Doctor Qasem Al-Tashi is a Data Scientist / AI Research Engineer at National Oilwell Varco (NOV), a former Research Scientist at The University of Texas MD Anderson Cancer Center, and a member of the Elsevier-Stanford list of the World's Top 2% Scientists (2025 and 2026, AI and Image Processing). Al-Tashi's work develops machine learning and deep learning methods — from swarm-intelligence optimization and deep survival networks to causal inference and retrieval-augmented LLM systems — that advance clinical decision-making and industrial AI. With 60+ publications, 7,000+ citations, and an h-index of 24, the research has appeared in Nature Communications, The Lancet Digital Health, Patterns (Cell Press), and Cell Reports Medicine.

In industry, Al-Tashi is passionate about advancing enterprise AI with intelligent, scalable solutions that transform industrial operations, accelerate AI adoption, and drive smarter, more sustainable decision-making. At NOV, the RAG and LLM systems built on AWS Bedrock have boosted structured-query accuracy by 40% and cut manual query handling by 80%.

Al-Tashi's research spans AI-driven biomarker discovery and precision medicine, swarm intelligence and metaheuristic optimization for feature selection, causal inference and subgroup identification for treatment effect estimation, computer vision for industrial and medical imaging, large language models and retrieval-augmented generation for decision support, and survival analysis and prognostic modeling in oncology.

Al-Tashi holds a PhD in Information Technology from Universiti Teknologi PETRONAS (Malaysia) and completed a postdoctoral fellowship at MD Anderson Cancer Center. Beyond research, Al-Tashi serves as an editor and reviewer for AI and healthcare journals, sits on international conference committees, and mentors the next generation of researchers — co-advising 3 PhD and 4 MS students, and releasing open-source research software such as SwarmDeepSurv so that others can reproduce and build on the work.