program collaborates with governments and industries worldwide to implement health-focused building standards and exposure reduction strategies.

Christian KochView profile

Professor

• Construction Industry
• Climate Change
• Engineering
• +7 more

Christian Koch is a Professor and Head of Section at the University of Southern Denmark (SDU) Civil and Architectural Engineering, Department of Technology and Innovation, where he leads research on construction industry dynamics, climate change mitigation, and digital transformation. His work bridges institutional theory with practical challenges in sustainable development and organizational innovation. SDU Climate Cluster EU SAND Project Participant Creative Construction Conference Chair Research interests include circular economy implementation, blockchain in construction logistics, lean construction methodologies, and AI applications for safety analysis. His studies focus on institutional entrepreneurship, interorganizational networks, and policy impacts on construction practices, particularly in Denmark and Sweden. Recent article trends analyze machine learning for accident report analysis, blockchain-enabled resource marketization, and climate-resilient infrastructure. Notable awards include the Taylor and Francis Best Theoretical Paper (2025), SCC Fast Track Award (2024), and CME Best Paper on Societal Challenges (2022). Scientific awards include: Taylor and Francis Best Theoretical Paper (2025) SCC Fast Track November 2024 CME Best Paper Transformative Impact (2022) Best Paper Creative Construction Conference (2025) He actively participates in public discourse through media engagements on construction safety, climate adaptation, and sustainable sand extraction for green transitions.

Markus VenohrView profile

Researcher

• Nutrient fluxes
• River system modelling
• Water quality management
• +5 more

Dr. Markus Venohr is a Senior Scientist and Research Group Leader at the Leibniz-Institute of Freshwater Ecology and Inland Fisheries (IGB) in Berlin, Germany, where he leads the River System Modelling research group within Department 1 (Ecohydrology and Biogeochemistry). He holds a PhD from Humboldt-University Berlin and has been with IGB since completing his doctorate, first as a Post-doc (2006-2008) and then as a Senior Scientist since 2009. Dr. Venohr received his PhD from Humboldt-University Berlin (2001-2005), following studies in Geography, Meteorology and Oceanography at Christian-Albrechts University Kiel (1996-2000), and initial Geography studies at Ruhr-University Bochum (1994-1996). His research focuses on nutrient fluxes from land to sea , nutrient transport and transformation , biotic-abiotic coupling , river system modelling , climate change and management adaptation , and recreation ecology . Dr. Venohr specializes in understanding how human activities impact freshwater systems, particularly through nutrient pollution from agricultural and urban sources, and develops models to assess and predict these impacts. His work bridges the gap between scientific research and practical water management solutions. Dr. Venohr's recent publications demonstrate a strong focus on nutrient modeling (particularly the AGRUM-DE framework), water quality assessment across scales from Berlin waterways to the Danube basin, and the impacts of human activities on freshwater ecosystems. His research increasingly addresses urban pollution sources, recreation ecology impacts, and climate adaptation strategies, with significant international collaborations evident in his work on topics ranging from the Kakhovka Dam destruction to nicotine contamination in surface waters. AQUATAG (2019-2022): Water-based recreational activities analysis BAUM (2015-2018): Climate adaptation measures in Brandenburg MARS (2014-2018): Multiple stressors in aquatic ecosystems OSCAR (2017-2020): Riparian buffer strips optimization RESI (2015-2018): Ecosystem services of rivers and floodplains He leads the River System Modelling group at IGB, which develops and applies advanced modeling approaches including MONERIS and AGRUM-DE to understand human impacts on freshwater systems. The group works closely with water management authorities across Germany and Europe to translate scientific findings into practical management solutions, particularly regarding nutrient pollution reduction and climate adaptation strategies.

Neil LawrenceView profile

Professor

• Machine Learning
• Artificial Intelligence
• Uncertainty Quantification
• +3 more

Neil Lawrence is the inaugural DeepMind Professor of Machine Learning at the University of Cambridge's Department of Computer Science and Technology. He also holds positions as a Senior AI Fellow at The Alan Turing Institute and a Visiting Professor of Machine Learning at the University of Sheffield. After three years as Director of Machine Learning at Amazon, Lawrence recently returned to academia, bringing extensive industry experience to his academic work. Lawrence's research focuses on the intersection of machine learning with the physical world, particularly in uncertainty quantification and end-to-end solutions for real-world applications. His work was initially inspired by deploying machine learning systems in African contexts, where comprehensive solutions are often required. His technical expertise spans over two decades in machine learning methods, with a growing interest in public understanding of machine learning, policy decisions, and data governance implications. His recent publications reveal a diverse research portfolio spanning climate science, healthcare applications, systems engineering for AI deployment, data governance, and theoretical machine learning. Lawrence's work demonstrates a consistent theme of bridging theoretical machine learning with practical applications across multiple domains, with particular attention to uncertainty quantification and the societal implications of AI systems. Lawrence serves on the board of the AISTATS conference and the ELLIS Foundation, and acts as the founding and series editor for the Proceedings of Machine Learning Research. He is also the co-host of the Talking Machines podcast, demonstrating his commitment to public engagement with machine learning concepts. At Cambridge, Lawrence teaches Advanced Data Science (Part II) and Machine Learning and the Physical World (MPhil ACS, Part III), contributing to both undergraduate and postgraduate education in computer science. His work with the Accelerate Programme for Scientific Discovery and the Data Trusts Initiative positions him at the forefront of developing frameworks for responsible and effective AI deployment in scientific and societal contexts.

