News

🔆 March 16th 2024. My team is proud to announce the launch of Zalando Trend Spotter, a new experience that utilizes the vast array of Zalando data to highlight the latest fashion trends throughout Europe. This innovative tool has already gained recognition, being featured in prominent publications such as Wirtschaftswoche, FashionUnited, and Textilwirtschaft.

🔆 May 1st 2023. I start my position at Zalando SE as a senior principal scientist in Berlin, Germany. Zalando is a leading European online platform for fashion and lifestyle with more than 50 million active customers across 25 countries. More about Zalando can be found at corporate.zalando.com.

🔆 March 11th 2023. My patent, Artificial Intelligence System Using Deep Neural Networks for Pairwise Character-Level Text Analysis and Recommendations, US Patent 11,599,927, is granted by the US Patent Office. This was a joint invention by Valentin Flunkert and me.

🔆 Some of my talks are recorded:

news archive

Bio

Dr. Weiwei Cheng is an AI researcher with expertise in machine learning and natural language processing. After obtaining a double bachelor's degree in Computer Science and Business Administration at Zhengzhou University in June 2004, he studied Data and Knowledge Engineering at Otto von Guericke University Magdeburg from October 2005 to November 2007, where he received the Outstanding International Student Scholarship from the Ministry of Education and Cultural Affairs of Saxony-Anhalt in October 2006. He obtained his Master of Science degree with the highest honor in November 2007 and the Best Graduate of the Year award in October 2008. In December 2007, he joined the Computational Intelligence Group at Philipps University Marburg as a research staff member, where he obtained his doctorate, Dr. rer. nat., in May 2012. He joined Amazon in July 2013 and was a founding member of the Amazon Core Machine Learning team. As a senior scientist, he has led the development of AI-based products for teams such as Alexa, Search, Marketplace, Customer Reviews, and Kindle. As a Bar Raiser, he has conducted and supervised hundreds of interviews across both tech and non-tech roles. Since May 2023, Weiwei Cheng has joined Zalando as a senior principal scientist in the Ecommerce Platform organization.

Dr. Cheng has more than 50 peer-reviewed publications and holds over 10 US patents. His research won multiple accolades, including the Prominent Paper Award from the Artificial Intelligence journal, the Best Paper Award at the 21st International Conference on Case-Based Reasoning, recognition in the Notable Computing Books and Articles by ACM Computing Reviews, the Best Student Paper Award at the 19th European Conference on Machine Learning, etc. He was a recipient of the 2009 Chinese Government Award for Outstanding Self-Financed Students Abroad. His current research interests include question answering, preference learning, and multi-label classification. He was area chair at ACL and EMNLP, senior program committee member at AAAI and IJCAI.

curriculum vitae in pdf

Education

Publications

Marco Del Tredici, Gianni Barlacchi, Xiaoyu Shen, Weiwei Cheng, Adrià de Gispert
Question rewriting for open-domain conversational QA: best practices and limitations [pdf][bibtex]
Proceedings of the 30th ACM Conference on Information and Knowledge Management (CIKM-21): 2974-2978, ACM
Virtual Event, Australia, November 2021

Michael Sejr Schlichtkrull, Weiwei Cheng
Evaluating for diversity in question generation over text [pdf][bibtex]
arXiv:2008.07291 [cs.CL]

Nam Khanh Tran, Weiwei Cheng
Multiplicative tree-structured long short-term memory networks for semantic representations [pdf][bibtex][slides][code]
Proceedings of the 7th Joint Conference on Lexical and Computational Semantics (*SEM-18): 276-286, ACL
New Orleans, USA, June 2018  long oral presentation

Nedelina Teneva, Weiwei Cheng
Salience Rank: efficient keyphrase extraction with topic modeling [pdf][bibtex][poster]
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (ACL-17), Vol. 2: 530-535, ACL
Vancouver, Canada, July 2017

Eyke Hüllermeier, Weiwei Cheng
Superset learning based on generalized loss minimization [pdf][bibtex]
LNAI 9285 Machine Learning and Knowledge Discovery in Databases: 260-275, Springer
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD-15)
Porto, Portugal, September 2015

