Predict force information from vision for Robot-Assisted Minimally Invasive Surgery – Raven II• Create the teleoperation control interfaces from Xbox to remotely control Raven II used ROS library, CRTK, and Transformation Matrices with Python, C++ • Predict Force information from Stimulator AMBF to real Raven using ML Active Learning Regression model and Bayesian Optimizer models

Analyze 3D electron microscopy volume of the Drosophila’s brain to create a 3D reconstruction of the trachea system – the specialized respiratory system in Drosophila• Created a program in Python using Pandas, NumPy to analyze the characteristics of the trachea system and describe its anatomy in the Drosophila brain• Manually traced and reconstructed the trachea system using the specialized software, CATMAID• Visualized 3D reconstruction of the trachea system using Navis, Matplotlib library in Python and Blender softwareMentor: Professor Kenneth Colodner

Analyze the ERPs data of activity in brain’s vision center to explore the selective attention process in human• Designed programs for 3 cognitive psychology experiments on OpenSesame: visual oddball, auditory oddball & Sawaki’s experiment • Analyzed MMN data collected from Clark University (OH) and Mount Holyoke College (MA)• Conducted comparison analysis on existing programs and collected data for future projects• Recorded brain activity data using EEG during the experimentsMentor: Professor Jane Couperus

Analyze data to inform policymakers as they target retrofitting effort to maximize emission production• Prepared data from CIAA and Lawrence Berkeley National Laboratory• Built a linear regression model to predict 9705 buildings’ energy consumption• Managed and supervised a diverse team of 3, including distributing tasks and fostering communicationbetween team members