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Applied AI Scientist & Research Pharmacist

Youssef Abo-Dahab

Bridging advanced machine learning and the biomedical domain. Building multimodal deep learning frameworks for drug repurposing, genomic variant interpretation, and target discovery.

UCSF & Stanford University

01

About

Applied AI Scientist & Research Pharmacist bridging the gap between advanced machine learning and the biomedical domain. I develop multimodal deep learning frameworks for drug repurposing, genomic variant interpretation, and target discovery.

My technical expertise spans Graph ML (PyTorch & PyG), molecular docking, PK/PD modeling, and pharmacogenomics, integrating these distinct disciplines to build rigorous, biologically interpretable models.

I leverage a unique "Clinician-Coder" background (Pharm.D. + MS in AI) to validate computational predictions against real-world biological and clinical data, with training at both UCSF & Stanford University.

Affiliations

UC San Francisco

MS in AI & Computational Drug Discovery

Stanford University

CS224W: Machine Learning with Graphs

Focus Areas

Drug RepurposingGraph MLMolecular DockingPK/PD ModelingPharmacogenomicsDeep Learning

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Experience

University of California, San Francisco

Researcher & Instructor/Sept 2024 -- Present

Zhao Lab (Capstone Project)

Jul -- Dec 2025

Multi-Modal Computational Drug Repurposing: Conducted large-scale benchmarking of computational docking and ML-based scoring approaches. Integrated optimized pipelines with molecular simulations, scRNA analysis, UCSF's clinical data (RWE), and pharmacology-informed ML models to discover drug repurposing candidates for Parkinson's Disease.

Giacomini Lab

Since Feb 2025

Developed "TripleVar," a multimodal deep learning framework to predict pathogenic variants in SLC19A2/A3 thiamine transporters by integrating genomic (DNABERT-2) and protein (ESM-2) embeddings with allele frequency data. Achieved 93.3% accuracy and 1.0 AUC on ClinVar benchmarks. Deployed pipeline to screen ~29,000 unclassified variants, identifying 111 high-confidence pathogenic candidates currently undergoing functional HEK cell-based uptake assay validation. Abstract accepted for ASCPT Annual Conference 2026.

Instructor: Digital Therapeutics

Jan -- Feb 2025

Developed and taught a 6-session mini-course on Digital Therapeutics for Pharm.D. students.

Benet Lab (Research Assistant)

Sept -- Oct 2024

Studied the application of Kirchhoff's Laws to model drug elimination without traditional differential-equation frameworks under Dr. Leslie Z. Benet.

Egyptian Ministry of Health

Department Head & Clinical Pharmacist/Dec 2021 -- Jul 2024

Head of Health Education Department

May 2023 -- Jul 2024

Led health education strategy for Marsa Alam district (5 towns); directed campaigns on disease prevention, reproductive health, and community wellness.

Clinical Pharmacist

Mar 2022 -- May 2023

Optimized medication therapy through evidence-based pharmacotherapy and multidisciplinary collaboration.

Primary Care Provider

Dec 2021 -- Mar 2022

Examined, diagnosed, and treated patients with non-critical conditions. Led a team of 4 nurses.

Al-Azhar University

Graduate Research Assistant (Part-Time)/Feb 2023 -- Nov 2023

Microbiology Research Group

Investigated antimicrobial activity of fungal metabolites and performed in-silico evaluation using molecular docking (AutoDock via PyRx).

Medical Research Writing

Medical Research Writer (Part-time, On-demand)/May 2021 -- Jul 2023

Scientific Communication & Evidence Synthesis

Authored 40+ medical review articles across multiple specialties and conducted systematic literature analyses, demonstrating strong skills in scientific communication and evidence synthesis.

Ghamra Military Hospital (Military Service)

Soldier Hospital Pharmacist/Oct 2019 -- Jan 2021

Hospital Pharmacy & Logistics

Dispensed 100-400 prescriptions daily; additional duties included logistics and military training.

Sohag University

Undergraduate Research Assistant/Jul 2017 -- Jun 2018

Medicinal Chemistry Research Group

Designed anti-cancer molecules using ChemDraw and molecular docking, followed by wet-lab synthesis and structure verification via HNMR and C-13 NMR spectroscopy.



04

Projects

Pharmacology Knowledge Graph for Drug Repurposing

94% AUC / 244M Params

Built a multi-modal pharmacology knowledge graph using Graph ML at Stanford. Final model achieved 0.949 AUC with 2M nodes and 244M parameters using schema-expanded TransR. Published user-friendly interfaces on Hugging Face.

