Irving Fang

I am a graduate student at AI4CE Lab at NYU led by Prof. Chen Feng.

I obtained my bachelor's degree from UC Berkeley, double majoring in Data Science (Robotics Emphasis) and Mathematics, with minors in Japanese and EECS.
At UC Berkeley I was fortunate enough to work with Prof. Alice Agogino at her BEST Lab and Squishy Robotics.

During Summer 2022, I interned at Mitsubishi Electric Research Laboratories (MERL), working with Dr. Radu Corcodel on tactile sensing and deep reinforcement learning.

In my free time I enjoy playing with MCU/FPGA boards and painting. FPGAs are really cool btw.

Email  /  CV  /  Google Scholar  /  Github

profile photo
Research

I am interested in multi-modal robotic perception (tactile, visual, biosignal, etc.) and physics-informed robot learning. I want to utilize learning-based and classical methods to better leverage multi-modality data for solving robotics problems, especially manipulation.
I am also interested in the mathematical theories behind deep learning and reinforcement learning, and designing better sensors for robotic perception

Active Topological Mapping by Metric-Free Exploration via Task and Motion Imitation
Yuhang He*, Irving Fang*, Yiming Li, Chen Feng (* for equal contribution)
ICLR 2023, Under Review

A simple and effective framework for efficient and lightweight active visual exploration with only RGB images as input

Dynamic Placement of Rapidly Deployable Mobile Sensor Robots Using Machine Learning and Expected Value of Information
Alice Agogino, Hae Young Jang, Vivek Rao, Ritik Batra, Felicity Liao, Rohan Sood, Irving Fang, R Lily Hu, Emerson Shoichet-Bartus, John Matranga (Authors ordered by department affiliation, not contribution)
ASME IMECE, 2021
project page / arXiv

A framework for optimizing the deployment of emergency sensors using Long Short-Term Memory (LSTM) Neural Network and Expected Value of Information (EVI)

Personal Projects
Please visit this repo. It contains pointers to some personal projects ranging from robotics to a RISC-V CPU implemented on a Xilinx FPGA board.
Teaching
Teaching Aide, ROB-UY 3203 Robot Vision, Spring 2023
Teaching Aide, ROB-GY 6203 Robot Perception, Fall 2022
Teaching Aide, ROB-UY 3203 Robot Vision, Spring 2022

The website is based on Dr. Jon Barron's source code,