Machine Learning Data Science

Rishabh Patil

+1-929-***-**** *******@***.*** ï Rishabh Patil § rishabhpatil

EDUCATION

• New York University Sep 2024 - May 2026

MS in Data Science — CGPA: 3.55/4 New York, USA

Coursework: Natural Language Understanding, Machine Learning, Computational Linear Algebra

• University of Mumbai Dec 2020 - May 2024

B.Tech in Data Science with Honors in Computational Finance — CGPA: 9.53/10 (3.96/4) Mumbai, India Relavant Coursework: Big Data, Computer Vision, Reinforcement Learning, Cloud Computing SKILLS

• Languages and Tools:Python, R, SQL, MS Excel, Git, Github, Jupyter Notebook, Spyder, Pycharm

• Statistical Analysis:Distributions, Predictive Modeling, A B testing, Causal Inference, Data Validation, and Hypothesis Testing.

• Machine Learning:Tensorflow, Keras, OpenCV, Pandas, Numpy, Pytorch, YOLO, NLP, LangChain

• Web Technology and Visualization: Streamlit, Flask, React, Django, PowerBI, Tableau, Looker

• Databases and Cloud Platform:MySQL, PostgreSQL, SQLite, MongoDB, AWS

• Big Data:Hadoop, Apache Spark, Kafka, CUDA, BigQuery, Cassandra, Kubernetes, Snowflake PROFESSIONAL EXPERIENCE

• Solar Secure Solution Feb 2023 - April 2023

Junior Machine Learning Engineer (Intern) Bangalore, India

Designed an innovative script integrating Computer Vision, NLP, and Azure OCR, which facilitated the extraction of critical data points from diverse sources; reducing processing time by 25%.

Created an innovative machine learning capstone program featuring immersive labs and tailored resources for 100 employees, fostering a culture of continuous learning.

Achieved a 20% increase in skill assessment scores and an 85% project completion rate through the initiative, establishing a culture of ongoing professional development.

• Acmegrade Pvt Ltd July 2022 - Sept 2022

Artificial Intelligence and Machine Learning Trainee & Intern Bangalore, India

Contributed to a collaborative project on an advanced recommendation system, resulting in a 15% profit increase for over 50 small businesses through personalized recommendations.

Identified problem areas and conducted technical research, leading to the development of 3 innovative products that improved customer retention by 25%.

PROJECTS

• Personalized Recipe Recommendation System Using LLM July 2023 - May 2024 Retrieval Augmented Generation, OpenAI GPT-3.5, OpenAI text-ada-002 Embedding Model, Langchain [§]

Engineered a visually appealing interface dedicated to collecting essential user preferences, leading to a significant 35% rise in engagement.

Utilized the OpenAI text-ada-002 embedding model to create dense vector embeddings and develop a search algorithm, improving recipe match accuracy by 40% and reducing irrelevant suggestions by 25% .

Integrated OpenAI GPT-3.5 to enhance recipe recommendations, achieving a 50% increase in user satisfaction based on feedback.

• Driver Drowsiness Detection System Using YOLO V5 Jan 2022 - Jan 2024 YoloV5, Streamlit, CNN, Espeak Module, DL [§]

Developed two YOLOv5 models for driver drowsiness detection—Eye Position and Yawning Models—achieving 85% accuracy and improving alertness response time by 30% with real-time probability scores and an audible alarm.

Engineered an AI-driven system combining CNN outputs, reducing false positives by 20% and enhancing accuracy by 15% while processing over 1 million data points. PUBLICATIONS

[C.1] Patil, R., Jha, S., Vartak, P. (2024). Driver Drowsiness Detection System Using YoloV5. In: Sharma, N., Goje, A.C., Chakrabarti, A., Bruckstein, A.M. (eds) Data Management, Analytics and Innovation. ICDMAI 2024. Lecture Notes in Networks and Systems, vol 998. Springer, Singapore. [ ] AWARDS

• THIRD prize in AI and Deep Learning track- Driver Drowsiness Detection System Using YOLO V5 Jan 2024 International Conference on Data Management and Analytics and Innovation. ICDMAI 2024 [§]

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