Meet
Our Alumni
We have a great network of people who have worked at the Rabadan Lab. Like all of our current people, our alumni are a creative, collaborative, interdisciplinary group – interested in developing mathematical and computational tools to extract useful biological information from large data sets. Our alumni help to make the Rabadan Lab greater than the sum of its parts.
Alumni of The Rabadan Lab
Luis Arnes
Luis Arnes
Luis Arnes is an associate professor at the The Novo Nordisk Foundation Center for Stem Cell Biology (DanStem) at the University of Copenhagen. He received his PhD from the Department of Genetics and Cell Biology at the school of Biological Science at the Autonomous University in Spain in 2009. After graduation, he joined the laboratory of Dr. Lori Sussel in the Department of Genetics and Development at Columbia University to study the gene regulatory network that regulates pancreas development and maintenance of terminally differentiated endocrine lineages. He received extensive training in molecular biology and mouse genetics. In 2016, he joined the Rabadan laboratory and worked on integrating genome wide data and experimental validation to identify novel regulators of tumor progression with emphasis in signaling pathways required in development and aberrantly reactivated in tumorigenesis.
luis.arnes[at]bric.ku.dk · homepage
Pablo G. Camara
Pablo G. Camara is an Assistant Professor at the University of Pennsylvania. He is currently interested in the application of topological techniques to the study of recombination in organisms, with particular emphasis on human genetics. He received his Ph.D. in Theoretical Physics in 2006 and performed research in High Energy Physics between 2006 and 2014, with postdoctoral appointments at Ecole Polytechnique, the European Organization for Nuclear Research (CERN), and University of Barcelona.
pcamara[at]upenn.edu · homepage
Mathieu Carriere
Mathieu Carrière is a Research Scientist in Nice, France. Previously, he was postdoctoral research scientist in the Department of Systems Biology. He received his PhD in Informatics from Inria and Université Paris Saclay in 2017. He is interested in the application of Topological Data Analysis in Machine Learning frameworks, with an emphasis on biological data. He is currently working on bootstrap methods for Mapper complexes computed on gene expression data, as well as predictive analysis of single cell Hi-C contact maps through persistence diagrams.
mc4660[at]cumc.columbia.edu
Robyn Gartrell
Robyn Gartrell, MD, MS is a physician scientist and pediatric oncologist at Johns Hopkins University School of Medicine. Dr Gartrell completed her clinical fellowship in Pediatric Hematology/Oncology, postdoctoral training in Immunotherapy and Precision Medicine, a Master of Science in Patient Oriented Research as well as her first 5 years as faculty at New York Presbyterian/Columbia University Irving Medical Center (CUIMC). Dr Gartrell’s primary research focuses on combination approaches with immunotherapy including radiation, chemotherapy and other targeted agents to improve response, increase survival and decrease toxicity for children, adolescents and young adults with cancer. Her laboratory uses advances in tumor immunology to develop more effective and more personalized therapies using multiplex platforms and immunogenomics to evaluate the tumor microenvironment and determine which pediatric tumor types, and which patients, will respond to immunotherapy.
rgartre1[at]jh.edu
Benjamin Greenbaum
Benjamin Greenbaum is an assistant professor in the department of Medicine, Hematology and Medical Oncology at Mount Sinai. Previously , he was the Eric and Wendy Schmidt Member of the Simons Center for Systems Biology at the Institute for Advanced Study in Princeton. Prior to this, he spent a year as a postdoctoral fellow in the BioMaPS Institute for Quantitative Biology at Rutgers University. He received his Ph.D. in Physics from Columbia University in 2006.
benjamin.greenbaum[at]mssm.edu
Hossein Khiabanian
Hossein Khiabanian is an assistant professor at Rutgers University. In the Rabadan lab, Hossein's research was in quantitative biology—specifically, developing statistical methods to analyze genomic data, from the study of the molecular epidemiology of disease-causing organisms to investigating the genetics underlying human diseases. He also worked on methods for the early detection of outbreaks, real-time disease surveillance, and analyzing electronic health records. Prior to joining Dr. Rabadan’s group, he was a member of the Observational Cosmology group at Brown University, where he received his Ph.D. in Physics.
h.khiabanian[at]rutgers.edu · homepage
Michael Lesnick
Michael Lesnick is an Assistant Professor in the Department of Mathematics at SUNY Albany. He visited the Rabadan Lab in 2015. In 2012, he received his Ph.D. from Stanford University in computational mathematics. In 2012-2013, he was a Member of The School of Mathematics at the Institute for Advanced Study, and since then has been at the IMA. Michael's research focuses on topological data analysis; he is interested in theoretical foundations, development of new tools for exploratory data analysis, and applications to biology.
mlesnick[at]ima.umn.edu · homepage
Zhaoqi Liu
Zhaoqi Liu is a Professor and Principle Investigator in CAS Key Laboratory of Genomic and Precision Medicine in the Beijing Institue of Genomics. In the Rabadan Lab, he was an associate research scientist, studying cancer genomics in the Department of Biomedical Informatics at Columbia University. He received his Ph.D. in Applied Mathematics from the Academy of Mathematics and Systems Science, where he won the President's Scholarship prize. Zhaoqi joined Dr. Rabadan’s group in September 2015. His current work focuses on developing computational methods to analyze biological problems in cancer genomics.
zl2495[at]cumc.columbia.edu · homepage
Rachel Melamed
Rachel Melamed is currently an Assistant Professor in the biology department at UMass Lowell. She was a postdoctoral researcher in the Rzhetsky Lab at The University of Chicago. She received her Ph.D. from the Department of Biomedical Informatics at Columbia in 2015. Her undergraduate concentration was in computer science at Brown University. After a stint in software engineering, Rachel worked as a research assistant at the Benoist-Mathis Lab at Harvard Medical School, where she analyzed microarray data to understand mechanisms of T-cell activation as well as to compare mouse models of autoimmune disease. She has also worked on understanding cell signaling in immune cell types, and in immune-derived cancer cells, using many-dimensional single cell cytometric measurements.
