Chittapu Abhiram Reddy

Experience

SDE Intern - Providence June 2025 – August 2025

Software Development Engineer Intern Hyderabad, India

Designed an AI Agent for huge PDFs (containing >2500 pages, 20,000+ row tables), facilitating effective information retrieval from complex documents.
Implemented a custom preprocessing pipeline in snowflake to hide Personally Identifiable Information(PII) and Protected Health Information(PHI) to achieve HIPAA compliance.
Designed a RAG-based chatbot to deliver accurate, context-aware responses on organizational tools, processes and resource access to improve employee onboarding experience.

Chaitanya Bharathi Institute of Technology (Ongoing) Nov. 2022 – June 2026

B.E. Computer Science Engineering CGPA: 9.35 Hyderabad, India

Sri Chaitanya College June 2020 – May 2022

Intermediate Public Examinations: 97.5% | TSEamcet Rank: 2660 Hyderabad, India

Crypto-Master - A crypto themed game | FastAPI, React, JavaScript, Mongo DB,Azure, Tailwind CSS

Link

Developed a real-time, web based multiplayer game using Microsoft Azure, successfully hosting over 80 concurrent players with less than 70ms latency during a live event
Architected a scalable backend using python validated via automated load testing to ensure high availability and performance for over 500 simultaneous participants.
Implemented a dynamic leaderboard with real-time data synchronization to drive player engagement by displaying player rankings and scores.

MisclassifyMe - Fooling Image Classifiers | Pytorch, TorchVision, Pillow

Link

Engineered FGSM (Fast Gradient Sign Method) and PGD (Projected Gradient Descent) based algorithm to generate adversarial images to fool image classifiers to misclassify target images.
Generated Adversarial images with imperceptible changes using PGD which were misclassified by the VGG16 model with up to 95% confidence.
Simulated targeted attacks using PGD causing the VGG16 classifier to misclassify images to a chosen target class with over 85% reliability.

Verisite - Verifying website authenticity | Python, Pytorch, XGBoost, FastAPI, Transformers, QLora

Link

Built an ML-based browser extension to detect malicious/phishing websites with 83% accuracy.
Fine-tuned a DeBERTa-v3 language model using qlora to distinguish between benign and malicious websites.
Added a multi-input neural network on top of the DeBERTa model to improve precision by 3%, greatly decreasing the false positive rate.

Languages: Python, C, C++, JavaScript

Web & Backend: React, FastAPI, Azure, GitHub, HTML, CSS

Databases: MySQL, MongoDB, Postgres

Libraries & Frameworks: TensorFlow, PyTorch, Keras, Scikit-learn, LangChain, Langgraph, PowerBI

Competitive Programming

MongoDB Certified Developer, Associate (C100DEV)

Earned the MongoDB Certified Developer, Associate (C100DEV) certification, demonstrating proficiency in MongoDB database development and management.(Certificate)

Machine Learning Specialization

by Stanford and DeepLearning.ai

Completed the Machine Learning Specialization by Stanford university on Coursera covering the theoretical and practical aspects of machine learning

Vice President, HackItOn, CBIT February 2024 – Present

Spearheaded the organization of multiple large-scale hackathons with a price pool of up to rupees 1.2 Crore, attracting over 500 teams from various institutions.