Kranthi Kiran GV

I am a second-year M.S. Computer Science student at the Courant Institute of Mathematical sciences, New York University (NYU). I am working at NYU Center for Data Science as a research assistant with Prof. Krzysztof Geras.

From 2018-2021, I worked at Microsoft India as a Software Engineer 2. My work primarily involved building the PDF experiences in Office iOS. In 2017, I worked with Prof. S N Omkar and Dr. Amarjot Singh in the Computational Intelligence Lab at the Indian Institute of Science, Bangalore on aerial pose estimation and person identification systems.

Email  /  Resume  /  Google Scholar  /  Github  /  LinkedIn

profile photo
Research

I am interested in computer vision and machine learning. My research at NYU aims at building deep learning models to solve medical NLP and vision problems on breast cancer diagnosis data.

System detecting suspicious people Real-Time Aerial Suspicious Analysis (ASANA) System for the Identification and Re-Identification of Suspicious Individuals using the Bayesian ScatterNet Hybrid (BSH) Network
Kranthi Kiran GV, Onkar Harsh, Rishav Kumar, Koushlendra Singh, Chandra S S Vamsi, Amarjot Singh
Proceedings of the IEEE International Conference on Computer Vision Workshops, 2019
[Video]

Proposed a real-time aerial pose estimation and person identification system using ScatterNet based deep neural network based on Part Affinity Fields. The system was piloted in Punjab, India.

In use at Skylark Labs
Analysis on whole slide image patches Automatic Classification of Whole Slide Pap Smear Images using CNN with PCA based Feature Interpretation
Kranthi Kiran GV**, Meghana Reddy Ganesina** (** indicates equal contribution)
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2019

Modelled a segmentation-free direct classification network to classify cervical cancerous cells which outperformed previous baselines. We observed correlations between the factors analyzed by pathologists and learned feature representations of the network.


Updated on: 16th February, 2023 Website template from Jon Barron