Hare Krishna! 🙏
Hello! I’m Divyansh Pandey, a B.Tech student in Computer Science and AI at Manipal University Jaipur, passionate about building intelligent systems and advancing research in artificial intelligence.
My core expertise lies in Machine Learning, Deep Learning, NLP, Computer Vision, MLOps, LLMOps, and Generative AI. I am skilled in Python, Java, JavaScript, C, and SQL, with hands-on experience in frameworks and tools such as TensorFlow, PyTorch, Keras, XGBoost, LangChain, LangGraph, LangServe, Flask, Django, Streamlit, Tableau, PowerBI, and MATLAB. On the data side, I work extensively with Pandas, NumPy, Seaborn, Plotly, and databases including MySQL, PostgreSQL, MongoDB, FAISS, ChromaDB, and AstraDB.
For deployment and scalability, I bring experience in MLOps and LLMOps workflows using Docker, Kubernetes, MLflow, DVC, BentoML, DAGsHub, Airflow, Astro Airflow, TaskFlow, LangSmith, and Grafana. I am also comfortable with cloud platforms such as AWS (S3, EC2, IAM, RDS), GCP, and Azure, enabling me to take AI projects from development to large-scale deployment.
I also gained valuable research experience at IIT Hyderabad, contributing to the development of a federated learning model for decentralized medical image classification and segmentation. Our approach reduced communication overhead by 45% and used 55% fewer resources compared to standard baselines, while addressing data privacy and heterogeneity challenges.
My academic and research journey includes being on the Dean’s List for Excellence in Academics, and contributing as first author to a paper published by Springer Nature on barbell exercise recognition. I also have a paper under review on the role of AI in advancing medical diagnostics.
I am deeply motivated by the potential of AI to transform healthcare and society. My interests extend to Generative AI, Large Language Models, and advanced deployment practices (LLMOps). Beyond building models, I enjoy sharing knowledge, collaborating with peers, and continuously exploring new ideas at the intersection of AI, healthcare, and real-world applications.
I am now seeking opportunities in Machine Learning, Deep Learning, NLP, Computer Vision, MLOps, LLMOps, and Generative AI, where I can apply my skills, contribute to impactful projects, and grow as a researcher and practitioner. 🚀
