Portfolio

Work list

By YoungJoong Kim 14 March 2020
Work list

Skills

  1. Languages
    : Python
    : C++ [revsic/cpp-obfuscator]

  2. ML Framework
    : Tensorflow [revsic/tf-glow-tts, revsic/tf-diffwave]
    : PyTorch [revsic/torch-retriever-vc, revsic/torch-diffusion-wavegan]
    : Jax/Flax [revsic/jax-variational-diffwave]

  3. Windows Internal [revsic/cpp-veh-dbi]

Opensource Contribution

  • sgl-project/sglang [GIT, PR#411], 2024.05.
    Cohere Command-R chat template supports.

  • linfeng93/BiTA [GIT, PR#4], 2024.02.
    Hard-coded path removal.

  • SqueezeBits/QUICK [GIT, PR#3], 2024.02.
    Exclude router projection layers from QUICK quantization.

  • microsoft/TransformerCompression [GIT, ISSUE#81], 2024.01.
    Mixtral 8x7B SliceGPT post-train pruning supports.

  • casper-hansen/AutoAWQ [GIT, PR#251], 2023.12.
    Mixtral 8x7B Activation-aware Quantization supports.

Projects - Machine Learning

  1. np-gaussian-process [GIT], 2019.
    : Numpy implementation of Gaussian Process Regression.

  2. AlphaZero Connect6 [GIT], 2018.
    : AlphaZero training framework for game Connect6 written in Rust with C++, Python interface.

  3. numpy-rnn [GIT], 2017.07
    : Numpy implementation of vanilla-rnn and lstm for solving binary addition and mnist classification problem.

  4. Fine Dust Prediction [GIT], 2017.
    : Predict amount of fine dust for next 7 days via Convolutional LSTM based on Tensorflow.

  5. Behavior based Malware Detection Using Branch Data [GIT], 2017.
    : Classify malware from benign software using branch data via LSTM based on Tensorflow

Projects - Windows Internal

  1. cpp-veh-dbi [GIT], 2019.
    : C++ implementation of vectored exception handler based simple dynamic binary instrumentation tools.

  2. Branch Tracer [GIT], 2019.
    : C++ implementation of dll-based windows debugger for tracking branching instruction via vectored exception handler.

  3. Code-Injector [GIT], 2018.
    : C++ implementation of several code injection techniques like dll injection, queue user apc.

  4. AntiDebugging [GIT], 2017.
    : C++ implementation for defending windows debugger from attaching the target process.

Projects

  1. cpp-concurrency [GIT], 2019.
    : C++ implementation of golang-style concurrency supports, thread pool, channel, wait-group

  2. cpp-obfuscator [GIT], 2019.
    : C++ implementation of compile time string and routine obfuscator.

  3. TopMost [GIT], 2019.
    : C++ implementation of topmost library for windows and javascript support.

  4. RosettaStone [GIT], 2018.
    : C++ implementation of game ‘Hearthstone’ as training environment and A.I. for future work.

  5. Haskell Calculator [GIST], 2017.
    : Haskell implementation of calculator with generic binary operators.

  6. ThreeByteVM [GIST], 2017.
    : C implementation of simple virtual machine that word size is 3 bytes.

  7. PacketInjector [GIT], 2016.
    : C++ implementation of simple packet detector and injector.

  8. ELF Code Virtualization, 2015.
    : ELF (Executable Linkable Format) Virtualized Code Protection

Paper implementation

  • torch-nansy++ [GIT], 2022.12.
    : NANSY++: Unified Voice Synthesis with Neural Analysis and Synthesis, openreview, 2022.

  • torch-whisper-guided-vc [GIT], 2022.12.
    : Torch implementation of Whisper-guided DDPM based Voice Conversion

  • torch-nansy [GIT], 2022.09.
    : Neural Analysis and Synthesis: Reconstructing Speech from Self-Supervised Representations, Choi et al., 2021.

  • torch-retriever-vc [GIT], 2022.04.
    : Retriever: Learning Content-Style Representation as a Token-Level Bipartite Graph, Yin et al., 2022.

  • torch-diffusion-wavegan [GIT], 2022.03.
    : Parallel waveform generation with DiffusionGAN, Xiao et al., 2021.

