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Andrew O. Arnold is a Principal Applied Machine Learning Engineer at Shopify and an Adjunct Professor at New York University's Tandon School of Engineering, Department of Finance and Risk Engineering. He earned his Ph.D. in Machine Learning from Carnegie Mellon University and a BA in Computer Science and Artificial Intelligence from Columbia University. Education Ph.D., Machine Learning, Carnegie Mellon University BA, Computer Science and Artificial Intelligence, Columbia University His research focuses on robust machine learning , developing models that perform well in low signal-to-noise regimes, handle distributional shifts (transfer learning), and extract features from unstructured data. Key applications include time series analysis and natural language processing in financial and other domains. Recent publications highlight work on large language models (LLMs) for code generation, including multitask pretraining, contrastive learning, and quantization techniques for efficiency. He has contributed to understanding model robustness and adapting NLP methods to dynamic market conditions. Arnold teaches NYU FRE GY 7871: News Analytics and Machine Learning , covering NLP and ML techniques for quantitative trading strategies. The course emphasizes practical applications of sentiment analysis, text relevance, and novelty detection in financial contexts. He has led teams at Amazon Web Services (AI Labs), served as Chief Scientist at Oracle Alpha, and worked at Microsoft Research, IBM Research, and other institutions. His technical expertise spans code generation , anomaly detection , and NLP for commerce , with patents in these areas.

• Machine Learning
• Natural Language Processing
• Quantitative Trading
• +5 more

Christos Makris is an Associate Professor in the Department of Computer Engineering and Informatics at the University of Patras, Greece. His academic career spans over two decades with significant contributions to computer science, particularly in data structures, algorithms, and information systems. He maintains active research collaborations and supervises graduate students in his areas of expertise. Dr. Makris's research spans several key areas in computer science with a strong focus on efficient data organization and processing. His work encompasses Data Structures , Information Retrieval , Data Mining , String Management and Processing Algorithms , Computational Geometry , Internet Technologies , Bioinformatics , and Multimedia Databases . His interdisciplinary approach bridges theoretical computer science with practical applications across various domains including web technologies, bioinformatics, and emergency response systems. Analysis of Dr. Makris's publication record reveals a consistent research trajectory focused on efficient algorithms for information management. His work demonstrates evolution from foundational data structure research in the 1990s to more applied work in web technologies, social media analysis, and machine learning applications in recent years. A notable pattern is his ability to adapt core algorithmic techniques to emerging application domains while maintaining theoretical rigor. Dr. Makris maintains an impressive scholarly record with over 3,000 citations, an h-index of 29, and an i10-index of 71 according to Google Scholar metrics. These indicators reflect the significant impact of his research within the computer science community. As an active faculty member, Dr. Makris maintains regular office hours on Tuesdays from 18:00-20:00 and Thursdays from 12:00-14:00. He is accessible via email at makri@ceid.upatras.gr or makri@upatras.gr for academic inquiries and student supervision.

• Data Structures
• Information Retrieval
• Data Mining
• +5 more

Pavel P. Kuksa is a Research Assistant Professor in the Department of Pathology and Laboratory Medicine, specializing in bioinformatics, computer science, and functional genomics. His work focuses on high-throughput sequencing analysis, chromatin interaction data, and developing scalable software platforms for genomics research.

• Bioinformatics
• Computer Science
• Functional Genomics
• +5 more

Tyler Simko is an Assistant Professor of Political Science at the University of Michigan, specializing in US state and local politics, political geography, and computational social science. His research focuses on understanding and addressing inequality in American public policy through innovative methodological approaches. Education: Ph.D. in Government, Harvard University (2024) A.B. in Politics, Princeton University Simko's research examines state and local politics in the United States with particular focus on political geography and subnational policymaking. His active research agendas include legislative redistricting ("gerrymandering"), local public meetings, school segregation, affordable housing, and data privacy. Methodologically, he develops new techniques in computational social science and machine learning to evaluate subnational inequality and how it can be reduced. His work regularly involves partnerships with federal, state, and local officials to improve the design of public policy. His recent publications demonstrate a strong focus on applying computational methods to address real-world policy challenges, particularly in school desegregation, redistricting, and local government transparency. His research often leverages large-scale data collection efforts, such as LocalView (the largest database of local government meetings in the US), to analyze patterns of political behavior and policy outcomes across different jurisdictions. Awards and Recognition: APSA 2024-25 Best Paper in Education Politics and Policy Award APSA 2024-25 Best Paper in Urban and Local Politics, Honorable Mention MPSA 2024 Robert H. Durr Award for "the best paper applying quantitative methods to a substantive problem" Derek C. Bok Award for Excellence in Graduate Student Teaching of Undergraduates (2023) Simko teaches graduate and undergraduate courses in American Politics and Political Methodology at the University of Michigan. His teaching experience spans multiple institutions, including Harvard University and Princeton University. He has designed innovative courses on US Local Policymaking, data science, and computational social science. As a Data Scientist at the Office of Evaluation Sciences, he partners with federal, state, and local officials to improve program design and reduce administrative burdens. He is a co-PI of the Algorithm-Assisted Redistricting Methodology (ALARM) Project and co-creator of LocalView, the largest audio, video, and text database of local government meetings in the United States. These projects represent significant contributions to the field of computational social science and provide valuable resources for researchers studying local governance and policy-making.

