I'm Anurag
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I am currently a Software Development Engineer.Completed BTech in Computer Science and Technology at IIEST Shibpur in 2026. Passionate about Software Engineering, ML/Deep Learning, Quantum Computing, and building impactful software. Open to research collaborations and exciting opportunities.
I'm Anurag Ghosh, a Software Development Engineer, Researcher, and a Programmer who loves ML and Quantum Computing.
Completed B.Tech in Computer Science and Technology at IIEST Shibpur (CGPA: 9.87), ranked 1st across all departments. I've interned at Amazon Web Services, conducted research at IIT Madras, IIT Kharagpur and ISI Kolkata, and published research on Cellular Automata and Deep Learning strategies to improve Brain Tumor Classification. Deeply interested in Deep Learning, Quantum computing, post-quantum cryptography, and efficient software development.
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Name:
Anurag Ghosh -
Degree:
B.Tech CST, IIESTS (2022–2026) -
From:
Kolkata, West Bengal, India
Qualification
Education
B.Tech in Computer Science and Technology
+Indian Institute of Engineering Science and Technology, Shibpur
2022 – 2026
CGPA: 9.87 — Ranked 1st in the department and across all departments (BTech batch 2022–2026).
Semester-wise GPA:
1st Semester: 9.13
2nd Semester: 10
3rd Semester: 10
4th Semester: 10
5th Semester: 10
6th Semester: 10
7th Semester: 10
8th Semester: 9.86
Higher Secondary Education — 12th Grade (ISC)
+Vivekananda Mission School, Joka
2022
Score: 98.50%
Awarded INSPIRE SHE Scholarship for excellent performance in 12th Board Examinations.
Secondary Education — 10th Grade (ICSE)
+Vivekananda Mission School, Joka
2020
Score: 98.40%
Experience
Software Development Engineer Intern — Amazon
+Amazon Web Services
Bengaluru
Jan 2026 – Jun 2026
Enhanced AWS Just Walk Out's End-to-End Testing Platform stability through an automated cross-service cleanup system using AWS Step Functions and Lambda across 6 dependent services.
Implemented production safety validations and CloudWatch observability dashboards, reducing manual effort by 15 minutes per incident and saving ~63 hours of manual effort annually.
Summer Fellow — SENSE Lab, IIT Madras
+Computer Science & Engineering, IIT Madras
May 2025 – Jul 2025Under Prof. Ayon Chakraborty, developed and evaluated deep learning models for Radio Environment Map (REM) prediction using wireless sensing data. Applied U-Net architectures and investigated novel Transformer and attention-based modifications to improve predictive accuracy.
Project Intern — R.C. Bose Centre for Cryptology and Security
+Indian Statistical Institute (ISI), Kolkata — ISEA Phase III
Sep 2024 – Dec 2024Contributed to a post-quantum cryptography project under Prof. Subhamoy Maitra by enhancing the NIST-standardized Kyber algorithm; implemented targeted optimizations to improve both cryptographic security and computational efficiency.
Project Intern — Indian Summer School on Cellular Automata
+Research Program (Hybrid)
May 2024 – Jul 2024Analyzed primitive polynomials using maximal-length cellular automata; implemented greedy strategies in C++ for generating primitive polynomials over GF(2). Work led to a research publication in the Northeast Journal of Complex Systems.
Achievements & Publications
Academic Excellence
Ranked 1st in the Department of CST and across all departments at IIEST Shibpur (BTech 2022–2026) with a CGPA of 9.87.
Awarded the Samsung Fellowship for the India Semiconductor Workforce Development Program.
Awarded INSPIRE SHE Scholarship for 98.50% in 12th Board Examinations.
Competitive Programming
Achieved a maximum rating of 1612 on Codechef and 1641 on Leetcode.
Participated in Flipkart Grid 5.0 Software Development Track and qualified for Level 2.0.
Awarded 2nd Place in BrainDead — the ML Hackathon at Revelation 2025, competing against 31 teams from across India.
Research Publications
1. "Exploring Maximal Length Cellular Automata to Generate Primitive Polynomials in GF(2)" — Northeast Journal of Complex Systems
2. "Brain Tumor Classification Using Attention-Based Medical Image Segmentation and Transfer Learning" — Paper presented at AIIoT 2025: 2nd International Symposium on AI and Internet of Things
Professional Skills
C++ / C Programming
Strong foundation in C and C++ — used extensively in algorithmic projects, research on primitive polynomials over GF(2), and competitive programming (Codechef max rating: 1612).
Java Programming
Skilled in Java with a strong grasp of OOP principles, used for the Automated Timetable Generator project which reduced scheduling time by 80%.
Quantum Computing
Proficient in basic Quantum Computing concepts, including qubits, superposition, and entanglement.Have interest in quantum algorithms, quantum error correction, and quantum machine learning.
