Dhanush

About

Computer Science undergraduate with hands-on experience in machine learning, deep learning, and computer vision across research and internship roles at iHub-Data, IIIT Hyderabad. Builds end-to-end ML pipelines and full-stack AI products, with strengths in Python, PyTorch/TensorFlow, and applied problem solving.

Experience

• AI Intern
  Internmo
  Jul 2026 – Present
• Research Intern
  iHub-Data, IIIT Hyderabad
  Mar 2026 – Aug 2026
• AI/ML Trainee
  iHub-Data, IIIT Hyderabad
  Sep 2025 – Feb 2026

Education

• BTech
  Sri Indu Institute of Engineering and Technology
  Computer Science · 2024 – 2028
• Intermediate (12th)
  FIITJEE Jr. College
  MPC · 2022 – 2024
• Secondary School Certificate
  Naagarjuna Model School
  2016 – 2022

Skills

• SQL
• C
• CSS
• Computer Vision
• Deep Learning
• HTML
• Python
• Machine Learning
• Java
• JavaScript
• Node.js
• Tailwind CSS
• Classification
• Matplotlib
• Model Evaluation
• NumPy
• Pandas
• Streamlit
• scikit-learn
• OpenCV
• React
• PyTorch
• TensorFlow
• Seaborn
• Dart
• Yolo
• R
• RAG
• XGBoost
• Regression
• Agentic AI Systems
• Generative AI (ChatGPT, Copilot, Gemini)

Projects

• AI Traffic Vision
  YOLOv8, YOLOv11, FastAPI, SQLAlchemy, SQLite, React, REST API

  Built a real-time traffic monitoring system using YOLO-based object detection on live camera feeds and uploaded video to count, classify, and track vehicles, detect accidents, and estimate speed/congestion. Designed a FastAPI backend for camera management, analytics, and alerts, with CSV/JSON report export, logging data to SQLite and serving a React analytics dashboard.

• AI Stock Analysis & Portfolio Platform
  Python, Pandas, NumPy, Scikit-learn, XGBoost, TensorFlow/Keras, NLTK, yfinance, PyPortfolioOpt, Streamlit

  Built a 4-phase end-to-end stock analysis platform covering data ingestion and feature engineering, classical ML, sentiment plus deep learning, and portfolio optimization, with each phase gated on a verified artifact before the next began. Implemented financial math and gradient descent linear regression from scratch, benchmarked classical models with time-series cross-validation, trained LSTM/GRU/BiLSTM/Transformer models, and shipped an interactive Streamlit dashboard.

• ResearchHub AI — Agentic Research Assistant
  React, TypeScript, Tailwind CSS, FastAPI, SQLAlchemy/SQLite, Groq Llama 3.3 70B, JWT, PyPDF2

  Built an agentic research assistant end to end with a React/TypeScript frontend and a FastAPI backend with authentication, persistence, and arXiv integration. Designed a retrieval-then-generate LLM pipeline, added multi-paper summarization and literature-review tools, supported PDF upload and summarization, and created a workspace system for organizing papers and notes.

• Diabetes Risk Prediction — KNN Classification
  Python, Pandas, Scikit-learn, Seaborn, Matplotlib

  Performed exploratory data analysis on the Pima Indians Diabetes dataset, identified key predictors, and built a K-Nearest Neighbors classifier with hyperparameter sweeps and 5-fold cross-validation.

• Water Potability Classification — Classifiers Built from Scratch
  Python, NumPy, Pandas

  Implemented three linear classifiers from first principles in NumPy: Perceptron, Gradient Descent classifier, and a max-margin classifier with hinge loss and L2 regularization. Compared convergence behavior and test accuracy on real water-quality data.

• Customer Segmentation for Targeted Marketing
  Python, Scikit-learn, UMAP, Plotly

  Built a two-stage customer segmentation pipeline using PCA, t-SNE, and UMAP on synthetic and real retail transaction datasets. Engineered RFM features and compared linear versus non-linear projections to profile customer segments.

• COVID-19 Case Forecasting with Regression
  Python, Pandas, NumPy, Scikit-learn, Matplotlib

  Transformed daily case records into a cumulative time series, engineered growth-factor metrics, and benchmarked Linear, Polynomial, and Bayesian Ridge regression models on a chronological split.

• Foodie — Real-Time Food Delivery Platform
  React.js, Vite, Tailwind CSS, Node.js, Express.js, MongoDB, Socket.IO, JWT, Razorpay, Google Maps API

  Built a full-stack food delivery platform connecting customers, restaurants, and delivery agents with authentication, menu management, online payments, real-time order tracking, and QR-based order verification.

Courses & certifications

• 10th Summer School on AI · CVIT Summer School Series, IIIT Hyderabad & iHub-Data · 2026
• ML for Geo Data Analysis · IIRS-ISRO · 2026
• Research Intern Certification · iHub-Data, IIIT Hyderabad · 2026
• AIML Student Trainee · iHub-Data, IIIT Hyderabad · 2026
• Introduction to Generative AI · IBM SkillsBuild · 2026
• AI Foundations, Applied AI Foundations & Agents and Workflows · OpenAI Academy · 2026
• Project Expo (Full-Stack MERN) · Sri Indu Institute of Engineering and Technology · 2026

⚽ Extracurricular activities

• NSS Volunteer

  Active volunteer and participant.