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Hi 👋, I'm marsggbo

A student who keeps slim and smart

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marsggbo

🇨🇳→🇭🇰→🇸🇬 I am currently a Research Scientist at A*star, Singapore, affiliated with CFAR, under the supervision of Prof Ong Yew Soon. Prior to this, I completed my Ph.D. in Computer Science at Hong Kong Baptist University (HKBU), where I was advised by Prof. Chu Xiaowen. I earned my Bachelor's degree with honors in the School of Electronic Information and Communications at Huazhong University of Science & Technology (HUST).

Driven by a mission to democratize deep learning, my research is dedicated to advancing the accessibility and efficiency of large-scale deep learning models, particularly Large Language Models (LLMs). My goal is to bridge the theoretical aspects of machine learning with practical system designs to create scalable, robust, and trustworthy AI systems that are widely accessible. My interested research directions include:

  • 1.Model-Centric AI:
    • Architecture Dearch: Neural Architecture Search (e.g., multi-objective NAS, Training-free NAS, resource-aware NAS), Sparse Model (e.g., Mixture-of-Experts)
    • Hyper-parameter optimization (HPO): Grid/Random Search, Evolutionary Algorithm, Differentiable Optimization
    • Model Compression: Pruning, Quantization, Knowledge Distillation
  • 2.Data-Centric AI:
    • Automatic Data Augmentation (ADA), Data Generation, Dataset compression,
    • RAG, LLM alignment
  • 3.HPC AI:
    • Memory efficiency: Offloading, KV-cache
    • LLM training acceleration: Distributed Parallellism (data parallel, tensor parallel, pipeline parallel)
    • LLM inference optimization: Batch Schedule, Dynamic Inference Paths

Contact Me

AutoML机器学习

marsggbo

marsggbo's Projects

automldemos icon automldemos

Demos for 自动机器学习:NAS从入门到实战

colossalai icon colossalai

Colossal-AI: A Unified Deep Learning System for Big Model Era

covidnet3d icon covidnet3d

[AAAI2021] Automated Model Design and Benchmarking of 3D Deep Learning Models for COVID-19 Detection with Chest CT Scans

detectron2 icon detectron2

Detectron2 is FAIR's next-generation research platform for object detection and segmentation.

eagan icon eagan

(ECCV2022) EAGAN: EAGAN: Efficient Two-stage Evolutionary Architecture Search for GANs

hkbu_hpml_covid-19 icon hkbu_hpml_covid-19

Source code of paper "Benchmarking Deep Learning Models and Automated Model Design for COVID-19 Detection with Chest CT Scans".

hyperbox icon hyperbox

https://hyperbox-doc.readthedocs.io/en/latest/

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