Adithya K Krishna

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Hi! I am a graduate student at Columbia University pursuing my master’s in Computer Science with a specialization in Machine Learning.

My attraction to Machine Learning(ML) grew from the fascination that a simple tool can perceive and learn. This allowed me to relive what I experienced during my days of learning Carnatic music and Karate. Both art forms stem from the basis of perfecting and improving over iterations which is the underlying principle of Machine Learning.

For my BTech in ECE, I joined NIT Trichy. Where in my sophomore year, I explored projects that leveraged ML to solve real-world problems, such as Medical image classification and detecting diseases, which helped to provide immediate attention and faster treatment to people in need. Working on research ideas that could be used as a solution in the immediate future was a revelation and inspired me to specialize in this field. As a member of the Spider R&D club of NITT encouraged me to focus on ML and to work on similar projects. Throughout my undergraduate studies, I have contributed to several Deep Learning, Computer Vision, and NLP-based projects, which have helped me explore the vast field of ML.

I am interested in the Real-world implications of ML and CV, such as self-driving cars, robots used in space exploration, and curing medical ailments.

news

Jun 2, 2022 Surgical-VQA Accepted in MICCAI 2022!! :sparkles:
Mar 8, 2022 Accepted into Columbia University for Masters!! :lion: :smile:
Jan 31, 2022 Rep-Ar Net accepted into ICRA ‘22!!

selected publications

  1. Surgical-VQA: Visual Question Answering in Surgical Scenes using Transformer
    Lalithkumar Seenivasan, Mobarakol Islam, Adithya Krishna, and 1 more author
    arXiv preprint arXiv:2206.11053 2022
  2. RepAr-Net: Re-Parameterized Encoders and Attentive Feature Arsenals for Fast Video Denoising
    SP Sharan, Adithya Krishna, A Siddharth Rao, and 1 more author
    In 2022 International Conference on Robotics and Automation (ICRA) 2022
  3. WaveLightNet: A Wavelet Decomposition Filter based CNN-LSTM Network for 6DOF Pose Estimation of Origami Robot
    Adithya Krishna, Lalithkumar Seenivasan, and Hongliang Ren
    2021