Embedded Files
About Me
About Me
I am a graduate student in Industrial Engineering and Operations Research at University of Massachusetts Amherst. Currently, I am doing a research internship at Stanford Graduate School of Business.
I am passionate about predictive modeling, data analysis and machine learning.
My Master's thesis is on development of a novel algorithm for predicting infectious disease spread using social network and graph theory.
Education
Education
M.S. Industrial Engineering and Operations Research, University of Massachusetts Amherst, 2015 - Present
B.A. Statistics and minor in Computer Science, Mount Holyoke College 2011-2015
Experience
Experience
Graduate Research Intern, Stanford Graduate School of Business, Jul 2018 - Dec 2018
Graduate Research Intern, Stanford Graduate School of Business, Jul 2018 - Dec 2018
Conducted statistical analysis in heterogenous treatment effect for implementing personalized survey and developed a web application for the survey.
Graduate Research Assistant, University of Massachusetts Amherst, Sep 2015 - Jul 2018
Disease Prevention and Prediction labGraduate Research Assistant, University of Massachusetts Amherst, Sep 2015 - Jul 2018
Worked on infectious disease simulation model and numerical validation of mathematical model of cancer parameterization.
Graduate Teaching Assistant, Mechanical and Industrial Engineering Department at UMass Amherst, Fall 2017
MIE 353 Engineering Economics Decision MakingGraduate Teaching Assistant, Mechanical and Industrial Engineering Department at UMass Amherst, Fall 2017
Facilitated and assessed student learning in individual group settings, and graded student exams. Gave a guest lecture on the chapter Effects of Inflation, and conducted multiple exam review sessions.
Undergraduate Research Intern, Center for Disease Control and Prevention, Summer 2014
The Division of Tuberculosis EliminationUndergraduate Research Intern, Center for Disease Control and Prevention, Summer 2014
Replicated results of a highly influential paper that models to assess the likely impacts of various diagnostic techniques for Tuberculosis control.
My work
My work
Publication
Publication
Chaitra Gopalappa, Jiachen Guo, Prashant Meckoni, Buyannemekh Munkhbat, Carel Pretorius, Jeremy Lauer, André Ilbawi, and Melanie Bertram. "A Two-Step Markov Processes Approach for Parameterization of Cancer State-Transition Models for Low-and Middle-Income Countries." Medical Decision Making 38, no. 4 (2018): 520-530.
Graduate Projects
Graduate Projects
Machine Learning
Non-linear Programming
Undergraduate Projects
Undergraduate Projects
Predicting Wine Quality by Rating Analysis - Applied the Neural Networks, SVM, and Logistic Regression to classify 1599 red wine data. Used MATLAB and R. Machine Learning class project - Fall 2014.
Assessing Gross Sales for Online Shopping Website - Studied the relationship between gross sales of the online shopping website and individual customer’s on-site behavior using 12802 users’ data. Used R. Applied Regression Methods class project - Fall 2014
Efficiency of Traffic Rules: Observing Outcomes at the Macro and Micro Levels - The Mathematical Contest in Modeling - February 2014
Talks
Talks
INFORMS 2017 - Austin, TX (A presenter, session chair)
LEAP symposium is Mount Holyoke's premier showcase of student summer work, organized by and for Mount Holyoke students. It hold on October 17, 2014, 12:00pm-6:00pm, Kendade Atrium at Mount Holyoke College.
Google Sites
Report abuse