Find Academic Supervisors

Harris H. WangView profile

Associate Professor

• Systems Biology
• Synthetic Biology
• Genome Engineering
• +17 more

Harris H. Wang is an Associate Professor in the Department of Systems Biology and Department of Pathology and Cell Biology at Columbia University's Vagelos College of Physicians and Surgeons, where he also serves as Interim Chair of Systems Biology. He is affiliated with the Center for Computational Biology and Bioinformatics (C2B2) and the Integrated Program in Cellular, Molecular and Biomedical Studies (CMBS). B.S., Physics and Mathematics, MIT Ph.D., Biophysics, Harvard University Dr. Wang's research lies at the intersection of systems and synthetic biology, focusing on developing foundational technologies for genome engineering, microbiome manipulation, and synthetic genomics. His lab pioneers methods such as MAGE, MAGIC, CAST, and CAMII to enable high-throughput genetic manipulation, in situ microbiome engineering, and AI-driven microbial culturomics. Key research themes include understanding microbial community dynamics, engineering cellular memory systems, designing biocontained genetic circuits, and applying synthetic biology to human health challenges in personalized medicine and infectious disease. His recent publications reveal a strong trend in spatial and functional metagenomics, CRISPR-based microbiome editing, and synthetic biology tools for data storage and genetic stability. The articles span high-impact journals like Nature , Science , and Nature Biotechnology , reflecting his leadership in developing scalable, programmable biological systems. Scientific Awards: NIH Director’s Early Independence Award Forbes 30 Under 30 in Science Sloan Research Fellowship NSF CAREER Award ONR Young Investigator Award Burroughs Wellcome Fund PATH Award Schaefer Scholar Blavatnik National Award Vilcek Prize PECASE Dr. Wang has advised numerous PhD and postdoctoral researchers, many of whom have gone on to independent scientific careers. His lab is supported by major grants from NIH, NSF, DARPA, DOE, and foundations including the Bill & Melinda Gates Foundation and CZ Biohub NY. He is actively involved in educational initiatives, including organizing Columbia’s iGEM team and the Cold Spring Harbor Laboratory Synthetic Biology course. The Wang Lab is based at the Columbia University Irving Medical Center and is part of national consortia such as the Engineering Biology Research Consortium (EBRC) and the Genome Project-Write (GP-Write) initiative. The lab develops and applies cutting-edge technologies in automation, machine learning, and synthetic biology to engineer microbiomes for applications in medicine, global health, and climate change.

Romain LopezView profile

Assistant Professor

• Single-cell omics
• Spatial transcriptomics
• Deep generative models
• +5 more

Romain Lopez is an Assistant Professor of Computer Science and Biology at New York University, with a joint appointment in the Courant Institute of Mathematical Sciences and the Department of Biology. He will be joining NYU in September 2025, bringing expertise at the intersection of machine learning and computational biology. Prior to joining NYU, he was a Postdoctoral Fellow at Genentech and Stanford Medicine from 2021 to 2025, working with Jonathan Pritchard and Aviv Regev. Dr. Lopez received his educational training at prestigious institutions: PhD in Computer Science (2021) from the University of California, Berkeley, advised by Mike Jordan and Nir Yosef M.S. in Applied Mathematics (2016) from École polytechnique, Palaiseau, France Dr. Lopez's research focuses on developing machine learning methods to understand biological systems at the cellular level. His work bridges computational techniques with biological applications, particularly in single-cell and spatial omics analysis. He pioneered probabilistic approaches for single-cell analysis with scVI and co-developed scvi-tools, now widely adopted tools in the field. His research spans deep generative models, causal inference, perturbation modeling, and representation learning for biological data. His publication record demonstrates a consistent trajectory of innovation in computational biology, with recent work focusing on spatial biology, disentangled representations of cellular perturbations, and causal modeling of cellular responses. He has made significant contributions to the field of single-cell analysis, developing methods that help scientists interpret complex cellular data and predict how cells respond to various perturbations. Dr. Lopez has received numerous honors and awards for his research: Best Paper Award from the ICML Workshop on AI for Science (2024) Best Paper Award Honorable Mention from the AAAI Conference on Artificial Intelligence (2021) Best Student Poster Award from the ICML Workshop on Computational Biology (2019) UC Berkeley EECS Departmental Graduate Fellowship (2016) Carnot Foundation Fellowship (2016) Monahan Foundation Fellowship (2016) French National Defence Medal, Bronze Echelon (2014) At NYU, Dr. Lopez will lead the Biological Machine Learning group, which develops probabilistic machine learning methods to uncover biological mechanisms governing cellular behavior and disease. His lab focuses on creating tools that transform complex cellular data into biological insights, with applications in understanding cancer, immune responses, and fundamental cellular processes. His work has significant implications for precision medicine and drug discovery.

