Ved Ramdurg
Intern @ LTIMindtree
About
I’m skilled in Python, C++, JavaScript, and frameworks like React, Flask, Django, with experience in cloud platforms (AWS, Azure, GCP), containerization, and TDD. My project work reflects a strong focus on scalable, secure, and user-focused systems—backed by industry exposure at LTIMindtree and College of Military Engineering, Pune. I enjoy solving complex problems, experimenting with ML algorithms like Q-learning and K-Means, and turning ideas into functional, tested code. I'm now seeking exciting opportunities in AI, data engineering, or software development where I can contribute and grow. Let’s connect and build something impactful!
Ireland
Dublin
Information Technology & Services
Problem Solving, Computer Science, Software Deployment, Programming, Microsoft Excel, Time Management, Presentation Skills, Team Collaboration, Analytical Skills, Circuit Design, Global Positioning System (GPS), Radio-Frequency Identification (RFID), ESP32 Microcontrollers, PostgreSQL, MySQL, MongoDB, Scikit-Learn, TensorFlow, Real time Analytics Dashboards , Plotly
Experience

Intern
Pune, Maharashtra, India
- Developed a tool using LangChain for automating news research: ingestion of news articles, semantic analysis, and summarisation. - Built pipelines for data extraction, keyword/topic clustering, and query - based retrieval to support efficient insight generation from largenewsdatasets. - Delivered a user - facing interface enabling real- time news querying and adaptive article summarisation, enhancing decision-making speed in research workflows.

Intern
Pune, Maharashtra, India
- Developed and trained machine learning models for camouflage generation, including object detection (Mask R-CNN) and image segmentation (semantic segmentation with CNNs). - Implemented generative models (GANs/VAEs) for diverse camouflage patterns, incorporating feature extraction, environment-specific parameters, and multiple styles (Pixelized, Marpat, Maple, Blots, UCP, Cache). - Conducted evaluation and refinement of generated patterns using objective metrics and expert assessment, optimizing model accuracy and pattern effectiveness for real-world applications.
Ved Ramdurg's Contact Information
Phone
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