ΑΙhub.org
 

#IJCAI2019 mini-interviews – Dimmy Wang from Tencent Cloud AI


by
12 August 2019



share this:

Meet Dimmy Wang who presented his work at the Deep Learning Workshop at IJCAI 2019. He graduated with a Masters from Tshinghua University and currently works as a researcher at Tencent Cloud AI.

 

Interviewer: What are you presenting at IJCAI?

A part-of-speech tagger for Chinese and English mixed sentences.

Interviewer: What does a part of speech tagger mean?

It means that the machine can pick out nouns, pronouns, adverbs, etc. from a given sentence, which further helps the machine understand the meaning of natural language.

Interviewer: What is the impact of this research?

Identifying parts of speech has been a large research area in computer science. However, most efforts are focussed on identifying parts of speech in sentences of a particular language. This is not enough as, in this rapidly globalizing world, cultures mix and people tend to use multiple languages at once to express themselves online. For example, on Weibo (a popular Chinese social media platform similar to Twitter), one might post “我的老师太push了” (my teacher is too strict). Notice part of the expression is in english. With our research, we are now a step closer to making sense of this sentence, and the word, as it expresses itself online!




Rahul Divekar is a PhD Candidate at the Department of Computer Science at Rensselaer Polytechnic Institute.
Rahul Divekar is a PhD Candidate at the Department of Computer Science at Rensselaer Polytechnic Institute.

            AUAI is supported by:



Subscribe to AIhub newsletter on substack



Related posts :

monthly digest

AIhub monthly digest: October 2026 – neurosymbolic planning, time-series forecasting, and robots for the home

  30 Oct 2026
Welcome to our monthly digest, where you can catch up with AI research, events and news from the month past.
AI pioneers

From teaching machines to teaching people: an interview with Michael Littman

  29 Oct 2026
AI Pioneer Michael Littman reflects on the evolution of reinforcement learning, the power of science communication, and how generative AI is changing the way we teach and learn.

From lab to life: Why translating AI advances to the real world is a major challenge

  28 Oct 2026
Systems that perform well in controlled lab settings often fall short when deployed in homes, in hospitals or on city streets.

Researchers get AI ‘drunk’ to expose new cyber security risks in chatbots

Fine-tuning large language models using drunken text makes them more likely to leak secrets and answer harmful questions.

AI is creating jobs as well as erasing them – but how rewarding are they?

  26 Oct 2026
One area of increased employment is in people “cleaning up” after LLMs, or quality controlling them.

How AI changes human decision-making

  23 Oct 2026
AI can identify patterns that people miss and bring new information into decision-making. However, this does not automatically lead to better decisions.

Competing in RoboCup@Home and winning the 2026 best paper award: an interview with Raphael Memmesheimer

  22 Oct 2026
Hear more about Raphael's research and his involvement in the RoboCup@Home league.

AI is distorting archaeology and flattening Indigenous Knowledge

While AI can help archaeologists, it can also spread pseudoscientific claims and false histories, stripping Indigenous Knowledge of context, consent and community control.


↑


AUAI is supported by:







Subscribe to AIhub newsletter on substack




 















©2026.05 - Association for the Understanding of Artificial Intelligence