• State and Local Politics
• Political Geography
• Subnational Policymaking
• +5 more

Christopher Bronk Ramsey is Professor in Archaeological Science and Head of the School of Archaeology at the University of Oxford, affiliated with Merton College. As chair of the INTCAL committee, he oversees global radiocarbon calibration. His expertise spans archaeological science, Quaternary environmental research, and nuclear instrumentation development. Research focuses on radiocarbon dating, Bayesian chronological modeling, and AMS techniques. Key areas include Quaternary chronology, human evolution, climate change impacts, and archaeological applications in the eastern Mediterranean, Amazonia, and Anglo-Saxon England. He develops the OxCal software for statistical chronology analysis. Recent publications emphasize radiocarbon calibration advancements, pre-Columbian land-use in Amazonia, European Neolithic chronologies, and high-precision dating methods. His work integrates archaeology, environmental science, and data science to address chronological challenges across diverse temporal and spatial scales. No specific scientific awards were detailed in the source material. He supervises numerous doctoral students on topics ranging from dendrochronology to digital archaeology and Middle Stone Age chronology. Major projects include FeedSax (Anglo-Saxon agriculture) and HERCA (Amazonian human-environment interactions), securing research grants for interdisciplinary teams. Professor Ramsey directs the OxCal project and co-leads IntCal, IntChron, FeedSax, and HERCA initiatives. These teams develop calibration standards, integrate chronological data, and investigate past human adaptations to environmental change, particularly in Amazonia and Europe.

• Radiocarbon Dating
• Chronology Building
• Archaeological Science
• +4 more

Alton Russell is an Assistant Professor at the Department of Epidemiology, Biostatistics and Occupational Health, Faculty of Medicine and Health Sciences, McGill University. He serves as an Affiliate Investigator at the Research Institute of the McGill University Health Centre (RI-MUHC) and is affiliated with the Quantitative Life Sciences program. His research focuses on data-driven decision modeling to optimize healthcare resource allocation through methods in decision analysis, simulation, health economics, and machine learning. PhD in Management Science and Engineering (2021), Stanford University MSc in Management Science and Engineering (2018), Stanford University BSc in Industrial Engineering (Health Systems concentration) and Interdisciplinary Studies (Global Health and Sustainability concentration) (2014), North Carolina State University Russell's research program develops advanced models for blood safety, pediatric kidney disease management, opioid crisis interventions, and infectious disease surveillance. His lab (D3Mod) integrates individual-level data with machine learning and Bayesian statistics to address heterogeneity in patient populations and policy impacts. His work emphasizes open science practices, with publications and code archived via DOIs. Current research themes include personalized donor risk assessment, emergency service optimization, and harmonization of serosurveillance data. Russell teaches advanced decision modeling (EPIB 676) and economic evaluation of health programs (PPHS 528) at McGill.

• Decision analysis
• Cost-effectiveness analysis
• Simulation modeling
• +4 more

Peter C. Lippert is an Associate Professor in the Department of Geology & Geophysics at the University of Utah , with research spanning paleomagnetism, tectonics, and environmental magnetism. His work connects geological time scales to climate dynamics, orogenic processes, and urban pollution monitoring. BS (2003) and PhD (2010) in Earth sciences Postdoctoral training at University of Arizona and UC Santa Cruz Research focuses include: Antarctic ice age cyclicity and Earth's orbital influences Hydrothermal alteration effects on paleomagnetic records in Tibet Magmatism during Mongol-Okhotsk Ocean closure Magnetofossils as climate proxies for rapid warming events Evergreen needle magnetization for urban pollution mapping Recent publications highlight collaborations across 50+ international institutions , with methodological innovations in site-level paleomagnetic analysis and FORC-PCA magnetofossil discrimination. His 15 most recent articles (2020–2024) address tectonic reconstructions, geomagnetic field evolution, and climate-ocean interactions. He serves on the Magnetics Information Consortium (MagIC) Steering Committee and has received the Taft-Nicholson Summer Faculty Fellow award. Teaching emphasizes Earth science as a philosophy, with courses on structural geology, dynamic Earth systems, and field research.

