About Me
Hello! I'm Pavan Bodanki, a passionate computer scientist with a diverse skill set spanning software development, data analysis, data science, and deep learning. I hold a Master's in Computer Science from the University of Georgia and a Bachelor's in Electronics, Computers, and Communication from Andhra University.
From an early age, I was drawn to logical reasoning and mathematics, and this interest naturally extended to programming when I was introduced to LOGO and basic C programming in the 8th grade. After a brief hiatus from coding during my high school years, I rekindled my passion for technology by pursuing certifications in programming. To my delight, I found that the foundational skills I had developed remained intact, which motivated me to further explore this field.
In college, I chose Electronics and Communications as my major, with a minor in Computer Science, to focus on the intersection of IoT and technology. This choice led me to work on several IoT projects and experiment with mobile applications and web development. It was during this time that I discovered my passion for machine learning and data science. I eagerly applied the concepts I was learning to real-world problems, integrating machine learning and AI in innovative ways.
My final year internship provided a valuable opportunity to experience the corporate environment, which was instrumental in shaping my professional journey. The pandemic prompted me to develop my finance and economics skills to enhance my data analysis capabilities. This journey took me to Thomson Reuters, where I worked on transitioning legacy projects to modern technologies like AWS and ETL pipelines. My role also involved analyzing user behavior data to improve web development outcomes, which deepened my interest in data-driven insights.
My passion for healthcare and data science led me to join ecology lab during my master’s program that focuses on disease forecasting. This role has been incredibly fulfilling as it allowed me to engage in a diverse range of activities—from web development to machine learning, statistical modeling, and MLOps. I continue to expand my knowledge and expertise in this field, driven by a genuine interest in using data science to make a meaningful impact in healthcare.
Beyond the technical realm, I have a keen interest in understanding market trends and researching public health. When I'm not immersed in code or data, you might find me traveling, exploring new cultures, and landscapes.
If you're interested in collaborating or just want to chat about the latest tech trends, feel free to contact me. You can also check out my projects on GitHub.
Education
University of Georgia (3.82/4)
AUG 2022 - AUG 2024
Masters, Computer Science.
Andhra University(9.02/10)
JUL 2016 - MAY 2020
Bachelor of Technology, Electronics ,Computers and Communication
Skills and Interests
Technical:
- Programming Languages: Python,JavaScript, TypeScript, R, SQL, Java, C, Rust
- Packages: NLTK, PySpark TensorFlow, PyTorch, BERT,OpenAI,Pandas, NumPy, Scikit-Learn, Matplotlib, Seaborn, Tidyverse,OpenCV
- Machine Learning: NLP,Computer Vision, Statistical Modeling, Bayesian Statistics, Ensemble Modeling,Forecast Modeling,Risk Modeling ARIMA, XGBoost, Random Forest, PCA,LSTM
- Databases & Web Development: MySQL, PostgreSQL, SQL Server, MongoDB, React.js, Angular, Node.js, Java Script, Spring Boot, HTML, CSS, JSP, Maven
- Data Analytics & visualizations: Tableau, SAS, PowerBI, Excel (vlookup, pivot tables), Airflow, ArcGIS, Leaflet, Plotly
- Tools & Platforms: AWS (EC2, Sagemaker, Lambda, S3, ECR, EMR,Glue), GCP, Git, Docker, Kubernetes,Azure,Jenkins,Postman ,SSMS ,SSIS,VS code ,Eclipse
- Other: Rshiny,R Markdown,GitHub, CI/CD, API Development,Apache arrow,Parquet,JSON, RESTful APIs, Agile methodologies, Data structures,System design,Jira
Interests:
- Research market trends,
- geographic information system (GIS)
- Traveling and
- Public health research
Ongoing Projects
Knee cartilage segmentation:
Developing an CNN model using deep learning techniques to analyze Knee-cartilage MRI scans and predict optimal timing for arthroscopic surgery in arthritis patients.
Flu forecast pipeline
Developing a scalable MLOps pipeline using Apache Arrow, AWS s3, Glue, lambda, and ECR for efficient model updates on the flu across US.
Experiences
University of Georgia - Research Data Scientist and software developer
OCT 2022 - Present
- Leveraged large language models (LLMs) to gather data on emerging infectious diseases (EID) from web sources and research papers for meta-analysis, reducing data collection time by 6 months.
- Conducted deep-dive analyses on global infectious diseases (1940-2023) using data science methods, providing pivotal insights.
- Developed interactive data visualizations in Tableau, guiding public health responses.
- Led DNN model development in TensorFlow to forecast disease spread across 114 countries.
- Architected a scalable MLOps pipeline using Apache Arrow, AWS s3, Glue, lambda, and ECR for efficient model updates.
- Created container image deploy my code in R environment using ECR in AWS and use lambda functions to draw data from John Hopkins.
- Pioneered advanced geospatial visualizations with Leaflet and Plotly and overhauled the EID database using PostgreSQL, enhancing data fidelity.
