CV

Education, research experience, awards and skills. A PDF version is available above.

Contact Information

Name Eugene (Yoogeun) Song | 송유근
Professional Title Physicist, Machine Learning Engineer, Quantitative Researcher
Email yoogeun.song24@imperial.ac.uk

Professional Summary

High-energy physicist at Imperial College London, working on neutrino physics with the Imperial High Energy Physics group on the NOvA and DUNE collaborations under Dr Linda Cremonesi - a variety of physics analyses on NOvA, and systematics-aware machine learning reconstruction with Bayesian and MCMC inference on DUNE, where the Near Detector is not a control detector but the constraint engine that makes precision oscillation measurements possible. My work sits at the point where physical modelling, machine learning and statistical inference stop being separate disciplines and become one problem: inference under uncertainty. Alongside the neutrino work I build physics-informed neural networks for real-time atrial fibrillation mapping - AtriPINN, at ~78 ms end-to-end latency and ~1.6 mm RMS localisation error on clinical data - and collaborate part-time with Singularity Quantum on quantum-accelerated computational fluid dynamics for non-invasive cardiovascular diagnostics. Previously I have worked on general relativity and early-universe cosmology, black hole magnetospheres and Blandford–Znajek energy extraction, and GRMHD modelling of Sagittarius A* at UCL; and, from October 2025 to August 2026, an independent quantitative research practice on alpha under non-stationary market dynamics.

Experience

  • 2026 - Present

    London Area,
    United Kingdom

    PhD Researcher
    Imperial College London
    • I work on neutrino interactions, oscillations, detector analysis, and ML reconstruction techniques with Fermilab’s (American) flagship collaborations - DUNE (Deep Underground Neutrino Experiment) and NOvA (NuMI Off-axis νe Appearance) programs - under the supervision of Dr Linda Cremonesi. On NOvA I work on a variety of physics analyses.
  • 2026 - Present

    California,
    United States · Remote

    Research Scientist Intern
    Singularity Quantum · Internship
    • I work alongside the research team across fluid dynamics, computational modelling, machine learning, software, quantum algorithms, and data analysis for cardiovascular computational fluid dynamics (CFD): blood-flow simulation, haemodynamic analysis, and the reconstruction problems underlying both.
    • I build the mathematical and computational models, simulations, quantum algorithms, software, papers, and technical reports that carry that work: from first formulation through to something reproducible.
    • I contribute to the research, development, testing, and documentation behind our cardiovascular products, principally FFR-CT and plaque analysis.
    • I design, train, and evaluate physics-informed machine-learning models. Foundational models where they earn their place; physics constraints where the data runs out.
    • I research tumour microcirculation, cancer-cell biology, and drug delivery, tracking the academic literature alongside the technologies, markets, and competitors moving in the same space.
    • I take on quantum computing research and the quantum engineering, analysis, and business work that sits around it.
  • 2025 - Present

    London Area,
    United Kingdom

    Graduate Researcher
    Imperial College London
    • I’m conducting cross-disciplinary research by fusing particle physics-style modelling, Machine Learning (ML), and bioengineering to decode atrial fibrillation (Afib), using spatiotemporal reconstruction and data-driven simulations to map Afib wave dynamics and reveal the underlying electrical mechanisms. To do so, my primary focus has been on utilising and implementing various Physics-Informed Neural Networks (PINN) and to architect my own framework.
    • For my current PINN research project, I’m collaborating with Prof. David Colling (Imperial HEP group) and Dr. Nick Linton (Imperial Department of Bioengineering).
    • Built end-to-end ML code “AtriPINN” (PyTorch): modular Wave and Eikonal and EP-PINNs backends with one shared data → train → viz pipeline.
    • Delivered real-time mapping: ~78 ms end-to-end latency, ~1.6 mm RMS localisation error (sub-2 mm target), ≥ 0.99 channel cross-correlation.
    • Software-engineered time-shifted kNN blending for inter-electrode signals + differentiable cross-correlation objective function for physiologic timing consistency.
    • Implemented local plane-fit velocity extraction and advection-based velocity fields, and implemented coordinate-agnostic features (Cartesian, cylindrical, spherical) into my code AtriPINN.
    • Scaled Neural Network training with AMP mixed precision, RAR and adaptive collocation, Adam → L-BFGS optimisation, gradient clipping, and curriculum scheduling.
    • Shipped v1–v11.2 with CLI tooling, robust logging, and edge-deployment optimisations (GPU memory and throughput).
    • Currently producing reproducible releases (configs, sample data, animations) to support clinical translation and benchmarking.
    • Tech used: Python (PyTorch), NumPy, SciPy, Matplotlib, CUDA/GPU, CLI tooling, Git.
  • 2024 - Present

