Sachet A. Shukla, Ph.D.
Department of Hematopoietic Biology & Malignancy
Department of Immunology
Director of Computational Biology, ECLIPSE
Director, HBM Cancer Vaccine Program
Tejas Jammihal, M.B.
Tejas is a computational biologist who graduated from Indian Institute of Technology, Madras with a degree in biological engineering and went on to receive a master’s degree in biotechnology at the Pennsylvania State University. He performed his master’s research at Novartis Institute of Biomedical Research, to create transcriptional signatures of response to smoking in preclinical mouse models. Following this, he worked as a Bioinformatics Analyst at Dana-Farber Cancer Institute under the direction of Dr. Toni Choueiri. Here, his projects focused on identification of genomic and transcriptomic determinants of response and resistance to immune checkpoint inhibitors in ccRCC. At the Shukla Lab, his work is focused on the multi-omics analysis of hematopoietic malignancies, and association with clinical outcomes. Outside of work, Tejas enjoys traveling, photography and all things food.
Chunlei Yu, M.S.
Chunlei is a computational biologist with a master’s degree in bioinformatics from the Chinese Academy of Sciences, Beijing Institute of Genomics in September 2017. Chunlei previously worked at Ziopharm as a Bioinformatics Scientist, which provided her with extensive experience in analyzing sequencing data from cancer patients. As an associate computational scientist in the Hematopoietic Biology and Malignancy department, her ongoing research studies focusing on antigen discovery through computational methods.
Arnau Peris Cuesta, M.B.
Associate Computational Scientist
Arnau graduated from University of Bologna and received his international Msc in Bioinformatics, completing his thesis research in the CSIC (Parc Cientific, Valencia, Spain). He studied the design of co-expression networks for regulatory pathways by using transcriptomic profiling. After his Msc, he joined YourBiome Therapeutics (Lisbon, Portugal) where he led the construction of a machine learning predictor for clinical response to COVID19 based on the patient's gut microbiome. In the Shukla’s lab, he is building a model for predicting neoantigens quality and tumor fitness while generating different pipelines for NGS approaches.
Juan Gallegos, M.S.
Pappanaicken R Kumar, Ph.D.