  • torch-tacotron [GIT], 2022.02.
    : PyTorch implementation of Tacotron, Wang et al., 2017.

  • tf-mlptts [GIT], 2021.09.
    : Tensorflow implementation of MLP-Mixer based TTS.

  • jax-variational-diffwave [GIT], [arXiv:2107.00630], 2021.09.
    : Variational Diffusion Models

  • tf-glow-tts [GIT] [arXiv:2005.11129], 2021.07.
    : Glow-TTS: A Generative Flow for Text-to-Speech via Monotonic Alignment Search

  • tf-survae-flows [GIT], [arXiv:2007.023731], 2021.05.
    : SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows

  • tf-diffwave [GIT] [arXiv:2009.09761], 2020.10.
    : DiffWave: A Versatile Diffusion Model for Audio Synthesis, Zhifeng Kong et al., 2020.

  • Rewriting-A-Deep-Generative-Models [GIT] [arXiv:2007.15646], 2020.09.
    : Rewriting a Deep Generative Model, David Bau et al., 2020.

  • tf-alae [GIT] [arXiv:2004.04467], 2020.09.
    : Adversarial Latent Autoencoders, Stanislav Pidhorskyi et al., 2020.

  • tf-neural-process [GIT] [arxiv: NP, CNP, ANP], 2019.05
    : Neural process, Conditional Neural Process, Attentive Neural Process

  • tf-vanilla-gan [GIT] [arXiv:1406.2661], 2018.01.
    : Generative Adversarial Nets, Ian J. Goodfellow et al., 2014.

School Works

  1. HYU-ITE2038 [GIT]
    : Database Systems and Applications in Hanyang University

  2. HYU-CSE4007 [GIT]
    : Artificial Intelligence

  3. HYU-ELE3021 [GIT]
    : Operating System

Study

  1. Modern C++ Challenge [GIT]
    : Challenge real-world problems with C++17 features

  2. Stanford-CS166: Data Structure
    : Data structure for undergraduate

Paper

  1. Behavior Based Malware Detection Using Branch Data
    : 2017 KIISE Korea Computer Science Conference, 2017.

Presentation

  1. Math for A.I., Generative Models
    : Mapo High School, 2023.11.28.

  2. The 2nd AI & Dining. Virtual Human and Generative Models
    : Sangmyung University, 2022.09.22.

  3. Deep learning and A.I.
    : Danggok High School, 2022.08.30.

  4. 2022 A.I.U. Research generative models in Startup [Google Drive]
    : A.I.U. 2022 AI Confrerence, 2022.05.

  5. Developing Environment for RL
    : Nexon Developers Conference 2019 as team RosettaStone, 2019.

  6. GP to NP: Gaussian process and Neural Process
    : A.I.U 1st Open AI Conference, 2018.

  7. Hearthstone++: Hearthstone simulator with reinforcement learning
    Deep Learning Camp Jeju, 2018.

  8. Behavior based Malware Detection Using Branch Data
    : CodeGate 2017 Junior, 2017.

Awards

  1. KISA, 2016 Software Contest,
    Application Security Section 2nd Prize (Minister of Interior Award) 2016.09

Education

  1. M.S. Department of Computer Science and Engineering
    Seoul National University, Visual & Geometric Intelligence Lab (2025.03. ~ )

  2. B.S. Department of Mathematics
    Hanyang University (2019.03. ~ 2025.02.)

  3. B.S. Department of Computer Science and Engineering
    Hanyang University (2018.03. ~ 2025.02.)

  4. Vulnerability Analysis Track
    : 5th KITRI BoB (2016.05. ~ 2017.03.)

  5. Department of Information and Communication Technology
    : Sunrin Internet High School (2015.03. ~ 2017.02.)

Works

  1. AI for Offensive Security, Senior Researcher
    Theori (2024.10. ~ )

  2. Research Team Lead
    Theori (2023.08. ~ 2024.10.)

  3. Video Synthesis, Deep learning Researcher
    LionRocket (2021.10. ~ 2022.10., 2023.03. ~ 2023.08.)

  4. Research Team Lead
    LionRocket (2021.04. ~ 2023.08.)

  5. Text-to-Speech, Deep learning Researcher
    LionRocket (2019.09. ~ 2021.10., 2022.10. ~ 2023.02.)