Dr. Dmitri Lapotko | Automated Cancer Diagnostics | Best Researcher Award

Published on by Robotics and Automation

Dr. Dmitri Lapotko | Automated Cancer Diagnostics | Best Researcher Award

Scorpido Photonics Inc | United States

Dr. Dmitri Lapotko is the pi, cto, and ceo at scorpidophotonics inc., and a pioneering researcher in the field of plasmonic nanobubbles. He invented laser-generated nano-explosions capable of detecting and treating lethal diseases such as cancers and malaria at the cellular level in real time, automating processes to minimize dependence on human expertise and reduce errors. His groundbreaking technology enables the instant detection of single cancer cells in vivo and selectively destroys them on-demand, achieving performance previously unattainable with conventional methods, Automated cancer diagnostics. Dr. lapotko has led numerous research initiatives, including the nih u01 project “harnessing cancer aggressiveness to overcome cancer resistance” and the nsf project “instant diagnosis of cancers with plasmonic nanobubbles,”. he has authored multiple scholarly documents in high-impact journals, with a total of 357 citations, an h-index of 8, i10-index of 7, and 349 citations, reflecting the influence and reach of his work in biomedical optics and nanomedicine. His contributions also extend to consultancy and industry projects focused on instant, automated, and minimally invasive detection of microscopic cancers in patients. With a consistent record of innovation, dr. lapotko continues to advance the frontiers of real-time cellular diagnostics and targeted therapy, merging cutting-edge photonics with life-saving medical applications.

Profiles: Orcid | Google Scholar

Featured Publication

Lapotko, D. (2009). Optical excitation and detection of vapor bubbles around plasmonic nanoparticles. Optics Express, 17(4), 2538–2556.

Lapotko, D. O., Lukianova, E., & Oraevsky, A. A. (2006). Selective laser nano‐thermolysis of human leukemia cells with microbubbles generated around clusters of gold nanoparticles. Lasers in Surgery and Medicine.

Lukianova-Hleb, E. Y., Ren, X., Sawant, R. R., Wu, X., Torchilin, V. P., & Lapotko, D. O. (2014). On-demand intracellular amplification of chemoradiation with cancer-specific plasmonic nanobubbles. Nature Medicine, 20(7), 778–784.

Lapotko, D. O., & Hleb, K. (2019). Diagnosis, removal, or mechanical damaging of tumor using plasmonic nanobubbles. U.S. Patent No. 10,471,159.

Lapotko, D. (2008). Plasmonic nanoparticle-generated photothermal bubbles and their biomedical applications. Nanomedicine, 4(7), 813–845.

Ms. Siona Prasad | Automated Early VTE Detection | Best Researcher Award

Published on by Robotics and Automation

Ms. Siona Prasad | Automated Early VTE Detection | Best Researcher Award

Harvard Medical School | United States

Ms. Siona Prasad is a dedicated medical researcher and md candidate at harvard medical school, boston, massachusetts, pursuing her degree through the pathways program with an expected graduation. She graduated summa cum laude from harvard university with an a.b. in computer science and global health & health policy. Her academic and research journey reflects a strong interdisciplinary blend of medicine, data science, and global health innovation. with a research portfolio spanning prestigious institutions such as brigham and women’s hospital, mass general brigham, and boston children’s hospital, dr. prasad has contributed to advancements in cardiovascular risk prediction, ai-driven diagnostics, and digital health innovation. Her notable projects include developing machine learning algorithms for early disease detection and ai-powered diagnostic tools, Automated early VTE detection highlighting her expertise at the intersection of healthcare and technology. her scholarly work has been cited 9 times across 6 published documents, demonstrating growing recognition within the academic community, and she holds an h-index of 3, reflecting the impact and relevance of her contributions to biomedical research. driven by a vision to integrate artificial intelligence into clinical decision-making, dr. siona prasad continues to shape the future of computational medicine and global health equity.

Profiles: Scopus | Orcid

Featured Publications

Prasad, S., Dykes, P. C., Schreiber, R., Hijjawi, S., Nawab, K., Kim, A., Lipsitz, S., Syrowatka, A., Samal, L., Bates, D. W., et al. (2025). Development of an algorithm for estimating the likelihood of venous thromboembolism in primary care using structured and unstructured electronic health record data. American Journal of Hematology. Advance online publication.

Rao, A. S., Prasad, S., Lee, R. S., Farrell, S., McKinley, S., & Succi, M. D. (2025). Development and evaluation of an artificial intelligence–powered surgical oral examination simulator: A pilot study. Mayo Clinic Proceedings: Digital Health. Advance online publication.

Alayande, B. T., Pai, M., Prasad, S., Abimpaye, M., Bakorimana, L., Niyigena, A., Nkurunziza, J., Cubaka, V. K., Kateera, F., Fletcher, R., et al. (2023). Image-based surgical site infection algorithms to support home-based post-cesarean monitoring: Lessons from Rwanda. PLOS Global Public Health, 3(2), e0001584.

Prasad, S. (2022, May). Robustness of a visible image machine learning surgical site infection diagnostic algorithm when image quality is degraded. Presented at the Rwanda Health Research and Policy Symposium.

Prasad, S. (2022, April 8). Urban inversions of air pollution sources/sinks and uncertainty quantification to pinpoint determinants of poor air quality. Presented at the Joint Mathematics Meeting.