Jan 2025 – Sep 2025 · 8 mos · Seattle, Washington, United States · On-site

• Working in the Alexa Shopping team.

Aug 2023 – Jan 2024 · 5 mos · Tempe, Arizona, United States

• Working on cardiovascular image analysis using computer vision and deep learning techniques.

May 2023 – Jul 2023 · 2 mos · Tempe, Arizona, United States

• In-depth Project: Sensor Color Change Analysis for Concentration Correlation
• Investigated the correlation between color changes in a wound sensor and sample concentration, utilizing image processing techniques.
• Implemented alternative approach involving color filtering and circular sensor geometry due to challenges with traditional image registration.
• Conducted image preprocessing to extract sensor regions and detect circular structures for analysis.
• Quantified color changes in sensor regions pre and post wound exposure, analyzing their relationship with sample concentration.
• Leveraged insights to enhance understanding of sensor behavior under varying concentrations, contributing to wound monitoring and healthcare applications.

Aug 2023 – Dec 2024 · 1 yr 4 mos · Phoenix, Arizona, United States · Hybrid

May 2020 – Aug 2022 · 2 yrs 3 mos · Hyderabad, Telangana, India

• Developed and maintained an edge detection library which improves the placement of 3d models of ornaments (rings, earrings, bracelets, glasses) onto the image/live video of a customer (Virtual Try-on), with the help of various image processing techniques that.
• Created and developed a 3D virtual placement feature in virtual try-on of jewelry(AR), using which the user can see the 3D placement of the jewelry in virtual tryon.
• Improved the TryOn FPS by 65% by developing a generic face/hand tracker library which helps reduce the usage of the time-intensive ML-based face/hand detection on every frame.
• Developed a feature which can predicts and automatically adjust the true jewelry size for different users based on Iris/ credit card.
• Leveraged knowledge in Image Processing, Typescript, Tensorflow.js, OpenCV.js, Three.js and React.

Jun 2019 – Aug 2019 · 2 mos · Bengaluru, Karnataka, India

• Advisor: Dr Anbumani Subramanian.
• Developed an image-based localization challenge at AutoNUE2 workshop held in conjunction with ICCV-2019.
• Created a data-set(IDD Multimodal, which has data from various sensors like Stereo Images, GPS, LIDAR) from IDD dataset, containing 10000 images from 182 drive sequence on Indian road. for the challenge.
• Proposed and implemented an evaluation metric and a baseline for the localization task, using ORB-SLAM2 (Feature-based SLAM system) on monocular images from IDD Localization challenge.

Jan 2019 – May 2019 · 4 mos · Hyderabad, Telangana, India

• • Worked as Teaching Assistant for Statistical Methods In Artificial Intelligence course.

May 2018 – Jun 2020 · 2 yrs 1 mo · Hyderabad, Telangana, India

• Full time honours student at Computer vision lab under the dean RnD of IIIT (Prof. CV Jawahar)
• Created a baseline for Pixel-Level semantic segmentation task for IDD Segmentation dataset
• Jan ’19 - May ’20
• Developed an app which helps VI(visually impaired) people understand information on slides. Also worked on creating a Localisation challenge on IDD dataset, as a part of Visual localization challenge workshop at CVPR 2019
• Lecture Analyzer: Developed a system which summarizes a video lecture or a meeting using Alexa and created a website in which the summary gets updated after every meeting.
• AI assistant Bot: Worked on AI assistant bot which can be used for assistance in the lab. Developed an interface (a mobile app using react native) for the interaction of user with the bot, which can act as an Tour Guide for the lab, can recognize the face and greet an user and can assist in planning your daily schedule.