An accomplished AI Developer with significant experience in the medical field, specifically in developing deep learning models for surgical scene understanding. They have a proven track record in leading projects, perfor…
An accomplished AI Developer with significant experience in the medical field, specifically in developing deep learning models for surgical scene understanding. They have a proven track record in leading projects, performing clinical validation, and collaborating with surgeons on data curation. Their expertise extends to supervising research internships, teaching research methods, and guiding the publication of original papers.
Developed deep learning models for surgical scene understanding (instrument & anatomy segmentation).
Led projects including Surg-SegFormer and CLIP-RL.
Performed clinical validation on robotic-assisted surgery datasets.
Reported results to guide deployment-readiness.
Collaborated with consultant surgeons on data curation, annotation standards, and error analysis for MIS/robot-assisted procedures.
Supervised two cycles of HMC Surgical Research internships.
Taught primary & secondary research methods, literature review, protocol writing, and reproducible coding.
First cohort submitted their first original paper.
The second cohort is preparing an original and a secondary study.
Developed deep learning models for surgical scene understanding (instrument & anatomy segmentation); led projects including Surg‑SegFormer and CLIP‑RL, Performed clinical validation on robotic‑assisted surgery datasets; reported results to guide deployment‑readiness, Collaborated with consultant surgeons on data curation, annotation standards, and error analysis for MIS/robot‑assisted procedures, Supervised two cycles of HMC Surgical Research internships; taught primary & secondary research methods, literature review, protocol writing, and reproducible coding. First cohort submitted their first original paper; the second cohort is preparing an original and a secondary study
Published multiple papers under the supervision of Dr. Shidin Balakrishnan the lead principal investigator on QNFR Project: Advancing Value-Based Surgical Care: A Real-Time Deep Learning Approach for Postoperative Complication Risk Stratification in Robot-Assisted Nephrectomy
نظام التوظيف التشغيلي المعتمد على الذكاء الاصطناعي أولاً، الذي يوحّد ويؤتمت دورة التوظيف بالكامل للمؤسسات الحديثة حول العالم.
د.جوب منطقة حرة ذ.م.م. 2026 © جميع الحقوق محفوظة
