Donghyun Lim

Curriculum Vitae

Donghyun LIM (임동현, 林東炫)

• donghyunismyname@gmail.com
• Software Engineer
• Theoretical Computer Scientist

Skills

C++, CMake, Python, PyTorch, OpenCV, Web, Computer Vision, Computational Complexity

Work Experience

(Mar2024-now) Software Engineer, Unnamed Startup

Various Technical Proofs of Concept, Fast Adaptation to New Domain

• Software Plugin
  • .NET Reverse Engineering
• Automated Content Generation
  • AI API (ChatGPT, HuggingFace, StableDiffusion, ElevenLabs)
• Business Analysis based on Online Data
  • Web Scraping (HTTP, TLS, TCP, IP, Javascript, Selenium, Puppeteer)
• Full Stack Dev
  • Front (HTML, CSS, Javascript, Kakao Map, KakaoTalk Chatbot)
  • Back (Docker, Flask, AWS Lambda, GCP Functions, GCP Firestore NoSQL DB)
  • Infra (AWS EC2, RunPod, GitHub Pages)

(Sep2021-Mar2024) Computer Vision Research Engineer, NALBI

Human Motion Capture with Vision AI (Apr2022-Mar2024)

• Algorithm Implementation
  • Implemented appropriate geometric algorithms for handling rotations in 3D
  • Optimized image processing pipeline by eliminating existing redundancy in C++
  • Devised a novel smoothing algorithm for human motion data sequence
  • Implemented various mathematical operations in C++
  • Designed motion data interpolation pipeline
• ML Inference Pipeline Deployment
  • Implemented full-tracking inference pipeline involving multiple deep learning models in C++ that runs cross-platform: iOS, Android, and Windows
  • Built Windows DLL for ML deployment with C++ and OpenVINO
  • Built iOS xcframework for ML deployment with C++ and CoreML
  • Built Android AAR library for ML deployment with C++ and Tensorflow Lite
• Miscellaneous
  • Encrypted and decrypted deep learning model weight and model output using AES256
  • Processed human pose datasets for deep learning training
  • Worked in between machine learning researchers and software engineers
  • Helped other researchers and engineers handle mathematical operations

Barcode Decoding from RGB Images (Sep2021-Mar2022)

• Developed a classical lightweight computer vision algorithm for barcode decoding
• Trained GAN-based image enhancement models using PyTorch
• Implemented deep learning pre/postprocessing algorithms in C++
• Converted PyTorch models into TensorRT models for on-device deployment

Education

(2019-2021) Ph.D. candidate in Computer Science, KAIST

• All But Dissertation (not finished)
• Complexity and Real Computation Laboratory

(2017-2019) M.S. in Computer Science, KAIST

• thesis
• Complexity and Real Computation Laboratory

(2012-2017) B.S. in Computer Science and Mathematics (double major), Chungnam National University

Awards and Honors

• (2018) 5th place, Samsung Collegiate Programming Cup (SCPC) 2018
• (2016) Honorable Mention, ACM-ICPC Asia Daejeon Regional, November 2016
• (2014) Bronze Medal, 33rd University Students Contest of Mathematics, Korean Mathematical Society

Publication

• ORCID

Preprints

• https://arxiv.org/abs/2002.04005
• https://arxiv.org/abs/2305.03439

Patents as Inventor, Korean Intellectual Property Office

• (submitted 2023) Publication Number 1020240040620
  • METHOD AND SYSTEM FOR 3D MOTION CAPTURE
• (submitted 2022) Registration Number 10-2519711-0000
  • METHOD AND SYSTEM FOR RECOGNIZING BARCODES BASED ON IMAGES
• (submitted 2017) Registration Number 10-1858178-0000
  • SYSTEM AND METHOD FOR FINDING AN APPROXIMATE SHORTEST PATH CONNECTING TWO PEOPLE IN A SOCIAL NETWORK

Internships

• (2018 Jul-Aug) Software Engineering, Elice
  • Customized Jupyter Notebook to capture the interaction between frontend and the language kernel
• (2018 Jan-Feb) Software Engineering, Elice
  • Wrote a program that performs syntax analysis on program codes to detect plagiarism
  • Expanded previous work to support not only Python, but other languages such as C, C++, and Java
• (2017 Jan-Feb) Chungnam-Purdue National Center for Excellence in Software Program 2017
  • UAV (Unmanned Arial Vehicle, flying drone) detection with acoustic analysis
  • Applied convolutional neural networks to recognize sound fingerprints generated by UAVs

Human Languages

• Korean (native)
• English (professional working proficiency)
• Japanese (JLPT N1, highest level)

Introduce Myself

Donghyun was a graduate student of theoretical computer science, a purely academic field based on mathematical rigor. At one point, he leaped into the industry and started working on practical problems.

Life does not go as planned. Life is full of surprises. Donghyun appreciates serendipity. He is willing to learn anything new. He is open to new adventures and challenges.

He is the type of person who constantly worries about small things. He hopes his constant worries will eventually lead to reliable software.

He loves optimization on all levels, from high-level algorithms to low-level code. He has a pathological obsession with making computation faster.

Military Service

Donghyun finished his Korean military service as a research personnel (전문연구요원).

last updated Jul 2024