Data Science & ML (Python)
Experienced with Python for data science, machine learning, and deep learning — libraries include TensorFlow, Keras, Sklearn, Pandas, NumPy, Matplotlib, OpenCV, and Streamlit.
Deep Learning
Designed CNN models for flower and dog-cat classification, U-Net for REM prediction at IIT Madras, and attention-based models for brain tumor classification.Know transformer achitectures and its use in NLP indepth.
JavaScript / React / Node.js
Built full-stack and frontend projects including a cryptocurrency tracker (TrendPulse), a React password generator, and a Tic-Tac-Toe game — deployed on Vercel.
AWS (Step Functions, Lambda, CloudWatch)
Hands-on experience from Amazon SDE internship building serverless orchestration pipelines, failure recovery systems, and observability dashboards at production scale.
SQL / Databases (MySQL, PostgreSQL, MongoDB)
Designed a 6-table Library Management System with optimized queries (50% faster) and automated triggers. Also experienced with MongoDB for NoSQL applications.
HTML / CSS
Proficient in HTML and CSS, adept at creating responsive and visually appealing web designs, including layouts, styling, and interactive elements.
Programming Languages & Tools
HTML 5
CSS3
JAVASCRIPT
Python
GIT
Linux
C/C++
Java
MongoDB
React
NODE.JS
AWS
Recent Works
MIRROR
Intelligent Agent System for Legal Document Analysis
FIR-IPC Predictor
Explainable Multi- Label IPC Section Prediction
IPL Data Analysis
Statistics is All You NeedEXPLORE MY PROJECTS
Flower Classification Using
Deep Learning
Leveraging CNNs and data augmentation for multi-class image classification to accurately identify 5 flower species. Achieved 73.57% accuracy after 12 epochs with data augmentation.
Visit Project
Statistics is All You Need: IPL Data Analysis and 2025 Winner Prediction
An ML-based IPL data analysis project predicting the winner of the 2025 season.Leveraged historical IPL data, player statistics, and team performance metrics to train predictive models.
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Dog vs Cat Classification
Using Deep Learning
CNN-based binary image classifier with Adam optimiser and binary cross-entropy loss, achieving 84.22% accuracy across 20 epochs — outperforming a baseline ANN.
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Password Generator
Using React
A Password Generator with light and dark themes, built using React. Features password generation with copy functionality and exploration of various React hooks.
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Tic-Tac-Toe Using React
An enjoyable Tic-Tac-Toe game built using React, focusing on responsiveness and user engagement across various devices.
TrendPulse — Crypto Tracker
Cryptocurrency tracking app using React JS, Context API, CoinGecko API for 24/7 updates, React Router for navigation, and React Google Charts for data visualization. Deployed on Vercel.
Library Management System (SQL)
6-table database managing books, members, and staff. Reduced data redundancy by 40%, optimized query execution by 50% via indexing, and designed automated triggers cutting manual tracking by 90%.
View Project
Titanic Survival
Prediction
ML model predicting survival of Titanic passengers based on features like class, gender, and age — developed during a data science internship.
Automated TimeTable Generation Algorithm
Engineered a robust Java algorithm for the NP-hard problem of timetable generation, reducing manual scheduling time by 80% and increasing accuracy by 95% using OOP principles.
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Kruskal & Prim Algorithm
on Vast Dataset
Implemented Kruskal's and Prim's algorithms on a large Stanford Network Dataset for Minimum Spanning Tree computation.
Data Analysis &
Customer Segmentation
Analyzed consumer behavior in virtual retail transactions using Jupyter, Sklearn, and Matplotlib to enhance client satisfaction and optimize business strategies.
Visit ProjectWhat I do for you
Machine Learning, Deep Learning & Quantum Computing
Hands-on experience building ML and DL solutions — from CNNs for image classification to U-Net models for wireless sensing. Proficient with TensorFlow, Keras, Sklearn, and Python data science tools. Interested in areas like NLP, Generative AI, and computer vision. Interested in Quantum Computing and post-quantum cryptography, with research experience in these domains.
01Full-Stack Development & System Design
Building responsive, modern web applications using React, Node.js, Express, and MongoDB. Skilled in HTML, CSS, and JavaScript, with a keen eye for clean UI/UX design. Projects deployed on Vercel and other platforms. I try to design systems that are scalable, maintainable, and efficient, with a focus on delivering high-quality software solutions with the customers in the center of attention.
02Cloud & Backend Engineering
Experience with AWS services (Step Functions, Lambda, CloudWatch) from my Amazon SDE internship. Comfortable designing serverless pipelines, observability dashboards, and distributed backend systems. Improving my skills in robust backend architecture, cloud-native development, and scalable system design everyday.
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