Siddhant H Mantri
AI/ML Enthusiast
siddhantmantri.com
About
I'm a tech enthusiast with a strong desire to learn and grow. I've self-taught various programming languages and technologies, and I'm always on the lookout for opportunities to advance my abilities. I'm an enthusiastic, people-oriented individual who enjoys expanding my network and collaborating with like-minded professionals. I thrive on the excitement of learning and look forward to contributing my passion for technology to any team or project.
Work Experience
Research Intern
CFITL - Indian Institute of Technology Bombay
Currently working on Shabdbot - a chatbot style application based on the Shabdamitra which itself uses various wordnets at Computation for Indian Language Technology Lab under guidance of Prof. Pushpak Bhattacharyya and Prof. Malhar Kulkarni.
ML Intern
Volkswagen Group Technology Solutions India
As part of Project AISHA 2.0, I contributed to multiple stages of developing an in-house, Retrieval-Augmented Generation (RAG)-based chatbot built from scratch. My key responsibilities included research on indexing and retrieval process which included comparison of various vector data stores to optimize the application. Additionally, I developed an enhancement service that significantly improved the chatbot's performance, reducing resource usage while accelerating response times. I also worked on Large Action Model development.
View LetterTechnical Intern
Misuraa Projects LLP
Specialized in leveraging Google Suite and Google Apps Script to create and manage various applications and manipulate data across the company's database. Developed and deployed a comprehensive warehouse management application featuring a QR generator and scanner. This system included a detailed database providing all necessary information for the warehouse manager, automating process and significantly increasing accuracy, speed, and cost-efficiency in the management process.
View LetterEducation
B.Tech Computer Science and Engineering (Cyber Security)
Mukesh Patel School of Technology Management and Engineering, NMIMS, Mumbai
CGPA: 3.86/4
B.S Data Science and Applications
Indian Institute of Technology Madras, Chennai
CGPA: 7.39/10 Project CGPA: 9.0/10
Projects
Automated Incident Response: Leveraging LLMs for Rapid Post-Attack Analysis and Reporting
Developed an AI-driven automated incident response framework integrating on-device Large Language Models (LLMs) and specialized classifiers to streamline post-attack analysis, reducing response times from days to hours. Architected a system for real-time log ingestion, multi-source data correlation, and comprehensive report generation, enabling rapid, accurate threat detection and response across networked environments.
Cybersecurity • Incident Response • Automation • Large Language Models (LLMs) • Machine Learning • Python • Flask • Wazuh • Suricata • SMTP • Log Analysis • Hugging Face • API Integration • Machine Learning • Log Analysis
View ProjectAI-Powered Learning Management System (LMS)
Contributed to the design and implementation of AI-driven features, including course summaries, peer-driven insights, and coding assistance, leveraging advanced language models such as Mistral8x7b and LLaMa3-70B. Integrated the vLLM inference engine to optimize performance, reducing latency and efficiently scaling AI-generated responses across the system. Implemented FastAPI to serve multiple endpoints for AI-powered features enhancing the overall learning experience for students.
Large Language Models • FastAPI • vLLM • Python • OpenAI
View ProjectRecipe for Rating: Predict Food Ratings using ML
Developed machine learning models to accurately predict food ratings based on recipe information and user reviews. Preprocessed and engineered features from a dataset containing multiple attributes. Evaluated multiple algorithms including logistic regression, boosting techniques like AdaBoost, and advanced algorithms like Multi Layer Perceptron. Achieved an accuracy of 77.166% by implementing a logistic regression model.
Python • Machine Learning Algorithms • Pandas • Numpy • Scikit-learn
View ProjectShelfSense
Developed a full-stack Library Management System called ShelfSense using Flask (Python) for the backend and Vue.js for the frontend, enabling comprehensive operations including book management, user management, issue tracking, and user feedback. Leveraged SQLAlchemy for database operations with SQLite, Redis for caching, and Celery for task scheduling to optimize performance. Implemented role-based access control, RESTful API, and authentication features for a robust and secure system.
HTML5 • CSS3 • JavaScript • Flask • Vue.js • SQLAlchemy • Flask-Restful • SQLite • Redis • Celery
View ProjectVybe
Built a robust music streaming app using Flask, SQLite, SQLAlchemy, and HTML/CSS/JavaScript. It mimics mainstream platforms with features like user registration, artist following, playlist creation, song rating/commenting, and extensive search capabilities. Users can create and manage their songs/albums, and an admin panel allows CRUD operations and provides detailed statistics. I also integrated Flask-Restful for API endpoints, enabling seamless interaction and CRUD operations.
HTML5 • CSS3 • JavaScript • Flask • SQLite • SQLAlchemy • Flask-Restful
View ProjectPhishit
Involved in the development of Phishit, a browser extension aimed at bolstering online security. The project utilizes HTML, CSS, JavaScript, Python, and machine learning (scikit-learn) to scan open email content, transmit it to a server, and detect potential phishing attacks. My role included development of machine learning models, web development and server scripting. Phishit represents a significant step towards proactive phishing threat identification.
Python • Scikit-learn • Machine Learning Algorithms • Pandas • Numpy • HTML5 • CSS3 • JavaScript
View ProjectJudge My Music
Developed 'Judge My Music,' a web app using Spotify API, HTML, CSS, JavaScript, and Vite framework. Integrated browser local storage for enhanced user experience and Selenium web scraping for artist data enrichment. The platform provides amusing music insights and recommendations, showcasing my blend of technical skills and creativity to entertain while celebrating diverse music tastes.
HTML5 • CSS3 • JavaScript • Vite • Selenium • Spotify API
View ProjectCase Study Of Project Shilpkaar
Led the data analysis for Project Shilpkaar, a venture aiding underprivileged weavers and addressing plastic waste. Responsibilities include data collection, cleaning, customer segmentation, product costing, and supply chain insights. Continuous analysis aimed to uncover sales trends, customer preferences, and optimization opportunities. Dedicated to enhancing Shilpkaar's operations through actionable insights and innovation.
Data Analysis • Customer Segmentation • Product Costing • Supply Chain Insights • Excel
View ProjectConnect
