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= <NAME>
*Ph.D. candidate* \

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    Department of Physics, Yonsei University \
    Seoul, 03722, Republic of Korea
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    #text(yonsei)[#fa-icon("envelope", solid:true)#h(0.75em)]: #link("mailto:<EMAIL>")[`<EMAIL>`] \
    #text(yonsei)[#fa-icon("github", solid:true)#h(0.6em)]:#hide("123") #link("https://github.com/Axect")[`github.com/Axect`] \
    #text(yonsei)[#fa-icon("house", solid:true)#h(0.55em)]:#hide("1234") #link("https://axect.github.io")[`axect.github.io`]
  ]
)
\
== Education
#chiline()

*Physics*, _Yonsei University, Seoul, Republic of Korea_ #h(1fr) Mar. 2017 -- Aug. 2025 \
#h(1fr) *Ph.D.* \

*Astronomy*, _Yonsei University, Seoul, Republic of Korea_ #h(1fr) Mar. 2012 -- Feb. 2017 \
#h(1fr) *B.S.* \

== Military Service
#chiline()

*Technical Research Personnel*, _Yonsei University, Seoul, Republic of Korea_ #h(1fr) Sep. 2022 - Aug. 2025

#v(0.25cm)

== Research Areas & Expertise
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- *Dark matter physics*
  - Phenomenology of Axion-like particles & Primordial Black Holes
  - Detectability studies of dark matter candidates using various astrophysical and cosmological probes
  - Theoretical modeling and simulation of dark matter interactions

- *Machine Learning for Physics*
  - Development of deep learning models for missing information search and anomaly detection in high-energy physics data
  - Neural network approaches to learn and emulate complex physical systems and dynamics
  - Functional and operator learning for solving differential equations and modeling physical phenomena

- *Scientific & High Performance Computing*
  - Design and implementation of efficient numerical algorithms for physics simulations
  - Optimization of computational methods for large-scale data analysis in astrophysics and particle physics
  - Development of high-performance software tools for scientific computing, with a focus on Rust-based solutions
  - Application of parallel computing techniques to accelerate physics computations

#v(0.25cm)

== Programming Skills & Tools
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- *Primary Languages:* Rust, Python, C++, Julia, Haskell

- *Frameworks & Libraries*
  - *Numerical Computing:* `peroxide, numpy, scipy, pandas/polars, BLAS/LAPACK, eigen, matlab, mathematica`
  - *Machine Learning:* `pytorch, jax/equinox/optax, wandb, optuna, candle, tensorflow, scikit-learn`
  - *Visualization:* `matplotlib, vegas, ggplot2, plotly`
  - *High Energy Physics:* `BlackHawk, galprop, madgraph, root`
  - *Quantum Computing:* `pennylane, qiskit, cirq, rustqip`
  - *Web:* `django, vue, firebase, hugo, zola, elm`

#v(0.25cm)

== Honors & Fellowships
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- Academy Research Fellowship, Yonsei University (2022-2023)
- Best Oral Presentation Award, KPS 70th Anniversary and 2022 Fall Meeting (2022)
- Student Fellowship, IBS-CTPU (2017-2018)

#pagebreak()

== Publications
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        2024\
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    align(left)[
        #journal()["Neural Hamilton"], <NAME>, <NAME>, [`2410.XXXXX`]
        \
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        #journal()["HyperbolicLR: Epoch insensitive learning rate scheduler"], <NAME>, [#link("https://arxiv.org/abs/2407.15200")[`2407.15200`]]
        \
        \
        #journal()["Unsupervised sequence-to-sequence learning for automatic signal quality assessment in multi-channel electrical impedance-based hemodynamic monitoring"], <NAME>, <NAME>, <NAME>, #link("https://doi.org/10.1016/j.cmpb.2024.108079")[_Comput. Meth. Prog. Bio. 108079_], [#link("https://arxiv.org/abs/2305.09368")[`2305.09368`]]
        \
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        #journal()["DeeLeMa: Missing information search with Deep Learning for Mass estimation"], <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, #link("https://journals.aps.org/prresearch/abstract/10.1103/PhysRevResearch.5.043186")[_Phys. Rev. Res. 5. 043186_], [#link("https://arxiv.org/abs/2212.12836")[`2212.12836`]]
        \
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        #journal()["Axions from Primordial Black Holes"], <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, [#link("https://arxiv.org/abs/2212.11977")[`2212.11977`]]
        \
        \
    ]
)

== Talks 
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        2023 \
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    align(left)[
        #talk()["Exploration of PBHs and ALPs through a novel decay model on cosmological scale"]
        at _27th International Summer Institute on Phenomenology of Elementary Particle Physics and Cosmology_, Nantou, Taiwan \
        \
        #talk()["Exploration of PBHs and ALPs through a novel decay model on cosmological scale"]
        at _16th International Conference on Interconnections between Particle Physics and Cosmology_, Daejeon, Korea \
        \
        #talk()["Constraining ALPs via PBH with time-varying decay process"]
        at _Workshop on Physics of Dark Cosmos: dark matter, dark energy, and all_, Busan, Korea \
        \
        #talk()["Constraining ALPs via PBH with time-varying decay process Part.2"]
        at _KPS 70th Anniversary and 2022 Fall Meeting_, Busan, Korea \
        \
        #talk()["Bird's eye view of Neutron star cooling"] 
        at _16th Saga-Yonsei Joint Workshop_, Saga, Japan \
        \
    ]
)