Róbert Busa-Fekete, Balázs Szörényi, Paul Weng, Weiwei Cheng, Eyke Hüllermeier
Preference-based reinforcement learning: evolutionary direct policy search using a preference-based racing algorithm [pdf][bibtex]
Machine Learning 97: 327-351, Springer

Willem Waegeman, Krzysztof Dembczyński, Arkadiusz Jachnik, Weiwei Cheng, Eyke Hüllermeier
On the Bayes-optimality of F-measure maximizers [pdf][bibtex]
Journal of Machine Learning Research 15: 3333-3388, Microtome Publishing

Weiwei Cheng, Sascha Henzgen, Eyke Hüllermeier
Labelwise versus pairwise decomposition in label ranking [pdf][bibtex]
Proceedings of Lernen-Wissen-Adaptivität 2013 (LWA-13): 129-136, Otto Friedrich University Bamberg
Bamberg, Germany, October 2013

Weiwei Cheng, Eyke Hüllermeier
A nearest neighbor approach to label ranking based on generalized labelwise loss minimization [pdf][bibtex][slides]
Proceedings of the 7th Multidisciplinary Workshop on Advances in Preference Handling (M-PREF-13)
The 23rd International Joint Conference on Artificial Intelligence (IJCAI-13)
Beijing, China, August 2013

Eyke Hüllermeier, Weiwei Cheng
Preference-based CBR: general ideas and basic principles [pdf][bibtex][slides]
Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI-13): 3012-3016, AAAI Press
Beijing, China, August 2013  invited paper

Amira Abdel-Aziz, Weiwei Cheng, Marc Strickert, Eyke Hüllermeier
Preference-based CBR: a search-based problem solving framework [pdf][bibtex][slides]
LNAI 7969 Case-Based Reasoning Research and Development: 1-14, Springer
The 21st International Conference on Case-Based Reasoning (ICCBR-13)
Saratoga Springs, USA, July 2013  best paper award

Dominik Heider, Robin Senge, Weiwei Cheng, Eyke Hüllermeier
Multilabel classification for exploiting cross-resistance information in HIV-1 drug resistance prediction [pdf][bibtex]
Bioinformatics 29: 1946-1952, Oxford University Press

Róbert Busa-Fekete, Balázs Szörényi, Paul Weng, Weiwei Cheng, Eyke Hüllermeier
Top-k selection based on adaptive sampling of noisy preferences [pdf][bibtex][slides][poster]
Proceedings of the 30th International Conference on Machine Learning (ICML-13): 1094-1102, Microtome Publishing
Atlanta, USA, June 2013

Róbert Busa-Fekete, Balázs Szörényi, Paul Weng, Weiwei Cheng, Eyke Hüllermeier
Preference-based evolutionary direct policy search [pdf][bibtex][poster]
Workshop Proceedings of Autonomous Learning 2013 (AL-13)
IEEE International Conference on Robotics and Automation (ICRA-13)
Karlsruhe, Germany, May 2013

Weiwei Cheng, Eyke Hüllermeier, Willem Waegeman, Volkmar Welker
Label ranking with partial abstention based on thresholded probabilistic models [pdf][bibtex][poster]
Advances in Neural Information Processing Systems 25 (NIPS-12): 2510-2518, Curran Associates
Lake Tahoe, USA, December 2012

Ali Fallah Tehrani, Weiwei Cheng, Eyke Hüllermeier
Preference learning using the Choquet integral: the case of multipartite ranking [pdf][bibtex]
IEEE Transactions on Fuzzy Systems 20: 1102-1113, IEEE Computational Intelligence Society

Weiwei Cheng, Eyke Hüllermeier
Probability estimation for multi-class classification based on label ranking [pdf][bibtex][slides]
LNAI 7524 Machine Learning and Knowledge Discovery in Databases: 83-98, Springer
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD-12)
Bristol, UK, September 2012

