Bo Jianyuan 薄健元

Bo Jianyuan 薄健元

PhD Candidate in CS

Singapore Management University

About me

Hi, I’m Bo Jianyuan 👋

I’m a PhD candidate in Computer Science (AI & Data Science) at Singapore Management University, expected to graduate in July 2025. My research interests span graph learning, self-supervised learning, large language models (LLMs), and retrieval-augmented generation (RAG).

🔭 Currently working on:

  • Graph representation learning and self-supervise learning
  • Graph-enhanced LLMs and GraphRAG
  • Retrieval-augmented generation for LLM applications

🎓 Previously:

  • MITB in AI from SMU
  • MS in Mechanical Engineering from USC
  • BE in Mechatronics Engineering

💻 Tech Stack: Python | PyTorch | TensorFlow | Java | C++

Interests

  • Graph Representation Learning
  • Self-supervised Learning
  • Large Language Models
  • Retrieval-augmented Generation
  • Graph-enhanced LLMs

Education

  • PhD in Computer Science, 2024

    Singapore Management University

  • Master of IT in Business (AI), 2020

    Singapore Management University

  • MSc in Mechanical Engineering, 2016

    University of Southern California

Recent Publications

Quickly discover relevant content by filtering publications.

Contrastive General Graph Matching with Adaptive Augmentation Sampling

Graph matching has important applications in pattern recognition and beyond. Current approaches predominantly adopt supervised …
Jianyuan Bo, Yuan Fang

A Recommendation System Approach to Tune a QUBO Solver

There are two major challenges to solving constrained optimization problems using a Quadratic Unconstrained Binary Optimization or QUBO …
Siong Thye Goh, Jianyuan Bo, Matthieu Parizy, Hoong Chuin Lau
PDF

Techniques to Enhance a QUBO Solver For Permutation-Based Combinatorial Optimization

Many combinatorial optimization problems can be formulated as a problem to determine the order of sequence or to find a corresponding …
Siong Thye Goh, Jianyuan Bo, Sabrish Gopalakrishnan, Hoong Chuin Lau
PDF Code Slides DOI
Techniques to Enhance a QUBO Solver For Permutation-Based Combinatorial Optimization

Experience

 
 
 
 
 

Secretary of Quantum Young Researchers Association (QYRA)

Quantum Engineering Programme (QEP)

Jul 2021 – Dec 2022 Singapore

Responsibilities include:

  • Work with other committee members to held seminars and activities about quantum computing and engineering for young researchers in Singapore
 
 
 
 
 

Teaching Assistant of CS606 AI Planning and Decision Making

Singapore Management University

Jan 2021 – May 2021 Singapore

Responsibilities include:

  • Conduct lab sessions on CPLEX and docplex
  • Create and grade the programming assignments
  • Answer questions from the students on Piazza
  • Guide the students through their final project
 
 
 
 
 

Teaching Assistant of CS606 AI Planning and Decision Making

Singapore Management University

May 2020 – Aug 2020 Singapore

Responsibilities include:

  • Work with Prof to create and programming assignment
  • Grade the assignment
  • Answer questions from the students
 
 
 
 
 

Research Assistant

Singapore Management University

Feb 2020 – May 2020 Singapore

Responsibilities include:

  • Convert PDF files of discussion forum into machine readable form

  • Perform text pre‐processing and text mining tasks to answer the research questions

  • Perform NLP to analyze the content and context of the discussion threads

 
 
 
 
 

Research Student

Fujitsu-SMU Urban Computing and Engineering (UNiCEN) Corp. Lab

May 2019 – Sep 2020 Singapore
Design algorithms to solve complex combinatorial optimization problems via quantum annealing

Accomplishments

Deep Learning Specialization

Coursera Oct 2018 – Feb 2019

The deep learning specialization contains five interconnected courses including

  • Neural Networks and Deep Learning
  • Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
  • Structuring Machine Learning Projects
  • Convolutional Neural Networks
  • Sequence Models
See certificate

機器學習基石下 (Machine Learning Foundations)—Algorithmic Foundations

Coursera Oct 2018 – Dec 2018
See certificate

機器學習基石上 (Machine Learning Foundations)—Mathematical Foundations

Coursera Jul 2018 – Aug 2018
See certificate

Mathematics for Machine Learning Specialization

Coursera Mar 2018 – Jun 2018

A sequence of 3 courses on the prerequisite mathematics in data science and machine learning.

  • Mathematics for Machine Learning: Linear Algebra
  • Mathematics for Machine Learning: Multivariate Calculus
  • Mathematics for Machine Learning: PCA
See certificate

Algorithmic Toolbox

Coursera Jun 2016 – Jul 2016
See certificate

Robotics: Aerial Robotics

Coursera May 2016 – Jun 2016
See certificate

Skills

Python

90%

Machine Learning

85%

Powerlifting

75%

CV

My CV is available in here. (Last updated: Mar 2025)

Contact