• Geology
• Geophysics
• Geochemistry
• +5 more

Martin Mayer serves as Associate Professor at the University of Inland Norway within the Faculty of Applied Ecology, Agricultural Sciences and Biotechnology and the Department of Forestry and Outback Studies. Based at the Evenstad study location, his research focuses on large mammal ecology in human-dominated landscapes across Scandinavia and Europe. His primary research interests center on Wildlife Ecology and Large Mammal Conservation , with particular emphasis on human-wildlife conflict resolution, road ecology, and carnivore management. Mayer investigates how species like moose, deer, and beavers adapt to anthropogenic landscapes through habitat selection, movement patterns, and population dynamics. His work integrates cutting-edge methodologies including GPS telemetry, drone surveillance, and citizen science data to address conservation challenges in agricultural and urban settings. Analysis of Mayer's recent publications reveals strong trends in using roadkill data for population monitoring, examining spatial constraints on wildlife movement, and developing mitigation strategies for human-wildlife conflicts. His research increasingly incorporates cross-border European perspectives on wildlife management while maintaining a strong foundation in Scandinavian field ecology. Mayer actively contributes to the LARGE research group (ecology of large animals), which conducts field studies on ungulate behavior, predator-prey dynamics, and landscape-scale conservation planning in Norway's boreal ecosystems.

• Wildlife Ecology
• Large Mammal Conservation
• Human-Wildlife Conflict
• +5 more

Nina Schwarz is Assistant Professor of human-environment interactions in cities at the Department of Urban and Regional Planning and Geo-Information Management, ITC—University of Twente. Holding a Diploma in Environmental Sciences (University of Lüneburg, 2003) and a PhD in Social and Economic Sciences (University of Kassel, 2007), she spent a decade as senior scientist at the Helmholtz Centre for Environmental Research – UFZ before joining ITC. Her interdisciplinary research integrates urban land-use science, ecosystem-service evaluation and advanced modelling techniques—especially agent-based models—to explore sustainable urban development under global change. Research interests revolve around three interconnected themes: (i) urban land-use change —understanding how residential, commercial and green-space dynamics co-evolve; (ii) urban ecosystem services —quantifying both supply and demand of services such as local climate regulation, recreation and biodiversity; and (iii) behavioural modelling —formalising human decision-making to simulate policy scenarios ranging from slum-upgrading to vineyard management. She actively links these themes to UN Sustainable Development Goals, notably SDG 11 (Sustainable Cities) and SDG 15 (Life on Land). Recent publications (2022-2025) reveal a methodological breadth spanning citizen-science impact assessment in Suriname, cooling effects of urban water bodies in Chinese mega-cities, European wine-growers’ adaptive behaviour, and methodological advances in upscaling and validating agent-based land-use models. Across these studies, Schwarz consistently combines empirical field data, geospatial analytics and participatory approaches to produce policy-relevant insights for cities in both the Global North and South. She has (co-)authored >80 peer-reviewed works, accumulating c. 5 900 citations and an h-index of 28 (Scopus). While specific honours are not itemised in the supplied text, her sustained citation impact and invited contributions to major conferences (e.g., iEMSs 2020, IAHR 2025) underscore scientific recognition. Schwarz frequently engages with societal stakeholders: her projects have generated open datasets on urban green-space monitoring in Paramaribo, e-learning modules for Latin-American universities, and interactive dashboards for sustainable water management. Within ITC she contributes to capacity-building programmes for emerging economies, supervises graduate researchers and maintains active collaborations across Europe, Latin America, Africa and Asia. No explicit lists of PhD students or personal grants are provided in the current corpus, but her leadership of externally funded projects (e.g., citizen-science evaluation, vineyard decision-making database) indicates ongoing acquisition of research funding.

• Urban land-use change
• Urban ecosystem services
• Agent-based modelling
• +7 more