Sriram SubramaniamView profile

Professor

• cryo-electron microscopy
• structural biology
• drug-design
• +4 more

Sriram Subramaniam is a Professor in the Department of Biochemistry and Molecular Biology at the University of British Columbia (UBC) and holds the Gobind Khorana Canada Excellence Research Chair in Precision Cancer Drug Design. His research leverages cryo-electron microscopy (cryo-EM) to advance structural biology and drug design, focusing on protein dynamics and therapeutic target identification. Education: PhD in Physical Chemistry (1987) from Stanford University; MSc in Chemistry (1981) from Indian Institute of Technology, Kanpur. Subramaniam's interdisciplinary work combines cryo-EM with computational tools and molecular biology to study protein structures at atomic resolution. His lab has pioneered cryo-EM applications in precision medicine, including mapping small molecule drugs on patient-specific cancer mutants. Recent publications (2024-2022) highlight his contributions to understanding SARS-CoV-2 immune evasion, structural mechanisms of ATPases, and AI integration in structural biology. His research spans viral entry mechanisms, CRISPR systems, and neurodegenerative disease pathways. Scientific Awards: Gobind Khorana Canada Excellence Research Chair NIH Director’s Award for Scientific Excellence Fellow of the Biophysical Society Breakthrough Prize nomination Based at the Djavad Mowafaghian Center for Brain Health, Subramaniam leads the Program in Cryo-EM Guided Drug Design, contributing to over 177 peer-reviewed publications with a career h-index of 58 and citations exceeding 12,340.

Alexis BattleView profile

Associate Professor

• Genomics
• Machine Learning
• Computational Biology
• +3 more

Alexis Battle is an Associate Professor at Johns Hopkins University with appointments in Biomedical Engineering , Computer Science , and Genetic Medicine (secondary). She directs the Malone Center for Engineering in Healthcare and serves as Deputy Director of the Data Science and AI Institute . Educated at Stanford University (PhD in Computer Science, 2013), Battle transitioned to academia after leadership roles at Google. Research Focus: Battle’s work bridges genomics and machine learning , emphasizing the impact of genetic variation on human health. Her lab develops tools like Watershed to predict functional effects of rare variants, aiming to enhance rare disease diagnosis. Key themes include non-coding DNA analysis , personalized genomics , and systems biology , with applications in cardiovascular disease and neurodegenerative disorders . Publications & Awards: Over 60 peer-reviewed articles in journals like Nature , Science , and Genome Biology , with recent emphasis on single-cell transcriptomics , multiomics integration , and telomere biology . Recipient of the President’s Frontier Award (2022), Microsoft Investigator Fellowship (2019), and Searle Scholar (2016). Scientific Awards: 2022 President’s Frontier Award 2019 Microsoft Investigator Fellowship 2019 Johns Hopkins Discovery Award 2017 Johns Hopkins Catalyst Award 2016 Searle Scholar Advising & Funding: Mentors 11 PhD students, 3 undergraduates, and postdoctoral fellows. Her research is funded by NIH, Searle Scholars, and institutional grants. The Battle Lab collaborates on projects like the GTEx Consortium , focusing on gene regulation and clinical genomics .

Gail E. KaiserView profile

Professor

• Software Engineering
• Static and Dynamic Program Analysis
• Software Testing
• +7 more