Weiwei Cheng, Krzysztof Dembczyński, Eyke Hüllermeier, Adrian Jaroszewicz, Willem Waegeman
F-measure maximization in topical classification [pdf][bibtex]
LNAI 7413 Rough Sets and Current Trends in Computing: 422-431, Springer
Joint Rough Set Symposium (JRS-12)
Chengdu, China, August 2012  invited paper of JRS 2012 Data Mining Competition

Ali Fallah Tehrani, Weiwei Cheng, Krzysztof Dembczyński, Eyke Hüllermeier
Learning monotone nonlinear models using the Choquet integral [pdf][bibtex]
Machine Learning 89: 183-211, Springer  selected paper (7 out of 599) from ECMLPKDD-11

Johannes Fürnkranz, Eyke Hüllermeier, Weiwei Cheng, Sang-Hyeun Park
Preference-based reinforcement learning: a formal framework and a policy iteration algorithm [pdf][bibtex]
Machine Learning 89: 123-156, Springer  selected paper (7 out of 599) from ECMLPKDD-11

Krzysztof Dembczyński, Willem Waegeman, Weiwei Cheng, Eyke Hüllermeier
On label dependence and loss minimization in multi-label classification [pdf][bibtex]
Machine Learning 88: 5-45, Springer  listed in Notable Computing Books and Articles 2012 by ACM Computing Reviews

Weiwei Cheng
Label ranking with probabilistic models
Doctoral thesis
Faculty of Mathematics and Computer Science, Philipps University Marburg
Marburg, Germany, May 2012  magna cum laude

Krzysztof Dembczyński, Willem Waegeman, Weiwei Cheng, Eyke Hüllermeier
An exact algorithm for F-measure maximization [pdf][bibtex][poster]
Advances in Neural Information Processing Systems 24 (NIPS-11): 223-230, Curran Associates
Granada, Spain, December 2011  NIPS travel grant

Weiwei Cheng, Eyke Hüllermeier
Label ranking with abstention: predicting partial orders by thresholding probability distributions [pdf][bibtex][slides][video]
Workshop Proceedings of Choice Models and Preference Learning 2011 (CMPL-11)
The 25th Annual Conference on Neural Information Processing Systems (NIPS-11)
Sierra Nevada, Spain, December 2011  NIPS travel grant

Thomas Fober, Weiwei Cheng, Eyke Hüllermeier
Focusing search in multiobjective evolutionary optimization through preference learning from user feedback [pdf][bibtex][slides]
Proceedings of the 21st Workshop Computational Intelligence (WCI-11): 107-117, KIT Scientific Publishing
Dortmund, Germany, December 2011

Weiwei Cheng, Gjergji Kasneci, Thore Graepel, David Stern, Ralf Herbrich
Automated feature generation from structured knowledge [pdf][bibtex][slides]
Proceedings of the 20th ACM Conference on Information and Knowledge Management (CIKM-11): 1395-1404, ACM
Glasgow, UK, October 2011

Ali Fallah Tehrani, Weiwei Cheng, Krzysztof Dembczyński, Eyke Hüllermeier
Learning monotone nonlinear models using the Choquet integral [pdf][bibtex][slides][poster][video]
LNAI 6913 Machine Learning and Knowledge Discovery in Databases: 414-429, Springer
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD-11)
Athens, Greece, September 2011  invited to Machine Learning Journal Special Issue

Weiwei Cheng, Johannes Fürnkranz, Eyke Hüllermeier, Sang-Hyeun Park
Preference-based policy iteration: leveraging preference learning for reinforcement learning [pdf][bibtex][slides]
LNAI 6911 Machine Learning and Knowledge Discovery in Databases: 312-327, Springer
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD-11)
Athens, Greece, September 2011  invited to Machine Learning Journal Special Issue

Ali Fallah Tehrani, Weiwei Cheng, Eyke Hüllermeier
Choquistic regression: generalizing logistic regression using the Choquet integral [pdf][bibtex][slides]
Proceedings of the 7th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-2011): 868-875, Atlantis Press
Aix-les-Bains, France, July 2011  nominated for best student paper award

Ali Fallah Tehrani, Weiwei Cheng, Eyke Hüllermeier
Preference learning using the Choquet integral: the case of multipartite ranking [pdf][bibtex]
Proceedings of the 20th Workshop Computational Intelligence (WCI-10): 119-130, KIT Scientific Publishing
Dortmund, Germany, December 2010