Anthea Monod
Anthea Monod is a lecturer in the Imperial College of London. She is a mathematical statistician whose primary research interests are theoretical topological data analysis and applications to computational biology. She is the PI on a 2016 Pilot Award from the Center for Topology of Cancer Evolution and Heterogeneity for research on radiogenomics and collaborates with the Samsung Medical Center on applications to glioblastoma multiforme. Prior to visiting the Rabadan Lab, she was faculty at Duke University from 2014-2016, and a postdoctoral scientist at the Technion–Israel Institute of Technology from 2012-2014. She received her PhD in Mathematics from the Swiss Federal Institute of Technology in Lausanne (EPFL).
Wesley Tansey
Wesley Tansey is a Principal Investigator in the Department of Epidemiology and Biostatistics at Memorial Sloan Kettering Cancer Center. His work focuses on machine learning and statistical modeling with applications to biological and medical questions in cancer. From 2017-2020, Wesley was a post-doctoral researcher in the Rabadan lab, where his work revolved around dose-response prediction and biomarker discovery in cancer drug studies. He received his Ph.D. in Computer Science from the University of Texas at Austin in 2017 with a focus on machine learning and computational statistics.
tanseyw[at]mskcc.org · homepage
Jiguang Wang
Jiguang Wang is a professor at The Hong Kong University of Science and Technology. In the Rabadan lab, he worked on cancer evolution and developed computational methods to reveal the evolutionary landscape of tumors under treatment. Jiguang received his Ph.D. in Applied Mathematics from the Academy of Mathematics and Systems Science, where he won the Special Prize of President Scholarship and Excellent PhD thesis Award in the Chinese Academy of Sciences. Prior to working in Dr. Rabadan’s group, he was an assistant research professor at the Beijing Institute of Genomics.
jgwang[at]ust.hk · homepage
Pingzhang Wang
Pingzhang Wang is faculty in the Department of Immunology, School of Basic Medical Sciences and NHC Key Laboratory of Medical Immunology, Peking University. Previously, he was a visiting associate research scientist in the Rabadan Lab. In 2011, he received his Ph.D. in Immunology from the Department of Immunology, Peking Univerity Health Science Center. He is also an associate professor of the department. His research interest focuses on omic big data-driven knowledge discovery (BD2K) in immunology and cancer fields. In Jan. 2017, Pingzhang joined Dr. Rabadan's group. Currently, he works on multiple omic data mining to address gene regulatory mechanisms in immune cells, and also in cancers.
Zikai Wu
Zikai Wu is faculty in the University of Shanghai for Science and Technology and Shanghai Key Laboratory of Intelligent Information Processing, Fudan University. Previously, he was a visiting associate research scientist, studying precision medicine in the Department of Biomedical Informatics at Columbia University. He received his Ph.D. in Operations Research and Cybernetics from Dalian University of Technology, China. He is an associate professor of University of Shanghai for Science and Technology, China. His current work is focusing on developing computational methods to study gene-drug interaction. Zikai joined Dr. Rabadan's group in September 2016.
Francesco Abate
Francesco Abate currently works at McKinsey & Company. He received his bachelor's and master's degrees at the Polytechnic University of Turin in Italy in 2004 and in 2007, respectively. In 2011 he received his Ph.D. in systems and computer engineering from the Department of Control and Computer Engineering (DAUIN). In 2008 he worked with the CAD Group at the university in the field of fault tolerance and embedded systems and was a visiting student at the Federal University of Rio Grande do Sul (UFRGS) in Porto Alegre, Brazil. In 2009 he joined the Polytechnic University of Turin's Electronic Design Automation Group. In the Rabadan Lab, he worked on the design of data mining tools applied to bioinformatics, the development of next generation sequencing analysis pipelines, and computational biology problems in cancer.
Tamar Sery Amster
Tamar Sery Amster is a software engineer at Bloomberg. She received her B.Sc. in Chemistry and Computer Science from Hebrew University in Jerusalem. She worked as a programmer in the Roichman lab at Tel Aviv University, applying image-processing techniques to study the process of wetting of surfaces. Later she worked in the Yitzchaik lab (Hebrew University), applying experimental polymerization and hydrosilylation techniques, as part of a team trying to develop better solar cells. In the Rabadan Lab, Tamar worked on a machine-learning project trying to predict drug sensitivity based on genomic and pharmaceutical data.
Jacqueline Aw
Jacqueline is undertaking a summer observership at the Rabadan Lab. She is a third year undergraduate majoring in Biochemistry and Cell Biology, at the Hong Kong University of Science and Technology. She is interested in elucidating lncRNA shuttling mechanisms based on sequence homology.
jtmaw[at]connect.ust.hk
Ohad Balaga
Ohad Balaga received his bachelor's degree in Computer Science and Computational Biology from The Hebrew University of Jerusalem. His research at HUJI revolved around combinatorial gene regulation by microRNA and the inference of such regulation from gene expression and network data. In the Rabadan Lab, Ohad's research focused on influenza mutations, evolution and quasispecies. He worked jointly with Dr. Sagi Shapira.
