Peter Ma Hi there! 👋 I'm a second 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. During undergrad 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 :) Papers First Author (Graduate projects) Deploying AI Driven Wavefront Estimation to the Vera C. Rubin Observatory Ma, P. et al. (2025) In prep. First Author (Undergrad projects) 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 characterizing dark matter subhalo perturbations in stellar streams with graph neural networks Ma, P. et al. (2025) - Astrophysical Journal Published here A Deployed Real-Time End-to-End Deep Learning algorithm for Fast Radio Burst Detection Ma, P. et al. (2025) - Accepted to Astronomy and Astrophysics Journal ... 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astronomical data T. Truong*, R. Sudharsan*, Y. Yang, P. Ma, R. Yang, S. Mandt, J.S.Bloom (2024) - Accepted ICLR 2025 Unpublished Manuscripts Developing Firmware and Algorithms for the Liquid Argon Signal Processor Ma, P. et al.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 Experience UofT Dept. Computer Science 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! 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. Teaching ASTRON 128 [Astronomy Data Lab] - Graduate Student Instructor Teaching Portfolio Here Mentoring 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) Education 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 Awards Research Funding / Fellowships LSST-DA Data Science Fellowship (DSFP) - 2026 April 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 2022 Finalist American Statistical Association Astrostatistics Best Student Paper Competition- 2022 Jan Mars Institute Honorary Distinction Award - 2020 June Silver Medalist and Best of Physical Sciences - IRIC INSPOScience Fair [North America] 2020 June McHacks Hackathon @ McGill MLH Award- 2020 Feb Hack the Hammer 2 @ McMaster Best Design Award - 2019 Dec Media Nature Astronomy Paper Press Nature Breakthrough Foundation The Globe and Mail VICE Motherboard The Verge The Inverse University of Toronto News CBC Radio The Conversation Popular Science Probably more, I've lost track ... 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