Summary
Overview
Work History
Education
Skills
Professional projects
Timeline
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Sharmilashree Vanniaperumal

Indianapolis,IN

Summary

Enthusiastic and detail-oriented Health Care Data Analyst with a strong passion for leveraging data to improve healthcare outcomes. Experienced in working on projects involving machine learning and natural language processing to analyze and interpret complex healthcare data.

Overview

1
1
year of professional experience

Work History

Graduate Research Assistant

Luddy School Of Informatics- Indiana University
01.2024 - 05.2024
  • Conducted comprehensive research on current AI technologies in mental health, specifically focusing on applications for dementia, anxiety, and depression.
  • Analyze extensive datasets from mental health studies to evaluate the effectiveness of existing robotic AI solutions.
  • Identify patterns and trends in data related to patient outcomes.
  • Prepared detailed reports and visualizations to communicate findings and recommendations to stakeholders.

Data Management Intern

Kasturba Medical College, Manipal University
01.2023 - 07.2023
  • Observe and document patient flow and hospital functions
  • Assist the Medical Records Department (MRD) in organizing and managing medical records.
  • Monitor and analyze inflow and outflow records within the hospital to ensure accurate and timely data capture.
  • Track and report on daily schedules, ensuring all activities are documented and discrepancies are addressed.
  • Support data entry, validation, and management tasks to maintain the integrity of hospital records.
  • Conduct data analysis to identify trends, patterns, and areas for improvement in hospital operations and patient flow.

Education

Masters in Health Informatics

Luddy School of Informatics
Indianapolis, IN
12.2024

Bachelor of Dental Surgery

SRM Dental College
Chennai,India
12.2021

Skills

Languages :Python,SQL,R,HTML,CSS

Frameworks : Pandas,numpy,pytorch,scikit- learn,Matplotib

Tools : Powerbi,Excel,powerpoint,MySQL

Platforms :Pycharm,Jupyter notebook,Visual studio code,spyder notebook

Professional projects

Predictive Modeling for Autism Spectrum Disorder  Sep2023-Oct2023

                                                                       

  • Developed predictive models using Logistic Regression, SVM, KNN, and Random Forest algorithms to predict autism spectrum disorder.
  • Achieved a predictive accuracy of 99%.
  • Technologies: Google Colab, Jupyter, MATLAB, Seaborn, TensorFlow, Python.

Homicide Data Analysis  Oct2023-Nov2023

  • Conducted an in-depth analysis of homicide data and developed a Decision Tree Classifier.
  • Achieved a predictive accuracy of 96%.
  • Technologies: Google Colab, Jupyter, MATLAB, Seaborn, TensorFlow, Python.

Machine Learning Project: Predicting Diabetes Status  Nov2023-Dec2023  

  • Analyzed lab results from Iraqi patients using 12 machine learning models.
  • Top performers were Random Forest, XGBoost, and Bagging Classifier, achieving 99% accuracy.
  • Technologies: Google Colab, Jupyter, MATLAB, Seaborn, TensorFlow, Python.

Predicting Significant Variables for Diabetes Nov2023-Dec2023

  • Employed statistical methods and non-parametric testing to identify influential factors for diabetes.
  • Technologies: RStudio, Data Visualization.

BERT-based Text Classification Project     Jan2024-March2024

  • Implemented a BERT-based classifier for sentence classification on the IMDb dataset.
  • Fine-tuned the model to achieve high performance metrics in sentiment analysis.
  • Technologies: Python, PyTorch, Hugging Face’s Transformers Library, BERT.

Predicting Drug-Target Interactions Using Language Models  Jan2024-May2024

  • Developed a Siamese Neural Network model using SMILES and amino acid sequences to predict drug-target interactions.
  • Achieved an AUROC of 0.8777 and an AUPRC of 0.6922.
  • Technologies: Python, PyTorch, ChemBERTa, ProtBERT, Neural Networks.NLP

Predictive Model for Alzheimer’s Disease         Jan2024-Feb2024

  • Created machine learning models to classify stages of Alzheimer’s disease using demographic, clinical, and neuroimaging data.
  • Achieved accuracies up to 91.70% with models like Random Forests.
  • Technologies: Python, Scikit-Learn, Pandas, NumPy, Matplotlib, Seaborn.

Text Classifier Development for NLP        Jan2024-Feb2024

  • Developed a neural network-based text classifier using a Deep Averaging Network (DAN).
  • Achieved a benchmark accuracy of 92.24% on development data.
  • Technologies: Python, PyTorch, NumPy.



Timeline

Graduate Research Assistant

Luddy School Of Informatics- Indiana University
01.2024 - 05.2024

Data Management Intern

Kasturba Medical College, Manipal University
01.2023 - 07.2023

Masters in Health Informatics

Luddy School of Informatics

Bachelor of Dental Surgery

SRM Dental College
Sharmilashree Vanniaperumal