Vivek Gopalakrishnan

Graduate Research Assistant @ Massachusetts Institute of Technology

About

I am a PhD student in Medical Engineering and Medical Physics at the Harvard-MIT Program in Health Sciences and Technology. My current research interests lie in the development of machine learning methods for the diagnosis and treatment of cardiovascular disease. My past research has focused on the development of computational methods to analyze multi-subject neuroimaging and cardiovascular data. Most recently, I developed statistical graph theory algorithms to perform biomarker discovery in network-valued maps of the brain (advised by Dr. Joshua T. Vogelstein and Dr. Carey E. Priebe). I also led a Design Team of undergraduate biomedical engineers to build a dynamic fusion image guidance system for minimally invasive heart surgery (advised by Dr. Elizabeth Logsdon and Dr. Rani Hasan).

Country

United States

City

Lexington

Industry

Research

Skill

Public Speaking, Python, Machine Learning, Research, LaTeX, Git, Leadership, Teaching

Experience

Graduate Research Assistant

Massachusetts Institute of Technology

2021-9 - Present · 5 yrs 1 mo

Design Team Leader

The Johns Hopkins University

2020-1 - 2021-6 · 1 yr 6 mos

Led a team of eight undergraduate biomedical engineers. Used deep learning, digital signal processing, and image registration techniques to develop an intraoperative image guidance system for minimally invasive cardiac surgery. Advised by Dr. Rani Hasan, Department of Interventional Cardiology, Johns Hopkins Medical Institute and Dr. Elizabeth Logsdon, Department of Biomedical Engineering, Johns Hopkins University.

Undergraduate Reseacher @ Neurodata

The Johns Hopkins University

2018-9 - 2021-6 · 2 yrs 10 mos

Baltimore, Maryland

Developed machine learning and statistical graph theory algorithms for multi-subject neuroimaging data to perform biomarker discovery in network-valued maps of brain connectivity. Advised by Dr. Joshua Vogelstein and Dr. Carey Priebe, Center for Imaging Science, Department of Biomedical Engineering, Johns Hopkins University

Teaching Assistant

The Johns Hopkins University

2020-8 - 2021-5 · 10 mos

Linear Algebra - Fall 2020 Computational Cardiology Lab - Fall 2020 Neuro Data Design - Fall 2020, Spring 2021 Responsible to teaching weekly recitations, grading homework/exams, and advising projects for about ~250 students across all classes.

PILOT Leader

The Johns Hopkins University

2018-8 - 2020-5 · 1 yr 10 mos

Baltimore, Maryland, United States

Head PILOT Leader for Linear Algebra. Responsible for teaching weekly problem solving sections with 10 students, and leading a team of 5 junior Linear Algebra PILOT leaders.

Summer Research Assistant

Ragon Institute of Mass General Brigham, MIT, and Harvard

2018-5 - 2018-8 · 4 mos

Cambridge, Massachusetts

Developed predictive models of HIV treatment outcomes using classical biostatistics methods (Cox PH model, logistic regression, Lehmann ROC analysis).

Summer Intern

Fondazione Bruno Kessler - FBK

2017-6 - 2017-7 · 2 mos

Trento, Italy

A special award at the 2017 Intel International Science and Engineering Fair (ISEF) allowed me to participate in a summer internship at FBK in Trento, Italy. I worked as a member of an international team of 20 students to design technological innovations in the field of digital agriculture. We mounted spectral cameras and spectrophotometers on drones to create autonomous data collection vehicles. Using a convolutional neural network, we created predictive tools that accurately predicted fruit ripeness and agricultural yield from images and spectrogram.

Independent Researcher

Tufts University

2016-6 - 2017-5 · 1 yr

Greater Boston Area

Conducted an independent next-generation sequencing (NGS) study to determine the impact of flossing on the health of the oral microbiome (as a senior in high school). Won 2nd place in microbiology at the Intel International Science and Engineering Fair 2017.