OBJECTIVE

Adaptable and quick-learning professional seeking a role to contribute to a dynamic team with problem-solving skills and effective collaboration.

EDUCATION

COURSES & CERTIFICATES

  • Complete Machine Learning With R Studio - ML for 2025 -Udemy
  • Descriptive Statistics With R Software - NPTEL
  • Introduction to Biostatistics - NPTEL
  • Biostatistics and Design of Experiments -NPTEL
  • Essentials Of Data Science With R Software - 2_ Sampling Theory And Linear Regression Analysis -NPTEL
  • Tidymodels in R: Building tidy machine learning models - Coursera
  • Google Cloud Big Data and Machine Learning Fundamentals -Coursera
  • Predictive Modeling, Model Fitting, and Regression Analysis -Coursera
  • Linear Regression For Business Statistics -Coursera
  • R Programming -Coursera
  • Data Visualization With R -Coursera
  • Data Analysis with R Programming -Coursera
  • Excel for Beginners -Great Learning
  • Python Course For Beginners With Certification Mastering the Essentials - Scaler
  • SQL for Beginners : Learn SQL using MySQL and Database Design Course -Scaler
  • Elements Of AI -University of Helsinki

PROJECTS

  • Statistical Study on Vital Reports

    Abstract: Analyzing the relationship between age of death for region and gender, and predicting future birth and mortality rates by region.

    Tools: R programming , SPSS , Jamovi , Excel

    Result: There is A strong relationship between age of death for region and gender , the birth rate and Mortality rate are slowly increasing in future

  • Optimizing Diabetes Management : A Predictive Approach to Medication Effectiveness

    Abstract: This project evaluates the effectiveness of Metformin, Glipizide, and Sitagliptin in managing blood glucose levels in Type 2 Diabetes patients over 8 weeks. Using ARIMA models on synthetic data, it forecasts blood glucose trends, identifies Glipizide as the most effective, and provides model accuracy metrics.

    Tools: R Programming

    Result: Our study found Glipizide to be the most effective in reducing blood glucose levels in Type 2 Diabetes patients, with a total reduction of 24.5. The ARIMA model reliably predicted glucose normalization within 10 weeks, with MAE of 6.75 and RMSE of 6.76. This emphasizes the value of data-driven approaches in diabetes management.

  • Bangalore Traffic Prediction

    Abstract: This project analyzes Bangalore’s traffic patterns to identify months with the highest traffic volume and predict future trends. It explores the relationship between average speed and congestion levels, showing how weather impacts speed and traffic volume. These insights aim to aid in effective traffic management and planning.

    Tools: R Programming

    Result: The analysis shows Bangalore’s traffic volume is highest on Wednesdays and peaks in June. Increased average speed reduces congestion, while adverse weather lowers speed, increasing traffic volume. Without intervention, traffic is expected to rise rapidly, highlighting the need for effective management strategies.

  • Enhancing Leukemia Detection With Machine Learning And Statistical Analysis

    Abstract: This study aims to develop highly optimized statistical and machine learning models for accurate leukemia prediction by fine-tuning hyperparameters through iterative methods. It also seeks to identify the best-performing model based on predictive accuracy and analyze key variables influencing leukemia status using feature importance or model coefficients.

    Tools: R programming , Jamovi

    Result: To reduce leukemia risk and improve early detection, individuals with family history or genetic risk should undergo regular screenings. Lifestyle changes, close monitoring of abnormal WBC counts, and public health awareness can aid prevention. More research is needed on socioeconomic and environmental impacts on leukemia development.

  • A Statistical And Machine Learning Approach To Early Detection And Affected Area Prediction In Neuromuscular Disorders

    Abstract: This study aims to explore the interplay between treatment adherence, disease severity, and patient outcomes in neuromuscular disorders. It investigates how clinical and treatment factors influence disease progression and patient strength, while evaluating various machine learning models to identify the most effective one for early-stage diagnosis. The best-performing model will be assessed and validated using ROC and AUC values to predict disease stages and major health issues, supporting more accurate diagnosis and treatment.

    Tools: R programming , Jamovi , Excel

    Result: This study explores how treatment adherence, disease severity, and patient outcomes interact in neuromuscular disorders, emphasizing the need for holistic, personalized care. It highlights the power of machine learning models like CatBoost and Random Forest to improve early detection, predict major health issues, and optimize treatment strategies. The findings stress the importance of continuous monitoring, tailored interventions, and further model validation to enhance long-term patient outcomes.

INTERNSHIP

Company Name : SIMA (South Indian Mill Association)

Role: Data Analyst

Duration: July-August 2022 & July -2024

SKILLS

  • Programming Languages: R , Python , SQL

  • Tools and Software: MS-Office, Excel, R-Studio, SPSS, SYSTAT, Jamovi, Latex

  • Version Control: Git , GitHub

AWARDS & ACHIEVEMENTS

  • BASIC LIFE SUPPORT AND RECOVERY POSITION–Voluntary work in the ’WORLD RECORD EVENT UNDER ASIA BOOK OF RECORDS’

    Year : 2023

  • Participated in Nova Nordisk Symposium for Innovative and Applied Statistics

    Year: June–2024 & July–2024

INTERESTED AREA

  • Analysis
  • Estimation
  • Coding

LANGUAGES KNOWN

  • Tamil
  • English
  • French

HOBBIES

  • Story Editing
  • Chess