PROFILE SUMMARY

Ubaid Ul Rehman is a versatile software engineering professional with strong expertise in full-stack development, system design, and modern application engineering. Skilled in building scalable, production-grade solutions, he has developed numerous web applications, enterprise dashboards, and intelligent software systems using technologies such as PHP, JavaScript, Bootstrap, MySQL, Express.js, React, MongoDB, and Node.js. His industry experience includes delivering 10+ client applications, architecting robust backend APIs, and deploying real-world software solutions that prioritize reliability, usability, and performance. Expanding beyond traditional software engineering, Ubaid integrates advanced capabilities from data science and artificial intelligence into his development workflow. With an MS in Data Science, he leverages knowledge graphs, NLP, LLM-based agents, and predictive modeling to create intelligent, automation-driven systems for healthcare, education, and enterprise domains. His research includes a knowledge-graph-driven predictive framework for Type-1 Diabetes, currently under journal review. With 4+ years of combined academic and industry experience, Ubaid has taught core computing courses, including Programming, Operating Systems, Networks, and DBMS, while mentoring over 150 students using a practical, hands-on learning approach. His academic contributions span curriculum implementation, lab design, and interactive content development. In his industry role as an AI Engineer at BlinkiTech, Ubaid has built advanced LLM-powered chatbots, retrieval-augmented systems, and intelligent agents using OpenAI, Gemini, LangChain, Flask, Neo4j, and MongoDB. His professional background further includes IT support, technical writing, and software deployment. Positioned at the intersection of software engineering, applied AI, and modern computing education, Ubaid is committed to building high-impact technological solutions and contributing to both industry innovation and academic excellence.

RESEARCH AREAS / INTERESTS

1. Knowledge Graphs & Semantic AI – Designing graph-based reasoning systems for healthcare, diagnostics, and intelligent decision support.
2. Natural Language Processing (NLP) – Developing domain-specific NLP pipelines, clinical text mining, and LLM-driven agents for automated information extraction.
3. Predictive Modeling in Healthcare – Machine learning applications for disease risk prediction, patient monitoring, and personalized treatment pathways.
4. AI-Enhanced Drug Discovery Informatics – Computational approaches to therapeutic insights, biomedical data integration, and molecular analysis.
5. Clinical Data Science & EHR Analytics – Structuring and analyzing clinical records for outcome prediction and evidence-based decision making.
6. Software Systems for Digital Health – Designing scalable, full-stack applications and intelligent dashboards for hospitals and healthcare workflows.
7. Multi-Agent and Autonomous Decision Systems – Building LLM-powered agents for scheduling, automation, and operational optimization.
8. Data Visualization & Big Data Engineering – Large-scale data processing, visual analytics, and information design for actionable insights.
9. Educational Technology & Computer Science Pedagogy – Technology-driven learning experiences, interactive lab design, and curriculum development.