Primary research and academic interests center on Urological Oncology and Precision Medicine, specifically through the innovative application of Artificial Intelligence (AI) and Big Data analysis. The core focus involves developing AI models for real-time surgical navigation in robot-assisted urological procedures, including the recognition of the ureter and prostate fascias. In clinical oncology research, he utilizes large international databases and advanced methodologies to evaluate therapeutic strategies for metastatic prostate cancer (mHSPC) and prognostic biomarkers for renal cell carcinoma (RCC), highlighting racial disparities in predicting RCC prognosis using preoperative C-reactive protein (CRP) levels. He also explores the molecular mechanisms of prostate cancer invasion and researches novel synergistic nanotherapies for bladder cancer. A secondary area of interest is Assisted Reproductive Medicine, where he investigates predictive strategies for oocyte maturation using peri-trigger hormonal change rates (delta-FRH) and studies the lncRNA NEAT1/miR-29a-3p/IGF1 axis in ovarian granulosa cells. His clinical and research contributions in minimally invasive adrenalectomy have been recognized globally, being cited in the authoritative text, Campbell-Walsh Urology.