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I am a Machine Learning Scientist at Huawei R&D Center Amsterdam. My work involves chatbots, information retrieval and conversational QA systems. In parallel, I am completing my PhD at the University of Amsterdam, under the supervision of Prof. Maarten de Rijke. In the past, I did two internships at Replika.ai and Amazon.com, respectively.
Download my CV in PDF
Skills
Python
90%
PyTorch
90%
Git
90%
Bash
70%
Photography
60%
Experience
Machine Learning Scientist
Responsibilities include:
- Lead of ChatEval challenge project at DSTC 11
- Contact person of the Conversational AI project
- Contact person of DReaMS Lab work package 3
Research Intern
This was a remote internship due to COVID-19. During this period, I worked on improving the engagingness of the Replika chatbot. It was a great experience to get my hands on a chatbot system that have real users (as opposed to a common lab environment of my daily research).
Applied Science Intern
Amazon
This was a remote internship as my travel to the originally agreed location Berlin was interrupted by COVID-19 pandemic. During this period, I worked on a review summarisation task with the Subjective NLP team (based in Barcelona and Berlin).
Poster presentation at TheWebConf
Poster presentation at SCAI Workshop
NLP Summit
Google
- Thanks to Google for paying everything
- Great opportunity to communicate with peers and Googlers
- Presented my WWW ‘19 poster
- Nice crystal clear water everywhere!
PhD student
University of Amsterdam
- Research direction: Open-domain Dialogue Systems
- Supervisors: Maarten de Rijke, Svitlana Vakulenko
- Expecting to finish thesis writing by April 2023
Master of Engineering
Northwest A&F University
- Thesis title: Research on Feature Representation and Optimization Methods in Structured Object Tracking
- Supervisor: Jifeng Ning
Bachelor of Engineering
Northwest A&F University
- Thesis title: Implementation of Single Image Haze Removal Using Dark Channel Prior
- Advisors: Dr. Yaojun Geng and Prof. Jifeng Ning
Recent Posts
Recent Publications
Quickly discover relevant content by filtering publications.
(2023).
Weakly Supervised Turn-level Engagingness Evaluator for Dialogues.
Proceedings of the 2023 Conference on Human Information Interaction and Retrieval.
(2022).
A Simple Contrastive Learning Objective for Alleviating Neural Text Degeneration.
arXiv preprint arXiv:2205.02517.
(2020).
TLDR: Token Loss Dynamic Reweighting for Reducing Repetitive Utterance Generation.
arXiv preprint arXiv:2003.11963.
(2019).
Improving Neural Response Diversity with Frequency-Aware Cross-Entropy Loss.
The World Wide Web Conference.
(2018).
Why are Sequence-to-Sequence Models So Dull? Understanding the Low-Diversity Problem of Chatbots.
Proceedings of the 2018 EMNLP Workshop SCAI: The 2nd International Workshop on Search-Oriented Conversational AI.
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