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| Harish KB | |
| 8248052926 | |
| # [email protected] | |
| ï Harish KB | |
| § HARISH20205 | |
| Education | |
| Vellore Institute of Technology (VIT) | |
| Vellore, India | |
| MTECH (Integrated) in Computer Science and Engineering(CGPA: 8.46) | |
| Aug 2022– July 2027 | |
| Experience | |
| AI Research and Development Intern (Remote) | |
| Jun 2024 – Oct 2024 | |
| eBramha Techworks Private Limited | |
| • Developed a speech-to-text summarization system integrating Whisper for transcription and Pegasus for | |
| summarization, enhancing processing speed and efficiency while significantly reducing overall processing | |
| time and improving system performance. | |
| • Conducted in-depth research on advanced NLP models such as PEGASUS, BERTsum and BART, | |
| contributing to the development of effective solutions for tasks like summarization and language | |
| understanding. | |
| • Built a neural network for handwritten digit classification (MNIST) from scratch, implementing core | |
| machine learning concepts like gradient descent and one-hot encoding. | |
| Projects | |
| VerbiSense: Interactive Document Retrieval System - Link | |
| • Built the VerbiSense backend with FastAPI, optimizing document uploads, query processing, and API | |
| performance for real-time interactions with the React frontend. | |
| • Integrated Retrieval-Augmented Generation (RAG) for improved document retrieval and response | |
| generation. | |
| • Applied PyTorch models for advanced NLP tasks like semantic understanding and context-based querying. | |
| Speech-to-Text Summarization | |
| • Developed a Python script that improved audio transcription accuracy by 30% and reduced | |
| post-processing time by 35%. | |
| • Designed and implemented the frontend interface to provide a seamless, user-friendly experience for | |
| individuals interacting with the speech-to-text summarization system. | |
| Technical Skills | |
| Languages: Python, Java, C/C++ | |
| Machine Learning: Supervised learning, unsupervised learning, NLP, LLMs | |
| Tools: GitHub, Docker, Linux, AWS, Hugging Face | |
| Computer Vision: OpenCV, YOLO | |
| Backend: FastAPI, Flask, MongoDB, Firebase | |
| Areas of Interest | |
| • Machine Learning and AI | |
| • Full Stack Development | |
| • Cloud Computing and DevOps Practices | |
| Certifications | |
| • Coursera: Supervised Machine Learning: Regression and Classification | |
| • Coursera: Advanced Learning Algorithms | |
| • Coursera: Generative AI with Large Language Models | |