Nitin Agarwal
agarwal at ics dot uci dot edu

I am a PhD student (2014-) in the Computer Science department at UC Irvine, where I am working with Prof. Gopi Meenaskshisundaram and also collaborating with Prof. Sung-Eui Yoon. Prior to joining UC Irvine, I was an algorithm developer at VisionGate, a medical device startup based in Phoenix, which uses 3D imaging of single cells and machine learning techniques for early cancer diagnosis. In summer 2016, I spent a wonderful time in the MCS Division at Argonne National Lab working on multi-view reconstruction of small insects using Lytro Camera's.

I received my Masters (2011-2013) from the University of Washington, Seattle where I was advised by Eric Seibel (Human Photonics Laboratory) and Anthony Reeves (Vision & Image Analysis group). I did my bachelors in Electrical Engineering from Birla Institute of Technology & Sciences (BITS), Pilani, India.

CV  /  Google Scholar  /  LinkedIn  /  Github



I am interested in applications of computer graphics, computer vision, geometry processing and machine learning. In the past I have worked on problems related to 3D reconstruction, rectification of tiny documents, medical visualization and medical image processing.

I am currently working on modeling 3D scenes from 2D images using Deep Learning.


Towards Automated Transcription of Label Text from Pinned Insect Collections
Nitin Agarwal, Nicola Ferrier, Mark Hereld
Winter Conference on Application of Computer Vision (WACV), 2018
project page / slides / poster


Geometry Processing of Conventionally Produced Mouse Brain Slice Images
Nitin Agarwal, Xiangmin Xu, Gopi Meenakshisundaram
Journal of Neuroscience Methods, 2018
project page / bibtex

In this work we present techniques and algorithms for automatic registration and 3D reconstruction of conventionally produced mouse brain slices in a standardized atlas space.


Designing a high-throughput pipeline for digitizing pinned insects
Mark Hereld, Nicola Ferrier, Nitin Agarwal, Petra Sierwald
BigDig Workshop (eScience), 2017  (Oral Presentation)
project page / bibtex

We designed a pipeline for multi-view reconstruction of small pinned insects (found in museum collections) with their labels using Lytro cameras.


Robust Registration of Mouse Brain Slice with Severe Histological Artifacts
Nitin Agarwal, Xiangmin Xu, Gopi Meenakshisundaram
Indian Conference on Computer Vision, Graphics & Image Processing (ICVGIP), 2016  
project page / poster / bibtex

We proposed a method for non-linear registration of mouse brain histology slices (with various histological artifacts) to the Allen reference atlas.


Automatic Detection of Histological Artifacts in Mouse Brain Slice Images
Nitin Agarwal, Xiangmin Xu, Gopi Meenakshisundaram
Workshop on Medical Computer Vision: Algorithms for Big Data (MICCAI), 2016  (Long Oral Presentation)
project page / slides / poster / bibtex

We proposed a method to automatically detect artifacts, which are common to slices produced from conventional histological techniques.

DNA ploidy measure of Feulgen-stained cancer cells using 3D image cytometry
Nitin Agarwal, Yiting Xie, Florence Patten, Anthony P. Reeves, Eric Seibel
IEEE Engineering in Medicine and Biology (EMBC), 2014   (Oral Presentation)
project page / slides / bibtex

We propsed a method to accurately measure the full DNA content (in three-dimension) of single cells without compromising their 3D morphology. This has been proven to be a valuable alternative method for assessing tumorgenesis of enriched microsamples in diagnostic cells.

3D DNA image cytomtery by optical projection tomographic microscope for early cancer diagnosis
Nitin Agarwal, Alberto Biancardi, Florence Patten, Anthony P. Reeves, Eric Seibel
Journal of Medical Imaging (JMI), 2014  
project page / bibtex

We extend the current cytopathological techniques from 2D to 3D for early cancer detection. We do this by accurately imaging individual cells along with novel 3D nuclear segmentation algorithms.


Quantification of relative chromatin content in flow cytometry standards using 3D OPTM imaging technique
Nitin Agarwal, Alberto Biancardi, Florence Patten, Anthony P. Reeves, Eric Seibel
SPIE Medical Imaging (SPIE), 2013  
project page / poster / bibtex

We accurately measure DNA content in small Flow Cytometry standards (chicken and trout nuclei).

Course Projects

Guess the Celebrity in TV Shows!
Nitin Agarwal, Jia Chen, 2015.

In this project we develop a system that takes a TV show or a movie as input and not only detects but also identifies all the characters in that video sequence. We obtained intresting results when we trained our classifier on Season 9 of Friends and later tested it on the Friends movie trailer released in 2014.


Predicting Keypoint location on face images
Nitin Agarwal, Jia Chen, Hao Zhang, 2015.

For this project, the problem was taken from Kaggle. To solve this multivariate (30 labels) problem we tried a gamut of approaches including linear regression, SVM, ensemble techniques, feed forward neural network, convolutional neural networks, etc.


In my spare time I love to do photography. Do check out my images.

Home Remedies For Wrinkles Thanks Jon!