Find Academic Supervisors

Gregory ParadisView profile

Assistant Professor

• Sustainable Forest Management
• Operations Research
• Forest Economics
• +7 more

Gregory Paradis is an Assistant Professor in the Department of Forest Resources Management at the University of British Columbia (UBC) Faculty of Forestry. His research focuses on sustainable forest management, integrating operations research, mathematical optimization, and systems modeling to address complex interactions between ecosystems, industries, and society. He works with the FRESH Lab and collaborates with the Integrated Remote Sensing Studio, emphasizing ecological and economic integration in forest planning. Sustainable Forest Management Operations Research Forest Economics Data Science Risk Assessment GIS-based Methods His research spans forest inventory optimization, climate change adaptation strategies, wildfire risk modeling, and decision support systems for invasive species. He develops computational frameworks to enhance wood supply planning, carbon management, and ecological resilience. Recent work includes machine learning applications for fire safety in timber structures and automated road planning tools for wildlife conservation. Paradis’s publications highlight trends in applying optimization methods to sustainable forestry, with a focus on biodiversity, climate adaptation, and value chain innovation. He advocates for interdisciplinary approaches that bridge silviculture, industrial engineering, and data science to tackle emerging challenges in forest ecosystems. As an educator, he seeks motivated students with quantitative and creative problem-solving skills. His lab collaborates on remote sensing integration, risk assessment models, and policy-relevant forest management strategies, ensuring plans account for uncertainties like insect infestations or windthrow events.

Ovijit ChaudhuriView profile

Associate Professor

• Mechanobiology
• Cellular Mechanics
• Extracellular Matrix
• +5 more

Ovijit Chaudhuri is an Associate Professor of Mechanical Engineering at Stanford University, with a courtesy appointment in Bioengineering. He leads research at the interface of mechanics and biology, focusing on how cellular and extracellular mechanical properties influence biological processes like cancer progression and tissue formation. His work employs advanced tools such as atomic force microscopy and 3D cell culture systems. Education: Ph.D., University of California, Berkeley/San Francisco (Bioengineering, 2009) B.S., University of California, Berkeley (Engineering Physics, 2003) Postdoctoral Fellow, Harvard University (Biomaterials, 2013) Research Interests: His lab explores molecular mechanisms behind cellular mechanics, extracellular matrix dynamics, and how mechanical cues regulate cell behavior. Key areas include cancer metastasis, mechanotransduction, and engineered biomaterials for 3D cell culture. Publications Trends: Recent work emphasizes viscoelastic hydrogels, matrix mechanics in cancer progression, and mechanistic insights into cell migration. Over 50 publications since 2015 highlight interdisciplinary approaches in biomaterials and mechanobiology. Awards: Not explicitly listed in provided materials. Advising & Labs: No specific advisee names listed, but his lab focuses on collaborative projects in mechano-biology. Active in developing biomaterial systems for drug discovery and tissue engineering applications. Labs/Teams: Leads the Chaudhuri Lab at Stanford, which integrates engineering principles with biological systems to address complex disease mechanisms and therapeutic strategies.

Michael BaymView profile

Associate Professor

• Microbial Evolutionary Genomics
• Antibiotic Resistance
• Computational Biology
• +7 more

Dr. Michael Baym is an Associate Professor of Biomedical Informatics at Harvard Medical School with affiliate appointments in Microbiology and the Laboratory of Systems Pharmacology, and as an Associate Member of the Broad Institute. He leads the Baym Lab, which studies microbial evolutionary genomics and antibiotic resistance through a hybrid of experimental, computational, and theoretical approaches. His research focuses on: Antibiotic Resistance Evolution and practical interventions Mobile Genetic Elements (plasmids, phages, transposons) Computational Genomic Algorithms for big data analysis Synthetic Biology tools and technologies Key recent publications explore phage discovery systems , phylogenetic compression of microbial genomes, and RNA-guided gene drives in plasmids. His work is supported by multiple NIH/NIGMS and NSF grants including a MIRA award. Scientific honors include: Packard Fellowship (2018) Pew Biomedical Scholarship (2020) Sloan Research Fellowship (2020) A. Clifford Barger Excellence in Mentoring Award (2021) SSQBio Mentorship Award (2022) The lab actively trains PhD students and postdoctoral fellows with alumni occupying academic and industry positions globally. Current team members include researchers from interdisciplinary backgrounds working at the intersection of experiment, computation, and theory .

