Name: Yogeshwar Shendye
Profile: Data Scientist
Email: yushendye@gmail.com
Phone: +1 7828824819
Technical Skills
About me
I am a Data Scientist with expertise in RAG systems, LLMs, computer vision, and NLP. I hold a Master of Computer Science degree from Dalhousie University (2023-2024) with a thesis on semantic segmentation for medical image analysis.
Currently, I work as a Data Engineer at IBM, where I build production-grade RAG pipelines using Amazon Bedrock and AWS technologies. I have designed and optimized deep learning models for medical image segmentation, achieving state-of-the-art results (F1 score: 0.966).
My expertise spans PyTorch, TensorFlow, Vision Transformers, U-Net architectures, and cloud platforms like AWS and Azure. I have published research in peer-reviewed journals and presented findings at international conferences. I am passionate about solving real-world problems through machine learning and artificial intelligence.
Certifications
In this section I am mentioning all of the certificates and internships that I have recieved throughout my college days!
Object Oriented Programming in Java
Ceritificate from Coursera, University of California, San Diego
Tensorflow in Practice Specialization
This was the specialization course on deep learning by deeplearning.ai
Deep learning specialization
This was the specialization course on deep learning by deeplearning.ai
Python specializaion
This was the specialization course from Coursera from University of Michigan on python programming.
Internships
In this section I am mentioning all of the internships that I have recieved throughout my college days!
Training cum internship in Android Development, IBM
This was a work from home training cum internship at IBM. Duration of this internship was 2 months. During this internship, I was mentored by Mr. Rahul Kumar Sir, and Mr. Krishna Pal Sir. During this internship I worked on a real time project of MPLAD, which was developed for helping lay men communicate with members of parliament.
Training cum internship in Data scinece and Machine learning
This was a work from home training cum internship at IBM. Duration of this internship was 2 months. During this internship, I was mentored by Mr. Karan Mehta Sir, and Mr. Rohit Kumar Sir. During this internship I worked on a real time project of bicoin price prediction.
Research internship in machine learning (Currently working)
This was a work from home research based internship at Aero2Astro. In this internship I was mentored by Mr. Ted Soloman sir and Mr. Hemanth Dandi. In this internship, my main role was reading research papers, data collection, data processing and model creation.
13
Projects Completed4
Internships16
Certificates3
Research papersProjects
I have been working on various projects based on android development, wweb development and machine learning. I really enjoy working on machine learning projects.
Professional Experience
My recent professional work in data engineering, computer vision, and machine learning
Data Engineer
IBM, Halifax, Nova Scotia | April 2025 - Present
Built and owned production RAG pipeline using Amazon Bedrock, improving retrieval accuracy by 35% and cutting LLM hallucinations by 25%. Deployed OpenSearch Serverless vector search, reducing latency from 250ms to 80ms. Automated data ingestion with Airflow DAGs, reducing manual maintenance by 90%.
Computer Vision Researcher
Alentic Microscience, Halifax, Nova Scotia | Apr 2023 - Aug 2024
Designed U-Net and Vision Transformer models for medical image segmentation, improving F1 score to 0.966. Processed and curated 3000+ blood smear microscopy images with augmentation pipelines. Presented research findings at Dalhousie AI Symposium to 150+ attendees.
Machine Learning Intern
PM AM IT Services, Mumbai, India | Sep 2022 - Dec 2022
Developed real-time human pose estimation using OpenVINO for video analytics, achieving 5% error rate. Built edge-optimized computer vision pipeline using Open3D and Docker, achieving 93% precision on embedded devices.
Data Science Trainee
MyVishwa, Pune, India | Nov 2021 - Mar 2022
Led end-to-end development of CNN-based object detection system for financial document verification. Designed preprocessing pipelines and built interactive visualizations using D3.js and Plotly.
Publications & Research
My research contributions in computer vision and artificial intelligence
Platelet Enumeration
"Platelet enumeration in dense aggregates"
Gillis, H. M.; Shendye, Y.; et al. | arXiv:2505.02751 | May 2025
AI in Urology - Part 1
"Implementing AI in Urology: Instance Segmentation"
Journal of Urology, 213(5S) | May 2025
AI in Urology - Part 2
"Getting Started with AI in Urology: Tips and Tricks"
European Urology, 87 | 2025