Feroz Ahmad

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About

Feroz Ahmad is pioneering the integration of artificial intelligence into surgical practice, with a focused expertise in real-time surgical phase recognition and computer vision for robotic-assisted procedures. His research addresses a critical bottleneck in modern medicine: bringing AI directly into the operating room to enable automated workflow analysis and quality assessment. Ahmad’s most impactful work, "Bringing Artificial Intelligence to the Operating Room: Edge Computing for Real-Time Surgical Phase Recognition" (2023, 21 citations), demonstrates how edge computing can overcome latency and privacy constraints to deliver AI-driven insights during live surgeries. He further established a robust baseline for AI-based surgical phase recognition in his study on inguinal hernia repair (2023, 20 citations), analyzing a substantial dataset of 209 video-recorded robotic-assisted surgeries. By validating deep learning models for automated workflow analysis, Ahmad is laying the groundwork for a future where AI assists surgeons in real-time, improving consistency, training, and patient outcomes. His work sits at the intersection of surgical innovation and practical AI deployment, marking him as a rising leader in the field of AI-assisted medicine.