Aditi Goyal, MS

2023-2024: Aditi Goyal is a bioinformatics scientist with the BaaS team. She also serves as an active member and as the BaaS team's representative within Data Studio team in the department of Statistics. Aditi aims to investigate bioinformatics problems by combining the powers of biostatistics, computer science, and molecular biology. 

Aditi has a MS in Biomedical Data Science from Stanford University, and previously earned a double bachelors in Genetics and Statistics from UC Davis. Aditi has published papers in the fields of microbial genomics, bioinformatics pipeline development, and computational drug repurposing. She has also worked as a bench lab scientist at a private vaccine development company, where she has honed her skills in microbiology and immunology assays. She is intimately familiar with the experimental design and data collection process and leverages this information when conducting her downstream bioinformatics analyses. 

When away from her laptop, Aditi enjoys spending time at the beach, various art projects, and tending to her 18 houseplants. 

Paul Billing-Ross, MS

2015-2023: Paul was an SCGPM software developer who is passionate about building the roads and bridges of genomics research. He broke into computational biology studying models of molecular evolution under Dr. Sudhir Kumar at Arizona State University and then transitioned to studying mitochondrial genetics as an NSF Graduate Research Fellow at Cornell University. At SCGPM, he migrated the Stanford sequencing pipeline on DNAnexus, and used cloud technologies to open and streamline the process of biomedical innovation for our collaborator, the VA Palo Alto Health Care Center.

Meng Wang, PhD

2022-2023: Meng was a senior bioinformatician for the BaaS team whose interests are in developing statistical methods and computational tools to better understand the complexity of biology.  She was most recently a research scientist with the Snyder Lab and led the algorithm development in several projects.  In the GTEx project, she was in charge of proteomics data analysis and integration, and developed several new algorithms in robust normalization and data-adaptive quantification of tissue-specificity (AdaTiSS).  In the project to predict the onset of COVID-19 from wearable device data, she developed both offline and online detection algorithms to detect infection-associated heart rate anomalies from smartwatch data.  Meng received her PhD in Mathematical Statistics from the University of California, San Diego.

Jina Song, PhD

2018-2022: Jina Song was a Big Data Architect at SCGPM. In her work on the VA Million Veteran Program, she established the variant calling and quality control pipeline for whole genome sequencing data and led the initial release of WGS data to MVP researchers. Prior to joining SCGPM, Jina worked as a postdoctoral researcher in Biostatistics & Computational Biology Branch in National Institute of Environmental Health Science (NIEHS/NIH), where she analyzed ChIP-seq data in cancer research. Jina has a Ph.D in Electrical and Computer Engineering from NCSU.

Jina departed Stanford to apply her big data skills at MEDiC, an early stage biotech startup focussed on improving cancer treatment through better tumor modelling.

Vandhana Krishnan, MS

2016-2022: Vandana most recently worked as a bioinformatician on the VA's Million Veterans Project.  Before that she worked on the Stanford Clinical Genomics Service, and was responsible for implementing computational pipelines on the cloud and conducting benchmarking for clinical data. Prior to joining SCGPM, she was an Associate in Research at Washington State University, managing the bioinformatics research and services in the Western Regional Small Grains Genotyping Laboratory, USDA-ARS, where she built the lab’s computational facilities and helped develop a computational pipeline used for variant calling mainly from wheat genotype data.

Vandhana has a MS in Computer Science from Washington State University and a MS in Bioinformatics and Computational Biology from University of Idaho. Previous research experience includes fruit genomics, archaea genomics, and human microbiome.

Pratima Nallagatla, MS

2020-2022: Pratima solved research problems for labs as a bioinformatician for the BaaS team. Prior to joining the GBSC, she worked as a senior member in the Product Care team at Roche Molecular Systems, conducting root-cause investigations into assay performance (CAPA) and leading post-launch product improvement projects from feasibility to verification and validation. Pratima received her MS in Bioinformatics from Johns Hopkins University and her BS in Bioengineering from UC Riverside.

Yan Yang, PhD

2019-2021: Yan worked as a Bioinformatician at SCGPM dedicated to BaaS. She has a broad range of research interests in big data, bioinformatics, population genomics, and statistical genomics. Her postdoctoral work at the DOE Joint Genome Institute, a division of Lawrence Berkeley National Lab, focused on population genetics using various types of NGS data to reveal molecular mechanisms underlying adaptive strategies in sorghum. Yan received her PhD in Plant Breeding and Genetics from Texas A&M University in 2018.

Yan left SCGPM to take the role of Bioinformatics Scientist at Tempus.

Wenyu Zhou, PhD

2019-2020: Wenyu is a Bioinformatics Scientist at SCGPM dedicated to BaaS. She recently finished her post-doctorate training with Dr. Michael Snyder at Stanford University. With Dr. Snyder, she studied Type 2 Diabetes (T2D) and utilized multi-omic techniques to measure both host and microbial molecular changes over time and to understand underlying associations with the disease onset and development. She led the Integrative Personal Omics Profiling (iPOP, http://med.stanford.edu/ipop.html) project over the last five years, and has expertise in analyzing different types of high-throughput data (NGS, mass-spec based and others) and applying statistical modeling and visualization techniques. Wenyu has first-authored research articles published in Nature, Cell Stem Cell, Cell Systems, and EMBO Journal, and actively serves as a reviewer for a number of scientific journals in the genomics field. Wenyu received her PhD in Biology from the University of Washington at Seattle in 2012.

