Masters Thesis: Cognitive Load Aware User Interfaces for Mixed Reality Environments

Presented at Women in Machine Learning Workshop, co-located with NeurIPS 2020

– Coming Soon –

Early fall detection from video using 3D-CNNs

Winner of Intuitive Surgical Best Project Award

According to the CDC, over 3 million adults are treated in emergency departments for fall related injuries each year. Accurate and real-time detection of falls is vital to timely intervention and minimization of long term effects. Our work uses a transfer learning approach from action recognition models pre-trained on the Kinetics-700 dataset to perform detection and localization of falls in video feed to both alert care providers and provide information that can help to assess fall severity.

Haptic Feedback for Upper Limb Motion Guidance

Accepted to 2020 Haptics Symposium

Wearable device prototype to enable motion guidance for rehabilitation through cutaneous haptic feedback.

6-DOF Robot Manipulation Using Inverse Kinematics, Resolved Rate, and Gradient Control Methods

Developed manipulation algorithms in MATLAB to perform pick and place with intention and writing tasks using a UR5 robot.

UPenn Senior Design: Automated Pancreatic Cancer Diagnostic

Winner of Bioengineering Senior Design Award
First Honorable Mention, School of Engineering and Applied Science Senior Design Competition

Detected pancreatic cancer cell derived exosomes from human serum at concentrations modeling precancerous stages bydeveloping an automated, microfluidics based point-of-care diagnostic device.