Dr. Christoph Trinkl serves as Head of the Institute of new Energy Systems (InES) at Technische Hochschule Ingolstadt, a position he has held since 2008. His work focuses on renewable energy technologies and sustainable energy systems development, with particular expertise in solar thermal applications and system integration. His research interests include: Green Technologies Renewable Energy Technologies Solar Energy Engineering Solar Heating and Cooling Renewable Energy Systems for Industrial, Domestic and Mobility Applications Technology Transfer and Network Management Dr. Trinkl's educational background includes a PhD in Engineering from De Montfort University Leicester's Institute of Energy and Sustainable Development (UK) in 2007, following his work as a researcher at Technische Hochschule Ingolstadt from 2001-2007. His degree course in Mechanical Engineering and Business (1997-2001) provided the foundation for his interdisciplinary approach to energy systems. His recent publications demonstrate a strong focus on practical applications of renewable energy technologies, particularly in solar thermal systems, heat pump integration, and district heating networks. His research spans from fundamental engineering analysis of collector technologies to large-scale system integration and optimization, with increasing emphasis on real-world implementation challenges and optimization techniques including AI-driven approaches. Dr. Trinkl's extensive publication record spanning over two decades shows an evolution from fundamental collector technology research to broader energy system integration, addressing both technical and practical implementation considerations across diverse contexts from industrial applications to rural energy access solutions.

• Green Technologies
• Renewable Energy Technologies
• Solar Energy Engineering
• +6 more

Tej Chajed is an Assistant Professor in the Department of Computer Science at the University of Wisconsin-Madison, where he conducts research in formal verification of systems software. His work focuses on building and proving the correctness of critical systems, particularly file systems and concurrent software. Dr. Chajed earned his PhD from MIT in the PDOS group, followed by a one-year postdoc at VMware Research before joining UW-Madison. His academic journey reflects a strong commitment to bridging theoretical formal methods with practical systems implementation. Chajed's research centers on formal verification techniques for systems software, with particular emphasis on concurrent and crash-safe systems . His work aims to eliminate bugs in critical software through mathematical proofs of correctness. Key contributions include DaisyNFS (a verified concurrent file system), the Perennial framework for reasoning about crash safety, and Goose for connecting proofs to Go code. His research spans the intersection of programming languages, operating systems, and formal methods, developing practical tools that bring verification to real-world systems. His recent publications demonstrate a consistent trajectory toward more practical and scalable verification techniques for increasingly complex systems. The research shows progression from foundational verification frameworks to applied work on specific systems like file systems, journaling, and distributed protocols. A notable trend is the focus on making verification more accessible and practical for systems developers, bridging the gap between theoretical formal methods and real-world software engineering. Dr. Chajed serves on numerous program committees including OSDI 2025 PC, PLDI 2024 PC, SySDW 2023 PC, ECOOP 2023 ERC, CPP 2023 PC, POPL 2023 PC, PLDI 2022 PC, POPL 2022 AEC, EuroDW 2021 PC, POPL 2021 AEC, PLDI 2020 AEC, POPL 2020 AEC, and SOSP 2019 AEC, reflecting his standing in the systems and programming languages research community. In teaching, Chajed has developed and instructed courses on systems verification, operating systems, and protocol verification. He previously helped create MIT's 6.826 (Principles of Computer Systems) during his PhD. His passion for technical communication was cultivated during his time as a Communication Fellow in the EECS Communication Lab at MIT, where he continues to offer guidance to students on writing and presentation skills. His research group at UW-Madison focuses on advancing the state of the art in systems verification, with current projects centered around practical verification frameworks for concurrent and crash-safe systems.

• Formal verification of systems software
• Concurrent systems verification
• Crash-safe file systems
• +5 more

Paola Ricaurte is a Professor in the Department of Media and Digital Culture at the School of Humanities and Education, Monterrey Institute of Technology. She serves as a Faculty Associate at Harvard University's Berkman Klein Center for Internet & Society and represents Mexico in the OECD's Global Alliance for Artificial Intelligence. Institution: Monterrey Institute of Technology School: School of Humanities and Education Department: Department of Media and Digital Culture Additional Affiliations: Faculty Associate, Berkman Klein Center for Internet & Society (Harvard University); Member, Mexican Expert Committee in Global Alliance for AI (OECD) Ricaurte is a leading Latin American activist against hegemonic technological systems that deepen global injustices. Her research examines how AI systems reproduce systemic inequalities, particularly focusing on data-driven modeling biases that exclude women and linguistic diversity. She argues commercial AI is built on principles of economic benefit, making it extractivist, patriarchal, racist and colonialist, with internet data reflecting only hegemonic knowledge rather than true human diversity. Her work analyzes how AI trends emerging from an unequal world impact governance and individuals, especially marginalized communities. The Decolonial Artificial Intelligence Manifesto she authored forms the foundation of her advocacy for technologies that serve diverse populations while preserving ancestral knowledge. Ricaurte coordinates the Feminist AI Research Network (FAIR), which creates feminist action research agendas by and for women across the Global South. Key Publication: Manifiesto de la Inteligencia Artificial descolonial (2024) Ricaurte envisions an inclusive AI future where Indigenous communities develop their own databases and technologies to achieve sovereignty. She advocates for Latin American technological sovereignty, citing successful examples like tools developed with Mexico's Yaqui tribe for water governance, demonstrating how region-specific technologies can solve local problems without colonial, patriarchal, or capitalist logic.

