As a researcher, I'm immersed in a groundbreaking project focused on the social navigation of humanoid robots, split into two pivotal modules. The first module involves crafting a modified YOLO-based model tailored to process point cloud data, ensuring precise detection of human coordinates pivotal for seamless navigation. Transitioning to the second module, I dive into datasets like ZARA, Student, and multiple trajectory prediction datasets to engineer a specialized deep learning model. This empowers our robot to intricately learn human movement patterns within bustling environments. By applying this knowledge, our Digit humanoid robot adeptly navigates, generating and following waypoints derived from learned human navigation behaviors in dense settings. This elevates its adaptability, enabling fluid movement in crowded environments.

GTA for CS 4641/7641 Machine Learning

Engage actively in guiding students through intricate machine learning concepts, offering comprehensive support and clarifications to bolster their understanding. Provide hands-on assistance in navigating diverse projects, ensuring students grasp fundamental and advanced ML principles effectively.

During my Keysight Technologies internship, I spearheaded Cpk plugin development for PathWave Analytics, elevating its analytics with Process Capability Analysis and advanced statistical insights. I refined the plugin with outlier detection and precise data filtration. I also revamped the Cygnet project's front end, integrating intricate UI elements for a structured CPK report display. Simultaneously, I optimized both frontend and backend code using Angular and Python, while seamlessly integrating CPK analysis. This diagnostic tool unveiled critical dataset insights, driving substantial customer interest and a significant bulk order due to its impactful features.