Denver, Colorado, United States
At Elephas, our team harnesses the power of AI to revolutionize prognostic analytics in cancer immunotherapy. Leveraging my expertise in computer vision, analytics and data visualization, we're developing innovative tools and methods to improve the lives of those affected by cancer. My role involves transforming complex data from various sources into actionable insights, driving advancements in machine intelligence applications within the cancer treatment realm. With a background in bioengineering, my journey has led to impactful work in AI, where collaboration with cross-disciplinary teams has been key to our success. My commitment to pioneering new frontiers in technology is fueled by a passion for applying machine learning to novel challenges, fostering an environment where our insights propel the industry forward.
I developed regression-based image-processing algorithm for tissue characterization, using 20 GB image dataset, which achieved high (<0.4 mm) segmentation accuracy, registration agreement >70% and led to a 2014 patent filing. I designed signal-processing algorithms to measure dynamic, low SNR signals of cellular electrophysiolic processes, achieving a 40 dB SNR increase while maintaining 40% bandwidth sensitivity. I adapted an optical transport model (Monte Carlo) to simulate experiments and generate a high-dimensionality data set (>10k) for system optimization, identifying a previously unknown optimal system configuration using ANOVA, correlation and ROC analysis.
I devised an image registration method for comparison of electrogram maps and MRI data I developed, as a team member, the AMS database (MySQL), both identifying key features for database inclusion and processing queries and joins to generate tables for analysis