Kyle Bolo
Kyle graduated from Williams College in 2013 with a B.A. in mathematics. For two years, after graduating, he worked on software for Emergency Departments and coordinated a support team as a technical engineer at Epic, the electronic health record company. He is currently an MD student at Columbia University's College of Physicians and Surgeons. He investigates intra-host HIV recombination using topological data analysis.
Nikhil Bommakanti
Nikhil is an MD student at Columbia University College of Physicians and Surgeons. He graduated from the University of Illinois at Chicago with a BS in Bioengineering then deferred entry to P&S to spend one year at the University of Oxford on a Whitaker Fellow Grant. Nikhil is working on a project on long noncoding RNA in pancreatic cancer with the support of an NIH T35 training grant.
Mykola Bordyuh
Mykola Bordyuh served as a postdoctoral research scientist in the Department of Biomedical Informatics. He received his B.S. and M.S. degrees from the Moscow Institute of Physics and Technology in Applied Mathematics and Physics and his Ph.D. in Electrical Engineering from Princeton University. His current research interests are applications of topological data analysis to biological data with an emphasis on cancer genomics.
Miguel Brown
Miguel Brown is a bioinformatics programmer at The University of Chicago School of Medicine. He graduated from the University of Rochester in 2004 with a B.A. in biology. He has worked as a researcher at the University of Rochester, Ortho-Clinical Diagnostics, the Rabadan Lab, and the Tuschl Lab at Rockefeller University.
Francesco Brundu
Francesco G. Brundu works as a Bioinformatics Scientist at Illumina. He received his B.S., M.S. and Ph.D. from the Polytechnic University of Turin, where he collaborated with the Candiolo Cancer Institute on the stratification of Colorectal Cancer using transcriptomics. In 2017, he joined the Rabadan lab as a postdoctoral research scientist, where his research focused on the design and application of single-cell RNA sequencing methodologies and analyses. His work involved contributions in the context of T-ALL, Intrahepatic Cholangiocarcinoma and, since 2019, on the characterization of the etiology of Schizophrenia.
fb2505[at]cumc.columbia.edu
Zachary Carpenter
Zachary Carpenter currently works at McKinsey & Company. He received a Ph.D from the Columbia Department of Pharmacology and Molecular Signaling in 2014. He was also a fellow of the Med into Grad Scholars (MIG) Program at Columbia University's College of Physicians and Surgeons. He graduated from the College of New Jersey in 2009 with a B.S. in biology and minors in chemistry and computer science. His participation in the MIG Scholars program at Columbia enabled him to obtain medical experience in pediatric and adult hematological oncology, which was his main research focus under Dr. Rabadan and Dr. Adolfo Ferrando. He also studied structure-based drug design, in silico pharmacology, and clonal evolution and phasing in cancer.
Joseph Chan
Joseph Chan is an Oncology and Post-doctoral Fellow in Computational Biology at Memorial Sloan Kettering Cancer Center. He received his B.S. in Biomedical Computation at Stanford University and graduated from the Columbia University MSTP program in 2014 with an MD and PhD in computational biology. His PhD dissertation, under the mentorship of Dr. Rabadan, focused on developing novel techniques in algebraic and network topology of influenza evolution. In particular, he modeled the global spread of seasonal influenza as a network that predicted the importance of different nodes (locations) in the transmission of the virus. He also developed a novel method based on algebraic topology that captured clonal and reticulate evolution in viruses. The second half of his thesis focused on cancer—in particular, the detection of gene fusions in glioblastoma, which led to the discovery of targetable, recurrent FGFR-TACC and EGFR-SEPT14 fusions.
Andrew Chen
Andrew Chen is an MD/PhD student at Columbia University. He received his PhD in 2020 from Columbia's Integrated Program in CMBS and a B.S. in Physics from MIT in 2015. His dissertation research in the Rabadan lab focused on spatial and genomic features of the glioblastoma tumor microenvironment.
Tim Chu
Tim received his B.A. in biology at NYU in 2012 and his Masters' in computer science at NYU in 2016. Previously, he worked in a microbiology lab studying the spore coat of B. subtilis. In the Rabadan, his work focused on pipeline design and data visualization. He currently works at the New York Genome Center.
Oliver Elliott
Oliver Elliott received his B.A. from Amherst College and his M.S. from Columbia University. In the Rabadan Lab, Oliver led the tech team. He also worked on pathogen discovery in high throughput sequencing data, transcriptome annotation, and identifying somatic variants in cancer.
Kevin Emmett
Kevin Emmett received his Ph.D. in the Rabadan Lab. His research interests are applications of topological data analysis to genomic data and the statistical topology of models in population genetics. Areas of focus include population structure and human demographic models, lateral gene transfer in bacteria and viruses, and statistical models of chromatin spatial organization. Additional work has involved machine learning methods for predicting host adaptation in infectious diseases, statistical models for analyzing next generation sequencing data, and signaling network inference in cancer. Kevin was jointly advised by Chris Wiggins.
Ioan Filip
Ioan Filip works at Illumina as a Bioinformatics Scientist. Previously, he was an Associate Research Scientist in the Systems Biology Department, and a member of the Program for Mathematical Genomics. He received his Ph.D. in Mathematics from Columbia University in 2016. While he was at the Rabadan Lab, Ioan studied the genetic basis of the immune response to viral infections, as well as the role of the immune system in cancer progression and treatment. He is interested in further developing algebraic and topological methods to model both viral and tumor evolution.
if2179[at]cumc.columbia.edu
Monika Francsics
Monika is an undergraduate at Columbia University pursuing a B.A. in computer science and mathematics. She is interested in algebraic topology and big data analytics techniques. At the Rabadan Lab, she is studying bacterial and viral interactions in the human microbiome and their role in infection using topological data analysis.
mf3145[at]columbia.edu
Angelica Galianese
Angelica graduated from Rutgers University with a BA in Genetics. Her undergraduate work under Derek Gordon involved in silico data simulation and power caulcations. Next, she worked at the New York Genome Center in the Landau Lab, where she analyzed single-cell multi-omic data (scATAC-seq, scRNA-seq) to identify subpopulations in murine cells associated with reprogramming and pluripotency. As a data analyst from November 2021 to April 2024, she was interested in aberrant gene function, identifying molecular subtypes for improved personalized medicine, and elucidating genetic and environmental effects contributing to oncogenesis.
