Armando Fortes

fmq22 [at] mails [dot] tsinghua [dot] edu [dot] cn

I am a first-year Master's student in the Department of Computer Science and Technology at Tsinghua University, advised by Prof. Jun Zhu in the Tsinghua Statistical Artificial Intelligence & Learning (TSAIL) Group.

My research interests are in Machine Learning (ML) and Natural Language Processing (NLP) in general, including representation learning, reinforcement learning, knowledge graph, and graph neural networks.


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Tsinghua University
Sept 2022 - July 2024

  MSc in Computer Science and Technology
  Advisor: Prof. Jun Zhu

Tsinghua University
Sept 2021 - July 2022

  Graduate Visiting Program in Department of Computer Science and Technology

Instituto Superior Técnico, University of Lisbon
Sept 2018 - July 2021

  BSc in Computer Science and Enginnering

Selected Projects
XRDict: XLM-R Cross-Lingual Reverse Dictionary

NLP Research Project @ Tsinghua University.

The reverse dictionary is a tool which allows finding the words that best represent a given description/concept. We propose a cross-lingual solution based on the pretrained multilingual language model XLM-RoBERTa.

[Code] [Report coming soon...] [Poster coming soon...]
Image Matching Challenge

CVPR 2022 | Kaggle Competition Silver Medal 🥈 (34th out of 642 teams).

Finding point-to-point correspondences between images, a crucial task for several 3D Computer Vision problems, such as Structure-from-Motion (SfM), Simultaneous Localization and Mapping (SLAM), and Visual Localization.

[Code] [Report] [Presentation]
TMALL Repeat Buyers Prediction

Alibaba | Tianchi Competition Top 0.7% solution 🏆 (51st out of 6803 teams).

Merchants run big promotions on particular dates to attract new buyers, however, there are many one-time deal hunters. made their accumulated user behaviour logs available and hosted a related competition, in order to identify who can be converted into repeated buyers.

[Code] [Report] [Presentation] - Pawpularity Contest

Kaggle Competition Bronze Medal 🥉 (205th out of 3537 teams).

Millions of stray animals wait for a new home and family. With the aim of understanding the impact of pet photo features on their popularity, designed the Pawpularity metric and hosted a competition.

[Code] [Report] [Poster]

Website inspired from here.