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Data Scientist

I leverage AI, ML, Data Science and software solutions to creatively solve real-world problems. Join me in exploring innovative ideas and building impactful solutions!

Thirupathi Kadari Profile Photo
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About Me

AI/ML & Data Science Practitioner

Hi, I’m Thirupathi Kadari. I build intelligent AI and ML systems, including RAG pipelines, LLM-powered agents, and scalable ML models, turning insights from data into impactful solutions.

More About Me

Technical Skills

Python SQL R Cypher
95%
PostgreSQL Neo4j FAISS
85%
Scikit-learn PyTorch TensorFlow Keras OpenCV
90%
LangChain LangGraph NLTK SpaCy
90%
Azure AWS GCP
85%
Power BI Visual Studio Code Jupyter
85%
Streamlit FastAPI Flask OOP Techniques
85%
MLOps MLflow CI/CD, GitHub Docker & Kubernetes
85%
Classification Regression Clustering Time-series Forecasting
90%
LLMs Prompt Engineering RAG Agentic AI Transformers
85%
Object Detection Image segmentation Image Generation
85%

Professional Skills

90%
Creativity
95%
Communication
80%
Problem-Solving
90%
Agile Framework
90%
Innovation
80%
Team Work and Leadership
View My exprience / Acedamics

My Research

NutriDetect – Food Detection & Nutrition Analysis

Published in ACM Conference. Developed a deep learning-based food detection system with nutritional insights using computer vision models.

NutriDetect Research Paper 📄 View Research Paper
YOLO Computer Vision Deep Learning Nutrition AI

Face Landmarks Prediction – Comparative Analysis

Compared different deep learning models for accurate facial landmark detection and performance evaluation.

Face Landmarks Research Paper 📄 View Research Paper
Computer Vision Deep Learning Facial Recognition

Cows Teat-End Condition Classification using CNN

Built a CNN-based classification model using PyTorch to analyze teat-end conditions for dairy cattle health monitoring.

Cow Teat-End Research Paper 📄 View Research Paper
CNN PyTorch Veterinary AI

Image Segmentation of Lungs Dataset in PyTorch

Implemented deep learning segmentation techniques for lung dataset analysis, improving medical image understanding.

Lungs Segmentation Research Paper 📄 View Research Paper
Segmentation Medical Imaging PyTorch

Object Detection for Cow Stall Number using ResNet152

Designed an object detection model using ResNet152 for identifying stall numbers in smart dairy farm environments.

Cow Stall Research Paper 📄 View Research Paper
Object Detection ResNet152 PyTorch
View All Publications

My Projects

📊 Exploratory Data Analysis (EDA)

Performed data cleaning, visualization, and insights extraction using Python, Pandas, and Matplotlib.

Pandas EDA Visualization
🔗 Source Code

🧠 Brain MRI Classification using GANs

Built GAN-based model for brain tumor classification and synthetic data generation using deep learning.

GAN Deep Learning Medical AI
🔗 Source Code

🎬 IMDB Movie Case Study (MySQL)

Analyzed movie datasets using SQL queries to extract business insights and trends.

MySQL SQL Analytics
🔗 Source Code

📈 Lead Scoring Case Study

Built predictive model to identify high-quality leads using machine learning techniques.

Classification ML
🔗 Source Code

📉 Linear Regression Model

Implemented regression model to predict continuous outcomes with performance evaluation.

Regression ML
🔗 Source Code

📡 Telecom Churn Prediction

Built churn prediction model using classification techniques to reduce customer attrition.

Classification ML
🔗 Source Code

🛣️ Dijkstra Algorithm

Implemented shortest path algorithm for efficient graph traversal and optimization.

Graph Algorithms
🔗 Source Code

♟️ Alpha-Beta Pruning

Optimized Minimax algorithm for game decision making using pruning technique.

AI Game Theory
🔗 Source Code

🏠 House Price Prediction

Advanced regression model to predict house prices using feature engineering techniques.

Regression ML
🔗 Source Code

🚲 Bike Sharing EDA

Analyzed bike rental dataset to identify patterns and usage trends.