Morgan Goetz
Morgan Goetz is a rising senior at the University of North Carolina at Chapel Hill majoring in Biomedical Engineering. She is working in Rabadan Lab this summer as a part of the 2018 National Cancer Institute Systems Biology and Physical Sciences Summer Research Program. Morgan’s work is focused on building a model to predict the immune response to anti-PD1 therapy in Glioblastoma patients.
Karen Gomez
Karen Gomez is an MD/PhD student at Columbia University. She received her Ph.D. in 2023 from the Columbia University Integrated Program in Cellular, Molecular, and Biomedical Studies and her B.S. in Biochemistry from Temple University in 2017. Her dissertation research in the Rabadan Lab focused on the role of the major histocompatibility complex class I in the pathogenesis B-cell lymphomas.
kg2726[at]cumc.columbia.edu
Junwei Gong
Junwei received his BS in Biology with a focus in Bioinformatics from University of Pittsburg. Currently, he is a master student at Columbia University furthering his skills in bioinformatics and data science. His undergraduate research focused on viral tumorigenesis study and novel virus discovery. In the Rabadan Lab, he is investigating the association between EHR data and diseases, particularly the discovery of novel risk factors. He is also interested in developing and applying data-driven approaches for solving biological problems.
jg4179[at]cumc.columbia.edu
Mrinalini Gururaj
Mrinalini "Mini" Gururaj graduated from Bangalore University in 2007 with a master's in biotechnology. As part of her master’s thesis, she co-authored a paper on computational drug discovery for alternative herbal remedies for tuberculosis, which was published in the Journal of Biomolecular Structure and Dynamics. In 2011 she got her master's from Columbia University in biotechnology. Her master's thesis was entitled "DNA Transfection Methods for Mammalian Cells."
David Gu
David is a second-year M.D. student at Columbia University College of Physicians and Surgeons. He graduated from Columbia University in 2012 with a B.S. in Operations Research, and he spent several years working in finance prior to matriculation. His current interests are in genomics and cancer evolution.
yg2206[at]cumc.columbia.edu
Alex Hawson
Alex Hawson is an anesthesiology resident at University of Rochester Medical Center. He graduated from Columbia University College of Physicians and Surgeons in 2012 and magna cum laude from Columbia University with a B.A. in Economics. Prior to medical school, Alex worked as a senior consultant at Deloitte focused on medical management and pharmaceutical pricing regulatory compliance. After Deloitte, he worked as a consultant developing custom software for hedge funds. Alex did a year
of research in the Rabadan Lab applying data mining techniques to identify new associations
for rare diseases.
Carlos Hernández
Carlos Hernández is pursuing his Ph.D. at Stanford University. He graduated from Columbia University's School of Engineering and Applied Science, where he studied Applied Mathematics with a concentration in quantitative biology. His research interests include the molecular epidemiology of viruses and oncoviral discovery. In the past, he has worked on discerning the swine-origin of A/H1N1 human influenza pandemic using Bayesian analysisi and pathogen discovery in sequencing data. He has been awarded both Genentech and HHMI fellowships to work in the labs of Stephen Goff and Andrew McCammon, respectively.
cxh[at]stanford.edu · homepage
Antony Holmes
Antony Holmes is a postdoctoral research scientist in the lab of Riccardo dalla Favera at Columbia University. He studied computer science at the University of Warwick in the UK between 2000 and 2004. During this time he also undertook several internships at Unilever Research where he worked in the bioinformatics department on database projects to manage patient data. In 2005 he moved to a newly opened interdisciplinary research center at the University of Warwick to read for his Ph.D. which looked at understanding morphogenesis in myxobacteria.
antony.holmes[at]dbmi.columbia.edu
Ian Huang
Ian is an undergraduate student at Columbia University, double majoring in computer science and financial economics. His past research has been focused on machine learning applied to the classification of heart transplant rejection severity within medical images. Now he is working on finding the relationship between noncoding and coding RNA genes in pancreatic cancer. He is also part of the Columbia Organization of Rising Entrepreneurs (CORE) and the Columbia University Medical Informatics Society, and enjoys playing violin and watching Netflix in his free time.
iyh2110[at]columbia.edu
Nirvaan Iyer
Nirvaan Iyer is a rising senior at Columbia University double majoring in Mathematics and Computer Science. In the past he has worked on projects related to estimating intrinsic properties of manifolds and is currently working on a project to see how randomized sketching affects eigenvalue distributions of random matrices. This summer at the Rabadan Lab he will be working on methods in deep learning to extract disease-relevant spatial patterns.
Jessica Kasamoto
Jessica was a Master's student in the department of biomedical engineering. She graduated from Johns Hopkins University in 2021 with a bachelor of science in biomedical engineering, focusing in genomics and systems biology. Her research at Hopkins was primarily in creating new tools to reconstruct gene regulatory networks from single-cell data. In the Rabadan lab, she worked on a project characterizing peripheral T cell lymphomas and their complex interactions within the tumor microenvironment.