Noman MohammedView profile

Associate Professor

• Data Security
• Privacy-Preserving Techniques
• Healthcare Data Privacy
• +7 more

Noman Mohammed is an Associate Professor of Computer Science at the University of Manitoba’s Faculty of Science, leading the Data Security & Privacy (DSP) laboratory. He specializes in privacy-preserving techniques for data sharing, addressing challenges in healthcare, genomic, and financial data. In 2020, he received the Terry G. Falconer Memorial Rh Institute Foundation Emerging Researcher Award for his contributions to bridging privacy and data utility gaps. His research focuses on balancing data accessibility and individual privacy through technical solutions like federated learning, differential privacy, and secure genomic data processing. He emphasizes integrating policy guidelines with advanced technologies to mitigate privacy risks from interconnected data sources. Notable achievements include developing toolkits for data anonymization and federated learning frameworks, as well as advancing methods to secure cloud-based data storage and analysis. His work aligns with societal needs for robust privacy mechanisms in an era of expanding personal data collection. Future objectives involve addressing privacy challenges in emerging technologies, such as heterogeneous data integration and scalable systems for personal data management. Despite his research focus, he notably avoids social media platforms.

Lucas JansonView profile

Associate Professor

• High-Dimensional Inference
• Statistical Machine Learning
• Reinforcement Learning
• +4 more

Lucas Janson is an Associate Professor of Statistics and Affiliate in Computer Science at Harvard University. He leads the Harvard Statistical Consulting Service, supervising PhD students advising hundreds of researchers annually. His research focuses on high-dimensional inference, statistical machine learning, and applications in genetics, political science, and climatology. He teaches courses such as Statistical Inference I, Reinforcement Learning, and Statistical Machine Learning. His work bridges theoretical advancements with practical applications, including contributions to robotics motion planning and microbiome data analysis. Key research areas include variable importance inference, safe reinforcement learning, compositional data analysis, and robust paleoclimate reconstructions. His methodologies are implemented in software packages like Floodgate, EigenPrism, and Fast Marching Tree (FMT*). He advises a dynamic group of PhD students and has mentored alumni now in academia and industry roles. Notable contributions include the development of model-X knockoffs for controlled variable selection, conditional randomization tests, and optimization algorithms for adaptive control systems. His work emphasizes statistical rigor while addressing real-world challenges in healthcare, environmental science, and robotics.

• Infectious Disease Modeling
• Mathematical Epidemiology
• Rotavirus
• +5 more

Virginia Pitzer is a Professor of Epidemiology (Microbial Diseases) at Yale School of Public Health, where she joined as an assistant professor in 2012. She serves as Co-Director of the Public Health Modeling concentration and is an Affiliated Faculty member at the Yale Institute for Global Health. Dr. Pitzer is also a member of the Graduate Studies Executive Committee overseeing the PhD program and currently serves as Co-Editor-in-Chief for PLOS Computational Biology. She has contributed to World Health Organization advisory groups, including the Immunization and Vaccine-related Implementation Research Advisory Committee (WHO IVIR-AC). Dr. Pitzer's research focuses on mathematical and statistical modeling of infectious disease transmission dynamics, with special emphasis on rotavirus, typhoid fever, and Respiratory Syncytial Virus (RSV). Her work examines how interventions such as vaccination, improved treatment of cases, and improvements in sanitation affect disease transmission at the population level. She has published extensively on vaccine effectiveness, transmission patterns across age groups, and the impact of vaccination programs in both high and low-income countries. Her research has significant implications for public health policy and vaccine implementation strategies globally. Dr. Pitzer has received recognition for her scholarly contributions through her editorial role at PLOS Computational Biology and her participation in WHO advisory committees. Her work bridges mathematical modeling with practical public health applications, particularly in global contexts where infectious diseases pose significant challenges. As Co-Director of the Public Health Modeling concentration, Dr. Pitzer plays a key role in training the next generation of researchers in mathematical epidemiology. Her collaborative approach is evident through her numerous co-authored publications with researchers across Yale and international institutions. The Pitzer Lab continues to advance methodologies for modeling infectious disease transmission and evaluating public health interventions.

