1. Worked on the development of a ML model DeepARG+ that predicts antibiotic resistance from large scale genomic data. Paper to be published in a high impact factor journal 2. Led a team on NSF funded project CI-WARS for creating a pipeline for end to end resistance analysis3. Developed a visualization tool in D3.js for anomaly detection for monitoring antibiotic resistance.Advisor: Dr. Liqing Zhang

CS1114

Statistics for Social Sciences Course

Our solution aims at detecting suspended impurities and foreign objects in beverages. We are working specifically on buttermilk for quality detection and assurance with the help of computer vision and sensors, which will act as a contact-free technology for foreign object detection. The data (images of bottles on the assembly line and that gathered from the sensors) is collected and classified for further QA using Deep Learning.

I worked on the Machine Learning and Computer Vision aspects of a live project, ‘Smart Scope™’. It involved software development for the detection of cervical cancer at an early stage with the help of images taken by doctors. Abnormalities like cervicitis could also be detected at early stages. Specifically, I built the algorithm required for cervix segmentation and examined the applicability of transfer learning for solving the given problem. I also deployed the ML platform on Amazon Web Services. In a resource-constrained country like India, the application enables remote screening of cervical cancer and provides real time diagnosis for prompt action. The Government of India has also shown a keen interest in the application and provided sponsorship for the same.

Worked on Web Development and Persistent Artificial Intelligence platform. Successfully Implemented POC right from SRS to Automated Testing and successfully coordinated in the software engineering process. Learnt and implemented REST API'sSkills learnt : Software Engineering, PHP, Drupal, Python, Selenium, MySQL, AIML, XML,REST