• Decolonial AI
• Technology Ethics
• Data Justice
• +3 more

Dr. Silvi Rouskin serves as Assistant Professor in the Department of Microbiology at Harvard Medical School (Harvard University), where she leads groundbreaking research on RNA structural biology. Her work bridges computational biology, biochemistry, and single-molecule modeling to decode RNA's role in cellular processes and disease mechanisms. Her primary research focuses on RNA structure formation and its impact on gene regulation , alternative splicing , and viral pathogenesis . By pioneering tools like DMS-MaPseq and the DREEM algorithm, her lab detects multiple RNA conformations at single-nucleotide resolution in living cells. Current investigations target human, bacterial, and viral RNA structures to develop machine-learning prediction models for therapeutic applications in cancer and infectious diseases. Dr. Rouskin's publication record centers on RNA structural dynamics, exemplified by her 2020 HIV study revealing how alternative RNA configurations regulate viral gene activity. This work underpins her broader mission to build a comprehensive RNA structure database for accelerating drug target discovery. Her scientific accolades include: Pew Biomedical Scholar (2024) Vilcek Prize for Creative Promise in Biomedical Science (2021) Dr. Rouskin actively mentors the next generation of scientists, having guided at least one PhD candidate (Phil) to completion. Her lab currently supports undergraduate researchers including Tammy and Stuti (studying tau alternative splicing) and Sherry (investigating SMN1/SMN2 structures), reflecting her commitment to hands-on training in RNA biology. The Rouskin Lab operates at the Harvard Medical School campus (77 Avenue Louis Pasteur, NRB 930, Boston), combining wet-lab experimentation with computational innovation to advance structural RNA biology.

• RNA structure
• Gene regulation
• Alternative splicing
• +4 more

Wendy M. Murray is a Professor of Biomedical Engineering and Physical Medicine and Rehabilitation at Northwestern University's McCormick School of Engineering. She leads the ARMS Lab, focusing on biomechanical models of upper limb muscles to improve rehabilitation and prosthetic design. Her work addresses spinal cord injury, stroke, and orthopedic interventions. Education: Ph.D. and M.S. in Biomedical Engineering from Northwestern University, B.S. in Mathematics (summa cum laude) from University of Notre Dame. Research interests include musculoskeletal modeling, prosthetics control, and surgical simulations. Key contributions include widely cited anatomical databases and models for hand/wrist function. Current projects explore neuromuscular control, exoskeletons, and injury prevention in sports like baseball. Publications (selected 2024-2017) highlight advancements in motion capture, ultrasound imaging, and computational models for clinical applications. Her work bridges bioengineering with clinical practice to enhance functional recovery. Labs/Teams: Directs the ARMS Lab, collaborating with clinicians and engineers to translate biomechanical insights into real-world medical solutions.

• Biomechanical Modeling
• Upper Limb Rehabilitation
• Prosthetics and Exoskeletons
• +5 more

Laura Dugan is the Ralph D. Mershon Professor of Human Security and Professor of Sociology at The Ohio State University. She co-leads the Global Terrorism Database (GTD) and Government Actions in Terrorist Environments (GATE) project, which are foundational datasets for understanding terrorism and government responses. Her work focuses on violence prevention policies, methodological innovation for overcoming data limitations, and the intersection of terrorism with political and social contexts. Education includes a Ph.D. and M.S. in Public Policy and Management from Carnegie Mellon University (1995–1999), an M.S. in Statistics (1998), and a B.F.A. in Applied Media Arts from Edinboro University (1987). Research interests span terrorism studies, criminological explanations for violence, government counterterrorism strategies, and methodological approaches to analyzing large-scale datasets. Her work bridges criminology, political science, and sociology, with a focus on empirically grounded analyses of terrorism’s causes and consequences. Publications emphasize terrorism’s global patterns, the efficacy of interventions, and interdisciplinary methodological advancements. Key works include analyses of the GTD’s insights into terrorism’s evolution and GATE’s revelations about government actions’ impact on terrorism. Her grants and advising involve leading large-scale projects like GTD and GATE, which are pivotal for academic and policy communities. She collaborates extensively on datasets and policy-oriented research, influencing both scholarly discourse and practical counterterrorism measures. Laura Dugan’s research teams and labs focus on maintaining and expanding these databases while exploring their applications in policy contexts, ensuring data accessibility for global researchers and practitioners.

• Terrorism Studies
• Criminology
• Political Sociology
• +5 more