Greetings, I'm

Shreyas Tembhare

MS in Data Science at RIT focusing on LLMs/RAG, Computer Vision, and end-to-end ML systems that ship. Applied AI/ML engineer passionate about building reliable AI systems.

Currently working on RAG platforms over enterprise PDFs, computer-vision analytics pipelines, and practical ML with measurable latency/relevance wins.

Let's connect and explore how data can shape the future.

Sir Codealot

Loyal assistant to Master Shreyas.

  • Greetings! I'm Sir Codealot, Master Shreyas's loyal knight assistant. Ask me about his skills, projects, and professional background.

Skills & Expertise

Programming Languages

Python
Java
SQL
JavaScript

Machine Learning & AI

TensorFlow
PyTorch
scikit-learn
XGBoost

Computer Vision & NLP

OpenCV
DeepFace
LangChain
NLP

Cloud & Tools

AWS
Git
Docker
Streamlit

Data Analysis & Visualization

Pandas
NumPy
Matplotlib
Plotly

Backend & Infrastructure

FastAPI
PostgreSQL
Redis
K8s

Featured Projects

EcoHarvestors

Agricultural AI Platform

EcoHarvestors

ML-powered crop planning & demand forecasting to reduce waste. Built prediction models for crop yield, demand forecasting, and optimal planting schedules with AWS deployment.

Python TensorFlow XGBoost Scikit-learn AWS
Exoplanet Detection

ML Pipeline Tool

Exoplanet Detection Tool

Time-series ML pipeline for detecting exoplanet transit candidates from light curve data. Features preprocessing, ensemble classifiers, and interactive visualization for review.

Python Lightkurve Time Series Analysis Outlier Detection Matplotlib
Resume Analyzer

AI Document Analysis

Resume Analyzer

AI-powered Resume Analyzer using NLP and machine learning techniques for text classification and analysis. Built web interface for recruiters with advanced text processing capabilities.

Python NLP Scikit-learn TF-IDF Streamlit

Research & Publications

Multimodal Machine Learning for Retrieval-Augmented Generation

Research on token length variations and retrieval accuracy in multimodal models. Evaluating SOTA models (CLIP, OpenCLIP, Long-CLIP, ALIGN, BLIP-2) on diverse datasets to analyze model robustness, depth estimation, and retrieval efficiency for RAG applications.

Academic Research 2024-2025
View Research Paper

Computer Vision & AI Fairness Analysis

Development of video tracking and attribution systems with human-in-the-loop evaluation for detecting subtle bias patterns in video content. Focus on ensuring fairness in AI systems through comprehensive computer vision analysis and demographic-aware processing.

Industry Research 2024-2025
View Research Paper

Experience & Education

Applied AI Intern

Jun 2025 - Jul 2025
CIO Infotech Pvt. Ltd., Pune, India
  • Built and optimized a Retrieval-Augmented Generation pipeline using LangChain, AWS Bedrock (Llama 3), and PGVector, enabling context-aware Q&A over extensive legal document collections
  • Automated intelligent PDF text extraction and chunking workflows to streamline embedding and retrieval processes
  • Engineered prompt-design strategies and dynamic summarization features to toggle between concise answers and in-depth responses based on user intent
  • Enhanced system reliability and observability with robust error handling, end-to-end logging, and cross-functional collaboration for stakeholder feedback

Computer Vision Researcher

May 2025 - Aug 2025
FairwAI, New York, US
  • Developed an end-to-end face-labeling pipeline in Python and OpenCV to automate face detection, SORT-based multi-object tracking, and demographic analysis (age, gender, race) in video streams
  • Leveraged DeepFace and face recognition to extract high-quality face crops and infer attributes via pretrained deep-learning models
  • Generated anonymized, structured reports for downstream analytics and research, ensuring data privacy and compliance

Research Assistant

Oct 2024 - Mar 2025
Rochester Institute of Technology, New York, US
  • Conducted research on multimodal machine learning models, focusing on token length variations and retrieval accuracy
  • Evaluated SOTA models (CLIP, OpenCLIP, Long-CLIP, ALIGN, BLIP-2) on diverse datasets (ROCO, Urban1k) to analyze model robustness, depth estimation, and retrieval efficiency
  • Investigated the impact of dataset variations on retrieval thresholds, identifying computational bottlenecks affecting ML performance

MS in Data Science

Aug 2024 - May 2026
Rochester Institute of Technology, NY, USA
  • Focus: LLMs/RAG, Computer Vision, end-to-end ML systems
  • Research Assistant working on multimodal ML and retrieval accuracy optimization

Machine Learning Intern

Apr 2023 - Jul 2023
TechR, Pune, India
  • Developed an AI-powered Resume Analyzer using NLP and Deep Learning (BERT), improving text-classification accuracy by 25% and reducing compute time by 30% on AWS SageMaker GPU instances
  • Optimized large-scale resume processing by implementing batch processing, increasing system efficiency and boosting user adoption
  • Built a web interface for resume analysis, enhancing recruiter usability and cutting processing time by 40% through query optimization

Machine Learning Intern

Feb 2023 - Mar 2023
YBI Foundation, Remote
  • Developed an ML-driven predictive model using Python, Scikit-learn, and hyperparameter tuning, demonstrating strong foundations in optimization mathematics and resource scheduling
  • Processed large-scale data pipelines using NumPy, Pandas, and Matplotlib, focusing on scalable ML solutions
  • Implemented feature selection techniques to reduce model complexity while maintaining high predictive accuracy
  • Conducted statistical validation (ANOVA, confidence intervals) to ensure model reliability and optimize decision-making

BE in Artificial Intelligence & Machine Learning

Aug 2020 - May 2024
Savitribai Phule Pune University, Pune, India
  • Scholarship: Gogate Educational Foundation
  • Specialized in AI/ML with practical project experience

Ready to Collaborate?

I'm always interested in new opportunities and exciting projects. Let's discuss how we can work together to solve complex data challenges.