Weiwei Cheng, Michaël Rademaker, Bernard De Baets, Eyke Hüllermeier
Predicting partial orders: ranking with abstention [pdf][bibtex][slides][poster]
LNAI 6321 Machine Learning and Knowledge Discovery in Databases: 215-230, Springer
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD-10)
Barcelona, Spain, September 2010  UNESCO ECMLPKDD conference grant

Krzysztof Dembczyński, Willem Waegeman, Weiwei Cheng, Eyke Hüllermeier
Regret analysis for performance metrics in multi-label classification: the case of Hamming and subset zero-one loss [pdf][bibtex][slides][poster]
LNAI 6321 Machine Learning and Knowledge Discovery in Databases: 280-295, Springer
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD-10)
Barcelona, Spain, September 2010  UNESCO ECMLPKDD conference grant

Krzysztof Dembczyński, Willem Waegeman, Weiwei Cheng, Eyke Hüllermeier
On label dependence in multi-label classification [pdf][bibtex][slides]
Workshop Proceedings of Learning from Multi-Label Data 2010 (MLD-10): 5-12
The 27th International Conference on Machine Learning (ICML-10)
Haifa, Israel, June 2010  invited paper

Weiwei Cheng, Krzysztof Dembczyński, Eyke Hüllermeier
Label ranking methods based on the Plackett-Luce model [pdf][bibtex][slides][poster]
Proceedings of the 27th International Conference on Machine Learning (ICML-10): 215-222, Omnipress
Haifa, Israel, June 2010  ICML scholarship

Weiwei Cheng, Krzysztof Dembczyński, Eyke Hüllermeier
Graded multi-label classification: the ordinal case [pdf][bibtex][slides][poster]
Proceedings of the 27th International Conference on Machine Learning (ICML-10): 223-230, Omnipress
Haifa, Israel, June 2010  ICML scholarship

Krzysztof Dembczyński, Weiwei Cheng, Eyke Hüllermeier
Bayes optimal multi-label classification via probabilistic classifier chains [pdf][bibtex][poster]
Proceedings of the 27th International Conference on Machine Learning (ICML-10): 279-286, Omnipress
Haifa, Israel, June 2010  ICML scholarship

Weiwei Cheng, Eyke Hüllermeier
Label ranking with partial abstention using ensemble learning [pdf][bibtex][slides][video]
Workshop Proceedings of Preference Learning 2009 (PL-09): 17-23
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD-09)
Bled, Slovenia, September 2009

Weiwei Cheng, Eyke Hüllermeier
A simple instance-based approach to multi-label classification using the Mallows model [pdf][bibtex][slides]
Workshop Proceedings of Learning from Multi-Label Data 2009 (MLD-09): 28-38
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD-09)
Bled, Slovenia, September 2009

Weiwei Cheng, Eyke Hüllermeier
Combining instance-based learning and logistic regression for multi-label classification [pdf][bibtex][slides][poster][video][code]
Machine Learning 76: 211-225, Springer
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD-09)
Bled, Slovenia, September 2009  Machine Learning Journal Best Student Paper Award

Weiwei Cheng, Jens Hühn, Eyke Hüllermeier
Decision tree and instance-based learning for label ranking [pdf][bibtex][slides][poster][video]
Proceedings of the 26th International Conference on Machine Learning (ICML-09): 161-168, Omnipress
Montreal, Canada, June 2009  ICML scholarship

Weiwei Cheng, Eyke Hüllermeier
A new instance-based label ranking approach using the Mallows model [pdf][bibtex][slides]
LNCS 5551 Advances in Neural Networks: 707-716, Springer
The 6th International Symposium on Neural Networks (ISNN-09)
Wuhan, China, May 2009

Weiwei Cheng, Eyke Hüllermeier
Ranking skylines using active learning techniques [pdf][bibtex]
Proceedings of Chinese Intelligent Systems Engineering 2008 (CNISE-08)
Chengdu, China, October 2008