Adrian LinacreView profile

Professor

• Forensic Science
• Forensic DNA Analysis
• Wildlife Forensic Science
• +12 more

Adrian Linacre is a Professor and Chair in Forensic DNA Technology at Flinders University, within the College of Science and Engineering, Department of Biological Sciences. He is a leading figure in forensic science, with a focus on DNA analysis, wildlife forensics, and crime scene investigation. BSc in Biological Sciences (Hons), University of Edinburgh, 1984 DPhil in Molecular Genetics, University of Sussex, 1988 His research centers on getting more from less at crime scenes , particularly through developing highly sensitive DNA typing methods and studying the transfer and persistence of biological materials. He also pioneers the use of non-human DNA in forensic investigations, notably in wildlife forensic science , aiding in species identification and combating illegal wildlife trade. His recent publications reflect a strong trend in trace DNA analysis , body fluid identification , and DNA transfer dynamics , with applications in drug cases, sexual assault investigations, and environmental DNA degradation. His work increasingly integrates molecular techniques with real-world forensic challenges. Notable scientific awards include: Medal of the Order of Australia (OAM), 2020 Inspirational Scientist of the Year, Royal Society of Edinburgh, 2005 Fellow of the Royal Society for the Encouragement of Arts and Commerce (FRSA) Finalist, South Australian Science Excellence and Innovation Awards (2023, 2024) He has successfully supervised several students, including Piyamas Kanokwongnuwut and Alicia Haines, many of whom have won international recognition. He has secured significant research funding and contributed to national and international forensic policy, including a key review for the UK Home Office on low-template DNA. His professional leadership includes presidencies of the ANZFSS and ISFG, and vice presidency of the IAFS. Linacre is actively involved in editorial roles, serving as Associate Editor for Forensic Science International: Genetics and on the boards of Forensic Science, Medicine and Pathology and the Australian Journal of Forensic Science . He is a sought-after expert witness and media commentator in forensic science.

Steven SicilianoView profile

Professor

• Soil Toxicology
• Environmental Science
• Polar Ecosystems
• +5 more

Steven Siciliano is a Professor and NSERC/FCL Industrial Research Chair in In Situ Remediation and Risk Assessment at the University of Saskatchewan's College of Agriculture and Bioresources. He leads the CREATE Human and Ecological Risk Assessment Program. His expertise spans soil toxicology, greenhouse gas dynamics in polar ecosystems, and nitrogen cycle interactions in contaminated environments. Education: Ph.D. in Toxicology, University of Saskatchewan B.Sc. in Biochemistry, Concordia University Research Interests: His work focuses on human-soil interaction dynamics, including soil pollution impacts on human health (e.g., PAH toxicity via soil ingestion) and ecosystem resilience (e.g., nitrogen cycle disruptions). He investigates Arctic/Antarctic soil microbiology, greenhouse gas production in polar deserts, and the ecological effects of pollutants like mercury and petroleum hydrocarbons. His lab is divided into toxicology (e.g., metal cardiovascular effects, soil ingestion models) and ecology (e.g., sub-zero water effects on gene expression, Arctic nitrogen cycles). Teaching: Teaches courses on environmental fate analysis, contaminated site management, and advanced risk assessment methodologies at both undergraduate and graduate levels. Courses include EVSC 420, TOX 820, and EVSC 821. Grants & Labs: Directs the CREATE Program and leads projects funded by NSERC and industry partnerships. His lab integrates fieldwork, molecular techniques, and modeling to address environmental remediation challenges. Collaborates on projects like cryoturbation-driven carbon dynamics and microbial community analysis in agricultural systems. Labs/Teams: Active in soil science research teams, including Arctic soil microbiology and bioremediation innovation groups. Engages in interdisciplinary collaborations with environmental engineers and ecologists to advance in situ remediation technologies.

Nicole C. RiddleView profile

Professor

• Epigenetics
• Chromatin Structure
• Drosophila melanogaster
• +3 more

Nicole C. Riddle is a Professor and Associate Chair for Research and Facilities in the Department of Biology at the University of Alabama at Birmingham (UAB). She holds a B.S. in Biology from the University of Missouri Columbia and a Ph.D. in Evolutionary and Population Biology from Washington University in St. Louis. Her research focuses on epigenetics and chromatin dynamics, particularly in the context of aging and sex differences using Drosophila melanogaster as a model system. Dr. Riddle's work explores how epigenetic mechanisms influence lifespan, genome stability, and phenotypic variation. She has pioneered the use of Drosophila to study exercise-induced physiological changes and their genetic underpinnings. Her lab investigates the roles of HP1 proteins in transcriptional regulation and chromatin organization, with recent studies emphasizing cross-species comparisons of aging mechanisms. Her research has been supported by grants including the BII: IISAGE project on sex-specific aging mechanisms. Notable contributions include developing novel tools like the Rotating Exercise Quantification System (REQS) to measure Drosophila activity levels. Dr. Riddle actively mentors students and postdoctoral researchers, inviting inquiries via riddlenc@uab.edu to join her lab.

