Peter Ma

Hi there! 👋 I'm a third-year math and physics undergrad at the University of Toronto and a Laidlaw Scholar. Broadly, I'm interested in leveraging deep learning to accelerate scientific discovery, safely.

Currently at UC Berkeley SETI Research Center I'm looking into leveraging geometric deep learning to search the nearest 1 million stars for signs of life beyond Earth with the Breakthrough Listen team. This work will temporarily be on pause during the summer.

Soon I'll be at CERN in the summer helping to develop the Liquid Argon Calorimeter responsible for precisely measuring the energies produced in proton-proton collisions of the future High Luminosity Large Hadron Collider. This work is done jointly with the Experimental Particle Physics group at McGill.

Previously at Caltech I developed deep learning algorithms to assist controlling LIGO. Before that I was at Dunlap Institute of Astronomy and Astrophysics, where I developed an ensemble learning algorithm deployed on the CHIME radio telescope. For other experiences please see below.

When I'm not busy teaching computers, I love climbing and making art. Come say hi \(\Rightarrow \)Twitter @peterma02 Email: peterxy.ma [at] gmail [dot] com :)

CERN - Large Hadron Collider

Intern Researcher: July 2023 - Sept 2023

Coming soon ....

McGill University - Experimental Particle Physics Group

Intern Researcher: May 2023 - July 2023

Coming soon ....

California Institute of Technology - LIGO

Intern Researcher: June 2022 - Sept 2022

I work on tackling non-linear dynamic control problems using deep learning. I specifically investigated attention-based state estimators and reinforcement learning for LIGO's locking acquisition to help detect gravitational waves. I work with Dr. Gabriele Vajente on this ambitious project.

Our preprint paper can be found here

UofT - Dunlap Institute for Astronomy & Astrophysics

Researcher Assistant: Dec 2021 - Apr 2022

Work on developing novel ensemble machine learning models for FRB detection with the CHIME/FRB project. My algorithm now actively runs in production to help improve the core detection pipeline. I am grateful to have worked under Prof. Bryan Gaensler! The goal is to one day use these detections to help astronomers answer important questions regarding the origins of these objects and potential cosmological questions.

UC Berkeley SETI Research Center

Co-mentor: Sept 2022 - Dec 2022

I co-mentor with Dr. Steve Croft. a group of undergraduates from UC Berkeley on developing a deep learning based "reverse image search" method for radio spectrograms leveraging the techniques from computer vision.

Intern Researcher: [June 2020 - April 2022] and [Sept 2022 - May 2023] On pause

Currently developing attention-based geometric deep learning models for the MeerKAT telescope to conduct the largest search effort for signs of life beyond Earth, surveying 1 million stars over a span of 2 years. I am supervised by Dr. Cherry Ng and Dr. Steve Croft,.

Previously I explored how deep neural nets like Disentangled B-VAE's can search 820 stars for technosignatures. My first paper was published in Nature Astronomy! Supervisors were Dr. Cherry Ng, and Dr. Andrew Siemion

In high school I helped build a distributed cloud computing platform for Astronomy Research with Dr. Steve Croft and Yuhong Chen!

AI For Good - Volunteering

Volunteer Researcher: May 2022 - Aug 2022

I work on developing Natural Language Processing models for text classification in building the sustainable development goal (SDG) data catalogue pipeline. The goal is to help build tools that power data driven policy making in achieving the 17 SDG goals set by the UN.