Weiwei Cheng, Eyke Hüllermeier
Instance-based label ranking using the Mallows model [pdf][bibtex]
Workshop Proceedings of Preference Learning 2008 (PL-08)
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD-08)
Antwerp, Belgium, September 2008

Weiwei Cheng, Eyke Hüllermeier
Instance-based label ranking using the Mallows model
Workshop Proceedings of ECCBR-08: 143-157
Uncertainty and Knowledge Discovery in CBR
The 9th European Conference on Case-Based Reasoning (ECCBR-08)
Trier, Germany, September 2008

Weiwei Cheng, Eyke Hüllermeier
Learning similarity functions from qualitative feedback [pdf][bibtex][slides]
LNAI 5239 Advances in Case-Based Reasoning: 120-134, Springer
The 9th European Conference on Case-Based Reasoning (ECCBR-08)
Trier, Germany, September 2008  nominated for best paper award

Eyke Hüllermeier, Johannes Fürnkranz, Weiwei Cheng, Klaus Brinker
Label ranking by learning pairwise preferences [pdf][bibtex]
Artificial Intelligence 172: 1897-1916, Elsevier  Artificial Intelligence Journal Prominent Paper Award 2015

Weiwei Cheng
Interactive ranking of skylines using machine learning techniques
Master's thesis
Faculty of Computer Science, Otto von Guericke University Magdeburg
Magdeburg, Germany, October 2007

Weiwei Cheng, Eyke Hüllermeier, Bernhard Seeger, Ilya Vladimirskiy
Interactive ranking of skylines using machine learning techniques [pdf][bibtex][poster]
Proceedings of Lernen-Wissen-Adaptivität 2007 (LWA-07): 141-148, Martin Luther University Halle-Wittenberg
Halle, Germany, September 2007

my page on Google Scholar

Patents

Valentin Flunkert, Weiwei Cheng, inventors; Amazon Technologies, Inc., assignee
Artificial intelligence system using deep neural networks for pairwise character-level text analysis and recommendations [pdf]
US Patent 11,599,927, March 2023

Weiwei Cheng, inventor; Amazon Technologies, Inc., assignee
Artificial intelligence system for generating network-accessible recommendations with explanatory metadata [pdf]
US Patent 11,367,117, June 2022

Weiwei Cheng, inventor; Amazon Technologies, Inc., assignee
Artificial intelligence system for automated generation of realistic question and answer pairs [pdf]
US Patent 10,929,392, February 2021

Weiwei Cheng, Amanda Dee Bottorff, Sandeep Ranganathan, inventors; Amazon Technologies, Inc., assignee
Extracting keywords from a document [pdf]
US Patent 10,796,094, October 2020

Weiwei Cheng, Christopher Gonzales, inventors; Amazon Technologies, Inc., assignee
Document content analysis based on topic modeling [pdf]
US Patent 10,558,657, February 2020

Weiwei Cheng, Amanda Dee Bottorff, Sandeep Ranganathan, inventors; Amazon Technologies, Inc., assignee
Extracting keywords from a document [pdf]
US Patent 10,387,568, August 2019

Weiwei Cheng, Christopher Gonzales, inventors; Amazon Technologies, Inc., assignee
Document content analysis based on topic modeling [pdf]
US Patent 10,255,283, April 2019

Weiwei Cheng, inventor; Amazon Technologies, Inc., assignee
Generating a set of representative items using a maximum-set-coverage selection strategy [pdf]
US Patent 10,248,712, April 2019

Weiwei Cheng, inventor; Amazon Technologies, Inc., assignee
Generating a set of representative items using a dynamic selection strategy [pdf]
US Patent 10,114,887, October 2018

Weiwei Cheng, inventor; Amazon Technologies, Inc., assignee
Generating a set of representative items using a clustering-selection strategy [pdf]
US Patent 10,114,885, October 2018

Weiwei Cheng, inventor; Amazon Technologies, Inc., assignee
Determining representative items using a diversity scoring strategy
US patent application, November 2016

Weiwei Cheng, inventor; Amazon Technologies, Inc., assignee
Generating a set of diversified items
US patent application, December 2015

