Cambridge, Massachusetts, United States
I graduated top of the Electrical and Computer Engineering department at Carnegie Mellon University in 2022, with the E.M. Williams award. At CMU, my research focused on extracting features from contact and non-contact (wireless) sensors for applications in robotic manipulation and security. I also explored training schemes to improve performance in highly imbalanced datasets.
Focus: I am actively engaged in developing sensing frameworks for robotic manipulations. I have developed quantitative benchmarks to evaluate the performance of robotic hands. I am advised by Professor Nancy Pollard from the Foam Robotics Lab. Skills: Computer-Vision Algorithms, Signal-Processing Algorithms, Graph Search Algorithms, Sensor Fusion Techniques, Sensor Placement Optimization, Robot Operating System (ROS)
Focus: I am actively engaged in fusing high-precision mmWave radar signals with camera images for robust object detection and texture classification. I am advised by Professor Swarun Kumar from the WiTech Lab.
Focus: I helped to implement semi-supervised learning models in unilabel, multiclass, class imbalance environments. I also studied scoring metrics used to compare the performance of machine learning models. I was advised by Dr Foo Chuan Sheng from the Deep Learning for Medical Imaging Group. Skills: PyTorch, Semi-supervised Learning Algorithms, Statistical Data Analysis, Graph Theory, AWS Cloud Services