Name: Dhinesh Babu C M
Education: B.E. Computer Science and Engineering, College of Engineering Guindy, Anna University
Year: Final Year Undergraduate (2023 - 2027) | CGPA: 9.19/10.0
Experience: SWE Intern @ American Express, Bengaluru (May - Jul 2026)
Focus: Full Stack Development · Data Science · Machine Learning
Currently_exploring: Building impactful tech solutions that solve real-world problems
SWE Intern, American Express — Bengaluru, India · May 2026 – Jul 2026
Built Change Studio, an internal change-readiness platform for ITSM reporting, CI/workgroup management, and RFC conflict detection.
- Developed the CAART Report, Conflict View, CI Inventory, and Workgroup Directory modules using React, TanStack Start, PostgreSQL, Drizzle ORM, and REST APIs
- Integrated multiple ITSM APIs to generate team-specific change reports and consolidate RFC, task, CI, and workgroup data
- Implemented conflict detection to flag overlapping change windows on the same CI across different RFCs
- Collaborated with mentors and stakeholders to refine requirements, improve UI/UX, and prepare the app for production
AIML Intern, Elevate Labs — Remote · May – Jun 2025
- Built practical NLP/ML applications — resume ranker, sign language recognition — using Python, ML libraries, and Gradio
Certification: IBM Data Science Professional Certificate (May – Jul 2025) — Data Analysis, Visualization & Machine Learning foundations
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Real-time traffic analytics pipeline using Apache Kafka and Apache Flink to process high-volume streaming data with low latency, enabling congestion detection and traffic pattern analysis. Stack: Apache Kafka, Apache Flink |
Eco-friendly item donation platform with login/auth and AI microservices for image-based classification and auto-description via the Gemini API. Stack: MERN, Gemini API |
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Full-stack study management platform with smart folder organization, priority tagging, and efficient study resource management. Stack: Spring Boot, React |
Complete modern landing page built as an intern interview task — responsive design, clean UI, contemporary web design patterns. Stack: HTML, CSS, JavaScript |
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End-to-end ML pipeline to classify Falcon 9 landing success using real-world SpaceX data — EDA, modeling, validation, and an interactive Dash dashboard. Stack: Python, Pandas, scikit-learn, Dash |
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- 🏅 Certifications/Recognition: React, Data Science, NPTEL
- 📌 Office Bearer, IR Domain – CSEA, CEG
- 🤝 Volunteer, National Service Scheme (NSS)
English (Professional) · Tamil (Native)