PASCUAL ALVAREZ GOMEZView profile

Professor

• Ground Engineering
• Thermal Engineering
• Production Technologies

PASCUAL ALVAREZ GOMEZ is a Professor at the University of Cádiz, affiliated with the Department of Industrial Engineering and Civil Engineering. His research focuses on Ground Engineering and Thermal Engineering, with a particular emphasis on geothermal heat pumps and thermal performance modeling. He is associated with the TEP221 Thermal Engineering research group and contributes to the PAIDI area of Production Technologies. Education: PhD in Industrial Engineering from the University of Cádiz (2014), with a thesis on "Vertical Ground Heat Exchanger Simulation Model for Geothermal Heat Pumps" Research: Specializes in hybrid thermal modeling, CFD analysis for evaporation rates, and machine learning applications in corrosion prediction His publications highlight advancements in geothermal systems, low-concentration photovoltaics, and biogas environment corrosion analysis. He employs both analytical and computational fluid dynamics (CFD) approaches for energy efficiency improvements.

Priyanko GuchaitView profile

Professor

• Organizational Behavior
• Error Management Culture
• Leadership
• +7 more

Priyanko Guchait is a tenured Full Professor and Program Director of the Doctorate in Global Hospitality Leadership (DGHL) at the Conrad N. Hilton College of Global Hospitality Leadership , University of Houston. His research focuses on organizational behavior, leadership, human resources, and service management in hospitality contexts, with over 75 peer-reviewed articles published. Education: B.E. in Mechanical Engineering, University of Pune, India M.S. in Hospitality Management, University of Missouri M.S. in Human Resources and Employment Relations Ph.D. in Hospitality Management, The Pennsylvania State University Research Interests include error management culture, psychological safety, service recovery performance, leader behavioral integrity, and AI’s impact on hospitality workers’ mental health. His work examines shame, forgiveness climate, and team dynamics in service environments. Article Trends show a focus on multi-level error management, human-robot collaboration in service recovery, diversity inclusion climates, and cross-cultural leadership studies. Recent papers explore AI ethics, pandemic response strategies, and emotional labor in hospitality roles. Awards & Honors Stephen Rushmore/HVS Research Excellence Award (2023, 2015) Donald Greenaway Excellence in Research, Teaching, and Service Award (2022) Best Paper Award, The Service Industries Journal (2023) ICHRIE Faculty Collegiality Award (2021) ICHRIE McCool Breakthrough Award (2021) Honored as 50-in-5 Scholar (2021) Provost’s Excellence Award (2015) Best Reviewer Awards (IJCHM 2016-2017) Committee & Editorial Roles include Associate Editor of IJCHM, Coordinating Editor of IJHM, and leadership positions at ICHRIE (President 2020-2021, Vice President 2019-2020). He has served on university curriculum, research, and Ph.D. selection committees.

Zakaria BABUTSIDZEView profile

Professor

• Behavioral Economics
• Environmental Economics
• Consumer Behavior
• +6 more

Zakaria BABUTSIDZE is a Professor of Economics at SKEMA Business School in France, where he has been teaching since 2011, progressing from Assistant Professor to Associate Professor and finally to full Professor in 2021. His academic affiliations also include positions at Côte d'Azur University, Sciences Po Paris (where he serves as an Economist at OFCE since 2011), and previous visiting positions at institutions including Griffith University, North Carolina State University, and Maastricht University. His research interests span behavioral and environmental economics, with a particular focus on consumer decision-making in digital contexts, green consumer behavior, social networks, and agent-based modeling of economic phenomena. BABUTSIDZE has made significant contributions to understanding how digital environments shape consumer interactions, environmental attitudes, and trust formation. His recent publications demonstrate a strong trend toward interdisciplinary research combining economics with psychology, computer science, and environmental studies. His work frequently employs experimental methods, both laboratory and field-based, to examine consumer behavior in digital environments, the impact of social networks on market dynamics, and the relationship between media consumption and environmental attitudes. SMBG special prize for innovation 2015 (awarded to MSc Digital Business in capacity of Academic Director) The Best Young Scholar Paper Award 2011 (DIME final conference / DIME network of Excellence) The Outstanding PhD Paper Award 2009 (European Meeting on Applied Evolutionary Economics) As an academic advisor, BABUTSIDZE has supervised multiple doctoral students at SKEMA Business School and Université Côte d'Azur. His research has been supported by numerous grants from Université Côte d'Azur, the Sloan Foundation, and other institutions. He is also actively involved in conference organization and serves as a reviewer for numerous prestigious economics and interdisciplinary journals.

