Hi there! 👋 I'm a first year Astrophysics PhD student at UC Berkeley. Previously, I did my undergrad at the University of Toronto in Applied Mathematics. Broadly, I'm interested in Machine Learning applied to (astro)physics. I'm fascinated both by the world of atoms and bits.
In the past I've written ML models in firmware on FPGA's for the High-Luminosity Large Hadron Collider at CERN. Before that, I developed deep learning algorithms to assist controlling LIGO at Caltech. I have also worked on applying neural simulation based inference to study Dark Matter effects on stellar streams in simulations at the Dunlap Institute of Astronomy and Astrophysics. At the same time, I was at UofT's Computer Science Dept looking at building transformers for equation discovery and symbolic regression. And before that, I developed an ensemble learning algorithm for Fast Radio Burst detection deployed on the CHIME radio telescope at the Dunlap Institute of Astronomy and Astrophysics.
My first research project was developing an end-to-end deep learning algorithm to search for signs of advanced life beyond Earth with Breakthrough Listen.
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 :)
First Author Published Papers (Undergrad)
A deep-learning
search for radio technosignatures from 820 nearby stars
Ma, P. et al. (2023)
Nature Astronomy - Published here
A Deep Neural Network Based Reverse Radio Spectrogram Search
Algorithm
Ma, P. et al. (2024)
RAS Techniques and Instruments - Published
here
A Deep Learning Technique to Control the
Non-linear Dynamics of a Gravitational-wave
Interferometer
Ma, P. & Vajente, G. (2024)
Classical and Quantum Gravity IOP - Published
here
Towards Identifying the Fundamental Properties of Dark Matter through Graph Neural Network Analysis of Stellar Streams
Ma, P. et al. (2024)
- In prep
...
Co-Authored Papers
AstroCompress: A benchmark dataset for
multi-purpose compression of astronomical data
T. Truong*, R. Sudharsan*, Y. Yang, P. Ma, R. Yang, S. Mandt, J.S.Bloom (2024)
- Submitted Neurips Dataset
Unpublished Manuscripts
Developing Firmware and Algorithms for the Liquid Argon Signal Processor
Ma, P. et al. (2023) - CERN report here
Machine Learning and Simulation Strategies To Improve Fast Radio Burst Detection
Ma, P. et al. (2022) - report here
Researcher Assistant: Sept 2023 - April 2024
Investigating the emergence of sparsity in the development of deep learning models in solving physics based problems. Also look at the use of Large Language Models and prompting for novel knowledge generation in physics based problems. Supervised by Prof. Vardan Papyan.
UofT - Dunlap Institute for Astronomy & Astrophysics
Researcher Assistant: Sept 2023 - April 2024
First we look into building faster emulators for dark matter simulations. Look into using JAX for faster gradient computation when producing forward progating models. Secondly we look symbolic regression on deep learning models in learning cosmological struture formation. Supervised by Dr. Keir K. Rogers.
CERN - ATLAS / Large Hadron Collider
Intern Researcher: July 2023 - Sept 2023
Continuing my work at McGill [below] I worked on building deep learning algorithms on low level FPGA's to reconstruct energy readouts from the Liquid Argon Digital Signal Processor for the ATLAS detector on the future High Luminosity Large Hadron Collider. I also help around with developing firmware on digital electronics.
McGill University - Experimental Particle Physics Group
Intern Researcher: May 2023 - July 2023
I work on developing high performance FPGA firmware for the Liquid Argon Signal Processing Unit (LASP) to be attached on the ATLAS detector. I also worked on developing functional hardware test for our LASP digital electronics. Supervised by Prof. Brigitte Vachon
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!
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.
ASTRON 128 [Astronomy Data Lab] - Graduate Student Instructor
Teaching Portfolio Here
I am grateful to have supported students on various research projects in the past!
Mentoring/Co-Mentoring Undergradate Students
Stephanie Lee @ UofT Astronomy [2024 May - 2024 Aug] Co-mentor: Prof. Renee Hložek (Proj: Improving Simulation of Stellar Streams and Dark Matter Halo Interactions )
Daniel Saragih @ UofT CS [2024 May - 2024 Aug] Co-mentor: Prof. Renee Hložek (Proj: Improving Simulation Based Inference Models for DM Stellar Stream Interactions)
Ben Jacobson-Bell @ Cornell Astronomy [2024 May - 2024 Aug] Dr. Steve Croft (Improved Candidate Searches in Green Bank Telescope Data)
Corrina Wu @ UC Berkeley CS [2022 Sept - 2023 Jan] Co-mentor: Dr. Steve Croft ( Proj: computer vision models for radio astronomy data using RESNET-50) Poster
Mentoring/Co-Mentoring High School Students
Jacob Lipman [2024 May - 2024 Aug] (TBD)
UC Berkeley - Astrophysics PhD 2024 - present
University of Toronto - Math and Physics Specialist 2020-2024
The Knowledge Society (TKS) 2018-2020
Unionville High School 2016-2020
Research Funding / Fellowships
Allan and Kathleen Rosevear Gateway Fellowship - 2024 April
Berkeley Fellowship - 2024 March
UCL Research Excellence Award [declined] - 2024 March
NSERC Undergraduate Student Research Awards - 2023 March
IPP Summer Student Fellowship - 2023 Jan
Caltech SURF Fellowship - 2022 April
Laidlaw Research Scholar - 2021 April
Scholarships
Victoria College Incourse Scholarship- 2022 August
The Gregory L and Margaret I Baker Scholarship - 2021 August
Invited Talks
APS [American Physical Society] New York [Speaker]- April 2022
RFI2022 Reading UK [Speaker]- Feb 2022
Regular Awards
Mars Institute Honorary Distinction Award - 2020 June
Silver Medalist and Best of Physical Sciences - IRIC INSPOScience Fair [North America] 2020 June