I am a Research Software Engineer in Google Brain Tokyo. Prior to that, I obtained my PhD in Computer Science at Stony Brook University in May 2019 advised by Prof. Steven Skiena. and my B.S. in Computer Science and Technology at Fudan University in 2014 advised by Prof. Yanghua Xiao. My Curriculum Vitae is available in PDF or online.

My research interests lie in generative models and representation learning, as well as their applications in image generation, natural language processing, knowledge base modeling, social network modeling, bioinformatics, and much more. Details can be found in publications.

Timeline Google Brain Tokyo: Research Software Engineer Summer 2019 - Now Research on generative models and more Magenta, Google Brain: Intern Summer 2018 Research on the latent space of generative models Facebook SearchNLP: Intern Summer 2017 Researches on Web Query Parsing and Natural Language Interface to Database System, both with Haixun Wang Google Brain: Intern Summer and Fall 2016 Research on representation learning with Stephan Gouws Google: Intern Summer 2015 Profiling and analysis for user-generated activity with Xiaomeng Ban Microsoft Research Asia: Intern Feb. 2013 - Dec. 2013 Learning semantic vector representation from large knowledge base with Haixun Wang
Concept level semantic analysis with Zhongyuan Wang
Publications / Working Papers KaoKore: A Pre-modern Japanese Art Facial Expression Dataset
Yingtao Tian , Chikahiko Suzuki, Tarin Clanuwat, Mikel Bober-Irizar, Alex Lamb, Asanobu Kitamoto [paper] [dataset] [project]
To Appear in the Proceedings of the Eleventh International Conference on Computational Creativity, ICCC'20
A Natural Language Interface for Database: Achieving Transfer-learnability Using Adversarial Method for Question Understanding
Wenlu Wang, Yingtao Tian , Haixun Wang, Wei-Shinn Ku [paper]
In the Proceedings of the IEEE International Conference on Data Engineering (ICDE) 2020
Learning to Represent Bilingual Dictionaries
Muhao Chen*, Yingtao Tian *, Haochen Chen, Kai-Wei Chang, Steven Skiena, Carlo Zaniolo (* Equal Contribution) [paper]
In the Proceedings of the SIGNLL Conference on Computational Natural Language Learning (CoNLL) 2019
SpatialNLI: A Spatial Domain Natural Language Interface to Databases Using Spatial Comprehension
Jingjing Li, Wenlu Wang, Wei-Shinn Ku, Yingtao Tian and Haixun Wang [paper]
In the Proceedings of the ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems 2019
Fast and Accurate Network Embeddings via Very Sparse Random Projection
Haochen Chen, Syed Fahad Sultan, Yingtao Tian , Muhao Chen and Steven Skiena [paper]
In the Proceedings of the International Conference on Information and Knowledge Management (CIKM) 2019
Learning Bilingual Embeddings Using Lexical Definitions
Weijia Shi, Muhao Chen, Yingtao Tian , Kai-Wei Chang [paper]
In the Proceedings of the 4th ACL Workshop on Representation Learning for NLP (RepL4NLP) 2019
Social Relation Inference via Label Propagation
Yingtao Tian , Haochen Chen, Bryan Perozzi, Muhao Chen, Xiaofei Sun, Steven Skiena [paper]
In the proceeding of the 41st European Conference on Information Retrieval (ECIR 2019)
Enhanced Network Embeddings via Exploiting Edge Attributes
Haochen Chen, Xiaofei Sun, Yingtao Tian , Muhao Chen, Bryan Perozzi and Steven Skiena [paper]
In Proceedings of the International Conference on Information and Knowledge Management (CIKM) 2018
DeepAnnotator: Genome Annotation with Deep Learning
Mohammad Ruhul Amin, Alisa Yurovsky, Yingtao Tian , Steven Skiena [paper]
In Proceedings of the 9th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB), 2018.
Simple Neologism Based Domain Independent Models to Predict Year of Authorship
Vivek Kulkarni, Yingtao Tian , Parth Dandiwala, Steven Skiena [paper]
In Proceedings of the 27th International Conference on Computational Linguistics (COLING), 2018.
Co-training Embeddings of Knowledge Graphs and Entity Descriptions for Cross-lingual Entity Alignment
Muhao Chen, Yingtao Tian , Kai-Wei Chang, Steven Skiena, Carlo Zaniolo [paper]
In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI), 2018.
Syntax-Directed Variational Autoencoder for Structured Data
Hanjun Dai*, Yingtao Tian * , Bo Dai, Steven Skiena, Le Song (* Equal Contribution) [paper]
In Proceedings of the International Conference on Learning Representations (ICLR), 2018.
Best paper award, NIPS 2017 workshop for Machine Learning for Molecules and Materials.
Embedding-based Relation Prediction for Ontology Population
Muhao Chen, Yingtao Tian, Xuelu Chen, Zijun Xue, Carlo Zaniolo [paper]
In Proceedings of the 17th SIAM International Conference on Data Mining (SDM), SIAM 2018.
Towards the Automatic Anime Characters Creation with Generative Adversarial Networks
Yanghua Jin, Jiakai Zhang, Minjun Li, Yingtao Tian, Huachun Zhu, Zhihao Fang [paper] [web demo]
Accepted and presented in spotlight, NIPS 2017 workshop for Machine Learning for Creativity and Design.
Multilingual Knowledge Graph Embeddings for Cross-lingual Knowledge Alignment
Muhao Chen, Yingtao Tian, Mohan Yang, Carlo Zaniolo [paper] [code] [data]
In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), IJCAI/AAAI Press 2017.
Online Showcase Previously, I have made some interesting things in the show case that can be accessible from the web. * means joint work with friends. As I am not anymore working on these projects, these links are for archival purpose only. Deep GAN (Generative Adversarial Network) in Browser: A deep GAN that generates (or dreams) images completely in browser . Pre-trained high resolution realistic image generators now run on web browser that supports WebGL, with the help of web-runnable TensorFlow.js model. * Crypko: Next generation crypko-collectibles powered by deep generative models and consensus-based smart contracts from blockchain that attracts attention from both machine learning and blockchain communities. * MakeGirlsMoe: High-quality Anime Characters Generation with Generative Adversarial Networks in Browser that attracts both community and academic attention. Professional Services Reviewer AAAI, IJCAI, LREC, COLING Patents US Patent Training and/or utilizing recurrent neural network model to determine subsequent source(s) for electronic resource interaction Honors and Awards The Best Presentation Award Graduate Research Conference, Computer Science Department, Stony Brook University, 2015 27th place 35th Annual World Final of the ACM-ICPC, 2011 Gold Medal ACM-ICPC Asia Chengdu Regional Contest, 2011 Championship and Gold medal ACM-ICPC Asia Amritapri Regional Contest, 2010