After leaving Stanford, Wenyu became Head of Translational Endocrinology at Tempus.

Ziye Xing, MS

2018-2020: Ziye Xing is a software engineer at SCGPM. His research interests lie in large-scale parallel computing, distributed systems, and data analysis using machine learning techniques. He worked on building a Hadoop ecosystem and HBase database in the cloud when he worked with our center as an intern, and then he fully joined our team to continue developing Hummingbird, an application helps to optimize performance of genomics pipelines on the cloud.  He is also helping to analyze genomic data from the VA's Million Veteran Project. Ziye received his Computer Science Masters Degree from UCLA, and did his undergraduate study at Michigan State University, where he contributed to the Ribosomal Database Project.

Ziye continues to tackle complex engineering problems as a Software Engineer at Google.

Nathaniel Watson, MS

2013-2019: As a Bioinformatician at SCGPM, Nathaniel was responsible for bioinformatics for ENCODE ChIP-Seq processing; prior to that, he managed informatics for the Stanford Genome Sequencing Center. Prior to joining SCGPM, Nathaniel was a Research Associate at Bayer Vegetable Seeds. He has a MS in Bioinformatics from the University of North Carolina at Charlotte.

After SCGPM, Nathan joined Stanford Health Care as a Biomedical Applications Engineer with the Clinical Genomics Service team.

Gao Zhou, PhD

2017-2019: Gao was a Bioinformatics Scientist at SCGPM. Gao has broad knowledge in computational biology, bioinformatics and molecular biology. He has hands-on experience in analyzing different types of next generation sequencing (NGS) data. He has expertise in machine learning and algorithm development. He enjoys applying, defining, and validating computational approaches to deliver important biological insights.

Prior to joining SCGPM, Gao has been part of the wearable team in Snyder Lab who performed the first systematic analysis and demonstrated the power of using wearable and portable for monitoring human and early detection of inflammatory diseases and diabetes. Gao has a PhD in Biomaterial Science from University of Toronto in Canada.

Gao continues his work as a Senior R&D Scientist at Case Western Reserve University.

Yue (Wendy) Zhang, PhD

2016-2018: Yue was a Senior Bioinformatics Scientist dedicated to analyzing the data which comes into the GBSC Bioinformatics-as-a-Service resource. Prior to joining the SCGPM, Yue was a postdoctoral scholar with Prof Mark Kay in the Departments of Pediatrics and Genetics. She has a PhD in Theoretical Physics from Xiamen University in China.

Yue has broad knowledge and solid experience in different bioinformatics fields, especially in next-generation sequencing data including RNA-seq, single cell RNA-seq, small RNA-seq, Ribosome profiling, ChiP seq, PAR-CLIP seq, ATAC-seq and other cutting-edge sequencing type. She has expertise in statistical modeling, library normalization, classification, programming and visualization. Yue developed active and close collaborations with dozens of labs at Stanford and brought her interdisciplinary knowledge and professional skills to help Stanford researchers achieve their goals.

Yue left SCGPM to apply her breadth of knowledge and skills as a Bioinformatics Consultant at Genentech.

Priya Desai, MS

2016-2018: Priya was a Biomedical Engineer at SCGPM responsible for technologies and applications at the Genetics Bioinformatics Service Center. Priya has a background in Physics and Astronomy and started her career at the Harvard Smithsonian Center for Astrophysics in Cambridge, MA where she was part of the Chandra X-ray Center and involved in analyzing spectral data of sun-like stars. As the PI of her own NASA grant, she continued working in the field of X-ray spectroscopy at the Space Science Labs at UC Berkeley. It was while working on a project to predict solar flares at the Stanford Solar Center that she got interested in machine learning and data science. Most recently, she was part of the Pritchard Lab in the Genetics department at the Stanford where she helped develop SciReader, a recommendation engine for biomedical literature. She has a blog where she discusses bioinformatics and other related topics. 

Priya has a MS in Physics from Indian Institute of Technology, Bombay and completed her graduate coursework in Math at the University of Texas in Austin. 

Somalee Datta, PhD

2012-2017: Somalee is now the Director of Research IT at the Stanford School of Medicine IRT.

Prior to joining IRT, she was Director of Bioinformatics at SCGPM. During her tenure at SCGPM, she was responsible for starting Stanford’s first computational service center Genetics Bioinformatics Service Center, a facility that provides comprehensive computational solutions to enable large scale genomics research and clinical projects.  

Prior to joining SCGPM, Somalee worked at various start-ups in Silicon Valley as well as large organizations such as Life Technologies (now Thermo Fisher) and Gen-Probe (now Hologic). Among her start-ups is Verseon, a drug design company, where she was founding team member responsible for building the platform that brought together multiple innovations in molecular modeling, library design, large scale computation and data mining. Verseon is backed by one Nobelist (Steven Chu, Prof of Physics at Stanford & Former Secretary of Energy) and multiple heads of R&D at large pharmaceutical companies and has produced several novel pre-clinical candidates in Thrombosis. Somalee has a PhD in Statistical Physics from Boston University, and an MS in Physics from Indian Institute of Technology Madras.