Jianhua XingView profile

Associate Professor

• Biophysics
• Systems Biology
• Cell Biology
• +7 more

Jianhua Xing is an Associate Professor in the Department of Physics & Astronomy at the University of Pittsburgh , affiliated with the Dietrich School of Arts and Sciences . His research focuses on applying physics-based approaches to study biological systems, particularly cell phenotypic transitions (CPTs) and their underlying dynamics. He integrates quantitative single-cell measurements with computational and theoretical analyses to understand how cells transition between stable states. Key research areas include: Nonequilibrium systems and rate theories for biological transitions Single-cell trajectory analysis and live-cell imaging Epithelial-mesenchymal transition (EMT) dynamics Gene regulatory networks and stochastic processes Biological applications of dynamical systems theory Recent work highlights the coupling between EMT and cell cycle arrest, leveraging machine learning frameworks (e.g., LivecellX ) for high-resolution imaging analysis. His lab also explores chromosomal dynamics and mechanotransduction in stem cell aging. Publications emphasize data-driven modeling and theoretical insights, with contributions to frameworks like GraphVelo and Graph-Dynamo for inferring cellular state transitions. Collaborative efforts bridge physics, biology, and computational science to address fundamental biological questions. No awards or grants are explicitly listed in the provided texts. His research group focuses on advancing systems biology through interdisciplinary methods, with a lab dedicated to quantitative analysis of cellular processes.

• Microbiomics
• Genomics
• Complex Diseases
• +4 more

Elin Org is a Professor of Microbiomics at the University of Tartu's Institute of Genomics, where she also serves as Head of the Estonian Genome Centre and Vice Director of the Institute. Her academic career spans over two decades with significant contributions to microbiome and genomic research. Education: PhD in Genetics, University of Tartu (2006) Master's Degree in Molecular Biotechnology and Biomedicine, University of Tartu (2000) Bachelor's Degree, University of Tartu (1997) Classical Singing, Heino Eller Tartu Music School (1996) Professor Org's research primarily focuses on the intricate relationships between host and gut microbiota and their influence on metabolism and common complex diseases. Her work bridges microbiomics, genomics, and complex disease research, with particular emphasis on understanding how gut microbiome composition affects human health. She has pioneered research connecting long-term antibiotic usage with microbiota-dependent effects and has made significant contributions to understanding the role of gut microbiome in conditions such as gestational diabetes, endometriosis, and polycystic ovary syndrome. Her approach integrates advanced computational methods with comprehensive health data to uncover causal relationships in microbiome research. Her recent publications demonstrate a strong trend toward integrating microbiome data with extensive digital health metrics, using machine learning approaches to identify microbial predictors of health outcomes. This work is increasingly focused on translating microbiome research into clinical applications for disease prediction and personalized medicine approaches, particularly in the context of the Estonian Biobank initiative. Major Scientific Recognition: 2025 National Science Award in medical and health sciences 2023 and 2022: Recognized among the world's top 1% most cited researchers by Clarivate Analytics 2020: Member of AcademiaNet, a portal for top female researchers 2017: EMBO Installation grant 2013: Marie Curie International Outgoing Fellowship Professor Org has secured substantial research funding as principal investigator for multiple significant projects, including 'DISCERN - Discovering the causes of three poorly understood cancers in Europe' (€245,466, European Commission) and 'Improving colorectal cancer screening and prediction using microbiome-based biomarkers' (€760,450, Estonian Research Council). She has served as an opponent for numerous PhD theses across European institutions, contributing to the development of emerging researchers in her field. As Head of the Estonian Genome Centre, Professor Org leads a multidisciplinary research team that plays a crucial role in Estonia's transition from biobanking to personalized medicine applications. She is actively involved in international collaborations through COST networks including INFOGUT (focused on in vitro colon models) and ML4Microbiome (statistical and machine learning techniques in human microbiome studies), positioning her at the forefront of global microbiome research initiatives.

Kumar SomyajitView profile

Associate Professor

• DNA Repair Mechanisms
• Genome Stability
• Replication Stress
• +4 more

Kumar Somyajit is Associate Professor at the University of Southern Denmark's Department of Biochemistry and Molecular Biology. He leads research on DNA replication and genome surveillance mechanisms using mammalian cell models. Research focuses on: Metabolic regulation of DNA replication Replisome plasticity under stress Homology-directed repair mechanisms Chromatin dynamics in cancer Recipient of Lundbeck Foundation Fellowship (2021). Current projects investigate metabolic coupling to genome surveillance in cancer and development. Supervises PhD students in DNA repair and replication studies.

