👋 Hi, I'm Hariom Pandya
🎓 Ph.D. in Artificial Intelligence | 🤖 AI/ML/NLP Researcher | 🧠 Python Developer | 🤗 Hugging Face Contributor
I’m a research-oriented AI and ML professional with a Ph.D. focusing on Deep Learning, NLP, and LLMs.
My work bridges academic research and practical AI solutions, particularly in question answering, multilingual NLP, and language model adaptation.
I actively publish open-source models on 🤗 Hugging Face and author peer-reviewed research papers in top-tier journals and conferences.
🌍 Passionate about making AI accessible, interpretable, and multilingual.
- 🧩 Natural Language Processing: Question Answering, Sentiment Analysis, Embeddings
- 🧠 Deep Learning: Transformer-based architectures, low-resource learning
- 🧑💻 Python Development: AI pipelines, automation, and applied research tools
- 🧾 Research & Publications: Author of 6+ international papers in AI and NLP
- 🌐 Open Source: Contributor on Hugging Face and GitHub AI projects
| 📝 Title | 📚 Venue |
|---|---|
| Does learning from language family help? A case study on a question-answering task | Cambridge University Press |
| Enhancing Low-Resource Question-Answering Performance Through Word Seeding and Customized Refinement | International Journal of Advanced Computer Science Applications (IJACSA) |
| Cascading Adaptors to Leverage English Data to Improve Performance of Question Answering for Low-Resource Languages | ACL Anthology (ICON Conference) |
| Question Answering Survey: Directions, Challenges, Datasets, Evaluation Matrices | arXiv-cs |
| Satellite Image Classification with Data Augmentation and Convolutional Neural Network | Springer – Lecture Notes in Electrical Engineering |
| A Novel Approach for Vehicle Detection and Classification | IEEE International Conference on Computer Communication and Informatics |
📖 View all publications on Google Scholar →
Explore my 12 AI/NLP models on Hugging Face:
👉 https://huggingface.co/hapandya
🔍 Focus Areas:
- Multilingual Question Answering
- Contextual Embeddings for Low-Resource Languages
- Transformer Fine-tuning Experiments
| 📝 Title | 📚 Repo link |
|---|---|
| Railway QA | RAG based QA System |
| Retrival QA - Chromadb | similarity-search |
| Chat Agent LiveApp | ai-chatbot |
| Echo Agent | ai-echo-agent |
| Category | Tools |
|---|---|
| 💻 Languages | Python, C, C++ |
| 🧩 AI/ML/NLP | Transformers, LLMs, QA, Chatbots, Sentiment Analysis, Embeddings |
| 🌐 Frameworks | FastAPI, Odoo |
| 🗄️ Data | VectorDB, PostgreSQL |
| 🧰 Tools | Git, Linux, JSON, XML |
- ⚡ Efficient fine-tuning for multilingual transformer models
- 🔍 Custom retrieval-augmented generation (RAG) pipelines
- 🧩 Model interpretability and optimization techniques
⭐ “Bridging academic AI research with real-world innovation through open collaboration.”