Brendan Kelly
Brendan Kelly is currently a practicing physician. He received his M.D. from the Columbia University College of Physicians and Surgeons in 2007. He completed his residency in the Department of Internal Medicine at New York Presbyterian Hospital and did a fellowship at the University of Pennsylvania.
Cole Khamnei
Cole Khamnei is an MD/PhD student at Columbia University Vagelos College of Physicians and Surgeons. He graduated from UC Berkeley with a B.S. in Engineering Physics in 2019. After graduation, Cole worked on machine learning methods for ctDNA detection in the Landau Lab at the New York Genome Center. He is interested in developing computational methods for studying cancer genomics. He completed a summer doctoral rotation in the summer of 2022.
Naomi Klickstein
Naomi Klickstein is a PhD student at Columbia University in the Department of Biological Sciences. She is mentored by Jellert Gaublomme. After graduating from Brandeis University with a B.Sc. in Biology and Neuroscience, she worked at Mass General Hospital researching Alzheimer’s Disease. In the Gaublomme labs, she is using and developing multiplexed imaging methods and analyses to interrogate spatial organization in tissue physiology and pathology.
Oleksandr Kravets
Oleksandr Kravets was a Postdoctoral Research Scientist in the Department of Systems Biology. He received his Ph.D. in Mathematics from Columbia University in 2020. His research interest at Rabadan Lab focused on developing and implementing mathematical methods for analyzing the role of the immune system in cancer development. Since moving to Kiryluk Lab in the Department of Medicine in 2024, he shifted his focus to analyzing genetic data from large datasets, specifically targeting applications for kidney diseases and related phenotypes.
ok2241[at]cumc.columbia.edu
Judith Kribelbauer
Judith Kribelbauer is a PhD student in the Integrated Program (C2B2 track) at Columbia. In 2012, she received her bachelor degree in Chemistry from the University of Heidelberg with a focus in theoretical and biological chemistry. Before starting the PhD-program at Columbia, she did a research year in Dr. Weeks lab at UNC-Chapel Hill working on structural alterations of HIV-RNA using next-generation sequencing.
jfk2132[at]columbia.edu
Erik Ladewig
Erik Ladewig was awarded a PhD in computational biology in Columbia's Integrated Program in Cellular, Molecular, Structural and Genetic Studies. His current interests include algorithms in statistical analysis of high throughput data to infer disease mechanisms and evolution. Before attending Columbia, he was a member of the Eric Lai Laboratory at Memorial Sloan Kettering Cancer Center. His research included biogenesis and post-transcriptional modifications of small non-coding regulatory RNAs.
Alberto Langtry Yáñez
Alberto Langtry is a PhD student in "Epidemiology and Public Health" at the Spanish National Cancer Research Center (CNIO), who is doing his stay in Dr. Raul Rabadan's Lab at Columbia University. He obtained a B.S in Biology and an M.S in "Therapeutic Targets on Cell Signaling: Research and Development" at the University of Alcala de Henares. He is currently doing an M.S in Bioinformatics and Biostatistics at the Universidad Oberta de Catalunya. His thesis project focuses on the role of the Major Histocompatibility Complex (MHC) on the "genetic susceptibility to Pancreatic Cancer risk", during the course of which he has been actively collaborating with Dr. Raul Rabadan within the "Stand Up To Cancer" project. His main interests are cancer research and immunology.
Albert Lee
Albert Lee is currently a bioinformatics scientist at Counsyl. He received his Ph.D from the Department of Biomedical Informatics and his B.S. in molecular, cell, and developmental biology with honors from the University of California at Los Angeles. In 2013, he received his master's in Biomedical Informatics. His research interest centers on the statistical analysis of RNA sequencing data to elucidate the transcriptomes of uncharacterized species. He has also worked on problems in cancer and infectious disease.
Renwei Li
Renwei received his B.S. of Biological Science from Huazhong University of Science and Technology in 2019. During his undergraduate, his research focused on the genomics and mechanism of pediatric leukemia with the whole genome sequencing data. His research interest is about the system biology and genomics problems in human diseases. Renwei is currently a master student at Department of Biomedical Informatics in Columbia University. In the Rabadan Lab, he is working on the analysis single cell sequencing data of B cell acute lymphoblastic leukemia to discover how the disease develops in different stages of treatment.
rl3088[at]cumc.columbia.edu
Baihan Lin
Baihan Lin is pursuing PhD in Computational & Systems Biology at Columbia University. He graduated from the University of Washington (UW) in 2017 in Computational Neuroscience Program with B.S. in Applied & Computational Mathematics and B.A. in Psychology with Honors. Before attending Columbia, he researched on various interesting problems spanning vision neuroscience, mathematical biology, genome sciences, protein design, and human-computer interaction. Industry-wise, he maintains close collaborations with IBM Research on artificial intelligence and Microsoft Research on computational neuroscience. His major theoretical research interest lies in the intersection between geometric topology, Bayesian machine learning, dynamical/evolutionary systems and network inference, with extensive application interests in multiscale biological systems and networks, especially in genomics and neuroscience.
Aaron Liss
Aaron Liss is a senior at Columbia University studying computer science with a special interest in AI and biology. His current research project is using deep learning to predict alternative splicing in diseases with splicing factor mutations.
Eric Minwei Liu
Eric Minwei Liu is currently a PhD student at Weill Cornell Medical College. He holds a master’s degree from the Department of Biomedical Informatics at Columbia University, where he received the 2012 Mitsubishi UFJ Trust Scholarship. He graduated from National Taiwan University in 2005 with a dual B.S. degree in chemistry and information management and in 2007 with an M.S. degree in pharmaceutical science. After graduation, he continued working at NTU in the Jung-Hsin Lin Lab, where he built activated structure models of adenosine A2A and designed potential ligands for treating Huntington’s disease by conducting simulations of molecular dynamics.