Gail E. Kaiser is a Professor of Computer Science and the Director of the Programming Systems Laboratory (PSL) in the Computer Science Department at Columbia University. She has been with Columbia University since 1985, becoming a full Professor in 1998. Prof. Kaiser's research spans software engineering, program analysis, software testing, and software security, with recent focus on addressing challenges in AI/ML systems testing and security. Prof. Kaiser received her PhD in Computer Science from Carnegie Mellon University in 1985 and her ScB in Computer Science and Engineering from MIT in 1979. Her dissertation at CMU was titled "Semantics for Structure Editing Environments" under advisor Nico Habermann, and at MIT she completed "Automatic Extension of an Augmented Transition Network Grammar for Morse Code Conversations" under advisor Al Vezza. Prof. Kaiser's research interests primarily focus on software engineering following a systems building approach, with recent emphasis on static and dynamic program analysis techniques to improve software reliability and security. Since 2005, she has investigated testing "non-testable" programs, particularly in machine learning, data mining, and scientific computing applications where traditional testing oracles are insufficient. She has developed novel techniques and tools for detecting bugs and verifying repairs in complex systems. Concurrently, she has worked on collaboration environments for computational scientists, creating knowledge sharing and domain-aware environments to support scientific workflows. Prof. Kaiser's recent publications demonstrate a strong focus on the intersection of software engineering and artificial intelligence. Her work addresses critical challenges in testing AI systems, code understanding through deep learning, vulnerability detection, and educational tools for computational thinking. There's a clear evolution from traditional software engineering topics toward AI/ML applications, with particular emphasis on metamorphic testing for non-testable systems, code similarity analysis, and educational applications. Prof. Kaiser has received numerous prestigious awards throughout her career: Distinguished Journal Award (10 Years) from 18th IEEE International Conference on Software Testing, Verification and Validation (ICST), April 2025 Best Research Paper Award at 24th IEEE International Conference on Source Code Analysis & Manipulation (SCAM), October 2024 Distinguished Reviewer Awards for ASE 2024 and FSE 2024 ACM SIGSOFT Distinguished Paper Award for "CONCORD: Clone-aware Contrastive Learning for Source Code", July 2023 Best Student Paper Award at ICCE 2021 Multiple ACM SIGSOFT Distinguished Paper Awards dating back to 2014 Presidential Young Investigator in Software Engineering and Software Systems from NSF (1988-1993) Prof. Kaiser has chaired Columbia's doctoral program since 1997 and served on editorial boards including IEEE Internet Computing and as a founding associate editor of ACM Transactions on Software Engineering and Methodology. Her lab has been continuously funded by major agencies including NSF, NIH, DARPA, ONR, NASA, and numerous companies. Current grants include significant NSF funding for secure containers architecture, learning semantics of code for software assurance, and finding semantic security bugs. As Director of the Programming Systems Laboratory (PSL), Prof. Kaiser leads research in software systems, program analysis, and software testing. The lab has developed numerous tools and techniques for software reliability and security, with recent focus on challenges in AI/ML systems. Her work bridges theoretical foundations with practical applications, often resulting in deployable tools that address real-world software engineering challenges.

Britt AdamsonView profile

Associate Professor

• Stress Response Networks
• DNA Damage Response
• Genome Editing
• +3 more

Britt Adamson is an Associate Professor in the Department of Molecular Biology and the Lewis-Sigler Institute for Integrative Genomics at Princeton University, where she serves as Director of the Undergraduate Program in Quantitative and Computational Biology. Her lab investigates molecular networks in human cells with focus on stress response mechanisms and genome editing technologies. She received her B.S. in Biology from the Massachusetts Institute of Technology (2005) and Ph.D. in Genetics and Genomics from Harvard University (2012), followed by postdoctoral training at UCSF under Jonathan Weissman supported by a Damon Runyon Cancer Research Foundation Fellowship. Adamson's research centers on how cells organize stress response networks during DNA damage and endoplasmic reticulum stress, developing CRISPR-based functional genomics and single-cell sequencing tools to map molecular behaviors. Her work bridges fundamental cell biology with therapeutic applications in genome editing. Analysis of her 15 most recent publications reveals dominant themes in precision genome editing (prime/base editing optimization) and systematic dissection of DNA repair pathways through combinatorial CRISPR screening. Her lab consistently integrates computational approaches with high-resolution experimental techniques to uncover context-dependent cellular behaviors. Her scientific recognitions include: Damon Runyon Cancer Research Foundation Postdoctoral Fellowship Princeton IP Accelerator Award (2025) STAT Who to Know: 10 Scientists leading a new generation of gene editors (2024) Adamson actively mentors eight graduate students (including alumni Ann Cirincione and Jun Hussmann) and two postdocs, with research funded through institutional awards and collaborative grants. Her lab's technological developments have enabled projects spanning virology, immunology, and developmental biology. The Adamson Lab operates within Princeton's Lewis-Sigler Institute for Integrative Genomics, fostering an interdisciplinary environment that merges cell biology, genomics, and computational science. Current projects focus on improving prime editing efficiency and understanding stress response adaptation in disease contexts.