    London Area,
    United Kingdom

    Member
    Imperial College Algorithmic Trading Society
    • Attended the Algorithmic Trading (Algo) courses organised by the IC Algorithmic Trading Society.
  • 2024 - Present

    London Area,
    United Kingdom

    Member
    Imperial College Investment Society
  • 2025 - 2026

    London Area,
    United Kingdom

    Quantitative Researcher
    Independent
    • Independent quantitative research on alpha generation under non-stationary market dynamics.
    • Emphasis on structural constraints (impact, inventory, liquidity, latency) as anchors for models.
    • Study agent adaptation and regime shifts without overfitting.
    • Physics-inspired approach to separating signal from noise.
  • 2024 - 2025

    London Area,
    United Kingdom

    Master's Studies
    Imperial College London
  • 2023 - 2024

    London Area,
    United Kingdom

    Visiting Researcher
    UCL
    • Began remotely (Jan–Jun 2023) with Dr. Ziri Younsi via weekly Zoom sessions, designing general relativistic magnetohydrodynamic (GRMHD) modelling strategies for Sagittarius A* and M87*, and the subsequent radiative transfer post-processing.
    • Performed a comprehensive literature review of the Event Horizon Telescope (EHT) collaboration’s relevant works on Sagittarius A* and M87*.
    • Invited on-site as a visiting researcher (Jul 2023–Apr 2024), working with Dr. Ziri Younsi and Prof. Kinwah Wu to implement and optimise GRMHD simulations integrated with general relativistic radiative transfer (GRRT) codes, both in Fortran and Python.
    • Modelled the multi-wavelength variability of Sagittarius A* by integrating GRMHD simulations with GRRT calculations: publication in preparation.
    • Connected with and held Zoom discussions with Event Horizon Telescope (EHT) collaboration’s key researchers, including Dr. Christian M. Fromm and Dr. Koushik Chatterjee (UMD).
    • Gained hands-on experience with high-performance computing, data visualisation, and interdisciplinary teamwork in a leading astrophysics environment.
  • 2020 - 2022

    Europe

    Independent Researcher
    Collaboration with National Astronomical Observatory of Japan
    • During the worldwide pandemic, to maintain research momentum despite pandemic-induced changes, I collaborated remotely (2020–2022) with Dr. Isao Okamoto (NAOJ) to develop modified Blandford–Znajek energy-extraction models for Kerr black holes (see arXiv:1904.11978 and 2401.12684).
    • I also attended multiple conferences across Europe, including key events in Spain, e.g. EAS 2022.
    • Reconnected and held discussions with various researchers in Europe while I was there, including Prof. Francisca Kemper, Dr. Frank M. Rieger, Dr. Benoît Cerutti, Prof. Bożena Czerny, Dr. Oliver Porth, and Dr. Ziri Younsi.
    • Mainly travelled to the Netherlands and Spain to expand my professional network and cultural insights.
    • As a lifelong language enthusiast passionate about European languages, already intermediate in French and German, I also picked up Spanish in my spare time during this period (2022).
  • 2018 - 2020

    7th Engineer Brigade,
    VII Corps,
    Republic of Korea

    National Service
    Republic of Korea Army
    • Completed mandatory military service as an Army Driver with the VII Corps’ 7th Engineer Brigade, responsible for vehicle operations, vehicle maintenance, and training new drivers.
    • Honoured with the brigade’s “Exemplary Army Driver” (모범 운전병) distinction in 2020 in recognition of my outstanding operational and driving skills and commitment to safety.
    • Regularly trained in marksmanship and consistently ranked among the top 5 marksmen with the K2 assault rifle in my company.
    • Excelled in physical endurance and fitness training: regular 3 km runs, push-ups, sit-ups, and pull-ups, and represented my company in the brigade-level bodyweight fitness competition (2020).
    • Awarded the “Special Grade Warrior” (특급전사) distinction by the brigade in 2020 for my outstanding performance across all key military competencies, including marksmanship, combat training, tactical expertise, weapon proficiency, and most importantly, fitness.
    • Promoted to Sergeant before my honourable discharge in 2020.
  • 2018 - 2018

