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Waylon Li

Weixian (Waylon) Li

PhD Student in AIAI at University of Edinburgh

I am currently a PhD student at the Artificial Intelligence Applications Institute at School of Informatics in University of Edinburgh, proud to be supervised by Prof. Tiejun Ma. I finished my Master by Research degree (2021-2022) at the Institute for Language, Cognition and Computation in University of Edinburgh with Prof. Shay Cohen and my bachelors degree at University of Edinburgh as well. I am mainly interested in applying deep learning and NLP method to financial area. More specifically:

  • Machine learning method for risk detection in financial market
  • Neural ranking models and retrieval
  • The development and application of pretrained language models (PLMs)
  • Domain adaptation of NLP models

Education

University of Edinburgh
2022-Present
PhD in AIAI
University of Edinburgh
2021-2022
Master by Research in ILCC
Degree classification: Distinction (Thesis)
University of Edinburgh
2018-2021
Bachelor of Science in Artificial Intelligence
Degree classification: First-Class Honours
South China University of Techonology
2016-2018
Bachelor of Science in Applied Mathematics

Publications

SynthRank: Synthetic Data Generation of Individual’s Financial Transactions Through Learning to Ranking. Weixian Waylon Li, Mengyu Wang, Carsten Maple, Tiejun Ma (2024). To appear in AI in Finance for Social Impact @ AAAI 2024

Generative AI Information Retrieval LEarning-TO-Rank Financial AI
Paper

BERT is not The Count: Learning to Match Mathematical Statements with Proofs. Weixian Waylon Li, Yftah Ziser, Maximin Coavoux and Shay B. Cohen (2023). In Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2023)

NLP Information Retrieval
Paper Code Poster Slides Video

Experiences

1
Research Assistant
The Alan Turing Institute

July 2022 - Present, United Kingdom

Supervised by Prof. Tiejun Ma

Responsibilities:
  • Working on the topic of “Synthetic Data Generation for Finance and Economics”
  • Collaboration with University City College London (UCL) on time series financial data generation
Teaching Assistant for Introductory Applied Machine Learning
University of Edinburgh

June 2020 - Present, Edinburgh, United Kingdom

Responsibilities:
  • Tutoring and demonstrating the course Applied Introductory to Machine Learning
  • Supporting undergraduates and postgraduates who are taking this course on better understanding the knowledge and sharing my experience in machine learning study
  • Giving feedback to the professors and helping them better organise the course
2
3
Teaching Assistant for Python Summer School
University of Edinburgh

July 2022 - Aug 2022, Edinburgh, United Kingdom

Lab Demonstrator for Foudation of Natural Language Processing
University of Edinburgh

Jan 2022 - May 2022, Edinburgh, United Kingdom

4
5
System Engineer
International Business Machine Corporation

July 2019 - Sep 2019, Canton, China

Responsibilities:
  • GF Bank Z14 mainframe upgrade project: helped with wiring installation and switching the Hardware Management Console (HMC)
  • Chaozhou Sanhuan IT Consultation: attended the first meeting with Chaozhou Sanhuan as a member of the consultation team
  • Canton Mobile Server Room Maintenance: helped maintain the server models including Power 780, S814 servers, DS 8870, 8880 storages
Big Data Platform Engineer
China Unicom

May 2019 - July 2019, Canton, China

Responsibilities:
  • Managed the daily maintenance of the big data platform and helped with the security upgrade project
  • Participated in the internal Spark computing framework training
6

Conferences

Conference on Empirical Methods in Natural Language Processing (EMNLP) 2023reviewerJuly 2023
TSDiP Workshop @ Warwick UniversityattendeeJuly 2023
Conference of the European Chapter of the ACL (EACL) 2023presenterMay 2023
Conference on Empirical Methods in Natural Language Processing (EMNLP) 2022reviewerAug 2022
Conference on Empirical Methods in Natural Language Processing (EMNLP) 2021attendeeNov 2021
ACL-IJCNLP 2021attendeeJuly 2021
Annual Conference of the North American Chapter of the ACL (NAACL) 2021attendeeJune 2021
World Artificial Intelligence Conference 2019attendeeAug 2019
Huawei Developer Conference 2019attendeeAug 2019

News

  • Jan, 2024

    Will attend the 2nd TSDiP Workshop @ Warwick University

  • Dec, 2023

    One paper accpeted by AI in Finance for Social Impact Workshop @ AAAI 2024

  • Nov, 2023

    One paper submitted to AI in Finance for Social Impact Workshop @ AAAI 2024

  • July, 2023

    Attended the TSDiP Workshop @ Warwick University

  • July, 2023

    Attended OxML 2023 in Oxford University

  • May, 2023

    Attended EACL 2023 in Croatia presenting our paper and really had a great time!

  • March, 2023

    - Started a one-month annual leave

    - Visited to Shenzhen Stock Exchange

  • Feb, 2023

    - Start my PhD in AIAI at University of Edinburgh

    - One paper got accpeted in EACL 2023

  • Oct, 2022

    - Obtained the Master by Research degree with distinction at University of Edinburgh

  • Oct, 2021

    - Started my Master by Research with Prof. Shay Cohen

  • June, 2021

    - Obtained the Bachelors of Science degree with First-Class Honours

Recent Posts

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Can LLM Have Spatial Intelligence?

Recently, our school celebrated the 60th anniversary of Computer Science & AI. To mark the occasion, the organizers invited Fernando Pereira to deliver a lecture on the connection between form and meaning in language. This subject has captivated the minds of linguists, computer scientists, and cognitive researchers for many years. During the lecture, Pereira presented a thought-provoking example. He posed the question: “Bob is sitting to the right of Alice, and Jack is to the left of Bob.

October 13, 2023 Read
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EACL 2023 Trip to Croatia

I went to Dubrovnik, Croatia for the EACL 2023 conference. It was my first time there. I made new friends and had an amazing time watching the most beautiful sunset in Kings Landing.

May 11, 2023 Read
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Contrastive Learning Note

Related reading: The Beginner’s Guide to Contrastive Learning SimCSE: Simple Contrastive Learning of Sentence Embeddings A Simple Framework for Contrastive Learning of Visual Representations Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks Background Contrastive learning aims to learn effective representation by pulling semantically close neighbors together and pushing apart non-neighbors. Initially, contrastive learning was applied to computer vision tasks. As what it is shown in the figure below, we expect the model to learn the communities between two images that share the same label and the difference between a pair of images with different labels.

August 8, 2022 Read
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