I am a PhD student at Columbia University in the Department of Biomedical Informatics, interested in using artificial intelligence and biomedical data for causal inference and predictive analysis.
I graduated with honors from Barnard College in May 2020 with a degree in Computer Science and Asian and Middle Eastern Cultures.
Education
Columbia University, Department of Biomedical Informatics | September 2020-present
PhD in Biomedical Informatics
Barnard College of Columbia University | September 2016-May 2020
B.A. in Computer Science and Middle Eastern and Asian Cultures
Publications and Preprints
Anand TV,
Ribeiro AH, Tian J, Bareinboim E. Effect Identification in Cluster Causal Diagrams. Published online February 22, 2022.
Garcia SM. Determining user segmentation based on a photo library. (U.S. Patent No. 11,036,786). U.S. Patent and Trademark Office.
Conference Presentations and Posters
Anand TV,
Suchard MA, Hripcsak G. Reproducibility in comparative effectiveness and safety of ACE inhibitors and thiazides for modified monotherapy treatment criteria. To be presented at: American Medical Informatics Association 2022 Annual Symposium; 2022 Nov 5-9; Washington D.C. [Poster] a photo library. (U.S. Patent No. 11,036,786). U.S. Patent and Trademark Office.
Bear Don’t Walk IV O, Pichon A, Volpe S, Liu LG, Desai PM,
Anand TV,
Richter L, Schiffer K, Massey B. A Workshop to Build a Research Agenda for Justice Informatics. To be facilitated at: American Medical Informatics Association 2022 Annual Symposium; 2022 Nov 5-9; Washington D.C. [Workshop]
Desai PM,
Anand TV,
Mamykina L. Towards Personalized Meal Recommendations for Type II Diabetes Self-Management. Presented at: National Library of Medicine Informatics Training Conference; 2022 June 22-24; Buffalo, NY. [Poster,
Finalist for Best Poster
]
Desai PM*,
Anand TV*,
Mamykina L. MedMessages: A Chatbot for Chemotherapy Management and Symptom Reporting. Presented at: American Medical Informatics Association 2021 Annual Symposium; 2021 Oct 30-Nov 3; San Diego, CA, NY. [Podium Presentation,
Finalist for Student Design Challenge
]
Anand TV,
Liu C, Chung WK, Weng C. Characterization of Dispersed Rare Disease Phenotypes in EHR Narratives. Presented at: National Library of Medicine Informatics Training Conference, 2021 June 21-23; Online. [Tech Talk Presentation]
Anand TV,
Wallace BK, Chase HS. Prevalence of Potential Multi-Drug Interactions in Ambulatory Patients. Presented at: American Medical Informatics Association 2020 Annual Symposium; 2020 Nov 14-18; Online. [Poster]
Research and Work Experience
Undergraduate Researcher, Clare Boothe Luce Scholar | May 2019-June 2020
Department of Biomedical Informatics, Columbia University Medical Center, New York NY
Researching physician prescribing behaviors through analysis of patient electronic health records and databases from the Observational Health Data Science and Informatics distributed data network standardized to a common data model
Performed network analysis on graphical representations of patient prescriptions and drug interactions
Leveraged RxNorm and other drug databases to map interactions to classes
Developed algorithms in Python and MySQL to reconcile drug-use timelines, identified concurrent use with >2 day overlap and mapped to clinical decision support alert system’s DDI database to determine prevalence and DDI severity
Undergraduate Researcher | September 2018-May 2019
Programming Systems Lab, Columbia University, New York NY
Implemented control-flow analysis in HitoshiIO, a behavioral-code-similarity detector for Java methods
Researched performance of different similarity metrics, de-compilers, and methods of data-flow and control-flow analysis
Computer Scientist Intern | May 2018-August 2018
Adobe Systems, San Jose, CA
Researched methods of gathering insights for user segmentation
Wrote algorithms to analyze associations between image metadata and user characteristics
Developed novel method of utilizing supervised ML algorithms that preserve privacy by localizing sensitive information to a user’s device
Developed iOS App in Swift to process image metadata from users’ photo library and highlight significant images
Patented research “Determining User Segmentation Based on a Photo Library”, U.S. Patent No. 11,036,786
Data Science/Computer Science Intern | May 2017-August 2017
IBM, North Castle, NY
Investigated generating standardized, accurate labels for large datasets through training machine learning NLP models in Watson Knowledge Studio and BlueMix’s Natural Language Classifier
Created an ontology to eliminate redundancies and stratify potential labels within logical groups, establishing the type system for the NLP model
Developed a structured pipeline for integrating feedback from subject matter experts into the NLP model
Developed a dashboard to analyze project metrics in NodeRED
Student Researcher | June 2015-August 2015
Medical University of South Carolina, Charleston, SC
“Gene x Environment Interactions in Systemic Lupus Erythematosus: Polymorphisms in ITGAM and Smoke Exposure among African Americans”
Evaluated associations between two single nucleotide polymorphisms in the gene ITGAM and passive exposure to smoke during childhood in a population of African-American women with systemic lupus erythematosus
Performed polymerase chain reaction tests
Teaching Experience
Computational Methods: Machine Learning for Healthcare
[Graduate]
Teaching Assistant | Spring 2023
Department of Biomedical Informatics, Columbia University, New York, NY
Computing in Context: Health Policy and Management
[Graduate]
Teaching Assistant | Fall 2022, Fall 2021
Mailman School of Public Health, Columbia University, New York, NY
Research Methods: Analysis for Large Scale Datasets
[Graduate]
Teaching Assistant | Spring 2022
Mailman School of Public Health, Columbia University, New York, NY
Symbolic Methods
[Graduate]
Teaching Assistant | Fall 2021
Department of Biomedical Informatics, Columbia University, New York, NY
Big Data, Machine Learning, and Their Real World Applications
[High School]
Teaching Assistant & Lecturer| Summer 2020
Pre-College Programs, School of Professional Studies, Columbia University, New York, NY
Data Structures and Algorithms
[Undergraduate]
Teaching Assistant | Spring 2020, Summer 2019
Department of Computer Science, Columbia University, New York, NY
Introduction to Computer Science in Java
[Undergraduate]
Teaching Assistant | Fall 2019
Department of Computer Science, Columbia University, New York, NY
Jumpstart for Aspiring Developers and Entrepreneurs
[Undergraduate]
Coordinator & Instructor | Winter 2019
Undergraduate Student Life, Columbia University, New York, NY
Girls Who Code
[High School]
Instructor | Summer 2018, Spring 2017
Adobe Systems, San Jose, CA & Girls Who Code, Columbia University, New York, NY
General Chemistry Lab
[Undergraduate]
Teaching Assistant | Fall 2017
Department of Chemistry, Barnard College, New York, NY