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林煜轩 Yuxuan Lin

yl6061@columbia.edu|+1 (646) 705-7015|+86 19533230071

Hi! I am currently pursuing a M.S. in Computer Engineering at Columbia University, expecting to graduate in December 2026.
Prior to this, I earned a B.S. in Computer Engineering from University of Illinois Urbana-Champaign and a B.Eng. in Electronic & Computer Engineering from Zhejiang University.

LinkedIn/Github

Yuxuan Lin

Research Experiences

My research explores generative models for medical imaging and 3D content creation.

Flow-based Deep Generative Model for PET Image Reconstruction - Senior Thesis
Flow-based Deep Generative Model for PET Image Reconstruction - Senior Thesis
Adviser: Bo Zhao (ZJU CIIP Group)Dec. 2024 - Jun. 2025
  • Formulated PET (Positron Emission Tomography) reconstruction as a Bayesian inference problem, using conditional normalizing flows (RealNVP, Glow) to model the posterior distribution of tracer activity.
  • Implemented a Deep Probabilistic Imaging (DPI) pipeline that outputs both posterior mean reconstructions and uncertainty estimates.
  • Scaled training with multi-GPU parallelization (3.7x speedup) while keeping image quality stable (<1% drop).
Generative AI Based 3D Models Generation
Generative AI Based 3D Models Generation
Adviser: Liuqing Chen (ZJU ICI Lab)Jun. 2024 - Nov. 2024
  • Built a GenAI powered Blender plugin with Python, supporting 3D prototype management, segmentation, and Gaussian ↔ Mesh conversion.
  • Enabled text-to-3D model generation using Transformer-based Gaussian Splatting and mesh rendering pipelines.
  • Deployed a Flask-based backend to track user interactions and support 3D generation services.

Professional Experiences

I had fun doing internships in software development.

Software Development Intern
Software Development Intern
IoT Product Group 5, EzvizJul. 2024 - Sep. 2024
  • Developed control system modules for commercial cleaning robots on FreeRTOS and Linux OS.
  • Designed and implemented sensor logic for GD32 microcontroller using the Keil environment, ensuring precise control and real-time operation.
Teaching Assistant - Math213 Discrete Mathematics
Teaching Assistant - Math213 Discrete Mathematics
Supervisor: Meng ZhangSep. 2024 - Jan. 2025
  • Led bi-weekly discussion sessions to strengthen students' grasp of core discrete mathematics concepts.
  • Contributed to the design of course materials, including homework and exam samples, ensuring alignment with learning objectives.
  • Graded assignments and exams with accuracy and provided constructive feedback; supported students through office hours.

Selected Projects

I am familiar with C/C++ and Linux. Also, I have experience in CUDA, Golang (Gin, GORM), Python (PyTorch, Flask), SQL/NoSQL, x86 Assembly, and UE5.

GPU Convolution Kernel Optimizations
GPU Convolution Kernel Optimizations
Supervisor: Volodymyr KindratenkoSep. 2024 - Dec. 2024
  • Implemented and optimized the forward-pass of a convolutional layer of the modified LeNet-5 using CUDA.
  • Used Streams to overlap computation with data transfer.
  • Used Tensor Cores and shared memory tiling to speed up matrix multiplication with an advanced GEMM kernel.
  • Further optimizations included loop unrolling, constant memory, and mixed-precision (FP16) arithmetic.
LOS - A Light Linux-Like Operating System
LOS - A Light Linux-Like Operating System
Supervisor: Kirill Levchenko, Dong Kai WangMar. 2024 - May 2024
  • Developed a Linux-like operating system kernel from scratch using C and x86 assembly.
  • Implemented interrupts, system calls, and exception handling managed by the 8259 PIC, including kernel/user state switching with TSS.
  • Completed the virtual memory system, file system, and terminal support; integrated devices including keyboard, RTC, and PIT.
  • Delivered multi-process scheduling with per-terminal buffers and process control blocks; led a four-person team using Git and GDB.
Infinity Revelation: Demo of an Adventure Puzzle-Solving Game
Infinity Revelation: Demo of an Adventure Puzzle-Solving Game
Supervisor: Eric ShafferMar. 2024 - Apr. 2024
  • Developed an adventure puzzle-solving game demo in a team of five, themed after Infinity Blade using Unreal Engine Blueprints.
  • Implemented core gameplay mechanics including health system, collectible items, and multiple enemy archetypes.
  • Built four integrated levels—Lava Parkour, Laser Puzzle, Riddle Maze, and Traffic Jam—to deliver varied gameplay.

Relevant courses:

Adapted design and styles from Jon Barron.