--> Nikhil Makkar

Nikhil Makkar

Founding Engineer @ Auric AI Labs | Computer Vision & ML Research

Email / Google Scholar / LinkedIn / Twitter

Nikhil Makkar

Building defense AI at Auric AI Labs - developing automatic target recognition systems using SAR imagery and synthetic data generation for aircraft and vehicle detection.

Previously: ML research at Oak Ridge National Laboratory with Dr. Lexie Yang and Dr. Dalton Lunga, PhD work at Purdue University (ABD). Published researcher in domain adaptation, self-supervised learning, and computer vision for challenging real-world datasets.

Research interests: Object detection, limited data scenarios, domain adaptation, 3D reconstruction, generative models.

Publications

Boundary-aware adversarial learning paper

H. L. Yang, N. Makkar, M. Laverdiere, and A. Rose, "Boundary-aware adversarial learning domain adaption and active learning for cross-sensor building extraction", IEEE Journal of Selected Topics in Earth Observations and Remote Sensing, 2024.

paper
Adversarial learning based discriminative domain adaptation paper

N. Makkar, H. L. Yang, and S. Prasad, "Adversarial learning based discriminative domain adaptation for geospatial image analysis", IEEE Journal of Selected Topics in Earth Observations and Remote Sensing, 2021.

paper
Learning to count grave sites paper

D. Lunga, R. Dhamdhere, S. Walters, L. Bragg, N. Makkar, and M. Urban, "Learning to count grave sites for cemetery observation models with satellite imagery", IEEE Geoscience and Remote Sensing Letters, 2020.

paper
Entropy and boundary paper

N. Makkar and H. L. Yang, "Entropy and boundary based adversarial learning for large scale unsupervised domain adaptation", in IGARSS 2020-2020 IEEE International Geoscience and Remote Sensing Symposium, IEEE, 2020

paper
unsupervised domain adaptation paper

X. Deng, H. L. Yang, N. Makkar, and D. Lunga, "Large scale unsupervised domain adaptation of segmentation networks with adversarial learning", in IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium, IEEE, 2019.

paper

Projects

DSM generation

Digital Surface Model (DSM) Generation Using Conditional Diffusion (2024).

Blog, Code
Point cloud classification

Point Cloud Classification in the Wild (2024).

Blog
Machu Llacta visualization

An Interactive Visualization of the Ruins of Machu Llacta using VTK and PyQt6 (2023).

Video, Code
Computer graphics project

Creating 3D Scenes From 2D Images Using Shaders (2022).

Presentation, Code
CNN for cancer detection

Impact of Transfer Learning in Extreme Change of Modality - Detecting Cancer Using CNNs (2017).

Article