Helmuth GehartView profile

Professor

• Stem Cell Biology
• Cancer Biology
• Regenerative Medicine
• +2 more

Prof. Dr. Helmuth Gehart is a faculty member at the Institute of Molecular Health Sciences , ETH Zurich . He leads the Tumor and Stem Cell Dynamics research group, focusing on dynamic cell identity in regeneration and cancer. Research Interests : Stem cell-environment interactions, organoid technology, single-cell sequencing, and mechanisms of tissue repair/tumorigenesis. Publications : 10+ articles (2015-2024) on organoid models, stem cell dynamics, and cancer biology.

Waldemar KolanusView profile

Professor

• Molecular Immunology
• Cell Signaling
• Signal Transduction Pathways
• +4 more

Prof. Waldemar Kolanus leads the Molecular Immunology and Cell Biology department at the University of Bonn's Life & Medical Sciences Institute (LIMES) . His research bridges immunoregulation , stem cell dynamics , and metabolic stress responses in immune cells. Unit 2 member at LIMES Principal investigator in SFB 704 and ImmunoSensation Cluster Leads a multidisciplinary lab with postdocs, PhD students, and technical staff His work focuses on intracellular signaling pathways connecting immune activation to tissue homeostasis, particularly through: Cytohesin proteins in integrin-mediated adhesion and migration TRIM71 in stem cell regulation and congenital hydrocephalus High-salt environments affecting macrophage function Publication trends show expertise in immune cell migration , genetic models , and chemical inhibition , with frequent use of mice and zebrafish for in vivo studies. Key articles explore: TRIM71's dual role in auditory development and germ cell maintenance Cytohesin family's Golgi regulation and insulin signaling Ruxolitinib's off-target migration inhibition of dendritic cells Contact details: Address: LIMES Institute, Carl-Troll-Straße 31, Bonn Email: kolanus.sekretariat@uni-bonn.de Phone: +49 228 73-62788

Lauren AndrewsView profile

Associate Professor

• Synthetic Biology
• Genome Engineering
• Metabolic Engineering
• +5 more

Lauren Andrews serves as Associate Professor and Marvin and Eva Schlanger Faculty Fellow in the Department of Chemical Engineering at the University of Massachusetts Amherst. Her research integrates synthetic biology and genetic engineering to develop programmable cellular systems for biotechnological applications. Education: Postdoctoral Training: Massachusetts Institute of Technology (Biological Engineering and Broad Institute of MIT and Harvard) PhD: University of Colorado Boulder, Chemical Engineering (2012) MS: University of Colorado Boulder, Chemical Engineering (2009) BS: Cornell University, Chemical Engineering (2006) Dr. Andrews' research focuses on establishing genetic design rules for reprogramming cellular regulation and metabolism. Her lab pioneers synthetic gene networks, genetically-encoded biosensors, and high-throughput methodologies for optimizing genetic designs in both model and non-model bacteria. This work enables precise control of cellular sensing, memory, and environmental responses through multiplexed DNA assembly and next-generation sequencing. Analysis of her 15 most recent publications reveals dominant themes in bacterial biosensor development (particularly for bioremediation), quorum sensing engineering, and programmable genetic circuits for probiotic applications. Her research consistently bridges fundamental genetic circuit design with practical implementations in bacterial consortia and non-model organisms. Scientific Awards: Marvin and Eva Schlanger Faculty Fellowship NSF CAREER Award (2020) for "Programmable synthetic microbial consortia for complex multicellular functions" Her grant portfolio demonstrates significant funding for collaborative research in bacterial communication systems and model-guided design of synthetic ecosystems. The Andrews Lab maintains active partnerships with the MIT-Broad Foundry and Cold Spring Harbor Laboratory, where she co-founded the Synthetic Biology Summer Course. Current projects focus on CRISPR-based regulation in non-model bacteria and algorithmic programming of sequential logic in probiotic strains. The Andrews Lab operates within the Life Science Laboratories at UMass Amherst, utilizing advanced facilities for genetic prototyping and high-throughput screening. Her team develops multiplexed tools for exploring genetic design spaces, with particular emphasis on soil bacteria and Gram-positive pathogens for environmental and therapeutic applications.

