Analyst Intern Machine Learning

SHRAVANI CHITINENI

919-***-**** ***********@*****.*** LinkedIn

OBJECTIVE Biostatistician broadly interested in data science and expanding modeling skills. This includes seeking opportunities outside of biomedical and public health. Research experience utilized R and SAS for statistical analysis and predictive modeling using machine learning techniques. EDUCATION

University of North Carolina at Chapel Hill Excepted Summer 2023 M.S. in Biostatistics

Capstone M.S. Paper: “Predicting Obesity in Children Aged 6-19 Years using Machine Learning Techniques” Relevant Coursework: Introduction to Survival Analysis, Introduction to Statistical Computing and Data Management, Intermediate Linear Models, Working with Data in a Public Health Research Setting, Analysis of Categorical Data, Applied Analysis of Longitudinal Data, Epidemiology, Intro to Public Health Hollins University, Roanoke, Virginia May 2021

B.S. in Biology, Minors in Mathematics and Chemistry 3.92 / 4.0 GPA Summa Cum Laude, Phi Beta Kappa, Chi Alpha Sigma, Biology Departmental Honors Senior Thesis: “Use of LYMESIM 2.0 to assess the potential for single and integrated management methods to control blacklegged ticks (Ixodes scapularis; Acari: Ixodidae) and transmission of Lyme disease spirochetes” Relevant Coursework: Data Wrangling, Regression Analysis, Machine Learning, One Health, Wildlife and Disease, Ecology, Cellular and Molecular Biology, Human Physiology, Developmental Biology, Biochemistry QUALIFICATIONS & SKILLS

• Programming (descending in order of proficiency): SAS, R, LaTeX, STATA, SQL, Python and HTML

• Analysis Techniques: regular expressions, data cleaning, deriving variables, web scraping, metadata analysis, random sampling, simulations, hypothesis testing, creating codebooks, random sampling, hypothesis testing, random forest regression, gradient boosting regression, LASSO/Ridge regression, Principal Component Analysis

• Language: proficient-native Telugu speaker, basic understanding of conversational Hindi and Spanish

• Certification: Human Biomedical Research IRB Certification, Collaborative Institutional Training Initiative

(CITI) Program, August 2021 - August 2024

RESEARCH EXPERIENCE

Graduate Statistical Consultant March 2023 – May 2023 University of North Carolina at Chapel Hill

Principal Investigator: Dr. Wei-Tang Chang and Dr. Kelly Sullivan Giovanello (Co-PI)

• Group research consulting project completed through Statistical Computing and Data Management class

• Post-processed and appropriately visualized messy, real-world fMRI data collected by the Cognitive Neuroscience of Memory Lab (CNML) and Biomedical Research Imaging Center (BRIC) at UNC-CH

• Completed systematic review of functional activity of different regions of the human brain to inform hypothesis testing to cleaned data

• Determine appropriate mixed-effects regression model to deal with repeated measures data and determine which hippocampal region has most activity given various memory tasks Student Led Research March 2023 – May 2023

University of North Carolina at Chapel Hill

Chapel Hill, NC

• Utilized open-source Kaggle Heart Failure Prediction Dataset to build classification regression utilizing various machine learning techniques including LASSO regression and random forest methods

• Data was standardized and visualized to determine data imbalance; data were cleaned, and missing values were imputed using missForest R package

• Models were trained, validated using 10-fold cross validation to tune hyperparameters; tested with unused dataset and models were evaluated using AUC values Student Fellow May 2020 – May 2021

Hollins University

Roanoke, VA

Principal Investigator: Dr. Elizabeth Gleim

• Coded, debugged, and ran LYMESIM 2.0 model in R to simulate population dynamics of black legged ticks under various environmental conditions

• Completed systematic review of reference material to identify pertinent field research results into model

• Organized, cleaned model's simulated data to visualize long-term population trends and applied appropriate statistical models to compute output significance

• Defended and published honors thesis, including public health significance and projected population trends Epidemiology Intern January 2020

CDC Division of Reproductive Health (DRH)

Atlanta, GA

Supervisor: Brenda Bauman

• Analyzed Pregnancy Risk Assessment Monitoring Systems (PRAMS) novel disability surveillance data to provide population-based prevalence estimates of disability and functional limitations among pregnant and parenting women by state

• Programmed and formatted new macro variables for analysis on SAS reflecting newly collected surveillance data

• Examined relationship between various levels of disabilities and race and socioeconomic outcomes by state; produced applicable data listings and tables

Summer Institute of Biostatistics (SIBS) Student June-July 2019 Emory Rollins School of Public Health

Atlanta, GA

Mentor: Dr. Reneé Moore

• Completed case studies focused on the identifying the effectiveness of suPAR as a biomarker for chronic kidney disease (CKD) and whether suPAR levels indicate associated with risk of developing CKD

• Gained experience using statistical software such as ArcGIS, R and SAS (including macros language) evaluating clinical trial cases study data

• Applied advanced statistical analysis methods, i.e., linear regression, logistical modeling, survival analysis and risk prediction modeling

Policy Research Analyst Intern January 2019

CDC’s Policy, Research, Analysis, and Development Office (PRADO) Atlanta, GA

Supervisor: Dr. Diane Hall

• Conducted independent research on the Tax Cuts and the Jobs Act of 2017 and determined possible adverse public health effects

• Focused on implications of “opportunity zones” and the possibility of gentrification and displacement of low-income families

• Successfully presented findings at PRADO monthly presentations LEADERSHIP

Director of BUSI 2023

University of North Carolina

Chapel Hill, NC

Student led Organization

• Coordinated communication between faculty mentors within the Biostatistics department and interested undergraduate students looking to conduct research

• Disseminated information regarding application and appropriately matched student interests to professors offering internship/research opportunities

• Planning a poster session for participating students to share research, and foster collaboration PUBLISHED WORK

Chitineni, S. (2023). Predicting Obesity in Children Aged 6-19 Years using Machine Learning Techniques. https://cdr.lib.unc.edu/concern/masters_papers/bv73c911g Chitineni, S., Gleim, E. R., Gaff, H. D., "Use of LYMESIM 2.0 to assess the potential for single and integrated management methods to control blacklegged ticks (Ixodes scapularis; Acari: Ixodidae) and transmission of Lyme disease spirochetes" (2021). Undergraduate Honors Theses, Hollins University. 31. https://digitalcommons.hollins.edu/ughonors/31

PRESENTATIONS

April 2021 Use of LYMESIM 2.0 to assess the potential for single and integrated management methods to control blacklegged ticks (Ixodes scapularis; Acari: Ixodidae) and transmission of Lyme disease spirochetes

Southeastern Society of Parasitologists

Hollins University Science Seminar

April 2019 Examining Questing Behavior of Blacklegged Ticks Hollins University Science Seminar

Contact this candidate