Fangda Li, PhD | 10x Genomics

About Me

Currently Computational Biologist - Image Analysis at 10x Genomics!

I obtained my PhD in the Robot Vision Lab (RVL) led by Prof. Avinash Kak at Purdue University in 2023. With 9 publications, I am interested in deep learning and computer vision, especially for medical imaging.

Site for my pictures.

Research Interests

Computer Vision: Medical Imaging, Computational Pathology, CT
Deep Learning: Generative Models, Image-to-Image Translation
Robotics, AR/VR, Graphics

Publications

MICCAI

Adaptive Supervised PatchNCE Loss for Learning H&E-to-IHC Stain Translation with Inconsistent Groundtruth Image Pairs

Fangda Li, Zhiqiang Hu, Wen Chen and Avinash Kak

Medical Image Computing and Computer Assisted Intervention (MICCAI), 2023.

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TMI

A Laplacian Pyramid Based Generative H&E Stain Augmentation Network

Fangda Li, Zhiqiang Hu, Wen Chen and Avinash Kak

IEEE Transactions on Medical Imaging (TMI), 2023.

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JOXST

DEBISim: A Simulation Pipeline For Dual Energy CT-based Baggage Inspection Systems

Ankit Manerikar, Fangda Li and Avinash C. Kak

Journal of X-Ray Science and Technology (JOXST), 2021.

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Technical Report

A Two-Pathway Framework for Automatic Explosive Detection in Dual-Energy X-Ray CT Baggage Security Imagery

Fangda Li, Ankit Manerikar, and Avinash C. Kak

Internal Report for Contract on X-Ray Based Explosive Detection in Airport Baggage, 2021.

EI

A Splitting-Based Iterative Algorithm For GPU-accelerated Statistical Dual-Energy X-Ray CT Reconstruction

Fangda Li, Ankit Manerikar, Tanmay Prakash and Avinash Kak

Electronic Imaging (EI), 2020.

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EI

A Spectrum-Adaptive Decomposition Method for Effective Atomic Number Estimation Using Dual Energy CT

Ankit Manerikar, Fangda Li and Avinash Kak

Electronic Imaging (EI), 2020.

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ICAPS

RMPD - A Recursive Mid-Point Displacement Algorithm for Path Planning

Fangda Li, Ankit Manerikar and Avinash Kak

International Conference on Automated Planning and Scheduling (ICAPS), 2018.

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CVPRW

A Novel Visualization Tool for Evaluating the Accuracy of 3D Sensing and Reconstruction Algorithms for Automatic Dormant Pruning Applications

Fangda Li, Somrita Chattopadhyay, Shayan A Akbar, Noha M Elfiky, Avinash Kak

IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2016.

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ISVC

Thresholding a Random Forest Classifier

Florian Baumann, Fangda Li, Arne Ehlers and Bodo Rosenhahn

International Symposium on Visual Computing (ISVC), 2014.

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Teaching

At Purdue University, I have served as a graduate teaching assistant for:

Deep Learning, ECE60146: Graduate level class on CNN, RNN, Transformer, GAN, etc. (Spring 2023)
Computer Vision, ECE664: Graduate level class on Geometric Computer Vision, e.g. Stereo Reconstruction. (Fall 2022)
Digital Systems Senior Design, ECE477: Senior undergrad level class on Embedded System design and programming. (2019, 2020, 2021)