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Research Interests

My primary research efforts have been devoted to developing fast algorithms. I have developed fast algorithms for graph isomorphim, graph isomorphism query processing, and multiple pattern Cartesian tree matching during my Ph.D. study. At LG Electronics, I have developed AI coding assistant using large language model (LLM).

Work Experience

LG Electronics - Artificial Intelligence Lab (Senior Researcher)

  • Aug. 2022 – Present: Fine-tuning large language models for AI coding assistance using PyTorch FSDP and DeepSpeed (for full parameter fine-tuning), and LoRA (for parameter-efficient fine-tuning) on AWS SageMaker. Development of data augmentation techniques for causal language models. Inference server development for large language model using NVIDIA Triton, FastTransformer, and FastAPI. Inference optimization for transformer models using flash attention and paged attention.
  • Apr. 2022 – Dec. 2022: Training a small language model (from scratch) for AI coding assistance using PyTorch. Web UI development using Python Streamlit. Inference server development for language models using Flask and ShannonAI/service-streamer.

Seoul National University – Institute of Computer Technology (Post-Doctoral Assistant)

  • Jan. 2022 – Mar. 2022: Algorithm development for graph isomorphism query processing (Efficient Graph Isomorphism Query Processing using Degree Sequences and Color-Label Distributions, IEEE ICDE 2022).

Tech/Skills

Competitive Programming

Solved.ac 프로필

Programming Languages

Libraries

  • PyTorch, TensorFlow, Triton (OpenAI), Seaborn, Pandas, PySpark, HuggingFace Transformers, DeepSpeed, NVIDIA Triton, NVIDIA Faster Transformer, FastAPI, gtest

Others

  • AWS (SageMaker, EC2, Lustre, S3)

CV

GeonmoGu_CV

Geonmo Gu's Projects

apps icon apps

APPS: Automated Programming Progress Standard (NeurIPS 2021)

casrel icon casrel

A Novel Cascade Binary Tagging Framework for Relational Triple Extraction. Accepted by ACL 2020.

ceci-release icon ceci-release

Source Code for "CECI: Compact Embedding Cluster Index for Scalable Subgraph Matching"

cliques icon cliques

Refined pivot selection for maximal clique enumeration in graphs, Theoretical Computer Science 2016

codegen icon codegen

CodeGen is an open-source model for program synthesis. Trained on TPU-v4. Competitive with OpenAI Codex.

daf icon daf

Efficient Subgraph Matching: Harmonizing Dynamic Programming, Adaptive Matching Order, and Failing Set Together

dfscode icon dfscode

To generate the minimum DFS code of a given graph

dmce icon dmce

Distributed Maximal Clique Computation, IEEE BigData 2014

gboost icon gboost

A fork of Sebastian Nowozin's and Koji Tsuda's gboost code

gmgu.github.io icon gmgu.github.io

:triangular_ruler: Jekyll theme for building a personal site, blog, project documentation, or portfolio.

graph_edit_distance icon graph_edit_distance

This project aims at exact graph edit distance (GED) computation and GED verification (verify whether the GED between two graphs is smaller than a given threshold), where all edit operators are assumed to have unit costs.

idar icon idar

Fast Supergraph Search Using DAG Integration

lasagne icon lasagne

A fork of the LASAGNE project (http://amici.dsi.unifi.it/lasagne/) looking for improvement.

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