Jul 2023 – Jan 2024 · 6 mos · Bengaluru, Karnataka, India · Hybrid

• Auction Parameter Optimization: Highly Rated Search Thematic Widget
• Examined the operational workflow of sourcing, ranking and display of Sponsored Products ads on user search pages
• Tuned the parameters of auction scoring function for improved ad ranking in Highly Rated search thematic widget
• Employed sobol search strategy for parameter optimization, enhancing long-term shopper metrics by 40% in IN marketplace
• Advertisement-Query Relevance model using LLMs
• Developing an ad-query relevance model via implementation of Parameter-Efficient Fine-Tuning techniques on LLMs

May 2023 – Jul 2023 · 2 mos · Mumbai, Maharashtra, India · On-site

• Built a robust feature extraction pipeline with three core components: expansion, selection and dimensionality reduction
• Explored python libraries for automated feature expansion of time series data in order to maximise information content
• Delved into feature selection algorithms like RFE, BorutaSHAP to drop out irrelevant features from the expanded set
• Leveraged PCA and Autoencoders to capture maximum variability within the chosen features into a compact feature set
• Evaluated using OLHCV data for monthly stock price trend prediction with LSTM achieving an accuracy of 0.85

Mar 2023 – Apr 2023 · 1 mo · Bengaluru, Karnataka, India · Remote

• Examined Planetary Computer for extraction of Sentinel-2 images for a given Area of Interest (AOI) and time of interest
• Selected the satellite image with the highest coverage area from the set of output images returned for a given input query
• Used Scene Classification Layer (SCL) band for masking clouds, masking the pixels with band values as 0, 8, 9, 10
• Applied morphological operations like dilation & erosion using OpenCV over the stored .tif files of RGB and NDVI bands

May 2022 – Jul 2022 · 2 mos · Bengaluru, Karnataka, India

• Explored document understanding models like LayoutLMv2 and LayoutLMv3 for extraction of entities from mortgage documents
• Improved F1 score of 0.76 for a document dataset, surpassing the existing NER approach which had a score of 0.66
• Analysed the results of LMv3 on the document dataset with that of the existing results obtained using LMv2
• Explored models like LayoutXLM to build key-value relation extractor for various form documents and wrote inference scripts for Semantic Entity Recognition of form documents for actual deployment to the production server

May 2022 – Jul 2022 · 2 mos

• Awarded Research Grant for working under the supervision of Prof. Salil Goel on the topic: "Object Detection on LiDAR Image" under the SURGE program 2022.
• Designed an object detection algorithm in Tensorflow to detect two classes on a dataset containing images collected from highways and rural areas
• Analysed the KITTI dataset to perform detection and 3D localization of two classes: Car & Pedestrian
• Used PyTorch to develop a Convolution Neural Network that takes LiDAR point cloud and images as input simultaneously

Oct 2021 – Dec 2021 · 2 mos

• Collaborated with a team of 45 AI engineers to build an automated Plant Health Prediction Model.
• Used QGIS to analyse the dataset comprising of drone-derived multispectral and thermal data combined with irrigation data.
• Identified the concerned regions with water stress, pest infestation, man-made plant stress and created shapefiles for the same.
• Impact: Improved Irrigation Management to save and optimize water consumption as well as to reduce the use of pesticides.
• Invited to join the Omdena Community. Invitations are sent to the top performers in the challenge.

Jun 2021 – Apr 2022 · 10 mos

• Acted as a point of contact for over 10 companies during the Placement Season as well as in the Internship Season 2021-22
• Worked with a 3 tier SPO team and managed interviews, Pre-Placement Talks, Group Discussions and tests for about 800+ students during the Internship Season and about 1200+ students in Placement Season 2021-22

Apr 2021 – Jun 2021 · 2 mos

• Mentored various students in UnchaAI , an ed-tech startup by IITK and NITP alumni which provides a mentorship platform to JEE aspirants.
• Guided JEE aspirants with their PCM doubts and designed a customized time table & metric to track their performance periodically.
• Conducted regular motivation sessions which helped them in gaining self confidence during the pandemic period.