Bryan Hisashi Louie
Bryan is a third year undergraduate at Columbia University pursuing a B.S. in Biomedical Engineering. He previously worked in the Cell and Molecular Biomechanics Lab at Columbia, where he studied the mechanotransduction pathway of primary cilia in bone. His current interests are in cancer biology and genomics. In the Rabadan Lab, he is currently working on a project on cancer evolution.
Chioma Madubata
Chioma Madubata was awarded a PhD in the Rabadan Lab and is currently pursuing an MD at Columbia University College of Physicians and Surgeons. She graduated from Harvard University in 2011 with a A.B. in molecular and cellular biology. As an undergraduate, she continued research at the United States Department of Agriculture studying parasite population genetics. She also completed an undergraduate thesis at the Broad Institute of Harvard and MIT, performing high content chemical screening for compounds that improve the pancreatic cell environment in diabetes. During her first summer of medical school, she performed research at Memorial Sloan-Kettering Cancer Center. She is interested in oncology, cancer genomics, and cancer therapeutics.
Rong Ma
Rong received his B.S in Biochemistry from McGill University in 2018. During his undergraduate, he focused on designing Sato Aptamers to enhance live-cell RNA imaging and improving genome-scale metabolic models with protein localization information. Currently, Rong is working on the analysis of non-coding mutations in acute lymphoblastic leukemia at the Rabadan Lab.
rm3707[at]cumc.columbia.edu
Nour Moustafa-Fahmy
Nour was a Masters student at Columbia University in the Department of Statistics. She graduated from Queen's University with a Bachelor of Science in Mathematics where she took a particular interest in the intersection of geometry, topology and algebra. Upon graduation she has been working as a data scientist on recommender systems that leverage textual and image data. She will be applying her experiences and skillset to cancer genomics at Rabadan Labs, and is interested in applying topological methods in the field.
Patrick van Nieuwenhuizen
Patrick van Nieuwenhuizen received his MD from Columbia University College of Physicians and Surgeons. He graduated from Princeton University in 2010 with an A.B. in Physics. After graduation he spent two years in Zimbabwe building Upenyu Health Group, a non-profit devoted to treating parasitic
worm infections. He is interested in applying topological data analysis to oncology and other aspects of medicine.
Rose Orenbuch
Rose Orenbuch is a senior at Columbia University, where she is majoring in Information Science with a concentration in biology and neuroscience. She is investigating associations between genetics and immune response during viral infections, using genomic data. Furthermore, she is developing an application for genotyping highly polymorphic regions using standard RNA sequencing reads.
rose.orenbuch[at]columbia.edu
Kernyu Park
Kernyu Park is currently an MA candidate in the department of biomedical informatics (DBMI) at Columbia. He received his BA in Biology from Columbia University in 2016. He has worked on cleaning genome variant data of cancer patients to better predict the correlation between the variants and cancer genes and is now interested in translational analysis of NGS whole genome sequencing data for infectious diseases.
Juan Angel Patiño-Galindo
Juan Angel Patiño-Galindo was a postdoctoral research scientist, working on virus evolution in the Department of Systems Biology. His PhD focused on studying different aspects of the mid- and long-term evolution of RNA viruses, with special interest in molecular epidemiology of HIV and HCV. His research at the lab involved the application of topological and phylogenetic methods to the analysis of viral evolution, as well as transcriptional analyses (bulk and single cell) of viruses and cancer. He is currently a Senior Scientist at the Dept. of Microbiology of the Icahn School of Medicine at Mount Sinai
Alex Penson
Alex Penson is a senior computational biologist at Memorial Sloan Kettering. In the Rabadan Lab, his research focused on searching for traces of disease-causing organisms in genetic data as well as studying the molecular basis of Myelodysplastic syndrome and Hodgkin’s lymphoma. He worked on computational and statistical methods to efficiently analyze large amounts of genomic data, drawing on skills honed during his doctoral work in high energy physics searching for hypothetical sub-atomic particles called gravitons at the LHC in Switzerland.
Tomin Perea-Chamblee
Tomin received his Bachelor of Science in Engineering from Columbia University where he studied Computer Engineering. Since he joined the Rabadan Lab as a Data Analyst in August 2019, he has largely worked on allocating and administering the cloud computing resources of the lab, as well as containerizing and adapting bioinformatics pipelines to be run in the cloud.
tep2116[at]columbia.edu
Efua Peterson
Efua Peterson holds a Bachelor's degree in Mathematics and Computer Science from Columbia University. She is interested in genomics and oncology, and in Rabadan Lab she is applying methods of topological data analysis to the study of genetic recombination.
Paula Ralph-Birkett
Paula Ralph-Birkett was the Administrative Manager for the Rabadan Lab within the Department of Systems Biology. She received her Bachelor of Arts in Communications at St. John’s University. Paula joined Dr. Rabadan’s group in January 2019, and in June 2022, was promoted to Assistant Director for the Program of Mathematical Genomics within the Department of Systems Biology.
pr2470[at]cumc.columbia.edu
Jonathan Reichel
Jonathan Reichel is currently lead bioinformatics scientist at the Innovation Laboratory in the Center for Molecular Oncology at Memorial Sloan Kettering Cancer Center. He graduated with high honors in Biological Sciences from the University of Maryland in College Park, where he worked on a human genetics association study and designed paramagnetic nanotubes made from silicon dioxide and magnetite for use in bioextraction and future drug delivery systems. Since then, he has studied computer engineering as a post-baccalaureate student at Rutgers University and served in the Peace Corps. In the Rabadan Lab, Jonathan worked on developing computational tools to discover signals in high-throughput sequencing data with a focus on cancer, gene fusions, and novel pathogens.
jbr95[at]cornell.edu
Samuel Resnick
Sam Resnick is an MD/PhD student at Columbia University College of Physicians and Surgeons. He graduated with a BS in Biology from the University of North Carolina at Chapel Hill in 2015. Previously, he studied how different chromatin remodeling complexes impact transcriptional regulation and contribute to tumorigenesis.