PyTorchPyGTransRGNNKnowledge Graph

Multi-Modal Drug Repurposing for Parkinson's Disease

25,410 patients

Capstone project integrating virtual screening, scRNA-seq, pharmacology knowledge graphs, and real-world evidence from 25,410 UCSF patients. Identified Atorvastatin as lead candidate (HR 0.920; 95% CI: 0.86-0.97).

AutoDock-GPUDiffDockGNINAscRNA-seqRWE

TripleVar: Multimodal Variant Pathogenicity Predictor

93.3% Accuracy / 1.0 AUC

Developed a multimodal deep learning framework integrating genomic (DNABERT-2) and protein (ESM-2) embeddings to predict pathogenic variants in thiamine transporters. Screened ~29,000 unclassified variants, identifying 111 high-confidence pathogenic candidates. Abstract accepted for ASCPT 2026.

DNABERT-2ESM-2Deep LearningClinVar

FDA Molecule Similarity Finder

Tool allowing users to identify the 10 FDA-approved molecules most structurally similar to their compound using Morgan fingerprints. Newer version integrates multiple comparison methods.

RDKitMorgan FingerprintsCheminformatics

AI-Driven hERG Channel Inhibition Predictor

Predicting inhibition of the human hERG channel using AI methods for cardiac safety assessment in drug development.

Machine LearningCardiotoxicityDrug Safety

Lung Disease Detection from Chest X-Rays

CNN models for binary and multi-label lung disease detection from chest X-ray images (BMI212 Coursework). Published on Zenodo.

CNNMedical ImagingPyTorch

Population Pharmacokinetic (PopPK) Model

Development of a Population Pharmacokinetic model with covariate analysis using NONMEM for drug dose optimization.

NONMEMPopPKPharmacometrics

Entresto Drug Discovery Monograph

Comprehensive monograph on Sacubitril/Valsartan: how one company managed a monopoly on the most important drug for heart failure.

Drug DiscoveryHeart FailurePharmacology

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Skills

Drug Discovery & Molecular Modeling

AutoDock VinaAutoDock-GPUUCSF ChimeraDiffDockDiffDock-NMDNGNINAAlphaFoldESM-FOLDGROMACS

Machine Learning & Deep Learning

PyTorchPyG (PyTorch Geometric)Graph Neural NetworksGraph TransformersCNNsTransformersScikit-LearnXGBoostRandom Forest

Programming & Tools

PythonRSQLShellGoC++GitDockerConda

Pharmacometrics & Data

NONMEMPiranaPK/PD ModelingEHR AnalysisPandasNumPy

Cloud & Infrastructure

Wynton HPCAmazon AWSNvidia BrevWSL-2 (Ubuntu)

LLM & Agentic AI

CrewAIOpenAI Agents SDKLangGraphRAG Pipelines

Wet Lab

Radioactive Uptake AssaysPlasmid AmplificationCell CultureChemical SynthesisNMR Spectroscopy

Clinical Practice

PharmacotherapyDose AdjustmentDrug Interaction ManagementPatient CounselingPublic Health Programs

Languages

Arabic -- NativeEnglish -- Fluent (IELTS Band 8)German -- Intermediate (B1)

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Education & Awards

Education

University of California, San Francisco

San Francisco, California

Master of Science in Artificial Intelligence & Computational Drug Discovery & Development

Sept 2024 -- Dec 2025GPA: 3.95

Stanford University

Stanford, California

CS224W: Machine Learning with Graphs (UCSF-Stanford Exchange Program)

Sept 2025 -- Dec 2025

Sohag University

Sohag, Egypt

Doctor of Pharmacy -- Pharm.D. (U.S. Equivalent), Honors

2014 -- 2019GPA: 3.92

Awards

UCSF AICD3 Merit Scholarship

$45,000

ASCPT 2026 Poster Abstract & Student/Trainee Travel Grant

$500

Certifications

PEBC Pharmacist Evaluating Examination (Highest Score: P0)SQL Fundamentals TrackIntermediate Deep Learning with PyTorchData Manipulation with PandasPython for Everybody SpecializationData Science Specialization (IBM)Learn C++Antibiotic Stewardship (Stanford Medicine)

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Get in Touch

I'm always interested in discussing new research opportunities, collaborations in computational drug discovery, or the intersection of AI and healthcare. Feel free to reach out.

San Francisco, California, USA