I am a second year Computer Science PhD student at Princeton University advised by Professor Thomas Funkhouser. My research interests are in the areas of data-driven computer vision, robotics, and graphics. Earlier, I graduated from U.C. Berkeley with a Bachelors double major in Computer Science and Applied Mathematics.

Email: andyz(at)princeton(dot)edu
Address: 35 Olden Street, Room 418b, Princeton, NJ 08540

CV  |  G.Scholar  |  LinkedIn  |  Github


  ♦  Two papers (3DMatch and SSCNet) accepted for Oral presentations at CVPR 2017
  ♦  Paper on our vision system for the Amazon Picking Challenge accepted at ICRA 2017
  ♦  3rd Place (Stow) and 4th Place (Pick) Winners at the Worldwide Amazon Picking Challenge 2016
            Leader of the robot vision system for Team MIT-Princeton (our ICRA paper here)
  ♦  Recieved the Gordon Y.S. Wu Fellowship in Engineering
            "A highly selective and prestigious award" from Princeton University

3DMatch: Learning Local Geometric Descriptors from RGB-D Reconstructions

Andy Zeng, Shuran Song, Matthias Nießner, Matthew Fisher, Jianxiong Xiao, Thomas Funkhouser

IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017.

Oral Presentation  |  PDF  |  Webpage  |  Code (Github)  |  BibTeX

Semantic Scene Completion from a Single Depth Image

Shuran Song, Fisher Yu, Andy Zeng, Angel X. Chang, Manolis Savva, Thomas Funkhouser

IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017.

Oral Presentation  |  PDF  |  Webpage  |  SUNCG Dataset  |  Code (Github)  |  BibTeX

Multi-view Self-supervised Deep Learning for 6D Pose Estimation in the Amazon Picking Challenge

Andy Zeng, Kuan-Ting Yu, Shuran Song, Daniel Suo, Ed Walker Jr., Alberto Rodriguez, Jianxiong Xiao

IEEE International Conference on Robotics and Automation (ICRA) 2017.

PDF  |  Webpage  |  Code (Github)  |  BibTeX


A growing collection of open-source code that I've written over the years. Includes a diverse set of functions that are useful and non-trivial to implement for fast-prototyping in computer vision and robotics research. Have a look!
Webpage  |  Github


3rd Place (Stow) and 4th Place (Pick) Winners at the International Amazon Picking Challenge 2016
Princeton Ph.D. Fellowship (2016-2017)
Wu Prize (2016)
Gordon Y.S. Wu Fellowship in Engineering (2015-2016)
FBLA 1st Place State (CA) Champion for Computer Programming (2011)


07.22.16 - The MIT-Princeton Robot Vision System for the Amazon Picking Challenge 2016
06.26.16 - Local-Level 3D Deep Learning for Feature Matching (PDF Slides)


Organizer, CVPR Tutorial: 3D Deep Learning with Marvin (CVPR 2016)
Reviewer, European Conference on Computer Vision (ECCV)
Reviewer, Special Interest Group on Computer GRAPHics and Interactive Techniques (SIGGRAPH)
Reviewer, Conference on Computer Vision and Pattern Recognition (CVPR)
Reviewer, International Conference on Pattern Recognition (ICPR)
President, Upsilon Pi Epsilon - Computer Science Honors Society (U.C. Berkeley)
IT Chair and Site Production Lead, The Berkeley Forum (U.C. Berkeley)

Optical Music Recognition

Create an optical music recognition (OMR) system to automatically read images of music sheets, interpret the melody using computer vision techniques, and generate a corresponding music file.

Smarter Baxter Robot

Program the Baxter robot to “impressively interact” with a human via drawings/writings on a small whiteboard. It can do many things, from solving math equations to solving python expressions!

Seam Carving

Shrink images horizontally and/or vertically while preserving as much detail as possible.


Experimenting with Gaussian and Laplacian stacks and multi-resolution blending.

Iris Recognition

Exploring and implementing various computer vision techniques to obtain reasonable accuracy for iris verification and identification.


Produce color images from the digitized Prokudin-Gorskii glass plate images.

Digit Recognition

Implement an algorithm to obtain reasonable digit identification accuracy (on the order of 0.5-3%) over the original MNIST handwriting dataset

Image Stitching Part 1

Experiments with homographies and morphing/warping/blending techniques to stitch images together to form a wide angled panorama.

Image Stitching Part 2

Fully automated point correspondences for image stitching using Harris corners, ANMS, and RANSAC.


Quantifying texture.

Lightfield Camera

Capture an evenly space grid of images over a scene and to perform simple shift/averaging operations in order to synthetically simulate cool effects like depth refocusing and aperture adjustments.

Semi-Autonomous Vehicles

Design and implement computer vision algorithms into a new type of car-safety system which utilizes a driver model to predict future driver steering and braking.

Bionic Exoskeleton

Design and develop computer vision and machine learning supplements for concurrent human mechatronics research for bionic exoskeletons.

Anthropomorphic Hand

Research Project with Bay Area Intellectual Property Group, Patent Firm. Research assistant responsible for computer vision algorithms to enable real-world perception/modeling and path/grasp planning for a robot hand.


General search algorithms applied to help Pacman collect food efficiently.

Face Morphing

Generate animations that morph from one face to another.

Disparity Mapping

Explore a variety of computer vision algorithms for the purpose of computing feature correspondences to create a disparity map post-stereopsis and calibration.

Phong Illumination

Using the generic Phong Illumination Model to perform shading computations from scratch.


Evaluation search design: applying minimax, expectimax, alpha-beta pruning etc. to Pacman and a few ghosts.

Ray Tracer

Everyone needs to write a ray tracer at some point in their life... here's mine!


MDPs, value iteration, Q-learning, reinforcment learning etc. algorithms written in gridworld, then applied to Pacman and a simulated robot controller named Crawler.

Canny Edge Detection

Image pixel intensity derivatives and edge detection. Rewrite a canny edge detection algorithm from scratch and compare to state-of-the-art performance.

Uniform/Adaptive Tessallation

Converts input from a Bézier surface representation to a polygonal representation, applies tessallation, and then displays it.

Bayes' Nets and SMCs (PF)

"Pacman spends his life running from ghosts, but things were not always so. Legend has it that many years ago, Pacman's great grandfather Grandpac learned to hunt ghosts for sport. However, he was blinded by his power and could only track ghosts by their banging and clanging." Particle Filtering!

Upsilon Pi Epsilon

President (2014-2015).

Inverse Kinematics

A system that computes the minimal change in join angles of an arm (or multiple branching arms) needed to produce the change in endpoint position.


Thoroughly exploring the mathematical models behind the concept of triangulation and stereopsis.

Taco Laundry

Website Creator and Manager until Summer 2011.

Tour Into the Picture

Using camera homography to create a simple, planar, 3D scene from a single photograph/painting.

The Berkeley Forum

Webmaster and Site Production Lead (associate member, on leave).