Assistant Professor
Associate Director, ML@GT
School of Interactive Computing
CODA room S1181B
Email: zkira at gatech dot edu
 

Latest News [All]

03/2020 Thesis defense - Yen-Chang Hsu, the first student in RIPL, defended! Congrats!
03/2020 Thesis defense - Chih-Yao Ma (Kevin) successfully defended his thesis. Great work!
03/2020 Area Chair for NeurIPS 2020.
02/2020 Three CVPR papers on group formation in distributed perception, out-of-distribution detection, and self-supervised cross-domain action segmentation! Congrats all!
01/2020 Two ICRA papers on uncertainty-aware fusion and distributed perception!
11/2019 Thanks to Samsung for research funding!
11/2019 Oral AAAI paper, congratulations Weiyu! (with RAIL) [arxiv]
11/2019 Oral IROS workshop paper on uncertainty-aware multi-modal fusion [arxiv]
09/2019 Funding for DARPA LwLL program
07/2019 Oral ICCV paper on video domain adaptation. Congrats Steve! [arxiv]
06/2019 Preprint: Manifold graphs for SoA semi-supervised learning! [project][arxiv]
03/2019 Oral CVPR paper. Congrats Chih-Yao! (work with Salesforce Research)
02/2019 Dataset released for our WACV PCB component detection paper! [download]
01/2019 Two ICRA/RA-L accepted papers. Congrats Jing-Dao and Angel!
01/2019 Journal paper on point cloud scene understanding
01/2019 Three ICLR accepted papers. Congrats Yen-Chang, Yen-Cheng, and Chih-Yao!
2018 We had a ICLR, CVPR, WACV, NeurIPS Continual Learning Workshop, and one journal paper. We received new funding from DARPA L2M and ONR.
08/2018 Assistant Professor!

About Me

I am an Assistant Professor at the School of Interactive Computing in the College of Computing. I am also affiliated with the Georgia Tech Research Institute and serve as an Associate Director of ML@GT which is the machine learning center recently created at Georgia Tech. Previously I was a Research Scientist at SRI International Sarnoff in Princeton, and before that received my Ph.D. in 2010 with Professor Ron Arkin as my advisor.

I lead the RobotIcs Perception and Learning (RIPL) lab. My areas of research specifically focus on the intersection of learning methods for sensor processing and robotics, developing novel machine learning algorithms and formulations towards solving some of the more difficult perception problems in these areas. I am especially interested in moving beyond supervised learning (un/semi/self-supervised and continual/lifelong learning) as well as distributed perception (multi-modal fusion, learning to incorporate information across a group of robots, etc.).