CEO and Founder
Dr. Penkova's focus is on developing patient data-driven algorithms to derive patient-specific physiological information from extensive imaging data, ultimately reducing diagnostic and therapeutic errors and advancing personalized care. These efforts involve extracting valuable information from inner surface eye imaging to diagnose non-ocular conditions such as diabetes, cardiovascular disorders, and mental illness. Our developed codes/software also includes the development of therapeutic drugs for glaucoma patients, which are informed by experimentation and modeling of glaucoma-related fluid transport. My expertise encompasses ML, DL, computer vision, ocular fluid dynamics and transport, oxygen transport processes in the eye, the effect of shear flow on protein clustering and aggregation, and studies on glaucoma-related fluid transport.
VMR Institute
He is presently Senior Research Scientist at the Doheny Eye Institute in Pasadena and Professor of Clinical Ophthalmology at UCLA. As of 2025, Dr. Sebag has authored 273 academic publications and delivered an equal number of lectures/abstracts on various aspects of vitreo-retinal health and disease. Dr. Sebag’s Google Scholar H-index = 59, with 13,742 citations to his work. His 2014 textbook (https://link.springer.com/book/10.1007%2F978-1-4939-1086-1) on vitreous has had 189,000 downloads and was translated into Chinese.
Partner
Qilong Pan specializes in machine learning engineering and software development, with expertise in ocular health diagnostics and predictive analytics. His current research involves developing innovative ocular ultrasound analytics tools aimed at constructing detailed vitreous liquefaction maps, integrated with advanced Physics-Informed Neural Networks (PINNs) for accurate prediction of intravitreal drug flow dynamics. Additionally, Qilong successfully developed an advanced U-Net-based neural network capable of diagnosing diabetes from ocular images with accuracy exceeding 95%. Beyond his research contributions, he actively collaborates on software development projects, transforming cutting-edge research findings into practical healthcare products.
Partner
Venkata Saai Praneeth Thota contributes to biomedical imaging research, building models like TransU-Net and GCNNs for vascular segmentation to identify cardiovascular biomarkers. Previously, at Share Ventures, he developed AI agents for market intelligence in the human performance industry using hybrid RAG Agents. His core expertise spans machine learning, LLMs, retrieval-augmented generation, biomedical AI, and time-series analysis, with publications in venues like IEEE TNSM. He is an AI Research Engineer at Modlee, a dynamic startup innovating with LLMs and deep learning for domain-specific intelligence solutions.