I am a final year Ph.D. student at The Robotics Institute at Carnegie Mellon University advised by Michael Kaess. Currently, my research is supported by Facebook AI Research, where I am a Visiting Researcher. I am also a recipient of the CMU Presidential Fellowship (2018).

Research:
My research focuses on machine learning and optimization for robot perception, tackling the question, "How can robots learn to efficiently infer latent states from a stream of sensor observations?" I approach this by leveraging machine learning to extract salient information from observations and optimization to efficiently fuse such information. My work spans the areas of machine learning, computer vision, sequence modeling, and sensor fusion. My long-term goal is enable seamless human-robot interactions via increasingly better perceptual interfaces and computational models.

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Applications:
I have applied my work to diverse real-world robot applications with varying sensor modalities such as tactile images, inertial measurements, sonar signals, and stereo vision.

robots


Recent News

Dec '21 Wrote a blog post, An Energy-based Perspective on Learning Observation Models, on some of my recent research!
Nov '21 Excited to present our work on learning energy-based models in factor graph optimization at CoRL 2021! Links: paper, code+video.
Nov '21 Our work, PatchGraph, on tracking unseen objects during in-hand manipulations available on arXiV! Links: paper, code+video.
Sep '21 Our work on learned GPR models selected as a best conference paper finalist at IROS 2021. Congratulations Alex! Links: arXiv.
Jul '21 Selected to the 2021 cohort of RSS Pioneers! Links: poster, statement.
May '21 Excited to present our work on learning tactile models for factor graph-based estimation at ICRA 2021. Links: paper, code+video.
Feb '20 Selected to the 2021 cohort of the Facebook Research and AI Mentorship Program!
Dec '20 Successfully completed my thesis proposal! Links: proposal talk.
Dec '20 Excited to present our work on learning tactile observation models in factor graphs as a contributed talk at the WiML workshop, NeurIPS 2020.
Aug '20 Spent a lovely summer at Facebook AI research on tracking object states using tactile image sensors during robot manipulation.
Jun '20 Excited to present our work on incremental constrained smoothing (ICS) in factor graphs at ICRA 2020. Check out our paper and talk!