mohammad farhady

Led end-to-end development and deployment of AI-enabled clinical decision-support systems used across 43 hospitals, supporting over 3,500 physicians and approximately 700,000 patients. Architected scalable clinical-data pipelines and developed interpretable temporal reasoning for patient-specific risk signals.

Engineered and fine-tuned a protein large language model pipeline using IBM MAMMAL to predict antibody–antigen binding affinity across 1.2M biological records. Collaborated on oncology registry development and contributed to peer-reviewed publications and conference abstracts.

Provided inpatient and outpatient care for adult and pediatric patients with hematologic and solid malignancies at a tertiary oncology referral center. Supported patients throughout hematopoietic stem cell transplantation and collaborated with multidisciplinary teams.

Assessed, stabilized, and managed critically ill and injured patients in a high-volume emergency department. Coordinated investigations, specialist consultations, admissions, and transfers to support timely multidisciplinary care.

Designed an end-to-end fault-detection and diagnostic system for automotive suspension testing, addressing a long-standing sensor-analysis challenge. Reverse-engineered proprietary sensor data formats and developed Python pipelines for time-series analysis and feature extraction.

Doctor of Medicine (MD) degree from Shiraz University of Medical Sciences, completed from January 2018 to February 2025.

Registered as a physician with the Islamic Republic of Iran Medical Council, membership code 228318.