- Generated ad-hoc analyses and reports to support various research initiatives, providing timely and accurate insights for stakeholders.
- Consulted with internal and external stakeholders to interpret analysis results, offering expertise and guidance.
- Engineered a sliding ARIMA model for flu forecasting every 4 weeks, utilizing ensembling methods and stochastic gradient descent.
- Engineered and optimized the department's websites, achieving a 40% reduction in page-load times and designing responsive interfaces to enhance user engagement and accessibility.
- Directed full-cycle development of web platforms for pandemic prediction, ensuring robust functionality and real-time data processing.
- Developed a custom API for precise geocoding, improving health forecast accuracy, and created advanced geospatial visualizations for better data interpretability.
- Overhauled the EID database, enhancing data fidelity, and developed robust APIs for efficient data retrieval and updates.
- Developing new packages in R to handle S3 buckets from RStudio
****visualizations to be uploaded here soon****
Thomson Reuters - Data Analyst and Software Developer
NOV 2020 -JUL 2022
- Spearheaded agile full-stack development for Thomson Reuters through Tata Consultancy Services using Java, Spring, and React.js.
- Managed development cycles, maintaining separate environments for robust testing and addressed a critical log4j vulnerability within 48 hours, earning the 'Best Employee' award.
- Led database migrations to AWS using SSMS and AWS RDS, optimizing storage and accessibility.
- Developed an automated certificate generation system with end-to-end encryption and Optimized database schemas using SSMS, enhancing application support.
- Developed SQL queries and stored procedures for dynamic data retrieval, improving financial reporting processes.
- Led the development of data processing pipelines for large financial datasets, streamlining data analysis and enhancing reporting accuracy.
- Optimized database schemas using SQL Server Management Studio (SSMS), and managed tasks and projects using Jira for agile software development and requirements management.
- Authored stored procedures for dynamic data retrieval, reducing manual handling. Upgraded legacy systems for compatibility and security with modern practices.
- Implemented continuous integration and deployment using Jenkins, testing and deploying functionalities. Collaborated with senior management and cross-functional teams to address critical security issues.
Nielsen - Data Science Intern
JAN 2020 - MAR 2020
- Led data integration at Nielsen Holdings using SQL and ETL tools, streamlining processes and enhancing data accuracy for complex analyses.
- Utilized regression analysis, clustering, and time series forecasting in Tableau and Python to identify trends and provide actionable insights.
- Developed and deployed machine learning models to predict user demand, improving cache hit ratios by 40% and reducing data retrieval times.
- Implemented a pre-caching system(A/B testing) based on predictive insights, reducing load times by over 50% and improving system responsiveness.
- Created and refined business requirement documentation, aligning with organizational needs.
- Optimized SQL queries and upgraded infrastructure, reducing data processing times from days to hours.
Projects
Recommendation System:
Recommendation systems on movie streaming data
Movie Booking System:
Designed a full-stack website using ReactJs,Spring MVC and SQL
RUST crate:
Crafted a secure library(crate) for implementing graph algorithms using rust which so far has 1600+ downloads through the developer community.
Tennis match predictor:
Developed a web app that pulls real-time player statistics from Wikipedia.
Derived match predictions using SQL queries.
Smart India Hackathons(SIH):
SIH 2018-E-Governance application--Developed an Android app emphasizing offline functionality and end-to-end encryption using firebase and android studio.
SIH 2019-Cisco Meraki router--Customized Cisco Meraki router with splash page integration,video calling, and an nltk-powered chatbot.
Video detection and counting:
Built a model using deep learning techniques to determine the vehicles passing through a particular Region of interest area
Sarcastic review analysis:
Designed a LSTM-based deep learning model for sentiment analysis in eCommerce websites.
Predictive Analytics for Abnormality in blood pressure:
Using Machine Learning algorithms and data mining techniques, I created a model for predicting hypotension/hypertension.
Smart Bin:
Developed using nodemcu and integrated waste management through mobile application.
ECG signal in domain analysis:
Optimizing ECG signal analysis by adaptively compressing signals and applying advanced classification algorithms using a modified Inception Block and LSTM, enhancing both diagnostic efficiency and robustness
Certifications
- IBM data scientist specialization from Coursera.
- Gained cloud knowledge on GCP and AWS through certifications.
- Machine learning specialist certification through Coursera and Udemy.
Leadership & Activities
Indian Student Association-ISA
OCT 2022 - MAY 2024
Organized various events for the ISA
Spardha hackathon - Student Organizer
OCT 2019 - DEC 2019
Organized a 24 hour hackathon at college while analyzing the feasibility of the projects to be done in a specific time span.
Workshop - Student Coordinator
JAN 2019 - FEB 2019
Curated workshop topics and partnered with Robokart for event coordination.
Poster Presentations
OCT 2023 & MAR 2024
Presented posters on my master’s project in Computer science research day and AI research day.
