- HonorNamed in the Elsevier-Stanford World's Top 2% Scientists for 2026, the second year in a row
- PaperPublished in the Journal for Immunotherapy of Cancer (2025): causal AI for patient selection in early-stage lung cancer
- PaperPublished in Nature Communications (2025): treatment-effect estimation for immunotherapy in lung cancer
Qasem Al-Tashi, PhD · Houston, Texas
Building the futureof Enterprise AI
AI/ML Engineer & Data Scientist at NOV Inc, Houston TX. Transforming industrial operations with intelligent, scalable solutions — from cancer research at MD Anderson to enterprise-scale AI systems.
Pillars of Impact: Oncology, Swarm AI & Enterprise Systems
Ranked Among the World's Top 2% Scientists in Artificial Intelligence
Consecutive single-year global recognition celebrating foundational contributions to swarm intelligence, deep prognostic survival modeling in oncology, and causal inference. Cited 7,000+ times across top journals including Nature Communications and The Lancet Digital Health.
AI Biomarker Discovery & Precision Oncology
Led deep survival modeling, biomarker identification, and subgroup treatment heterogeneity analysis published in high-impact medical journals.
Cloud RAG & Automated Industrial Systems
Architected scalable multi-modal RAG systems with AWS Bedrock, Amazon Athena SQL agents, and automated QA verification.
SwarmDeepSurv
Novel open-source Python framework combining swarm meta-heuristics with deep neural networks for high-dimensional survival modeling.
Academic Leadership
Co-advisor to 3 PhD & 4 MS candidates; peer reviewer for IEEE, Springer Nature, and Elsevier top journals.
Core Methodologies & Production Architectures
Bridging the frontier of computational oncology at world-leading cancer institutes with enterprise AI systems running at industrial scale.
Computational Oncology & Cancer Biomarkers
Developing deep prognostic survival models and causal inference algorithms for non-small cell lung cancer (NSCLC) and biomarker discovery, optimizing personalized therapy regimens.
Published in Nature Communications, The Lancet Digital Health & Cell Reports Medicine
- DeepSurv Neural Networks
- Cox Proportional Hazards
- Causal Forests
- Survival SVM
- High-Dimensional Genomics
Selected High-Impact Publications (Nature, Lancet & Cell)
“Weighting Subgroup Identification Methods for Estimating Treatment Effect in NSCLC Patients Receiving Immune Checkpoint Inhibitors Alone or with Chemotherapy.”
Saad MB, Al-Tashi Q, Hong L, Verma V, Li W, Boiarsky D, Li S, et al.
“Development and Validation of a Machine Learning Model to Predict Myocardial Blood Flow and Clinical Outcomes from Patients' Electrocardiograms.”
Alahdab F, Saad MB, Ahmed AI, Al-Tashi Q, Aminu M, Han Y, Moody JB, et al.
“Predicting Benefit from Immune Checkpoint Inhibitors in Patients with Non-Small-Cell Lung Cancer by CT-Based Ensemble Deep Learning: A Retrospective Study.”
Saad MB, Hong L, Aminu M, Vokes NI, Chen P, Salehjahromi M, Qin K, ..., Al-Tashi Q, et al.
A little about me
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%.
NOV Inc. · AWS Bedrock
MD Anderson Alumni
Stanford Top 2% (2×)
