Had a great time talking about my research, life as a postdoctoral research scientist, and the joys of mentoring young researchers in a Q&A with Rice’s Data to Knowledge (D2K) lab. The D2K lab provides several experiential data science courses, tailored towards building real-world data science skills. I have had a wonderful time mentoring a team of young undergraduate/1st year grad students, who won 1st prize in the fall and 2nd prize in the spring in the D2K showcase event. The full interview can be found here.
Our abstract titled A Novel Algorithm For Early Detection Of Junctional Ectopic Tachycardia In Patients With Congenital Heart Disease’ has been accepted as a poster at the prestigious 10th congress of the World Federation of Pediatric Intensive and Critical Care Societies (WFPICCS20). This work was done with a team I mentored as part of the D2K learning lab and Dr. Parag Jain at Texas Children’s Hospital. We have developed a framework for early detection of junctional ectopic tachycardia, a common form of cardiac arrhythmia in children who have had heart surgery. This framework can help clinicians respond quickly and administer life-saving treatment to patients in JET, whilst also reducing false alarms.
Thrilled to announce that I have been chosen for a Seed Fund award by PATHS-UP (https://pathsup.org/). PATHS-UP, or Precise Advanced Technologies and Health Systems for Underserved Populations , is a NSF funded engineering research center that aims to reimagine healthcare of underserved populations by developing revolutionary and cost-effective technologies and systems at the point-of-care. My award, in collaboration with the prestigious Sansum Diabetes Research Institute (SDRI), will aim to derive novel insight and prognostic biomarkers from glucose time-series data from a low-income cohort of diabetes and pre-diabetes participants.
More information here: https://pathsup.org/2020-paths-up-innovation-seed-fund-winners/
Really grateful to get the opportunity to co-teach DSCI 303: Machine Learning for Data Science in tandem with Dr. Akane Sano. We tried to teach fundamental ML concepts and techniques from a conceptual, less math-y framework. The students worked on several exciting projects in the domains of healthcare, entertainment, and even gaming!
I officially started a postdoctoral research scientist position at Rice’s Scalable Health labs under Dr. Ashutosh Sabharwal on August 1. I look forward to continuing my work in using machine learning, signal processing, and statistics to find clinically meaningful signatures in medical imaging and sensor data. I am especially excited to be focusing more on pediatric disorders, and looking to contribute to the nascent field of computational pediatrics!
I graduated with my Ph.D. from Rice University! Could not have been possible without my advisers, mentors, colleagues, amazing friends, and my loving family!
Work we did with Dr. Sangeetha Reddy and Dr. Jennifer Wargo to analyze the spatial relationships amongst various cell types in IBC is published in Cancer Immunology. Inflammatory breast cancer (IBC) is an aggressive form of primary cancer with low rates of pathologic complete response to current neoadjuvant chemotherapy (NAC) regimens. Our spatial analysis framework showed the close proximity of mast cells to CD8+ T cells, CD163+ monocytes/macrophages, and tumor cells when a pathologic complete response was not achieved. The proximity of mast cells to immune and tumor cells may suggest immunosuppressive or tumor-promoting interactions of these mast cells, and these can be a potential therapeutic target in IBC. Read more here: http://cancerimmunolres.aacrjournals.org/content/7/6/1025.abstract
Image courtesy Dr. Sangeetha Reddy
It is finally done! I defended my Ph.D. thesis on March 20, 2019. Big thank you to my advisor Dr. Arvind Rao and my committee chair Dr. Ashok Veeraraghavan for their invaluable support, guidance, and mentorship during the last five and a half years. Thanks to all my friends and family, without whom this day would not have been possible. 🙂
In this paper, we propose a co-localization metric derived from the G-function and show that this metric is significantly correlated with adverse tumor signatures, such as larger tumor size, increased vascular density, and greater depth of invasion. Pre-print to be uploaded soon! This work was done in collaboration with the wonderful Dr. Michael Tetzlaff from the Department of Pathology at the M.D Anderson Cancer Center.