Jonathan L. AuerbachView profile

Assistant Professor

• Data Science
• Causal Inference
• Survey Methods
• +6 more

Jonathan L. Auerbach is an Assistant Professor in the Department of Statistics at George Mason University . His work bridges statistics and public policy , focusing on causal inference , longitudinal data analysis , and official statistics . He has contributed to understanding urban myths (e.g., New York City rat populations, building height trends), election fraud , and policy evaluation for initiatives like Vision Zero. Education : PhD in Statistics (Columbia University, 2020), BA in Economics (Cornell University, 2010) Research Interests include data science , causal inference , survey methodology , and urban analytics . His recent work addresses climate change impacts on cherry blossom seasons, federal data security , and street vendor demographics in New York City. Scientific Awards include the 2024-2025 President of Washington Statistical Society , 2020-2021 American Statistical Association Science Policy Fellow , and 2019 Howard Levene Outstanding Teaching Award . He has served as an instructor for courses like Capstone in Statistics and Causal Inference , emphasizing technical communication and data ethics .

Ottar BjornstadView profile

Professor

• Population Ecology
• Epidemiology
• Mathematical Biology
• +2 more

Ottar Bjornstad is a Distinguished Professor of Entomology and Biology at Pennsylvania State University, holding the Huck Chair of Epidemiology. He is affiliated with multiple research centers, including the Center for Infectious Disease Dynamics, One Health Microbiome Center, and Center for Mathematical Biology. His research focuses on population ecology, epidemiological modeling, and the mathematical foundations of infectious disease dynamics. He investigates how climate change affects ecological systems, transmission patterns of zoonotic diseases, and the interplay between host demographics and disease spread. Recent publications highlight his work on dengue virus transmission, vaccine distribution logistics, and age-structured epidemic models. His studies span disciplines including ecology, virology, and computational epidemiology. Elected to Norwegian Academy of Sciences and Letters (2021) He collaborates with institutions worldwide, addressing global health challenges like Lassa virus spread and measles persistence mechanisms. His methodological contributions include statistical frameworks for epidemic analysis and spatial synchrony metrics.

Wai Kiong Oswald ChongView profile

Associate Professor

• Artificial Intelligence
• Engineering Systems
• Optimization
• +10 more

Dr. Wai Kiong Oswald Chong is an Associate Professor at Arizona State University's School of Sustainable Engineering and the Built Environment, with a dual affiliation as Senior Global Futures Scientist at the Global Futures Scientists and Scholars program. He holds a PhD in Civil Engineering from the University of Texas-Austin, MSc and BSc in Building from the National University of Singapore, and focuses on integrating artificial intelligence with sustainable engineering systems. PhD (2005): Civil Engineering, University of Texas-Austin MSc (1999) & BSc (1997): National University of Singapore His research bridges lunar construction with Earth-bound sustainable systems, covering topics like: Space habitat modularization Resource circularity systems AI-enhanced building codes Climate-resilient infrastructure Advanced energy modeling Construction supply chain optimization Publications demonstrate consistent focus on: Semiconductor facility HVAC optimization Building energy consumption anomalies Life cycle assessment frameworks Construction risk management Deconstruction and material reuse AI-driven system modeling Current research projects include: Lunar MVI (Moon Village Initiative) Semiconductor fab design optimization Human-AI knowledge interfaces Thermal insulation systems for extreme environments Smart grid energy modeling

Arnab NandiView profile

Professor

• Database Systems
• Human-in-the-Loop Data Analytics
• Next-Generation Query Interfaces
• +10 more

Arnab Nandi is a Professor in the Department of Computer Science & Engineering at The Ohio State University. His work bridges human interaction with data infrastructure, focusing on database systems, LLM-augmented analytics, and immersive query interfaces. Education: PhD in Computer Science & Engineering from the University of Michigan Leadership: Co-founder of OHI/O Hackathon Program and STEAM Factory interdisciplinary network Research spans human-in-the-loop data analytics , vibe querying (natural language + gestural interfaces), LLM integration into education, and climate response systems . Key projects include Omni (multimodal exploration), GestureDB , and Icarus (clinical pipelines). Recent publications analyze LLM-driven query stacks (HILDA 2025), video analytics (SIGMOD 2022), and data sunglasses for cognitive limits (HILDA 2025). Awards include NSF CAREER Google Faculty Research Award IEEE TCDE Early Career Award ACM Distinguished Member Advises students in database innovation , with alumni at Amazon, AWS, Roblox, and Meta. Teaches CSE 3241 (Database Systems), CSE 5889 (Software Startups), and CSE 5242 (Advanced Databases).