Hossein Khiabanian is a 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.
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.
Rachel Melamed is currently 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.
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.
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.
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.
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.
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.
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.
Efua Peterson is an undergraduate at Columbia University pursuing a B.A. in mathematics as a pre-medical student. 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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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."
Richard Wolff is a rising senior at Columbia College majoring in mathematics with a concentration 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.
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.
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.
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.
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.
Zikai Wu is 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.
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.
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.
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.
Pingzhang Wang is a visiting associate research scientist. 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.
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.
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.
Morgan Goetz is a rising senior at the University of North Carolina at Chapel Hill majoring in Biomedical Engineering. She is working in the 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 patents.