I'm a research scientist at Waymo (formerly the Google self-driving car project). Previously, I completed a PhD in CS at Princeton University where I worked with Ryan Adams in the Laboratory for Intelligent Probabilistic Systems. While I'm broadly interested in machine learning and its applications, my current areas of focus are generative modeling and program synthesis.
In the past few years, I've had the opportunity to work with teams at Google, the Ford Research and Innovation Center, and the National Institutes of Health on applications ranging from autonomous driving to computer-aided diagnostics.
I'm grateful to have been supported by the NDSEG Fellowship.
At Princeton, I served as an instructor for Neural Networks: Theory and Applications (COS 495) with Sebastian Seung and Mathematics for Numerical Computing and Machine Learning (COS 302) with Ryan Adams. I've also recently started creating short video tutorials on ML-related topics.
A complete list of publications may be found on my Google Scholar profile.
MotionLM: Multi-Agent Motion Forecasting as Language Modeling
Ari Seff, Brian Cera, Dian Chen, Mason Ng, Aurick Zhou, Nigamaa Nayakanti, Khaled S. Refaat, Rami Al-Rfou, Benjamin Sapp
Vitruvion: A Generative Model of Parametric CAD Sketches
Ari Seff, Wenda Zhou, Nick Richardson, Ryan P. Adams
SketchGraphs: A Large-Scale Dataset for Modeling Relational Geometry in Computer-Aided Design
Ari Seff, Yaniv Ovadia, Wenda Zhou, Ryan P. Adams
ICML 2020: Workshop on Object-Oriented Learning
Discrete Object Generation with Reversible Inductive Construction
Ari Seff, Wenda Zhou, Farhan Damani, Abigail Doyle, Ryan P. Adams
Continual Learning in Generative Adversarial Nets
Ari Seff, Alex Beatson, Daniel Suo, Han Liu
Learning from Maps: Visual Common Sense for Autonomous Driving
Ari Seff and Jianxiong Xiao
LSUN: Construction of a Large-Scale Image Dataset using Deep Learning with Humans in the Loop
Fisher Yu, Ari Seff, Yinda Zhang, Shuran Song, Thomas Funkhouser, Jianxiong Xiao
DeepDriving: Learning Affordance for Direct Perception in Autonomous Driving
Chenyi Chen, Ari Seff, Alain Kornhauser, Jianxiong Xiao
Leveraging Mid-Level Semantic Boundary Cues for Automated Lymph Node Detection
This work was recently featured
on the radiology website AuntMinnie.com
Ari Seff, Le Lu, Adrian Barbu, Holger Roth, Hoo-Chang Shin, Ronald Summers
Interleaved Text/Image Deep Mining on a Very Large-Scale Radiology Database
Hoo-Chang Shin, Le Lu, Lauren Kim, Ari Seff, Jianhua Yao, Ronald Summers
2D View Aggregation for Lymph Node Detection Using a Shallow Hierarchy of Linear Classifiers
Ari Seff, Le Lu, Kevin Cherry, Holger Roth, Jiamin Liu, Shijun Wang, Joanne Hoffman, Evrim Turkbey, Ronald Summers
A New 2.5D Representation for Lymph Node Detection using Random Sets of Deep Convolutional Neural Network Observations
Holger Roth, Le Lu, Ari Seff, Kevin Cherry, Joanne Hoffman, Shijun Wang, Jiamin Liu, Evrim Turkbey, Ronald Summers
Contextual CT Radiation Exposure Sentinel Event Detection
Sam Weisenthal, Ari Seff, Xioa Zhang, Ronald Summers, Les Folio, Jianhua Yao
Reliability of Negative BOLD in Ipsilateral Sensorimotor Areas During Unimanual Task Activity
Keith McGregor, Atchar Sudhyadhom, Joe Nocera, Ari Seff, Bruce Crosson, Andrew Butler
Brain Imaging and Behavior, 2014