    Tokyo, Japan

    Visiting Researcher
    National Astronomical Observatory of Japan (NAOJ)
    • Invited by Dr. Isao Okamoto for a four-month visiting research position to work on a modified Blandford–Znajek mechanism for electromagnetic energy extraction from Kerr black holes.
    • Developed a zero-angular-momentum-observer (ZAMO) treatment in which the force-free magnetosphere is divided at the null surface and electromagnetic energy is shown to be self-extracted across it (see arXiv:1904.11978).
    • Continued the collaboration remotely with Dr. Okamoto until the end of 2022, resulting in two arXiv preprints (1904.11978 and 2401.12684).
  • 2013 - 2018

    Republic of Korea

    Graduate Researcher
    University of Science and Technology & Korea Astronomy and Space Science Institute
    • Conducted advanced research on relativistic cosmology and high-energy cosmic ray emissions from the immediate vicinity of the magnetospheres of compact objects (e.g. black holes).
    • In my cosmology work, I derived Raychaudhuri-type and shear-evolution equations for timelike and null geodesic congruences in the Bianchi I anisotropic early Universe model, hinting at how primordial shear can imprint observable anisotropies on the gravitational-wave background (see arXiv:1604.07639).
    • Authored 4 academic papers in total whilst there; all accessible via arXiv.
  • 2009 - 2018

    Republic of Korea

    Graduate/Postgraduate Studies
    University of Science and Technology & Korea Astronomy and Space Science Institute
    • In Feb 2009, at the remarkable age of 11, I joined the integrative (Master’s + PhD) program at the Korea University of Science and Technology (UST), based at the Korea Astronomy and Space Science Institute (KASI) campus.
    • My PhD coursework was completed in February 2013 (age 15).
  • 2017 - 2018

    Taiwan

    Visiting Student
    Academia Sinica, Taiwan
    • Invited as a visiting student (Apr 2017 – May 2018) at the Academia Sinica Institute of Astronomy and Astrophysics, collaborating with Dr. Kouichi Hirotani and Dr. Satoki Matsushita.
    • In my high-energy astrophysics work, I performed a semi-analytic modelling of the acceleration of electrons and positrons in magnetic-field-aligned electric fields around accreting black holes (see Song et al. 2017, MNRAS). I wrote this at the age of 19.
    • Investigated gamma-ray emissions produced by stellar-mass black holes interacting with dense molecular clouds (see Hirotani et al. 2018, ApJ).
    • Published 2 peer-reviewed academic papers detailing these works in Monthly Notices of the Royal Astronomical Society (MNRAS) and The Astrophysical Journal (ApJ).

Education

  • 2026 - 2030

    London,
    United Kingdom

    PhD
    Imperial College London
    Elementary Particle Physics - Neutrino physics with DUNE and NOvA
    • Supervised by Dr Linda Cremonesi - UKRI Future Leaders Fellow and spokesperson of the NOvA experiment.
    • Systematics-aware ML reconstruction and Bayesian/MCMC inference for the DUNE Near Detector.
    • Neutrino oscillations and interactions with the NOvA experiment at Fermilab, working across a variety of physics analyses.
    • Near-Detector to Far-Detector constraint propagation for precision oscillation measurements.
  • 2024 - 2025

    London,
    United Kingdom

    Masters
    Imperial College London
    Physics
  • 2009 - 2018

    Daejeon,
    Republic of Korea

    Integrated MSc + PhD (Coursework Completed)
    University of Science and Technology (UST) & Korea Astronomy and Space Science Institute
    Astronomy and Space Science
    • Entered the integrated graduate programme at age 11; completed PhD-level coursework in February 2013, at age 15.
    • From 2013 to 2018, conducted graduate-level research on relativistic cosmology and high-energy astrophysics, advised by Dr Seok Jae Park.
    • Visiting student at the Academia Sinica Institute of Astronomy and Astrophysics (2017–2018), working with Dr Kouichi Hirotani and Dr Satoki Matsushita: two peer-reviewed papers, Song et al. (2017), MNRAS Letters and Hirotani et al. (2018), ApJ.
    • Four papers authored in total during this period, across cosmology and high-energy astrophysics; all available on arXiv.
    • Funded throughout by the government-established Song Yoo-geun Project (송유근 프로젝트), and regularly engaged in science communication and media outreach across Korea.
  • 2006 - 2009

