Find Academic Supervisors

Marynia Aniela KolakView profile

Assistant Professor

• Geographic Information Science
• CyberGIS and Geospatial Data Science
• GIS and Society
• +3 more

Marynia Aniela Kolak is an Assistant Professor and Principal Investigator of the Healthy Regions & Policies Lab at the University of Illinois, Urbana-Champaign. She holds affiliations with the Center for Social & Behavioral Sciences, National Center for Supercomputing Applications, and other campus units. Her research focuses on geospatial analysis of social and health inequities, particularly in urban contexts. She integrates CyberGIS, spatial statistics, and community engagement to address issues like opioid treatment accessibility, food access disparities, and social determinants of health. Key research areas include: CyberGIS and Geospatial Data Science GIS and Society Space-Time Analytics Social-spatial networks Urban health disparities Her recent work emphasizes spatial equity in healthcare access, particularly for marginalized populations. Notable projects include analyzing opioid use disorder medication accessibility in jails and quantifying neighborhood-level health determinants. She employs mixed-methods approaches combining GIS modeling with community engagement strategies. Dr. Kolak collaborates with interdisciplinary teams across public health, computer science, and urban planning. Her lab (Healthy Regions & Policies Lab) develops innovative geospatial tools to support evidence-based policy decisions. Current research trends show strong focus on applying advanced spatial analytics to urgent public health challenges.

Bryan MarkView profile

Professor

• Physical Geography
• Climate and Environmental Change
• Paleoclimatology
• +4 more

Bryan Mark is a Professor in the Department of Geography at The Ohio State University, affiliated with the College of Arts and Sciences. He is also involved with the Byrd Polar and Climate Research Center and the State Climate Office of Ohio. His research focuses on physical geography, climate-glacier-hydrologic dynamics, and mountain studies, with fieldwork in the Peruvian Andes, Great Basin, and Himalayas. Education: Ph.D. 2001, Syracuse University (Earth Sciences) M.A. 1995, Ohio State University (Geography) B.A. 1992, Brown University (History) Research Interests: Earth-Water-Atmosphere interactions, tropical glaciers, and climate change impacts on mountain regions. His work integrates field, lab, and computational methods across disciplines like paleoclimatology, geomorphology, and biogeochemistry. Recent projects include studying glacier retreat, proglacial hydrology, and climate adaptation strategies in vulnerable regions. Advising & Grants: Leads the Glacier Environmental Change research group, collaborating internationally. Active in interdisciplinary projects funded by NSF and other agencies. Courses taught include climatology, global environmental change, and mountain geography. Labs/Teams: Byrd Polar and Climate Research Center, State Climate Office of Ohio. His lab focuses on mountain hydroclimate dynamics and cryo-social systems in the American Cordillera and Himalayas.

Lucas Gomez TobonView profile

Adjunct Professor

• Applied Machine Learning
• Social Good Applications
• Statistical Analysis
• +3 more

Lucas Gomez Tobon is an Adjunct Professor at Universidad de los Andes, teaching machine learning and game theory. He serves as Deputy Director of the Data Mining Department at Quantil. Holding a Master’s in Economics from Universidad de los Andes, his research focuses on applied machine learning for social good, including crime modeling and music-driven statistical analysis. His notable works include predicting Colombian music charts using CNNs (69% recall) and linking musical trends to economic indicators (82% variability explanation in Consumer Confidence Index). Recent projects include a REDNACECYT-MD4SG Summer of Science intervention in a Mexican indigenous community and developing the tidyX NLP preprocessing package. His 2023 CLATSE presentation on underreported crime modeling received media attention via Caracol Radio. Research spans spatio-temporal crime patterns, econometric applications of music data, and social impact technologies.

Cory McCartanView profile

Professor

• Computational Social Science
• Bayesian Methods
• Causal Inference
• +5 more

Cory McCartan is the Hoben and Patricia Thomas and Thomas and Ann Hettmansperger Early Career Professor of Statistics at Penn State University, with an affiliate appointment in Political Science. His research focuses on methodological and applied problems in computational social science, including redistricting, Bayesian methods, causal inference, and racial disparities. He co-leads the Algorithm-Assisted Redistricting Methodology (ALARM) Project at Harvard University and develops open-source software for redistricting analysis (e.g., redist , birdie ). McCartan holds a Ph.D. in Statistics from Harvard (2023) and a B.A. in Mathematics from Grinnell College (2019). His work bridges statistical methodology and policy applications, with recent emphasis on legislative redistricting reforms, gerrymandering analysis, and privacy-preserving census data methods. Key projects include evaluating redistricting algorithms, quantifying partisan bias, and estimating disparities in administrative data using Bayesian models. Publications span topics like redistricting simulation, census privacy impacts, and neighborhood modeling. His ALARM Project produces 50-state redistricting simulations for public use, emphasizing reproducible workflows and open-source tools. McCartan's software packages ( e.g. , redist , conformalbayes ) are widely adopted in policy and academic research. Grants and collaborations involve the Voting and Election Science Team and Harvard Data Science Initiative, with computational support from Microsoft. His work has been covered in Science Advances , Proceedings of the National Academy of Sciences , and Science .

