Rohit P Mandal / Homepage / Twitter / LinkedIn / Google Scholar / LeetCode / YouTube
I am an Applied Machine Learning developer focused on building scalable machine learning solutions using Python, deep learning, and open-source systems. I have served as a Section Leader for Stanford Code in Place (CS106A), mentoring global learners in Python and computational thinking.
I have provided structured mentoring to international learners in programming fundamentals, data structures, and machine learning, supporting their academic development and technical interview preparation. My work includes developing and maintaining open-source AI projects used by a global community.
I have published research in applied machine learning, including Springer proceedings on Alzheimer’s detection using brain MRI images and CNN-based approaches for smart agriculture applications.
- Open Source Lead: Creator & maintainer of qxresearch AI (2,900+ GitHub stars)
- Stanford Code in Place (CS106A): Section Leader (2023, 2024, 2026)
- Industry Experience: IBM, Jio (training programs → offer letters), Juppiter AI Labs, IEMLabs
- AI Mentor: Guided global learners in Python, DSA, and Machine Learning
- Content Creation: 32,000+ YouTube views on AI & Python tutorials
- Technical Writing: 21,000+ reads on HackerNoon
- Contact:
[email protected]
Research Papers
- Water Content Prediction in Smart Agriculture of Rural India Using CNN and Transfer Learning Approach. Link
- Variational Autoencoder-Based Imbalanced Alzheimer Detection Using Brain MRI Images. Link