Yingtao Tian
E-mail: [email protected]
Experience Google DeepMind (formerly Google Brain) Research Scientist Summer 2019 - Now
Research on generative models and more
Google Brain Software Engineering Intern Summer 2018
Research on the latent space of generative models with Dr. Jesse Engel
Facebook Software Engineering Intern Summer 2017
Research on natural language understanding with Dr. Haixun Wang
Google Brain Software Engineering Intern Summer - Fall 2016
Research on representation learning with Dr. Stephan Gouws
Google Software Engineering Intern Summer 2015
User-generated activity profiling and analysis with Dr. Xiaomeng Ban
Microsoft Research Asia Research Intern 2013
Learning representation from large knowledge base with Dr. Haixun Wang
Concept level semantic analysis with Dr. Zhongyuan Wang
Education State University of New York at Stony Brook, New York, U.S. 2014 - 2019
Ph.D, Computer Science. Advisor: Prof. Steven Skiena
Fudan University, Shanghai, China. 2010 - 2014
B.Sc., Computer Science and Technology
Publications
/ Working
Papers
DiffCJK: Conditional Diffusion Model for High-Quality and Wide-coverage CJK Charac-
ter Generation Yingtao Tian
International Conference on Computational Creativity (ICCC) 2024
Evolution Transformer: In-Context Evolutionary Optimization Robert Tjarko Lange, Yingtao
Tian, Yujin Tang
The Genetic and Evolutionary Computation Conference (GECCO) 2024
Large Language Models As Evolution Strategies Robert Tjarko Lange, Yingtao Tian, Yujin
Tang
The Genetic and Evolutionary Computation Conference (GECCO) 2024
MingOfficial: A Ming Official Career Dataset and a Historical Context-Aware Represen-
tation Learning Framework You-Jun Chen, Hsin-Yi Hsieh, Yu Tung Lin, Yingtao Tian, Bert Chan,
Yu-Sin Liu, Yi-Hsuan Lin, Richard Tzong-Han Tsai
The 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023)
NeuroEvoBench: Benchmarking Neuroevolution for Large-Scale Machine Learning Ap-
plications Robert Tjarko Lange, Yujin Tang, Yingtao Tian
Thirty-seventh Conference on Neural Information Processing (NeurIPS 2023) Systems Datasets and
Benchmarks Track
Digital Typhoon: Long-term Satellite Image Dataset for the Spatio-Temporal Modeling of
Tropical Cyclones Asanobu Kitamoto, Jared Hwang, Bastien Vuillod, Lucas Gautier, Yingtao Tian,
Tarin Clanuwat
Thirty-seventh Conference on Neural Information Processing (NeurIPS 2023) Systems Datasets and
Benchmarks Track
Evolving Collective AI: Simulation of Ants Communicating via Chemicals Ryosuke Takata,
Yujin Tang, Yingtao Tian, Norihiro Maruyama, Hiroki Kojima, Takashi Ikegami
The 2023 Conference on Artificial Life
EEvolving Three Dimension (3D) Abstract Art: Fitting Concepts by Language Yingtao
Tian
Working paper
DEIR: Efficient and Robust Exploration through Discriminative-Model-Based Episodic
Intrinsic Rewards Shanchuan Wan, Yujin Tang, Yingtao Tian, Tomoyuki Kaneko
In the Proceedings of the 32nd International Joint Conference on Artificial Intelligence, IJCAI-23
Simultaneous Multiple-Prompt Guided Generation Using Differentiable Optimal Trans-
port Yingtao Tian, David Ha, Marco Cuturi
In the Proceedings of the twelfth International Conference on Computational Creativity, ICCC’22
EvoJAX: Hardware-Accelerated Neuroevolution Yujin Tang, Yingtao Tian, David Ha
In the Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) 2022
Optimal Transport Tools (OTT): A JAX Toolbox for all things Wasserstein Marco Cuturi,
Laetitia Meng-Papaxanthos, Yingtao Tian, Charlotte Bunne, Geoff Davis, Olivier Teboul
Working Paper
Modern Evolution Strategies for Creativity: Fitting Concrete Images and Abstract Con-
cepts Yingtao Tian, David Ha
In the Proceedings of the The 11th International Conference on Artificial Intelligence in Music, Sound,
Art and Design (EvoMUSART) 2022.
Machine Learning for Creativity and Design Workshop, NeurIPS 2021
Ukiyo-e Analysis and Creativity with Attribute and Geometry Annotation Yingtao Tian,
Tarin Clanuwat, Chikahiko Suzuki, Asanobu Kitamoto
In the Proceedings of the Eleventh International Conference on Computational Creativity, ICCC’21
KaoKore: A Pre-modern Japanese Art Facial Expression Dataset Yingtao Tian, Chikahiko
Suzuki, Tarin Clanuwat, Mikel Bober-Irizar, Alex Lamb, Asanobu Kitamoto
In the Proceedings of the Eleventh International Conference on Computational Creativity, ICCC’20
A Transfer-Learnable Natural Language Interface for Databases Wenlu Wang, Yingtao Tian,
Haixun Wang, Wei-Shinn Ku
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)
In the Proceedings of the IEEE International Conference on Data Engineering (ICDE) 2020
Enhanced Network Embeddings via Exploiting Edge Attributes Haochen Chen, Xiaofei Sun,
Yingtao Tian, Muhao Chen, Bryan Perozzi and Steven Skiena
In Proceedings of the International Conference on Information and Knowledge Management (CIKM)
2018
Social Relation Inference via Label Propagation Yingtao Tian, Haochen Chen, Bryan Perozzi,
Muhao Chen, Xiaofei Sun and Steven Skiena
In the proceeding of the 41st European Conference on Information Retrieval (ECIR 2019)
DeepAnnotator: Genome Annotation with Deep Learning, Mohammad Ruhul Amin, Alisa
Yurovsky, Yingtao Tian, Steven Skiena
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
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
In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI), IJCAI/AAAI
Press 2018.
Syntax-Directed Variational Autoencoder for Structured Data Hanjun Dai*, Yingtao Tian* ,
Bo Dai , Steven Skiena, Le Song (* Equal Contribution)
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
In Proceedings of the 17th SIAM International Conference on Data Mining (SDM), SIAM 2018.
Towards End-End Generation of High-Resolution Images with Generative Adversarial
Networks [Online Demo] Yanghua Jin, Jiakai Zhang, Minjun Li, Yingtao Tian, Huachun Zhu
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.
In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), IJCAI/AAAI
Press 2017.
Professional
Services
Organizer, NeurIPS 2022, 2023 Workshop on Machine Learning for Creativity and Design
Meta-Reviewer, AAAI
Reviewer, ICLR, NeurIPS, AAAI, IJCAI, LREC, COLING
Patents US20210398336A1 Method for generating image, image generator, and program
US10810493B1 Training and/or utilizing recurrent neural network model to determine subsequent
source(s) for electronic resource interaction
WO2022066156A1 Node embedding via hash-based projection of transformed personalized pagerank
Honors and
Awards
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
