Aditya Wagh

👋 Hi. I'm Aditya, a researcher in the AI4CE Lab at New York University headed by Prof. Chen Feng. My area of interest is Machine Learning + 3D Vision. Currently, I am working on improving unsupervised point cloud registration which is a key task in LiDAR based 3D reconstruction, mapping and self-driving.

I am also excited about Geometric Deep Learning, Probalistic Machine Learning, Continual learning, Generative Models, NeRFs (Neural Radiance Fields) and their applications in core 3D vision areas like AR, SLAM and SfM.

Prior to NYU, I did my Bachelors in Electronics Engineering at BITS Pilani where spent my senior year in the Intelligent Systems Group at CEERI, Pilani working with Dr. Sumeet Saurav to improve electric power systems inspection using drones.

In my free time, I watch science fiction, cook delicious food and contribute to open-source projects! To get a better insight on my work, have a look at my 📃Resume


Below is a list of my notable projects. Feel free to have a look at whatever you find interesting!

Dimensionality Reduction using Convolutional Autoencoders

A visualization in reduced dimension to show how autoencoders learn features in the Fashion MNIST dataset.


Plane Fitting in 3D Point Cloud Data

Robust plane fitting in 3D point cloud data using RANSAC.


Post-Earthquake damage assesment using FCNs

A deep neural network model for visual damage assesment.


Two-View geometry based pose estimation

Relative Pose estimation using OpenCV


Power Cable detection

A Mask R-CNN model for detecting power cables.


Variable Computation in RNNs

A modification in a RNN unit that reduces redundant computation.



A tango inspired dark theme for Visual Studio Code.


Clean Portfolio

A simple and elegant Jekyll theme for portfolio pages