Alannah Rodrigues
Alannah Rodrigues is a junior at the University of Illinois at Chicago studying Biomedical Engineering. She worked at the Rabadan Lab as part of the 2022 NCI Division of Cancer Biology Summer Undergraduate Research Program. During the summer, she used Random Matrix Theory to denoise Single Cell RNA Data.
Daniel Scholes Rosenbloom
Daniel Scholes Rosenbloom currently works at Merck. He received his Ph.D. in Organismic and Evolutionary Biology from Harvard University in 2013. As a member of the Program for Evolutionary Dynamics at Harvard, he focused on mathematical models of viral infection and evolution. In the Rabadan Lab, Daniel worked on developing methods in “topological genomics” — using tools from algebraic topology to characterize both human evolution and the spread of HIV. He also collaborated with the Siliciano Lab at Johns Hopkins Medical School on issues of HIV treatment and latency.
daniel.rosenbloom[at]gmail.com · homepage
Udi Rubin
Udi Rubin received his B.S.c in Natural Sciences from the Open University of Israel in 2013. Working for several years in the Israeli Hi-Tech scene alongside his growing passion for the life sciences, led him to pursue Columbia’s M.A Biotechnology degree. In his master’s thesis, Udi applies topological data analysis techniques on bulk and single-cell RNA-seq data to study non-small cell lung cancer.
Katyna Sada Del Real
Katyna was an exchange PhD student from the University of Navarra from September 2023 - January 2024. She is a Biomedical Engineer and holds a Master's degree in Biomedical Data Analytics from Tecnun School of Engineering, University of Navarra. Her recent work has focused on creating explainable artificial intelligence models for cancer research, with the goal of bridging the gap between clinicians and engineers. Katyna's interest lies in the field of machine learning applied to healthcare.
Irina Sagalovskiy
Irina Sagalovskiy is a Research Associate in the Department of Biomedical Informatics. She received her Ph.D. in Molecular Biology from Russian Academy of Sciences in 2006, studying immunology of cancer. She did her postdoctoral research at the Hospital for Special Surgery looking for new potential triggers of human autoimmune diseases. Irina joined Rabadan’s lab in January 2017, and her current research is focused on the role of non-coding RNAs in cancer.
Kripa Sivakumar
Kripa Sivakumar is software engineer at Amazon. He received a master's degree in the Department of Computer Science at Columbia University. In the Rabadan Lab, he collaborated with Joseph Chan on identifying somatic mutations related to tumor progression. In particular, he worked on inflammatory breast cancer, glioblastoma multiforme and melanoma.
Alexander Solovyov
Alexander Solovyov is postdoctoral fellow at the Icahn School of Medicine at Mount Sinai. Previously, he was an Associate Research Scientist working in the Ian Lipkin group at the Center for Infection and Immunity and the NorthEast Biodefense Institute. He received his Ph.D. in physics from Princeton University in 2009. His interests include phylogenetic methods, next generation sequencing technologies, evolutionary models and data clustering algorithms as they apply to the study of the evolution and the discovery of new viruses.
Vladimir Trifonov
Vladimir Trifonov is a research scientist at The Genomics Institute of the Novartis Research Foundation (GNF), in San Diego. He received his Ph.D. in computer science from the University of Texas at Austin in 2006. He spent a year as a postdoctoral fellow at the School of Mathematics at the Institute for Advanced Study in Princeton, and a year as a research assistant professor in the Department of Mathematics, Statistics, and Computer Science at the University of Illinois, Chicago.
Santiago Vilar
Santiago Vilar received his Ph.D. from the Laboratory of Pharmaceutical Chemistry at the University of Santiago de Compostela, Spain, in 2006. The following year, he was awarded a grant to work in molecular docking at the University of Padova, Italy. In 2008 Santiago began a two-year postdoctoral fellowship working in the Laboratory of Biological Modeling at the National Institutes of Health (NIH) in Bethesda, Maryland. His research interests span different methodologies in computational chemistry, such as QSAR/QSPR in small molecules and proteins, and molecular modeling applied to structure-based drug discovery and explanations of biomolecular mechanisms of action.
Zixuan Wang
Zixuan received her B.Eng. from Wuhan University and her Master Degree from University of Pennsylvania. In the Rabadan Lab, she worked as the Data Analyst and specializes in data visualization, data mining and web mapping.
zw2664[at]cumc.columbia.edu
Malcom Wells
Malcolm Wells is a PhD student in the Department of Physics. He graduated from Columbia College with a BA in physics. His undergraduate research was in experimental condensed matter physics. Currently, Malcolm is working on methods for single-cell RNA seq.
mw3079[at]columbia.edu
Richard Wolff
Richard Wolff is a graduate of Columbia University with a degree in mathematics and significant coursework in computer science. He goes by
Ricky, and in his free time enjoys playing the guitar. He hopes one day to use
his background in pure math to approach problems in medicine in new and fundamental ways.
