Work Experience

May 2023 - Aug 2023

Research Assistant, TEEL Lab

I worked on leveraging GPT-4 models to generate learning objectives for each module of a practical-oriented course, utilizing the course title and goals as input.
Building upon this, I further enhanced the process to generate the complete syllabus, including overall course learning objectives, course module structure, course goals, and core concepts.

Jul 2021 - Apr 2022

I played a key role in intensifying and improving the role of ML on breast cancer diagnosis, focusing on malignancy classification and tumor detection.
Collaborating with a multidisciplinary team, I led the development of a complete solution, resulting in a 28% increase in tumor detection accuracy from previous methods and a 90% hit ratio in terms of localization using Mask RCNN.
By combining insights from various modalities, I achieved more accurate diagnoses through redundant yet refined predictions.

Jan 2021 - Jul 2021

I automated tumor diagnosis for benign/malignant classification with explainability.
By extracting contrast, shape, texture, and boundary irregularity features from radiology scans, I created a 72-vector feature set.
Employing machine learning models (Logistic Regression, SVM, Random Forests) and feature engineering techniques like PCA, I achieved an 80% sensitivity in malignancy classification.

Jun 2019 - Jul 2019

I focused on developing an algorithm to automate the segmentation of armpit regions from thermal images of the torso to facilitate identification of unusually hot regions in the upper breast tissue.
I developed an additional feature in the diagnosis tool by using border irregularity metrics on the identified hot spots to enable flagging of suspicious lymph node activity, often associated with breast cancer.