Abid Hussain

Dual degrees in Computer Science and Mining Engineering with over seven years of experience in mining research and AI development. My earlier experience involved applying machine learning techniques to tackle practical challenges in the mining sector as research assistant and currently focused on designing intelligent systems leveraging natural language processing and advanced AI. Seeking to contribute to innovative research that integrates AI and mining to advance sustainable, data driven solutions.

• Programming Languages: Python, R, JavaScript
• AI/ML: TensorFlow, PyTorch, HuggingFace, Scikit Learn
• Data Analysis: PySpark, Numba, NumPy, Pandas
• Visualization: Matplotlib, Seaborn
• Web Development: Django, FastAPI, Flask, Node.js
• NLP & Agentic AI: spaCy, LangChain, OpenAI API, Chainlit, AWS Bedrock, Dialogflow CX
• LLMs: OpenAI, Claude, Mistral, Hugging Face Transformers
• DevOps & Collaboration: Docker, Git, Bitbucket, GitHub, CI/CD Pipelines
• Mining Softwares: SGeMs, Surpac
• Productivity Tools: Microsoft Office (Word, Excel, PowerPoint),

• Ahmed, W., Muhammad, K., Glass, H. J., Chatterjee, S., Khan, A., & Hussain, A. (2022). Novel MLR-RF-Based Geospatial Techniques: A Comparison with OK. ISPRS International Journal of Geo-Information, 11(7), 371. https://doi.org/10.3390/ijgi11070371

Constraint-Based Clustering Algorithm for Open-Pit Mine Planning

University of Engineering and Technology, Peshawar (Research Project)

• Developed a clustering method to group mining blocks by their attributes while respecting constraints like size, shape, and rock type.
• Enhanced short-term mine planning efficiency and lowered computational costs.
• Validated the approach on real-world datasets, achieving consistent and practical results.
• Tools: Python, geospatial libraries, heuristic optimization.

AI-Based Lithological Mapping Using Remote Sensing Data

Gomal University, Dera Ismail Khan (Research Project)

• Applied SVM and ANN models to classify lithological units in the remote Kohat Basin using Sentinel-2 MSI imagery.
• Used PCA, MNF, and geological maps for reliable data annotation and model training.
• Achieved 95%+ classification accuracy, with SVM outperforming in efficiency and deployment ease via Google Earth Engine.
• Tools: Google Earth Engine, Google Colab, PCA, SVM, ANN.

Advance AI Health Calling Agent

• Built a high-performance Retrieval-Augmented Generation (RAG) system using LLMs for accurate domain-specific responses.
• Integrated vector search, semantic retrieval, and custom prompt tuning to improve contextual accuracy.
• Tools: GPT-4, FAISS, LangChain, Hugging Face, Prompt Engineering.

AI-Powered HR Assistant – Sesame-HR

• Built a multilingual HR chatbot using Langchain and Chainlit for 24/7 employee support and platform guidance.
• Integrated automated ticketing with HubSpot for unresolved queries and issue tracking.
• Delivered scalable, real-time assistance for global teams across multiple locations.

Resume Recommendation Engine

• Built an AI/NLP-powered API to recommend relevant job matches based on resume content.
• Designed preprocessing, training, and inference pipelines using large-scale labeled job market data.
• Delivered a scalable, re-trainable system with real-time inference capabilities via API.

• Data Structures and Algorithms Specialization
• Applied Data Science with Python Specialization
• Python for Everybody Specialization
• DeepLearning.AI TensorFlow Developer Specialization
• AI for Everyone
• AWS Fundamentals: Going Cloud-Native