Sakellarios Zairis
Sakellarios Zairis is a Clinical Fellow in Medicine at Harvard Medical School. He received his Ph.D. in Computational Biology, as well as his MD, from Columbia. In the lab, his work focused on using machine learning approaches to understand how oncogenic viruses affect the mutational landscape of certain cancers. Sakellarios was also a member of the Wiggins Lab.
Junfei Zhao
Junfei Zhao was an Assistant Professor of Mathematical Genomics in Pathology and Cell Biology at the Columbia University Medical Center in the Vagelos College of Physicians and Surgeons at Columbia University. His research focused on developing computational methods to study biological problems in cancer genomics. His work has shed light on the genomic markers for predicting patients’ response to therapy and its underlying mechanism. He received his Ph.D. in Applied Mathematics from University of Chinese Academy of Sciences. Junfei joined Dr. Rabadan's group in September 2016, and left in January 2023 to be a Principal Scientist at Bristol Myers Squibb.
jz2845[at]cumc.columbia.edu
Liangyu Zhao
Liangyu (Ilyia) received her B.S. of Bioengineering-Bioinformatics from University of California, San Diego in 2019. During her undergraduate, her research focused on the application of machine learning algorithms for diagnosing relapses of CLL patients through Flow Cytometry Single Cell data. Her research interest is about the system biology and genomics problems in human diseases. Ilyia is currently a master student at Department of Biomedical Informatics in Columbia University. In the Rabadan Lab, she is working on the analysis of the effects of VAV1 alterations in T-cell lymphomas development and transformation.
lz2716[at]cumc.columbia.edu
Liyuan Zhu
Liyuan Zhu received his MA from the Department of Biomedical Informatics, and his B.S. in Biology from Tsinghua University, China. In 2015, he was awarded his master's in Molecular Virology and Microbiology from Baylor College of Medicine. In the Rabadan Lab, he worked on sequencing data of Ebola patients.
Amanda Zong
Amanda Zong is an undergraduate at Columbia in the Class of 2021. She is planning to major in computer science and is interested in the application of computational tools to diagnose diseases. This summer at the Rabadan lab, she will be working on TOBI, a computational model that identifies oncogenic mutations in bladder carcinomas, and will strive to improve its accuracy and performance.
Tianji Yu
Tianji Yu is a PhD student in the department of Systems Biology. Before he came to Columbia, he earned a bachelor's degree from UNC Chapel Hill where he studied quantitative biology and computer science. At UNC, he explored bioinformatic tools for single-cell RNA data. Currently, his research interest lies in characterizing TF-TF interactions in cancer with machine learning models.
Tommy Ly
Tommy Ly is a computer science student at Columbia University, where he is pursuing his second bachelor's degree. Prior to his studies, Tommy spent 4.5 years working at Uber Technologies in diverse data analytics roles across Asia and America. In 2022, he interned at the New York Genome Center, where he worked on image processing for the Illumina HiSeq package. Tommy's passion lies in the application of machine learning to the healthcare and bio fields.
Sanjay Natesan
Sanjay Natesan is a Junior (Class of 2025) at Columbia University pursuing a degree in Computer Science. During high school, he spent two years working on the statistical modeling of infectious diseases in the Han Lab at the Cary Institute for Ecosystem Studies. He also participated in the Rockefeller University Summer Science Research Program for two summers where he examined RNA gene expression in COVID-19 patients and identified patterns in infection and vaccination among various United States demographics. Sanjay joined the Rabadan Lab in Fall 2021 as an undergraduate student researcher; his interests include Data Science, AI/ML, and computational biology.
Theodore Nelson
Theodore Nelson is a senior in Columbia College, majoring in Computer Science, pursuing a premedical track. On campus, he serves as the President of Systems Biology Initiative, an undergraduate student organization organized around this crucial intersection between bioinformatics and medicine. His previous research has focused on long-read transcriptomics. In the Rabadan Lab, he was working to model alternative splicing in human diseases within spatial transcriptomics data.
Alejandro Buendia
Alejandro Buendia was a Computational Research Manager in the Department of Systems Biology. He received his BA in computer science and mathematics from Columbia University. He previously worked as a data scientist at Microsoft and a research engineer in the Clinical Machine Learning group at MIT, where he worked on modeling patient trajectories from longitudinal EHR data. He is currently interested in using techniques from natural language processing to model viral evolution and representation learning over single-cell transcriptomic data.
Raul Rabadan
Principal Investigator
Raul Rabadan
Principal Investigator
Raul Rabadan
Principal Investigator
Raul Rabadan, Principal Investigator
Raul Rabadan is the Gerald and Janet Carrus Professor in the Departments of Systems Biology, Biomedical Informatics and Surgery at Columbia University. He is the director of the Program for Mathematical Genomics at Columbia University and the NCI Center for Topology of Cancer Evolution and Heterogeneity. From 2001 to 2003, Dr. Rabadan was a fellow at the Theoretical Physics Division at CERN, the European Organization for Nuclear Research, in Geneva, Switzerland. In 2003 he joined the Physics Group of the School of Natural Sciences at the Institute for Advanced Study. Previously, Dr. Rabadan was the Martin A. and Helen Chooljian Member at The Simons Center for Systems Biology at the Institute for Advanced Study in Princeton, New Jersey. He has been named one of Popular Science's Brilliant 10 (2010), a Stewart Trust Fellow (2013), and he received the Harold and Golden Lamport Award at Columbia University (2014) and the Diz Pintado award (2018). Dr. Rabadan’s current interest focuses on uncovering patterns of evolution in biological systems through the lens of genomics. His recent interests include the development of mathematical approaches to uncover the evolution of cancer and infectious diseases, including topological data analysis and Random Matrix Theory, among others.