Computer Science

Presented at the Inference for Multi-Messenger Astrophysics Workshop held at BIDS May 30, 2019.

Presented at the Inference for Multi-Messenger Astrophysics Workshop held at BIDS May 30, 2019.

Presented at the Inference for Multi-Messenger Astrophysics Workshop held at BIDS May 30, 2019.

Presented at the Inference for Multi-Messenger Astrophysics Workshop held at BIDS May 30, 2019.

Presented at the Inference for Multi-Messenger Astrophysics Workshop held at BIDS May 30, 2019.

Presented at the Inference for Multi-Messenger Astrophysics Workshop held at BIDS May 30, 2019.

Note: The video for this panel discussion begins at 1:32:20.

Presented at the Inference for Multi-Messenger Astrophysics Workshop held at BIDS May 30, 2019.

Note: The video for this talk begins at 1:15:12.

Presented at the Inference for Multi-Messenger Astrophysics Workshop held at BIDS May 30, 2019.

Note: The video for this talk begins at 58:30.

Presented at the Inference for Multi-Messenger Astrophysics Workshop held at BIDS May 30, 2019.

Note: The video for this talk begins at 41:10.

Presented at the Inference for Multi-Messenger Astrophysics Workshop held at BIDS May 30, 2019.

Note: The video for this talk begins at 25:48.

Abstract: I will summarize my PhD thesis on applying deep learning using convolutional neural networks for detecting gravitational waves and estimating the parameters of their sources as well as classifying anomalies in LIGO data with state-of-the-art accuracy.