== Recent Conference Attendance & Schools
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        Jul. 28 - Aug. 2\
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        Jan. 16 - 19\
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        Nov. 14 - 17\
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        Aug. 21 - 25\
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        Feb. 12 - 18\
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        *The 3rd workshop on Symmetry and Structure of the Universe*, JBNU, Korea\
        \
        *Cosmology workshop on the crossroads of astrophysics and particle physics*, Hongcheon, Korea\
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        *Workshop on Black Holes and Gravitational Waves*, IBS, Korea\
        \
        *Workshop on Dark Universe*, Yeosu, Korea\
        \
        *AI and Quantum Information for Particle Physics*, KAIST, Korea\
        \
        *27th International Summer Institute on Phenomenology of Elementary Particle Physics and Cosmology*, Nantou, Taiwan\
        \
        *Machine Learning in Particle Theory 2023*, Oppenheim, Germany\
        \
        *AI and Quantum Information Applications in Fundamental Physics*, Gwangju(-si), Korea\
        \
    ]
)

#pagebreak()

== Teaching Experience
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      *Introduction to General Relativity*, PHY4208, Yonsei University, Seoul, Republic of Korea\ 
      \
      *Quantum Mechanics (2)*, PHY3102, Yonsei University, Seoul, Republic of Korea\
      *Quantum Mechanics (1)*, PHY3101, Yonsei University, Seoul, Republic of Korea\
      \
      *Quantum Mechanics (2)*, PHY3102, Yonsei University, Seoul, Republic of Korea\
      *Elementary Particle Physics I*, PHY8050, Yonsei University, Seoul, Republic of Korea\
      \
      *Gravity I: General Relativity*, PHY8030, Yonsei University, Seoul, Republic of Korea\
      *Mathematical Physics (1)*, PHY4205, Yonsei University, Seoul, Republic of Korea
  ]
)

#v(0.25cm)

== Selected Open Source Projects
#chiline()

*Peroxide* #h(1fr) Sep. 2018 -- Present
- Comprehensive Rust numeric library for linear algebra, numerical analysis, and statistics #h(1fr) #link("https://github.com/Axect/Peroxide")[#fa-icon("star")] #h(0.5em): #hide("421,")509
- Customizable features for pure Rust, BLAS/LAPACK integration, and plotting capabilities #h(1fr) #link("https://crates.io/crates/peroxide")[#fa-icon("download")] #h(0.5em): 445,676
- Includes automatic differentiation, special functions, DataFrame functionality, and various numerical algorithms

#v(0.2cm)

*Puruspe* #h(1fr) Feb. 2020 -- Present
- Pure Rust library for special functions with no external dependencies #h(1fr) #link("https://github.com/Axect/Puruspe")[#fa-icon("star")] #h(0.5em): #hide("428,4")14
- Implements gamma, beta, and error functions, including their regularized and inverse versions #h(1fr) #link("https://crates.io/crates/puruspe")[#fa-icon("download")] #h(0.5em): 444,079
- Lightweight and efficient implementation ideal for mathematical and scientific computing

#v(0.2cm)

*PyTorch Template* #h(1fr) Aug. 2024 -- Present
- Flexible PyTorch template for ML experiments with modular structure #h(1fr) #link("https://github.com/Axect/PyTorch-Template")[#fa-icon("star")] #h(0.5em): #hide("123,45")7
- Supports YAML-based configuration for easy experiment setup and reproducibility
- Supports multiple random seeds, device selection, and learning rate scheduling for robust experimentation

#v(0.2cm)

*Quantum Algorithms* #h(1fr) Dec. 2023 -- Jun. 2024
- Implement quantum algorithms in Pennylane, RustQIP, Qiskit and Cirq #h(1fr) #link("https://github.com/Axect/QuantumAlgorithms")[#fa-icon("star")] #h(0.5em): #hide("123,45")5
- Provide jupyter notebooks for quantum algorithms with detailed descriptions and interactive visualizations

#v(0.2cm)

*Radient* #h(1fr) Nov. 2023 -- Dec. 2023
- Rust library for automatic differentiation using computational graphs #h(1fr) #link("https://github.com/Axect/Radient")[#fa-icon("star")] #h(0.5em): #hide("123,45")2
- Implements forward and backward propagation for gradient computation #h(1fr) #link("https://crates.io/crates/radient")[#fa-icon("download")] #h(0.5em): #hide("12")1,366
- Supports various mathematical operations and provides flexible gradient calculation options

#v(0.2cm)

*Forger* #h(1fr) Nov. 2023 -- Nov. 2023
- Reinforcement Learning (RL) library implemented in Rust #h(1fr) #link("https://github.com/Axect/Forger")[#fa-icon("star")] #h(0.5em): #hide("123,45")3
- Modular design with components for agents, environments, policies, and utilities #h(1fr) #link("https://crates.io/crates/forger")[#fa-icon("download")] #h(0.5em): #hide("12")2,850
- Framework for creating diverse RL environments, including implementations of Epsilon Greedy Policy and Q-Learning

#v(0.2cm)

*RGE* #h(1fr) Aug. 2017 -- Oct. 2017
- Go package for solving Renormalization Group Equations with Julia integration for plotting #h(1fr) #link("https://github.com/Axect/RGE")[#fa-icon("star")] #h(0.5em): #hide("123,45")4
- Modular structure with customizable constants, variables, and beta functions for flexible RGE implementation
- Supports numerical integration methods and parallel processing for efficient computation