EDA Visualization
🔗 Source Code
Visit My GitHub

Education

Yeshiva University

Master’s in Artificial Intelligence

Jan 2023 – May 2024
  • GPA: 4.0 | Relevant coursework in Machine Learning, Artificial Intelligence, Data Science, Neural Networks, Deep Learning, Advanced NLP, and Cloud Computing.
  • Worked on core AI/ML concepts including supervised learning, unsupervised learning, regression, classification, clustering, and model evaluation.
  • Built projects in Generative AI, NLP, computer vision, and agentic workflows using Python, PyTorch, TensorFlow, LangChain, and LangGraph.
  • Strengthened applied skills in RAG pipelines, prompt engineering, deep learning architectures, and end-to-end AI solution development.

JNTU Hyderabad

Bachelor’s in Electrical and Electronics Engineering

Aug 2011 – June 2015
  • Built strong foundations in Linear Algebra, Matrices, Probability, Statistics, and mathematical concepts useful in Data Science, AI, and Machine Learning.
  • Learned Data Structures and Algorithms, problem-solving techniques, and logical thinking for efficient software design.
  • Gained programming knowledge in C, C++, and Java, strengthening computational and analytical skills.
  • Developed engineering fundamentals, quantitative reasoning, and technical problem-solving through practical coursework and projects.

Experience

AI/ML Engineer

Sync AI, New York, USA

Sept 2024 – Present
  • Built AI/ML solutions for business workflows using Python, machine learning, and data-driven optimization techniques.
  • Developed LLM-powered and LangChain-based workflows to automate analysis, ranking, and decision-support use cases.
  • Created intelligent scoring and prioritization systems using ensemble models such as XGBoost and Random Forest.
  • Designed dashboards, reports, and data visualizations to communicate insights and cost-benefit analysis to stakeholders.
  • Worked on applied AI initiatives involving predictive modeling, workflow automation, and operational efficiency improvements.
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Machine Learning Co-op

ZSAnalytics LLC

May 2024 – Aug 2024
  • Designed and deployed an end-to-end machine learning lifecycle for email marketing using MLOps best practices, achieving strong model accuracy and measurable ROI improvement.
  • Built ML pipelines for data ingestion, preprocessing, feature engineering, training, evaluation, deployment, and retraining with Azure ML Studio and AKS.
  • Developed a retrieval-augmented generation (RAG) pipeline using LangChain, GPT-4, and ChromaDB to index large-scale documents and reduce response latency.
  • Processed and analyzed large-scale datasets using SQL, NumPy, and Pandas, ensuring reliable downstream modeling.
  • Performed exploratory data analysis and visualizations with Matplotlib to uncover customer behavior patterns and campaign insights.
  • Applied feature engineering to improve model precision and enable more accurate customer targeting.
  • Tracked and compared model performance using MLflow for experiment tracking and model selection.
  • Implemented MLOps pipelines with Azure DevOps CI/CD, REST API integration, and Azure Monitor for deployment automation and troubleshooting.
  • Delivered insights through dashboards in Power BI, Excel, and PowerPoint to support data-driven marketing strategies.
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Data Scientist

Spring ML

Aug 2018 – Dec 2022
  • Collected, managed, and processed sales, customer, and inventory data using SQL and Python, ensuring accuracy and consistency for analytics and reporting.
  • Built ETL pipelines with SQL, Pandas, and NumPy to extract, clean, and structure large datasets for analysis.
  • Engineered preprocessing workflows that resolved missing values, outliers, and skewness, improving downstream model performance.
  • Conducted exploratory data analysis (EDA) using univariate, bivariate, and multivariate techniques to uncover customer behavior patterns and business trends.
  • Applied statistical techniques to identify key business drivers impacting revenue performance.
  • Built clustering models to segment customers into meaningful groups, improving targeting and retention strategies.
  • Designed and delivered interactive dashboards with Matplotlib, Seaborn, and Power BI for reporting and KPI tracking.
  • Delivered actionable insights on pricing, promotions, and inventory optimization, improving profitability and operational efficiency.
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Thirupathi Kadari

WRITE AN E-MAIL

tkadari.ai@gmail.com

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Let’s Collaborate

I’m always open to discussing AI/ML opportunities, research collaborations, innovative ideas, and impactful projects. Feel free to reach out.

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