Subra SureshView profile

Professor

• Algorithmic Fairness
• Machine Learning Ethics
• Data Privacy
• +3 more

Subra Suresh is a Professor at Large at the School of Engineering, Brown University. His email is Subra_Suresh@brown.edu . He focuses on interdisciplinary research at the intersection of technology and society, emphasizing algorithmic fairness, AI ethics, and computational law. His research interests include addressing biases in machine learning systems, ensuring equitable access to technology, and developing frameworks for ethical AI governance. He explores topics such as data privacy, social network disparities, and legal implications of emerging technologies. Recent publications highlight trends in auditing algorithms for fairness, mitigating bias in decision-making systems, and designing policies for responsible AI deployment. His work bridges technical innovation with societal impact, advocating for transparent and accountable technologies. No scientific awards or grants are explicitly listed in the provided materials. He has not disclosed advisee information, and there is no mention of lab affiliations or teams in the text.

Zeyana HamidView profile

Lecturer

• Public Health Informatics
• Health Information Systems
• Community Health
• +1 more

Dr. Zeyana Hamid is a Lecturer in Health Informatics at Indiana University Indianapolis's Luddy School of Informatics, Computing and Engineering. Her interdisciplinary work integrates health informatics, public health, and systems engineering to improve evidence-based practices in community health settings. Research focuses on: Public health information system design Interoperability of clinical and socioeconomic data Resource coordination for mental health services Geospatial analysis for health outcomes Dr. Hamid has developed statistical software integrating clinical, census, and socioeconomic data to analyze health disparities. She consults with NGOs on mental health informatics ecosystems and has implemented systems for resource sharing in Tanzania. Her approach emphasizes community-centered design and practical applications of informatics in underserved areas. She holds a Ph.D. in Health Informatics from the University of Missouri-Columbia, along with master's degrees in Health Informatics and Health Administration, and graduate certificates in Public Health and Geographic Information Systems.

• Machine Learning
• Healthcare Analytics
• Telecommunication Industry Analysis
• +3 more

Karl Hall is a Lecturer in Computing & Games at the Department of Computing & Games, Teesside University. His research focuses on machine learning applications across diverse domains including healthcare analytics, telecommunication, traffic modeling, and social network analysis. He specializes in developing predictive models for credit risk assessment, disease diagnosis, customer behavior analysis, and infrastructure optimization. Key research interests include machine learning algorithms (e.g., Random Forest, CNNs), explainable AI systems, and their practical implementations in real-world scenarios. He has conducted studies on diabetes prediction, pandemic forecasting, and metaverse risk assessment. His work often bridges theoretical models with practical industry challenges, particularly in finance, healthcare, and transportation sectors. Recent research trends show a focus on interdisciplinary applications of AI, such as biomedical information retrieval frameworks and transformer-based models. He has collaborated on projects analyzing UK traffic datasets and Bitcoin trader networks, highlighting his versatility in data-driven research. No awards or grants are explicitly mentioned in the provided texts. His advising and professional activities are not detailed in the current data, but his publications reflect active engagement with both academic and applied research challenges.

Robert BoriaView profile

Assistant Professor

• Ecology
• Evolutionary Biology
• Climate Science
• +3 more

Robert Boria is an Assistant Professor in the Department of Biology at San Francisco State University. His research focuses on ecology, evolution, and climate change impacts on small mammals, particularly investigating historical genetic diversity and climate refugia. He employs interdisciplinary methods including phylogenetics, ecological niche modeling, and field/museum sampling. Boria leads the Boria Lab, which studies urbanization effects on mammal evolution in the San Francisco Bay Area. Education: Ph.D. in Biology from the University of California, Merced. Specializes in phylogeography, species distribution modeling, and phylogenetics. His work integrates bioinformatics, spatial mapping, and lab techniques (DNA extraction, ancient DNA analysis). He emphasizes evidence-based teaching practices and inclusive classrooms. Research trends in his publications include advancing species distribution modeling tools (ENMeval), analyzing rodent population dynamics, and exploring historical climatic influences on biodiversity. His work bridges computational methods with field ecology to address global change challenges. No scientific awards explicitly listed. Advising and grants: Involves students in lab research projects, though specific grants/advising records are not detailed here. The Boria Lab website provides further details on current projects and collaborations. Labs: Boria Lab focuses on ecology-evolution-global change intersections, with facilities in Hensil Hall. Active in both fieldwork and computational research, addressing urbanization impacts and climate adaptation strategies.

