Dr. Regmi completed his MBBS in 2013 from Maharajgunj Medical Campus, Tribhuvan University Teaching Hospital, Maharajgunj, Kathmandu. He was ranked 1^st in the MD/MS Entrance Examination conducted by the Institute of Medicine in 2072. He completed his MD in Radiodiagnosis from the Institute of Medicine, Tribhuvan University Teaching Hospital (IOM, TUTH), and was awarded the Professor Tanka Bahadur Budhathoki Gold Medal from Tribhuvan University in 2018.  He was awarded an international fellowship on Pediatric Imaging from the European School of Radiology (ESOR) in 2018/19. He has completed and completed the prestigious European Diploma in Pediatric Radiology (EDiPR) and European Diploma in Pediatric Neuroradiology (EDiPNR). He has also completed the postgraduate course (1 year) in Artificial Intelligence and Machine Learning from the University of Texas at Austin.

Dr. Regmi is also a founding faculty member for the Incubation and Placement Department, Institute of Medicine, and a committee member for drafting the Artificial Intelligence Policy 2026, Institute of Medicine. Dr Regmi is a Full Member of the Nepal Radiologists’ Association (NRA), the European Society of Radiology (ESR), the Asian Oceanic Society of Pediatric Radiology (AOSPR), the Society of Pediatric Radiology (SPR), the Radiological Society of North America (RSNA), and the American Society of Pediatric Neuroradiology (ASPNR). He is working on the European Society of Pediatric Radiology Task Force for fetal imaging. He is currently a Reviewer for the Nepalese Journal of Radiology (NJR), Pediatric Radiology (Springer Nature), Eurorad (Pediatric Radiology section), the Journal of the Nepal Health Research Council (JNHRC), and the Journal of the Institute of Medicine (JIOM). He is now the section editor Outside America for Pediatric Radiology (Springer Nature) and has been working under Professor Amaka since 2024. He is a member for policy research institute (PRI) for the Government of Nepal. He has authored more than 90 publications in Radiology. He is also a co-author of the book IOMites Essentials for the Nepal Medical Licensing Exam (NMCLE), published in 2012, and the Nepal Radiologists Association Standard Practice Guideline for Obstetrics Ultrasound (2026). He has participated in various national and international conferences as a Guest speaker. As an outdoor sports lover, his hobbies include playing football and cricket.

Experiences in Artificial Intelligence 

1. 2025/26- Post Graduate Course in Artificial Intelligence and Machine Learning (PG AIML)

2. Co-PI in AI SAROSH project 2023 for AI-powered task-shifting for high-quality fetal ultrasound service in community healthcare settings (with NAAMII)

3. As a Co-PI (Nepal team) for Prospective Clinical Data Collection for Developing Machine Learning-Assisted Obstetric Ultrasound (MOBUS) Screening Algorithms in Low- and Middle-Income Countries (Protocol No: CAP-MOBUS-24-01)

4. Bill and Gates Foundation Grant (Inv: 078931), Data collection for third party for capstone health project in collaboration with NAAMII 

5. Consultant for Enhancing Reliability and Safety of AI-Enabled Diagnostics, as part of our Industry R&D services to GE Healthcare and NAAMII 

6. Invited as a faculty member for the workshop on AI in healthcare and its ethics in Singapore by AI-SAROSH (from NAAMII)

7. Annotator of the RSNA Intracranial Aneurysm Detection AI Challenge on the RSNA website and the Kaggle competition website.

8. Appointed as a faculty member for the Artificial Intelligence Policy draft committee for the Institute of Medicine, Office of the Dean

9. Diagnostic Accuracy of the YOLO tool in Detecting Pathologies in Chest X-rays: A Pilot Study in a Tertiary Care Center in Nepal  (Published: Giri, L., Regmi, P. R., Gurung, G., Gurung, G., Aryal, S., Mandal, S., Giri, S., Chaulagain, S., Acharya, S., & Umair, M. (2026). Diagnostic Accuracy of an Offline CNN Framework Utilizing Multi-View Chest X-Rays for Screening 14 Co-Occurring Communicable and Non-Communicable Diseases. Diagnostics, 16(1), 66. https://doi.org/10.3390/diagnostics16010066

Ongoing projects

1. Development and Validation of an Artificial Intelligence Model for Detection and Differential Diagnosis of Central Nervous System Tuberculosis on MRI Scans: A 5-Year Retrospective Study at a Tertiary Care Center in Nepal

2. AI-assisted myelination tracking in children below 2 years in a tertiary care hospital (with NAAMII)

3. Assessing Clinical Workflows, Interpretation Practices, and Readiness for AI integration in Chest X-ray in Primary Healthcare Settings in Nepal (with NAAMII)

4. Evaluation of Radiological Reporting Performance of Various AI Models in the Nepalese Population(with NAAMII)

5. Evaluating the Diagnostic Accuracy of a YOLOv7-Based AI Tool for Pediatric Chest Radiograph Interpretation

6. Measurement of hippocampus volume in the Nepalese population using artificial intelligence (with NAAMII)