Jennifer L ClarkeView profile

Professor

• Statistical Methodology
• Bioinformatics/Computational Biology
• Data Mining/Machine Learning
• +3 more

Jennifer L. Clarke is a Professor in the Department of Statistics at the University of Nebraska–Lincoln and Director of the Quantitative Life Science Initiative. She holds leadership roles in enabling big data integration across the University of Nebraska system through collaborative research programs. Her affiliations include the Institute of Agriculture and Natural Resources (IANR) and the College of Agriculture and Natural Resources. Dr. Clarke's research focuses on statistical methodology for high-dimensional data, computational biology, bioinformatics, and bacterial genomics. Her work bridges statistical innovation with applications in oncology, microbiome analysis, and agricultural phenomics. Key areas include predictive modeling, machine learning, and genomic/metagenomic data integration. Her recent publications span cancer biomarker discovery, plant phenotyping methodologies, and microbial community analysis, reflecting her interdisciplinary approach. Articles emphasize translational applications like therapeutic target identification and precision agriculture. Dr. Clarke leads initiatives fostering collaboration between statisticians and domain scientists, including the Quantitative Life Science Initiative and contributions to the Agricultural Genome-to-Phenome Initiative (AG2PI). Her work advances data-driven solutions for healthcare and food security challenges. Notable projects include developing statistical tools for microbiome studies, analyzing root architecture via 3D imaging, and investigating cranberry-derived compounds' cancer-inhibitory mechanisms. Her methodological contributions include hybrid clustering techniques and predictive model validation frameworks.

• Stem Cell Biology
• Genetic Engineering
• Epigenetics
• +5 more

Konstantinos Anastassiadis is a Professor at the Center for Molecular and Cellular Bioengineering (CMCB) of Dresden University of Technology , leading the Stem Cell Engineering group at the Biotechnology Center (BIOTEC) . His research focuses on unraveling molecular pathways regulating stem cell self-renewal and lineage commitment, with a strong emphasis on genetic engineering tool development and epigenetic mechanisms during cellular reprogramming. The lab utilizes mouse and human embryonic stem cells, neural stem cells, mesenchymal stromal cells, and induced pluripotent stem cells (iPSCs) in their investigations. Core Research Areas: Molecular regulation of stem cell fate Epigenetic mechanisms (e.g., UTX/UTY histone demethylases) Genetic engineering tool development (Flp, Dre, Vika recombinases, CRISPR protocols) Conditional immortalization systems for rare cell expansion Publications highlight his contributions to understanding: Role of histone methyltransferases (MLL1, MLL2, Setd1b) in hematopoiesis and cancer Epigenetic regulation during mouse development and spermatogenesis Genetic tools for protein tagging, transposon-mediated BAC transgenesis Interactions between stem cells and niche microenvironments Transcriptional and mechanical markers during reprogramming Collaborations span immunology , developmental biology , and bioinformatics . The lab actively participates in teaching activities at CMCB and maintains a focus on translational applications of stem cell research.

Mona SinghView profile

Professor

• Computational Biology
• Machine Learning
• Algorithms
• +3 more

Mona Singh is a Professor of Computer Science at Princeton University, with affiliations to the Lewis-Sigler Institute for Integrative Genomics and the Department of Molecular Biology. She has been a faculty member since 1999. Ph.D., Massachusetts Institute of Technology, 1995 A.B. and S.M. degrees in Computer Science from Harvard University Her research focuses on computational molecular biology, integrating machine learning and algorithms to analyze biological networks, protein interactions, and mutational impacts. Key areas include DNA/RNA binding prediction, protein structure analysis, and network-based disease gene discovery. Her recent work highlights trends in protein language models, kinase-substrate prediction, and equitable MHC binding algorithms. These span sub-fields like structural bioinformatics, network biology, and functional genomics. Scientific Awards: Presidential Early Career Award for Scientists and Engineers (PECASE) Rheinstein Junior Faculty Award ACM Fellow (2019) ISCB Fellow (2018) She has taught an introductory computational biology course with Professor Coleen Murphy, covering sequence analysis, phylogenetics, and network reconstruction. Her group has developed tools like dPUC , nCOP , and DiffMut . Her lab collaborates with institutions including Carnegie Mellon, Duke University, and the Broad Institute, advancing applications in cancer genomics, metabolic disease, and precision medicine.

John A. Copland, IIIView profile

Professor

• Cancer Biology
• Molecular Carcinogenesis
• Translational Research
• +3 more

Dr. John A. Copland III is a Professor of Cancer Biology and Biochemistry & Molecular Biology at Mayo Clinic in Jacksonville, Florida. He leads the Cancer Biology and Translational Research Laboratory, focusing on molecular mechanisms of carcinogenesis, tumor progression, and development of targeted cancer therapies. Education: PhD in Physiology & Endocrinology (Medical College of Georgia), MS in Endocrinology (Medical College of Georgia), BS in Chemistry (Columbus College), with postdoctoral training at University of Texas Medical Branch. Research interests center on: Identifying tumor suppressor genes (e.g., RhoB, TBR3, GATA3) and oncogenes (e.g., FOXO3a, SCD1, NPTX2). Developing patient-derived xenografts and live cell models for personalized medicine. Designing SCD1 inhibitors via in silico modeling for clinical trials. Recent publications highlight his work on SCD1 inhibition in leukemia and thyroid cancer ImmunoPET imaging of thyroid tumors CRISPR-identified drug synergies in cholangiocarcinoma Patient-specific combination therapies using xenograft models

