Austin Reiter

About

Austin Reiter is a prominent researcher whose work spans computer vision, surgical robotics, and deep learning for video understanding. He is perhaps best known for his groundbreaking contributions to action segmentation, most notably the development of Temporal Convolutional Networks (TCNs), published in 2017 and now boasting over 2,000 citations — a landmark achievement that fundamentally reshaped how researchers model temporal sequences in video analysis. This work introduced a powerful alternative to recurrent architectures for identifying and segmenting fine-grained human actions, with applications spanning robotics, surveillance, and education. Equally significant is Reiter's expertise in surgical robotics, where he has advanced tool tracking, robot arm calibration, and force prediction in minimally invasive surgery settings. His early work on appearance learning and feature classification for articulated surgical tools demonstrated sophisticated fusion of visual observations with robot kinematics, while later contributions explored ultrasound image enhancement using fully convolutional networks and RGB-point cloud approaches for surgical force prediction. His research on continuum robots and single-port surgical platforms further underscores his commitment to enabling safer, more intelligent human-robot collaboration in clinical environments. Across disciplines, Reiter's work exemplifies a rare blend of theoretical innovation and real-world surgical impact.

Research Focus

Key Achievements

Top Papers

1. 1
   Temporal Convolutional Networks for Action Segmentation and Detection

   2,028 citations · 2017
2. 2
   Segmental Spatiotemporal CNNs for Fine-Grained Action Segmentation

   248 citations · 2016
3. 3
   Feature Classification for Tracking Articulated Surgical Tools

   74 citations · 2012
4. 4
   Vision-Based Calibration of Dual RCM-Based Robot Arms in Human-Robot Collaborative Minimally Invasive Surgery

   71 citations · 2017
5. 5
   Appearance learning for 3D tracking of robotic surgical tools

   53 citations · 2013
6. 6
   Lessons learned using the insertable robotic effector platform (IREP) for single port access surgery

   30 citations · 2013
7. 7
   A Fully Convolutional Neural Network for Beamforming Ultrasound Images

   28 citations · 2018
8. 8
   Learning to See Forces: Surgical Force Prediction with RGB-Point Cloud Temporal Convolutional Networks

   26 citations · 2018
9. 9
   Temporal Convolutional Networks for Action Segmentation and Detection

   23 citations · 2016
10. 10
    A learning algorithm for visual pose estimation of continuum robots

    22 citations · 2011

Key Collaborators

Contact & Links