data/vector_store/documents.json

{"documents": {"fa2c3a25-75fe-40a7-b790-5a5480805ee7": {"title": "Computer Vision", "chunks": ["I am a Computer Vision Engineer specializing in developing intelligent systems that extract meaningful information from visual data. My expertise includes image classification, object detection, segmentation, OCR, and real-time video analytics using deep learning frameworks such as PyTorch and TensorFlow. I have hands-on experience working with CNNs, Vision Transformers (ViT), YOLO, and OpenCV, and I frequently deploy models in real-world applications like autonomous systems, surveillance, and medical imaging. I also integrate computer vision pipelines with APIs, cloud services, and edge devices for scalable, production-grade solutions."], "type": "text"}, "8e41a822-d13e-4565-9e3b-149377152424": {"title": "Computer Vision", "chunks": ["I am a Computer Vision Engineer with over 5 years of hands-on experience building intelligent visual systems using deep learning and traditional image processing techniques. My core expertise lies in object detection, image classification, instance and semantic segmentation, pose estimation, and OCR systems. I work extensively with PyTorch, TensorFlow, OpenCV, Detectron2, and YOLOv8, and I\u2019ve deployed several scalable vision models into production environments using FastAPI, ONNX, TensorRT, and cloud platforms like AWS and GCP.\r\n\r\n\ud83d\udd0d Notable Projects:\r\nReal-Time Traffic Violation Detection System: Built and deployed a computer vision pipeline that detects vehicles, reads license plates, and flags violations in real-time using YOLOv5 and EasyOCR.\r\n\r\nAI-Powered Quality Control System: Designed a defect detection system for manufacturing lines that reduced manual inspection costs by 70%.", "AI-Powered Quality Control System: Designed a defect detection system for manufacturing lines that reduced manual inspection costs by 70%.\r\n\r\nMedical Imaging Analysis: Worked on deep learning models to detect lung abnormalities in chest X-rays, improving diagnostic speed and accuracy for radiologists.\r\n\r\n\ud83c\udf93 Education & Certifications:\r\nB.Sc. in Computer Science & Engineering\r\n\r\nDeep Learning Specialization by Andrew Ng (Coursera)\r\n\r\nOpenCV AI Masterclass\r\n\r\nNVIDIA Certified Jetson Edge AI Developer\r\n\r\n\ud83d\udcbc Work Style & Values:\r\nI follow a data-centric and result-driven approach, emphasizing clean code, reproducibility, and efficient model deployment. I value collaboration, transparency, and ethical AI practices, especially in high-stakes domains like healthcare and surveillance.\r\n\r\n\ud83c\udfc6 Recognition:\r\nAwarded Top Innovator at the National AI Challenge 2023\r\n\r\nInvited speaker at CVPR Workshop on AI in Smart Cities"], "type": "text"}, "141ee532-923d-4b03-8ec4-e12b9ed71faa": {"title": "Natural Language Processing", "chunks": ["I am an NLP Engineer and researcher with over 6 years of experience specializing in transformer-based language models, sentiment analysis, named entity recognition, text summarization, and retrieval-augmented generation (RAG) systems. I am proficient in Hugging Face Transformers, spaCy, PyTorch, LangChain, and LLaMA-based LLMs, and have built NLP pipelines for domains ranging from healthcare and finance to legal tech and social media analytics.\r\n\r\n\ud83e\udde0 Notable Projects:\r\nBangla Sentiment Analysis Platform: Created a multilingual sentiment analysis model fine-tuned on Bangla social media texts, which outperformed BERT-baselines by 11% F1-score.\r\n\r\nAI Legal Assistant: Developed a question-answering and document summarization tool for legal documents using LLaMA and vector-based semantic search (FAISS).\r\n\r\nRAG-Based Research Assistant: Built an NLP-powered assistant for biomedical literature search using a custom Retriever-Ranker-Generator pipeline with Haystack and OpenAI embeddings.", "RAG-Based Research Assistant: Built an NLP-powered assistant for biomedical literature search using a custom Retriever-Ranker-Generator pipeline with Haystack and OpenAI embeddings.\r\n\r\n\ud83c\udf93 Education & Certifications:\r\nM.Sc. in Artificial Intelligence\r\n\r\nNLP Specialization \u2013 DeepLearning.AI (Coursera)\r\n\r\nHugging Face Transformers Certified Developer\r\n\r\nLangChain Bootcamp Graduate\r\n\r\n\ud83d\udcbc Work Style & Values:\r\nI embrace research-oriented engineering\u2014prototyping rapidly but optimizing for scalability and relevance. I prioritize fairness, multilingual support, and bias mitigation when building NLP systems. Collaboration with domain experts is a key part of my workflow.\r\n\r\n\ud83c\udfc6 Recognition:\r\nWinner of the AI4Good NLP Challenge 2022\r\n\r\nResearch paper on Low-Resource Sentiment Analysis accepted at EMNLP 2024 Workshop"], "type": "text"}}, "document_embeddings": {"fa2c3a25-75fe-40a7-b790-5a5480805ee7_0": {"doc_id": "fa2c3a25-75fe-40a7-b790-5a5480805ee7", "chunk_index": 0}, "8e41a822-d13e-4565-9e3b-149377152424_0": {"doc_id": "8e41a822-d13e-4565-9e3b-149377152424", "chunk_index": 0}, "8e41a822-d13e-4565-9e3b-149377152424_1": {"doc_id": "8e41a822-d13e-4565-9e3b-149377152424", "chunk_index": 1}, "141ee532-923d-4b03-8ec4-e12b9ed71faa_0": {"doc_id": "141ee532-923d-4b03-8ec4-e12b9ed71faa", "chunk_index": 0}, "141ee532-923d-4b03-8ec4-e12b9ed71faa_1": {"doc_id": "141ee532-923d-4b03-8ec4-e12b9ed71faa", "chunk_index": 1}}}