I teach AI and machine learning, build interactive learning tools for my students, and spent four years in industry as a technical and freelance consultant, turning data into models, dashboards and decisions.
- 🏫 Teaching AI, ML, deep learning and computer vision at SNMIMT Engineering College, Ernakulam
- 🧭 Supervising student projects, dissertations and internships
- 🛠️ Building interactive learning portals for KTU courses, from 3D networking labs to exam solvers
- 🔬 Exploring RAG, AI agents and LLM evaluation, and bringing them into the classroom
- 🤝 Open to research collaborations and consulting in intelligent systems
| Area | Tools and methods |
|---|---|
| 🤖 Generative AI & LLMs | Gemini and OpenAI APIs, prompt engineering, RAG, LangChain, LlamaIndex, embeddings and reranking, vector databases, LoRA / PEFT fine-tuning, AI agents and tool calling, agent workflows, Hugging Face Transformers, LLM evaluation (RAGAS, LangSmith), guardrails and structured outputs |
| 🧠 Machine & deep learning | Supervised and unsupervised learning, deep learning, NLP, time-series forecasting, anomaly detection, recommendation systems, reinforcement learning, explainable AI (SHAP / LIME), Optuna, scikit-learn, XGBoost, PyTorch, TensorFlow, Keras |
| 👁️ Computer vision | Image processing, YOLO, U-Net / SAM segmentation, ViT / CLIP, MTCNN, transfer learning, CNNs, OpenCV, ONNX Runtime, TensorFlow Lite, edge AI deployment |
| 📊 Data science & BI | Pandas, NumPy, SciPy, Matplotlib, Seaborn, Plotly & Dash, Power BI, Tableau, Microsoft Fabric, Databricks, PySpark, EDA, statistical analysis |
| 🗄️ Data engineering | SQL, MySQL, PostgreSQL, MongoDB, Azure Data Lake, ETL / ELT pipelines, Apache Spark, Apache Airflow, data modelling, pipeline automation |
| ☁️ MLOps & cloud | MLflow, Docker, Git and GitHub, CI/CD with GitHub Actions, FastAPI, Flask, Streamlit, REST APIs, model serving and monitoring, DVC, AWS, Microsoft Azure, Kubernetes |
| 💻 Programming | Python, SQL, C / C++, Java, MATLAB, JavaScript / TypeScript, React, Next.js, Pydantic, Pytest, Linux |
| 🔬 Research | Experimental design, statistical evaluation, benchmarking, ablation studies, reproducible experiments, Weights & Biases, literature review and research-gap analysis |
| 🌐 Web & visualisation | React, Next.js, Three.js, interactive data visualisation, 3D visualisation, interactive simulations |
| When | Role | Where |
|---|---|---|
| 2026 – now | 👩🏫 Assistant Professor, AI & ML | SNMIMT Engineering College, Ernakulam |
| 2025 | 👩🏫 Assistant Professor | Sri Vasavi Engineering College, Andhra Pradesh |
| 2022 – 2025 | 💼 Freelance Consultant | ML, computer vision and analytics for clients, Thrissur |
| 2021 | 💼 Technical Consultant | Technovalley Software India, Ernakulam |
| 2019 | 📄 IEEE ICACC paper | Harvestable black-pepper recognition with computer vision |
| 2017 – 2019 | 🎓 M.Tech, Information Technology (Software Systems) | Cochin University of Science and Technology |
| 2011 – 2015 | 🎓 B.Tech, Electronics & Communication | Sahrdaya College of Engineering and Technology (University of Calicut) |
Machine Learning · Artificial Intelligence Foundations: Machine Learning · Image Processing · Database Foundations: Creating and Manipulating Data · Advanced Selenium: Automation Frameworks
S. Joseph, N. F. Jane Rose and P. V. Akhil, "Harvestable Black Pepper Recognition Using Computer Vision," 2019 9th International Conference on Advances in Computing and Communication (ICACC), Kochi, India, IEEE, pp. 97–102. doi:10.1109/ICACC48162.2019.8986220
