About Me:
I am an ambitious and technically proficient solutions architect currently pursuing a Bachelor of Technology in Computer Science and Engineering with a specialization in Artificial Intelligence and Machine Learning at Sardar Patel Institute of Technology in Mumbai, India.
Current Role
Training Placement Office, SPIT
Point Of Contact
Location: SPIT, Mumbai
Duration: August 2023 – Present
Responsibilities:
Organized and oversaw mock interviews on campus for TE students, facilitating a total of 500 interviews within a week.
Implemented a streamlined process to efficiently manage the extensive interview schedule.
Actively participated in organizing various training sessions.
Oculus - IPL Auction
Role: Organizing Member
Duration: January 2024 – March 2024
Responsibilities:
Led marketing efforts to pitch and secure sponsorship opportunities.
Contributed significantly to project operations and logistics for seamless event execution.
Served as an auctioneer, engaging participants and ensuring smooth event flow.
Projects
Rupies: Personal Financial Tracker | Django, React, SQL
Duration: February 2024 – Present
Description:
Directed the development of the “Personal Finance Tracker” project, overseeing the backend design with a RESTful approach.
Aligned closely with team members utilizing React for the frontend, ensuring cohesive system integration.
Utilized SQL as the database technology for efficient data storage and retrieval.
Implemented user authentication using JWT tokens, ensuring secure access to the application.
Integrated a chatbot from Gemini’s API, enhancing user interaction.
Movie Recommendation Project | Python, Streamlit
Duration: April 2024
Description:
Developed a movie recommendation application using Python and Streamlit, allowing users to discover new movies based on their preferences.
Utilized pandas for data manipulation, NLTK for natural language processing, and scikit-learn for building the recommendation engine.
Developed a streamlined user interface with Streamlit for easy interaction with the recommendation system.
Education
Sardar Patel Institute of Technology, Mumbai
Degree: BTech in Computer Science and Engineering (Artificial Intelligence and Machine Learning)
Duration: November 2022 – May 2026
CGPA: 7.95
Pace Science Junior College, Thane
Level: Pre-University College
Duration: August 2020 - May 2022
Board: Maharashtra Board
Percentage: 88.67
MHT CET: 99.028 percentile
Euro School, Thane
Level: High School
Duration: April 2018 - May 2020
Board: ICSE
Percentage: 97.4
Contact Me
Email: [email protected]
LinkedIn: linkedin.com/in/Jiten-Ganwani
LeetCode: leetcode.com/u/JItz10
GitHub: github.com/Jitz10
Mobile: +91 9860566455
I am working on developing a YOLO-based model integrated with Explainable AI (XAI) techniques to enhance transparency and interpretability in high-stakes applications. By leveraging methods like Grad-CAM, Grad-CAM++, and Eigen-CAM, I aim to provide visual explanations of the model's predictions, highlighting the regions most influential in its decision-making process. This approach not only ensures accuracy and performance but also builds trust by making the model's reasoning more accessible to end-users. While the model is designed for a critical domain, the integration of XAI is a key step toward improving reliability and accountability in AI-driven systems.
Implemented a chatbot by fine-tuning large language models such as Gemma, LLama, Flan, and Falcon using Lora and
PEFT techniques for efficient parameter tuning. Enhanced performance by integrating these fine-tuned models with
RAG (Retrieval-Augmented Generation) pipelines, achieving accurate and context-aware responses.
• Developed multi-agent pipelines for improved model collaboration, enabling seamless data exchange and interaction
between specialized models for complex task handling.
Developed a Generative AI application using RAGs (Retrieval-Augmented Generation) and LangChain to analyze
content and generate thematic mappings, enabling insightful data-driven narratives.
• Engineered the application to scrape and process content from diverse sources such as social media, websites, and user
reviews, ensuring comprehensive content analysis and theme generation.