About
An individual with infinite energy, enthusiasm, daring, and patience ready to accomplish great deeds in the tech industry
Let me delineate my skills, contributions, achievements, qualifications, relevant experiences, and career goals on this page.
Professional Certifications & Exams
I earned this certificate by passing the exam which tested my ability to build and train deep learning models using TensorFlow. The participants of this exam will develop models for Image Classification, Natural Language Processing, Time Series Sequences and Prediction using CNNs, RNNs, LSTMs, GRUs.
I earned this certification by passing an exam that tested my fundamental understanding of IT services and their uses in the AWS Cloud. The earners of this certification demonstrates cloud fluency and foundational AWS knowledge. As an AWS badge owner I am skilled in identifying the essential AWS services necessary to set up AWS-focused projects.
This certificate is provided by Google to ceritfy that the candidate understands the advanced Google analytics concepts.
Those who earn the Google Data Analytics Certificate have completed eight courses, developed by Google, that include hands-on, practice-based assessments and are designed to prepare them for roles in Data Analytics. They are competent in tools and platforms including spreadsheets, SQL, Tableau, and R. They know how to prepare, process, analyze, and share data for thoughtful action.
Achievements & Contributions
- Awarded the Software Engineering Graduate Assistant role based on leadership and academic excellence
- Received a 20% tuition scholarship at RIT based on work and academic achievements
- Received a spot award from the Vice President of Research & Development at Daimler for saving $100,000 per annum
- Led an analytics team of 4 members at Luxgenic Infotech for developing and deploying deep learning models
Tech Stack
I have developed a specific set of skills over the years, solving problems with data and software. My experience with programming languages and industry-standard frameworks in agile work environments gives me the confidence to add value to the technology domain.
Programming
Python
Java
C++
R
Database Programming
SQL
MySQL
T-SQL
PostgreSQL
ML & DL Frameworks
LangChain
TensorFlow
PyTorch
Scikit-Learn
OpenCV
Numpy
Tools & Technologies
GIT
AWS
Azure
Docker
Kubernetes
MLFlow
Spark
Web Development
HTML
CSS
Plotly
Dash
Streamlit
Java Script
Reach.js
Node.js
Next.js
Data Visualization
Matplotlib
Seaborn
PowerBi
Tableau
AWS QuickSight
Academic Qualifications
As an undergrad, I found my passion for AI while specializing in Robotics and Statistics. This paved my way to becoming a graduate student specializing in Machine Learning and Deep Learning
MS Data Science
August 2021 - May 2023
Rochester Institute of Technology (received merit scholarship)
MS Data Science, Specializing in applied Machine Learning and Deep Learning
My Courses: Neural Networks, Data Science & Analytics, Software Constructions, Software Engineering, Applied Statistics, Database Design, Deep Learning, Capstone Machine Learning Project
BE Mechanical Engineering
May 2013 - May 2017
Anna University, St. Josephs College of Engineering (received Student Achiever Award in 2017)
BE Mechanical Engineering, Specialized in Robotics and Industrial Engineering
Relevant courses: Computer Programming with C++, Robotics, Mechatronics
Publications: Review on the effects of Hydrogen addition on performance, emission and combustion characteristics of CI engine
August 2022 - October 2022
DeepLearning.ai Online Course thought by Andrew Ng
The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online. This program contains 3 machine learning courses that will teach the fundamentals and how to use the techniques to build real-world AI applications.
Skills acquired:
Supervised Machine Learning: Linear Regression, Logistic Regression, Classification, Decision Trees, Random Forest, Regularization, Xgboost.
Unsupervised Machine Learning: K-Means clustering, Anomoly Detection, Collaborative Filtering, Recommender Systems, Reinforcement Learning
Google Tensorflow Specialization
August 2022 - October 2022
DeepLearning.ai Online Course thought by Andrew Ng
The TensorFlow Developer Professional Certificate Specialization is a hands-on, four-course Professional Certificate program, candidates will learn the necessary tools to build scalable AI-powered applications with TensorFlow. After finishing this program, learners will be able to apply the TensorFlow skills to a wide range of problems and projects.
Skills acquired:
Computer Vision, Natural Langauge Processing, Time Series Forecasting CNNs, RNNs, Transfer Learning, Dropouts, Data Augmentation, Tokenization
Work Experiences
My software engineering experiences have thought me the best professional practices to evolve as a Data Scientist and my goal is to build the best and ethical Machine Learning products in the industry.
Data Scientist Intern at BMW
January 2023 - December 2023
Data Management Team, BMW Financial Services
Developed a Financial Statement Analysis with LLM Powered Chatbot. The app loads and splits PDF documents creating embedding database to extract similar and relevant text embeddings using MMR to get the most relevant and appropriate summaries for the given question.
Deployed Customer Pain Points Analyzer using Hugging Face Language Models to deliver automated analytics for the Marketing team. Fine-tuned LDA to extract salient topics and sentiments for automated topic visualizations.
Enhanced Sentiment and Topic Analysis Model using OpenAI's GPT. The system is planned to be used for full-scale, comprehensive analytical inferences from the customer verbatim.
ADAS Engineering Team, BMW of North America, New Jersey
Designed & Implemented a Machine Learning workload using AWS S3 bucket, SageMaker, Autopilot, and PySpark. Extract, Transform and Load to preprocess real-time data sourced from BMW passenger vehicles.
Improved Emergency stop assist feature in Advanced Driver Assistance System by Detecting Anomalies. User's usage metrics were extracted and processed to be deployed as a QuickSight application on AWS to analyse real-time metrics.
Graduate Software Engineering Assistant at RIT
December 2021 - December 2022
Software Engineering Department, Rochester Institute of Technology, Rochester, New York
AWS image classification as service for academic department’s research. Built a Deep Learning Classifier with AWS SageMaker. Model was built using EC2, S3, and was deployed as a secure web app using Lambda, API Gateway and was made scaled using autoscaling. React.js, Node.js and MongoDB were used to build the full-stack website.
Recommendation of refactoring techniques to address Self-Admitted Technical Debts in software code bases. Given SATD comments the model will return a list of refactoring methods. The architecture included comparison of Random Forest, SVM, CNN, LSTM models using Keras. MongoDB was used to store the data and model.
Assisted a researcher with ML and Pattern Recognition in autonomous vehicles systems by building a novel model to accurately classify all 11 spoofed RADAR data inputs using Dempster Shafer Theory of Uncertainty.
Machine Learning & Analytics Volunteer at Luxgenic Infotech
March 2021 - March 2021
Luxgenic Infotech, Chennai, India
Designed & implemented an end-to-end data pipeline to move real-time telemetry data from a third-party AWS S3 bucket into the client’s Azure SQL DB using Azure Data Factory. Auto data validation was incorporated using the Azure function with blob trigger logic to perform analytics that added a new business model to the client’s portfolio.
Machine Learning - Senior Engineer at Mercedes Benz
April 2019 - March 2021
Daimler Trucks Asia, Chennai, India
Performed cost analytics for discovering raw material cost trends using Time Series Forecasting that led to 21 cost saving ideas that had the potential of saving 1,000 EUR.
Designed, maintained, and tested SQL relational databases to perform efficient queries for data analysis to reduce cost, saving the company 150,000 USD in sourcing costs.
Predicted internal temperature of a production unit using classification, regression, ensemble, and heuristic engines on Azure platform.