Jae-Won Chung

• Promoting energy as a first-class resource in DNN training on GPUs.
• Observation and optimization of GPU energy consumption.

• Worked with Professor Byung-Gon Chun.
• Developed Crane, an GPU cluster resource manager for elastic AutoML workloads.
• Kubernetes backend for Crane, efficient AutoML scheduling for GPU clusters.
• Took charge of bootstrapping and mentoring newer Crane team members (interns and graduate students).

• Worked with Professor Soo-Mook Moon.
• A novel server-client collaborative video DNN inference method that drastically reduces network traffic via intermittent knowledge distillation.
• Implemented with PyTorch & OpenMPI, evaluated using an NVIDIA Jetson Nano board as a client.

• Worked with Professor Kyoung Mu Lee.
• Better meta-initialization points for Model-Agnostic Meta-Learning (MAML) using an LSTM-based neural memory.
• Augmenting the feature maps of MAML with task-aware class embeddings generated with a convex program (DPP).

• Worked with Professor Jongho Lee.
• Designed a U-Net variant and trained it on augmented MRI data.
• Participated in the QSM challenge held by the 5th International Workshop on MRI Phase Contrast and QSM.

A free research group on all domains of deep learning

• Gained experience extensively in computer vision and meta-learning, and attended talks on computer vision, natural language processing, reinforcement learning, and speech recognition.
• Gave a talk with the title "Memory plus Meta-Learning".

An official Coursera community that traslates Coursera lecture subtitles

• Served as Language Coordinator, a selected position that reviews and confirms works by other translators.
• Created Korean subtitles for Coursera Lectures initially provided only in English. Focused on courses related to machine learning.