Isaac Liao, PhD

2014-2017: As a Software Engineer at SCGPM working on the Stanford Clinical Genomics Service (CGS), Isaac is responsible for implementing the software stack on Cloud. Prior to joining SCGPM, Isaac was a post-doctoral researcher at UC Davis where he developed an interactive plankton exhibit at the SF Exploratorium in collaboration with the MIT Darwin group. He has a PhD in Neuroscience at UC Davis. Prior to his graduate studies, he was a Research Associate at the VA Medical Center where he conducted MRI experiments and analyzed data.

Isaac took his talents to Los Angeles, to apply his skills in engineering, design, and visualization at Riot Games.

Greg McInnes, PhD

2014-2017: As a Software Engineer at SCGPM, Greg was responsible for streamlining our data mining infrastructure on our Cloud (a dbGaP-compliant gateway to Google Cloud Platform). He enabled cloud-based analysis of VCF data for VA's Million Veteran Program.

Greg has a BS in Biological Sciences from Arizona State University and, surprisingly, a PhD in Biomedical Informatics from Stanford University. In 2021, Greg accepted a position as Senior Scientist at Empirico where he studies pharmacogenomics.

Nathan Hammond, PhD

2013-2016: When he was a Software Engineer at SCGPM, Nate was responsible for development of the pipeline framework, Loom. Prior to joining SCGPM, Nathan worked as a Quality Engineer and Application Support Engineer with the Computational Biology group at Mathworks where he was responsible for the Bioinformatics Toolbox (Next-Generation Sequencing, Microarray Analysis, Visualization Tools) and SimBiology (Modeling tool for Systems Biology, Pharmacokinetics/Pharmacodynamics). He has a PhD in Mechanical Engineering from MIT where he designed peptide scaffolds with tailored mechanical properties for tissue engineering applications. He holds two patents for medical devices.

After SCGPM, Nathan joined Stanford Health Care as a Staff Scientist with the Clinical Genomics Service team.

Denis Salins, BS

2013-2016: As a Software Engineer at SCGPM, Denis was responsible for Information Data Management in several projects including ENCODE ChIP-Seq, iPOP, HMP2, and NASA Twin Astronaut Study. He was the lead software engineer (and co-author) on a wearable biosensor publication that got mentioned on NIH Director's blog. Prior to joining SCGPM, Denis managed a 10 person software development team responsible for complete lifecycle development of First Medical Solution’s flagship EMR product. He has a BS in Computer Science from Florida Atlantic University.

Amin Zia, PhD

2013-2016:  As a Senior Bioinformatician at SCGPM, Amin was responsible for the development of “best-in-class” variant discovery pipelines for DNA-Seq data. This pipeline served Stanford Clinical Genomics Service (CSGS) pilot. 

Prior to joining SCGPM, Amin was post-doctoral researcher at the Ontario Institute for Cancer Research (OICR) working on prostate cancer biomarker discovery. Prior to OICR, Amin was a post-doctoral fellow at University of Toronto where he focused on annotations of genetic variations. Prior to his bioinformatics stint, he was a pukka Signal Processing engineer. He was (Sr.) R&D Engineer at Evertz Microsystems and Digital Rapids Corp working on video compression and codec technologies. He has a PhD in Electrical and Computer Engineering from McMaster University, Canada.

Mingjie Wang, PhD

2015-2016: Mingjie was our Microbiome Bioinformatician at SCGPM embedded with Ami Bhatt's lab. Mingjie received his PhD in Bioinformatics from Indiana University Bloomington, where he worked with Prof. Yuzhen Ye on metagenomics and next generation sequencing. Prior to joining the SCGPM, he worked at Stanford with Dr. Michael Snyder and his iPoP team to analyze accuracy of some of the best practice tools and methods for various types of metagenomic samples. 

After SCGPM, Mingjie joined Synthetic Genomics as a bioinformatics scientist.

Alexander Wong, BS

2010-2013: Alex was one of our earliest engineers managing the data submissions to the ENCODE project.  He designed and developed ChIP-seq antibody validation pipelines which used motif discovery and alignment algorithms.  He also created the SNAP system, a web-based analysis tool and data repository for functional genomics analyses.  Alex got his BS in Bioinformatics at UC Davis.

Philip Cayting, BS

2010-2013: As a Software Engineer at SCGPM, Philip developed a high-throughput pipeline for scoring chromatin IP genomic sequencing (ChIP-Seq) results for one of the largest production centers of the ENCODE consortium (then in phase 2) and performed standardized analysis. Prior to joining SCGPM, Philip was a Programmer at at Gerstein Lab at Yale where he analyzed, mined and wrangled pseudogenes. Philip has a BA in Applied Mathematics from UC Berkeley.

After SCGPM, Philip joined Syapse as a Software Engineer.