    Seoul,
    Republic of Korea

    BSc (Academic Credit Bank System)
    National Institute for Lifelong Education (NILE)
    Computer Science
    • Read Computer Science through NILE’s Academic Credit Bank System; credits earned at Inha University were formally transferred and recognised here.
    • Graduated in 2009 at age 11, a milestone never previously achieved in Korea, and recognised the same year by the National Assembly’s Special Award (특별상).
  • 2006 - 2009

    Incheon,
    Republic of Korea

    BSc (transferred to NILE)
    Inha University
    Physics
    • Admitted to the Department of Physics in October 2005 as Korea’s youngest-ever undergraduate, at age 7, with coursework beginning in February 2006.
    • Held a full scholarship and a monthly subsidy from Inha throughout.
    • Completed first-year Physics, then transferred to the Computer Science programme at NILE, where the credits were recognised and the degree completed.

Awards

  • 2020
    Special Grade Warrior (특급전사) and Exemplary Army Driver (모범 운전병)
    Republic of Korea Army

    Awarded in 2020 for top-tier performance across physical, marksmanship and duty standards during national service.

  • 2009
    Special Award (특별상)
    The National Assembly of the Republic of Korea

    Issued by The National Assembly of the Republic of Korea, in association with the National Institute for Lifelong Education (NILE). Awarded in 2009, in recognition of graduating with a Bachelor of Science in Computer Science at the exceptional age of 11, marking a nationally celebrated academic milestone.

  • 2009
    Song Yoo-geun Project — National Talent Development Initiative
    Government of the Republic of Korea

    Started in 2009, a national initiative named in my honour (“송유근 프로젝트”) by the Government of the Republic of Korea to support the advancement of exceptional talent. Through the programme I received government funding for my graduate studies and research at the Korea Astronomy and Space Science Institute (KASI) and the University of Science and Technology (UST), from 2009 to 2018.

  • 2006
    Special (Pre-College) Scholarship & Monthly Subsidy
    Inha University

    A named scholarship and support programme, alongside Inha University and Real Company scholarships, 2006–2008.

Skills

Programming (Expert): Python, PyTorch, NumPy, SciPy, Pandas, Matplotlib, C, Fortran, Mathematica, CUDA/GPU, Git, CLI tooling, LaTeX, Julia
Methods (Expert): Physics-Informed Neural Networks, Bayesian inference, MCMC, Monte Carlo, statistical modelling, uncertainty quantification, GRMHD/GRRT pipelines, stochastic control (HJB), time-series analysis
Physics domains (Expert): Neutrino physics, particle physics, BSM, high-energy astrophysics, general relativity, cosmology, black hole magnetospheres
Quantitative finance (Intermediate): Alpha research, non-stationary regimes, market microstructure, futures and derivatives, equities, backtesting discipline

Languages

Korean : Native
English : Native / bilingual
French : Professional working proficiency
Italian : Intermediate (actively learning)
Spanish : Elementary
Japanese : Elementary
German : Elementary

Interests

Research: Neutrinos and BSM physics, machine learning for physics, inference under uncertainty, first-principles modelling
Markets: Non-stationary time series, stochastic control, market microstructure, risk
Beyond work: Running, triathlon, yoga, calisthenics, Brazilian Jiu-Jitsu, skiing and snowboarding, tennis, golf, chess and poker, languages, classical music, film
West London rooftops at sunset, a church spire in silhouette and the city skyline beyond
London at sunset, looking out over the rooftops from Imperial buildings.
Linkedin
Eugene (Yoogeun) Song
Eugene (Yoogeun) Song

Neutrino Physics @ Imperial College London, DUNE & NOvA Collab || Machine Learning || Quantum Computing || Quant Researcher || Multidisciplinary Scientist || Physics × ML × QC × Quant || 🇬🇧 London-based (2023–Present)

Imperial College London | Imperial College London

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