Kim LerschView profile

Professor

• Environmental Criminology
• Geographic Information Systems (GIS)
• Risk Terrain Modeling
• +3 more

Kim Lersch is a full Professor of Criminology at the University of South Florida School of Information , where she integrates Geographic Information Systems (GIS) with criminological research. Her work applies Risk Terrain Modeling and spatiotemporal analysis to study behavioral health issues (suicides, opiate overdoses), crime patterns, and police accountability. Current projects examine the geospatial aspects of suicide and community resources for recently released prison inmates. Ph.D. in Sociology from University of Florida (1995) M.A. in Sociology from University of Florida B.A. in Criminology from University of South Florida Her research focuses on environmental risk factors influencing crime, disorder, and mental health. Key projects include: Drug Overdose Geospatial Analysis in Detroit using 911 data Domestic Violence Spatiotemporal Trends during the pandemic Suicide Pattern Analysis with Risk Terrain Modeling Lead Exposure and Crime correlations in Florida Recent publications emphasize GIS applications in public safety , pandemic-related crime shifts , and policy recommendations for overdose response. While no specific awards are mentioned, her work bridges criminology , public health , and urban planning to address critical social issues.

Michael GavinView profile

Associate Professor

• Digital Humanities
• Computational and Quantitative Research Methods
• British Literature
• +3 more

Michael Gavin is an Associate Professor in the Department of English Language and Literature at the University of South Carolina's College of Arts and Sciences. He is also the Peter and Bonnie McCausland Faculty Fellow and a College of Arts and Sciences Innovative Teaching Associate (2020–2022). His work bridges literature, intellectual history, and digital humanities. Ph.D., English, Rutgers University (2010) B.A., English, The Ohio State University (1999) His research explores the intersection of technology, communication, and literary history. Current projects examine how digital writing and computational analysis enable new approaches to language and historical interpretation, with a focus on: Digital humanities methodologies Computational and quantitative research British literature analysis Language geopolitics The 15 most recent publications span 2025–2018, with a concentration on digital humanities frameworks, geospatial semantics, and computational approaches to historical texts. Trends include critical realism applications (2021), agent-based modeling of economic theories (2018), and linguistic analysis of geopolitical conflicts (2023). Peter and Bonnie McCausland Faculty Fellow (2020–2022) College of Arts and Sciences Innovative Teaching Associate (2020–2022)

• Poverty Studies
• Sociology of Inequality
• Quantitative Methods
• +4 more

Jennifer Laird is an Assistant Professor of Sociology at Lehman College (City University of New York, CUNY). She holds a Ph.D. in Sociology from the University of Washington. Her research focuses on poverty, inequality, and quantitative methods, with recent work examining energy insecurity, public sector employment disparities, and immigration policy impacts on vulnerable populations. She co-authored the 2025 book *Powerless: The People's Struggle With Energy Insecurity in America* (Russell Sage Foundation), advancing analysis of household energy hardships. Her peer-reviewed articles span topics such as job stability for Black public-sector workers, state-level poverty variations, and labor force dynamics among Mexican immigrants. Laird’s work has been featured in outlets like *Health Affairs*, *Socius*, and *Demography*, and she received an Honorable Mention for her 2014 student paper from the ASA Population Section. Laird teaches courses in data visualization and social research methods, emphasizing statistical programming and effective data interpretation. At Lehman College, she instructs Sociology 301 (Methods of Social Research) and Sociology 353 (Visualizing Data). Her teaching background also includes roles as a Teaching Assistant at the University of Washington for courses on stratification and applied statistics. Her research has garnered media coverage in *The New York Times*, *Washington Post*, and *Huffington Post*, highlighting the societal implications of her findings on topics like public sector layoffs during the pandemic and SNAP policy impacts on immigrant children.

David GoldbergView profile

Professor

• Theoretical Cosmology
• Extragalactic Astrophysics
• Gravitational Lensing
• +2 more

David Goldberg is Professor and Head of the Physics Department at Drexel University. His NSF-funded research focuses on theoretical cosmology, gravitational lensing, and large-scale structure. He holds a PhD from Princeton University and authored multiple books including The Standard Model in a Nutshell and A Relatively Painless Guide to Special Relativity . Research highlights: Cosmic structure formation modeling Flexion lensing techniques Cosmological applications of Bayesian statistics Recent publications analyze gravitational lensing signatures, galaxy mass estimations, and cosmic inflation models. He also contributes to cartography science, developing improved flat map projections.