Vinayak AgarwalView profile

Assistant Professor

• Natural Products
• Antibiotics
• Biochemistry
• +7 more

Vinayak Agarwal is an Assistant Professor at the Georgia Institute of Technology with joint appointments in the School of Chemistry and Biochemistry and School of Biological Sciences within the College of Sciences. His research investigates natural products—small organic molecules produced by living organisms that form the basis of most clinical antibiotics and drugs, while also addressing environmental toxins and pollutants. Dr. Agarwal's work integrates (meta)genomics, biochemistry, structural and mechanistic enzymology, mass spectrometry, and analytical chemistry to answer fundamental questions about natural product biosynthesis. His lab specializes in marine systems, particularly marine sponges and associated microbiomes, with a focus on enzyme discovery, pathway elucidation, and biosynthetic engineering. Key research themes include halogenation enzymes, polyketide synthases, and peptide natural products, driven by the dual goals of drug discovery and environmental protection. Analysis of recent publications reveals a strong emphasis on marine natural product discovery, enzyme characterization, and biosynthetic pathway engineering. His team frequently combines genomic mining with chemical and biochemical validation, with growing attention to environmental implications of natural product chemistry and applications in antibiotic development. Dr. Agarwal has received significant recognition for his research and teaching: ASP Matt Suffness Young Investigator Award (2024) Camille Dreyfus Teacher Scholar award (2023) NSF CAREER award (2023) Cottrell Scholar Award (2021) Blanchard Assistant Professorship (2020) Harold Nation young faculty award (2019) He has mentored multiple PhD students to completion (Ipsita, Dongqi, Luna) and currently advises Vidya and Grace. His lab secures major funding from the NSF (CAREER), NIH (NIGMS MIRA), and Research Corporation for Science Advancement (Cottrell Scholar), alongside the Camille Dreyfus award and Petit Institute seed grants for collaborative marine research. The Agarwal Lab operates from the Petit Biotechnology Building at Georgia Tech and maintains a dynamic team structure with postdocs (Weimao Zhong, Nirmal Saha), graduate students (Sophia, Vidya, Beeta, Grace), and undergraduates. The lab emphasizes interdisciplinary collaboration, particularly with marine biology groups at Georgia Tech and external institutions for sample collection and structural analysis.

Michael J. ShelleyView profile

Professor

• Applied Mathematics
• Biophysics
• Complex Fluids
• +4 more

Michael J. Shelley is the Lilian and George Lyttle Professor of Applied Mathematics and holds joint appointments in Mathematics, Neural Science, and Mechanical Engineering at New York University's Courant Institute of Mathematical Sciences. He also serves as Co-Director of the Applied Mathematics Laboratory and Director of the Center for Computational Biology at the Flatiron Institute. Education: PhD (Applied Mathematics) from the University of Arizona (1985), MS (Applied Mathematics) from the University of Arizona (1984), BA (Mathematics) from the University of Colorado (1981). Research: Focuses on complex phenomena in active matter, biophysics, and complex fluids. Key areas include fluid-structure interactions (e.g., swimming/flying mechanics), cytoskeletal dynamics, and collective behavior in biological systems. Collaborates closely with experimentalists through the Applied Math Lab and Flatiron Institute. Labs & Affiliations: Co-Director, Applied Mathematics Laboratory; Director, Center for Computational Biology (Simons Foundation); affiliated with NYU’s Courant Institute and Department of Mathematics. Notable Work: Models for microtubule-motor assemblies, active suspensions, and fluid-structure interactions. Pioneered computational frameworks for Stokes suspensions and fiber dynamics in viscous fluids.

Lyle H. UngarView profile

Professor

• Artificial Intelligence
• Machine Learning
• Natural Language Processing
• +7 more

Affiliations & Roles Professor of Computer and Information Science at University of Pennsylvania Faculty in Graduate Groups: Bioengineering (School of Engineering) Genomics & Computational Biology (School of Medicine) Operations, Information & Decisions (Wharton School) Psychology (School of Arts & Sciences) Research Affiliations: Annenberg Public Policy Center (Distinguished Fellow) Center for Cognitive Neuroscience Institute for Translational Medicine Research Interests Focuses on explainable AI, natural language processing (NLP), and machine learning applications in psychology and medicine. Key areas include: Language analysis for well-being and mental health Spectral methods for NLP (e.g., Eigenwords) Forecasting and decision-making models Bioinformatics and genomics Teaching Teaches advanced courses in Machine Learning, Deep Learning, and AI ethics, including: CIS 5200: Machine Learning CIS 5220: Deep Learning CIS 6200: Advanced Topics in Deep Learning Key Collaborations Works with interdisciplinary teams on projects like the Good Judgment Project (forecasting) and WWBP (Well-Being and Language). Collaborators include Martin Seligman (positive psychology), Dean Foster (statistics), and Michael Collins (NLP).