Debasmita Ghose
Computer Science Ph.D. Candidate
Yale University
I am a fifth-year Ph.D. candidate in Computer Science at Yale University, advised by Prof. Brian Scassellatti at the Yale Social Robotics Lab. I also collaborate with Prof. Marynel Vazquez from the Yale Interactive Machines Group. I work at the intersection of robot learning and human-robot collaboration.
Previously, I was a Master's student of Computer Science at the University of Massachusetts, Amherst. I worked as a Graduate Research Assistant at the Laboratory for Perceptual Robotics under Prof. Rod Grupen.
I earned my BS in Electronics and Communication Engineering from Manipal Institute of Technology, India, where I focused on Embedded System Design and building robots.
I have enjoyed interning at the Technical University of Dresden (Germany), Nanyang Technological University (Singapore), and Siemens Corporate Technology (Munich, Germany).
In my free time, I enjoy traveling, photography and cooking.
News
Spring 2023
Will be a Teaching Fellow for the Intelligent Robotics Lab course taught by Brian Scassellati at Yale University.
December 2022
Our paper Interactive Policy Shaping for Human-Robot Collaboration with Transparent Matrix Overlays was accepted to the ACM/IEEE International Conference on Human-Robot Interaction 2023 (HRI 2023), to be held in Stockholm, Sweden (Best Paper Award - Technical Track)
September 2022
Our paper Tailoring Visual Object Representations to Human Requirements: A Case Study with a Recycling Robot was accepted to the Conference on Robot Learning 2022 (CoRL 2022), to be held in Auckland, New Zealand (PDF). I will be attending in person.
May 2022
Our paper The Impact of an In-Home Co-Located Robotic Coach in Helping People Make Fewer Exercise Mistakes was accepted to the IEEE International Conference on Robot & Human Interactive Communication 2022 (RO-MAN 2022), to be held in Napoli, Italy (PDF)
September 2021
Our paper Active Learning for Improved Semi-Supervised Semantic Segmentation in Satellite Images was accepted to the IEEE Winter Conference on Applications of Computer Vision 2022 (WACV 2022), to be held in Waikoloa, Hawaii (PDF). I will be attending in person.
Spring 2021
Will be a Teaching Fellow for the graduate-level Artificial Intelligence course taught by Brian Scassellati at Yale University.
December 2020
Our paper Why we should build Robots that both Teach and Learn was accepted to the ACM/IEEE International Conference on Human-Robot Interaction 2021 (HRI 2021), to be held in Boulder, Colorado (virtual due to COVID) (PDF). I will be attending remotely.
Spring 2020
Will be a Teaching Fellow for the course Building Interactive Machines, a graduate-level robotics course taught by Marynel Vazquez at Yale University.
Fall 2019
Started working towards a Ph.D. in Computer Science at Yale University
May 2019
Graduated with a Masters in Computer Science from University of Massachusetts, Amherst
April 2019
Our paper Pedestrian Detection in Thermal Images using Saliency Maps was accepted to the IEEE Workshop on Perception Beyond the Visible Spectrum at CVPR, 2019, to be held in Long Beach, California (PDF). I will be attending in person.
Summer 2018
Received the DAAD RISE Professional Scholarship - 2018 to pursue a research internship in robotics with Siemens CT, Munich, Germany
Fall 2017
Started Masters program in Computer Science at the University of Massachusetts, Amherst
Spring 2017
Pursuing a research internship in machine learning at Nanyang Technological University, Singapore, through the NTU India Connect Program
October 2016
Received the Best Student Award for the Batch of 2013-2017, from the Department of Electronics and Communication Engineering, Manipal Institute of Technology, India
Summer 2016
Pursuing a summer internship in aerial robotics at Techniche Universitat, Dresden, Germany