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.
Co-Founder
Dr. Xiaodong Jia’s research focuses on developing advanced analytical solutions, including advanced sensing, monitoring, and advanced data analytics for maintenance and service innovations in next-generation industry systems. His research works have been successfully implemented in a broad range of applications, including semiconductor manufacturing processes, high-precision optical lens manufacturing, Traumatic Brain Injury (TBI) prognosis, high- precision linear motion equipment, wind turbines, among others. To date, Dr. Xiaodong Jia has successfully published 60+ peer-reviewed research articles, delivered 20+ research projects sponsored by various industry companies and government agencies, and maintained close collaborations with 30+ industry companies around the globe.
Partner
Rishikesh Sivakumar is a ML Engineer specializing in computer vision and deep learning for medical diagnostics. His pioneering work includes developing a hybrid model that combines Vision Transformers and CNNs to detect glaucoma with 99.4% accuracy, using both retinal images and clinical biomarkers. Published in the "Engineering Applications of Artificial Intelligence" journal, his research enhances early glaucoma detection and he is actively exploring other methodologies for diagnosing diabetic retinopathy (DR) and other medical conditions, offering a significant stride towards non-invasive and precise medical diagnostics.
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.