• Atmospheric Physics
• Environmental Science
• Dark Matter Research
• +6 more

Argiriou Athanassios is a Professor of Atmospheric & Environmental Physics at the Department of Physics, University of Patras, Greece. He has served as Head of the Laboratory of Atmospheric Physics (2006–2016), Head of the Applied Physics Section (2010–2011), Deputy Chair of the Physics Department (2011–2013), and Chair of the Physics Department (2013–2015). His academic journey includes a Physics Degree from the University of Patras (1983), a DEA in Physical Energy from the Institut National Polytechnique de Grenoble (1984), and a Doctorat in Physics from Université de Provence (1987). Research interests focus on atmospheric physics, environmental science, dark matter signatures, climate modeling, stable isotope analysis, and energy efficiency. Notable projects include studies on precipitation isotopes in China, quantum computing applications in atmospheric dynamics, and dark matter’s influence on geophysical observations. He has also contributed to energy performance regulations for buildings in Greece and maritime emissions’ impact on air quality in Mediterranean port cities. Recent publications (2020–2025) reveal a strong emphasis on interdisciplinary research, blending geophysics with astrophysics to explore dark universe phenomena and their terrestrial manifestations. His work on Bayesian statistical models for temperature trends and solar energy systems underscores practical applications in climate science and renewable energy. Professional affiliations include membership in the Hellenic Association of Physicists, Hellenic Meteorological Society, and American Geophysical Union. His teaching spans calculus, differential equations, and atmospheric physics courses. Key facilities include the Laboratory of Atmospheric Physics and collaborations with international institutions on climate and energy projects.

Giovanni QuattroneView profile

Senior Lecturer

• Artificial Intelligence
• Urban Informatics
• Crowd-Sourcing and Volunteered Geographic Information
• +5 more

Dr. Giovanni Quattrone is a Senior Lecturer in the Department of Computer Science at Middlesex University. His research focuses on the intersection of urban informatics, crowd-sourcing systems, and sharing economy dynamics. He has conducted extensive studies on platforms like Airbnb, analyzing their socio-economic impacts and spatial penetration patterns. His work also explores maintenance practices in collaborative mapping projects such as OpenStreetMap, emphasizing data quality and volunteer engagement. Education & Professional Background PhD in Computer Science (inferred from academic role) Research Interests Dr. Quattrone investigates urban data analytics, including: Crowd-sourcing methodologies for urban planning Social and economic implications of the sharing economy Machine learning applications for environmental forecasting Data maintenance in collaborative geospatial systems Publications Trends His recent work (2024-2015) demonstrates a sustained focus on: Sharing Economy Analysis : Evaluating Airbnb's impact on urban gentrification and socio-spatial equity Crowd-Mapping Systems : Improving data quality and volunteer retention in humanitarian mapping Deep Learning Applications : Hybrid models for rainfall prediction and urban pattern analysis Collaborations & Grants He collaborates with researchers on interdisciplinary projects involving: E-Government service optimization using multi-agent systems GIS-based urban well-being indices Crime hotspot modeling using mobile phone data Labs/Teams Associated with Middlesex University's Computer Science research groups focusing on: Urban informatics AI-driven spatial analytics

Yi HuangView profile

Associate Professor

• Biostatistics
• Causal Inference
• Comparative Effectiveness Research
• +9 more

Yi Huang is an Associate Professor in the Department of Mathematics and Statistics at UMBC since 2007, specializing in biostatistics with a focus on causal inference and public health. She holds a Ph.D. in Biostatistics from Johns Hopkins University (2007) and has been a key contributor to interdisciplinary research at the interface of statistics and public health/medicine/biology. Her work emphasizes methodological innovation in comparative effectiveness research, personalized medicine, and post-marketing safety evaluations. Education: Ph.D. in Biostatistics, Johns Hopkins University Bloomberg School of Public Health (2007) NASA Graduate Fellowship recipient (1999) for aerosol-cloud interaction research Research Interests: Causal inference methodologies, including latent propensity score frameworks Comparative effectiveness research (CER) and meta-analysis Applications in gerontology, environmental health, and maternal/child health Statistical design for evaluating traditional Chinese medicine Grants and Awards: NIH R01 Grant Co-PI ($897,348) for pediatric care coordination study (2015–2020) National Institute of Aging Grant ($77,289) for hip fracture studies (2014–2015) Two FDA Critical Path Grants ($50,000 each) for causal methodology development (2008–2011) NASA Graduate Fellowship (1999) Professional Activities: Member: American Statistical Association, International Biometric Society, American Gerontology Society NIH Grant Reviewer (NIDDK), FDA External Reviewer Editorial Board: Internet Journal of Mental Health Teaching and Mentoring: Developed courses in biostatistics principles, categorical data analysis, and longitudinal methods Advised over 20 graduate students across statistics and interdisciplinary programs Focus on critical thinking and real-world application in pedagogy