John K VanDykView profile

Adjunct Assistant Professor

• Information Technology
• Entomology
• Web Development
• +2 more

Dr. John K VanDyk is an Adjunct Assistant Professor at Iowa State University, affiliated with the College of Agriculture and Life Sciences and Department of Entomology. He manages the CALS/LAS Web Team and maintains BugGuide.net, a major online arthropod resource. His research bridges information technology and entomology, focusing on biodiversity databases, web development, and citizen science platforms. Educational background includes a PhD and MS from Iowa State University and BS from Dordt University. Digital Projects: BugGuide.net, ISU Sites service Technical Expertise: Drupal development, data systems architecture

• Cancer Biology
• Mathematical and Computational Modeling
• Bioinformatics
• +7 more

Dana Pe'er is a Professor and Chair of the Computational and Systems Biology Program at the Sloan Kettering Institute (SKI) of Memorial Sloan Kettering Cancer Center. She is also an Investigator of the Howard Hughes Medical Institute and holds the Alan and Sandra Gerry Endowed Chair. Dr. Pe'er leads an interdisciplinary research group that combines advanced genomics approaches with machine learning to address fundamental questions in biomedical science, with particular focus on cancer biology, developmental biology, and immunology. Dr. Pe'er earned her PhD from Hebrew University in Jerusalem, Israel. Her academic journey includes a postdoctoral fellowship with George Church at Harvard Medical School. Before joining Memorial Sloan Kettering Cancer Center in 2016, she held faculty positions at Columbia University. Dr. Pe'er's research focuses on understanding cellular plasticity, the consequences of intra-tumor heterogeneity, cancer evolution and metastasis, and the mechanisms by which regulatory circuits go awry in disease. Her lab combines single-cell and spatial profiling technologies with machine learning approaches to investigate gene regulation, cellular plasticity, and cell-cell communication in the contexts of cancer, immunity, and development. They are particularly interested in how organisms develop from a single cell to generate diverse cell types, how epigenetic control rewires during development, and how cells communicate to execute multicellular responses. Analysis of Dr. Pe'er's recent publications reveals a strong focus on developing computational methods for single-cell and spatial genomics data analysis. Her work spans cancer types including pancreatic, prostate, colorectal, and breast cancer, with emphasis on tumor heterogeneity, metastasis mechanisms, and cellular plasticity. A significant portion of her research involves creating novel algorithms and tools like CellRank, REUNION, and SEACells that enable researchers to extract meaningful biological insights from complex genomic datasets. 2023 Class of 2023 Inductee - American Academy of Cancer Research (AACR) Academy 2023 Innovator Award - International Society for Computational Biology (ISCB) 2021 Fellow - International Society for Computational Biology (ISCB) Howard Hughes Medical Institute Investigator (2021) 2019 Ernst W. Bertner Memorial Award - University of Texas MD Anderson Cancer Center 2016 Lenfest Distinguished Faculty Award - Columbia University 2014 Director's Pioneer Award - National Institutes of Health 2014 Overton Prize - International Society for Computational Biology (ISCB) Dr. Pe'er is known for her dedicated mentorship approach, describing herself as "a mama bear" who cares deeply about her trainees while expecting independence, innovation, and hard work. She mentors numerous PhD students and postdocs in her lab. Her HHMI Investigator award provides approximately $9 million over seven years, enabling ambitious research directions. She also collaborates extensively with the Single-cell Analytics and Innovation Lab (SAIL) at MSK to generate new data from emerging technologies, working closely with wet-lab collaborators at MSK and beyond to apply computational methods to cutting-edge datasets across multiple disease areas. The Pe'er Lab is an interdisciplinary group of computational biologists with diverse backgrounds ranging from pure mathematics to clinical medicine. They work closely with wet-lab collaborators to apply their computational methods to cutting-edge datasets across cancer, immunology, and developmental biology. The lab is described as open, supportive, collaborative, and fun, with access to world-class facilities at the Sloan Kettering Institute. Dr. Pe'er's work continues to push the boundaries of computational biology and cancer research, with the ultimate goal of developing more effective, personalized therapies for cancer patients.