Weiwei Cheng, inventor; Amazon Technologies, Inc., assignee
Machine learning based analysis of reviews
US patent application, December 2014

Talks & Tutorials

Generative AI and its applications
Zalando Senior Leadership Team Exchange
Berlin, Germany, July 2023

Salience Rank: efficient keyphrase extraction with topic modeling [slides][video]
Data Science Luxembourg
Luxembourg City, Luxembourg, September 2017

Salience Rank: efficient unsupervised keyphrase extraction with topic modeling
The 5th Amazon Machine Learning Conference
Seattle, US, May 2017

Applying natural language processing at Amazon
Amazon-Oxford-Warwick Workshop on Machine Learning Applications and Computational Statistics
Berlin, Germany, May 2016

Preference learning using statistical methods for label ranking [slides]
Seminars on Machine Learning at Poznan University of Technology
Poznan, Poland, March 2014

Preference-based evolutionary direct policy search [pdf][slides]
Dagstuhl Seminar 13321: The 11th European Workshop on Reinforcement Learning (EWRL-13)
Dagstuhl, Germany, August 2013

Preference-based reinforcement learning [slides]
The 25th European Conference on Operational Research (EURO-12)
Vilnius, Lithuania, July 2012  DAAD conference scholarship

Learning monotone nonlinear models using the Choquet integral [slides][video]
Lernen-Wissen-Adaptivität (LWA-11)
Magdeburg, Germany, September 2011

The RipOff! game: a tutorial of cooperative game theory [slides]
with Yoram Bachrach
Think Computer Science 2010
Cambridge, UK, December 2010

Graded multi-label classification: the ordinal case [slides]
Lernen-Wissen-Adaptivität (LWA-10)
Kassel, Germany, September 2010

Acceptance speech of 2009 Chinese Government Award for Outstanding Self-Financed Students Abroad [pdf-zh][pdf-en]
Embassy of China
Berlin, Germany, June 2010

Text classification: concepts and methods [pdf][slides]
Association of Chinese Computer Scientists in Germany (GCI) 2009 Annual Conference
Fürth, Germany, November 2009

Text classification: a back-to-school tutorial
GTO IES Audit & Risk Management Department, Deutsche Bank
Frankfurt, Germany, November 2009

Human vs computer: case studies [slides]
Association of Chinese Scholars and Students in Magdeburg (VCWSM e.V.)
Magdeburg, Germany, October 2009

Multi-label classification: a new machine learning problem [slides][video]
Lightning Talk, the 4th Annual Google Test Automation Conference (GTAC-09)
Zurich, Switzerland, October 2009

Combining instance-based learning and logistic regression for multi-label classification [slides][video]
Lernen-Wissen-Adaptivität (LWA-09)
Darmstadt, Germany, September 2009

Human-computation in internet [pdf][slides]
Association of Chinese Computer Scientists in Germany (GCI) IT Strategy Workshop
Schwetzingen, Germany, September 2009

Ranking the skyline: an application of preference learning [proceedings][slides]
Association of Chinese Computer Scientists in Germany (GCI) 2008 Annual Conference
Lahnstein, Germany, November 2008

Instance based label ranking [slides]
Student Talk, the 10th Machine Learning Summer School (MLSS-08)
Ile De Re, France, September 2008  MLSS scholarship

A brief introduction to preference handling [slides]
Colloquium for graduate students in Mathematics and Computer Science at Philipps University Marburg
Marburg, Germany, March 2007

Awards

Prominent paper award [pic 1 2]
Artificial Intelligence Journal Prominent Paper Award 2015
The 24th International Joint Conference on Artificial Intelligence
Buenos Aires, Argentina, July 2015

Best paper award [pic]
The 21st International Conference on Case-Based Reasoning
Saratoga Springs, USA, July 2013

Notable Computing Books and Articles of 2012 [pdf][link]
ACM Computing Reviews
New York City, USA, May 2013

DAAD conference scholarship
German Academic Exchange Service (DAAD)
Vilnius, Lithuania, July 2012

Data mining competition award [pic]
The 2nd place at JRS 2012 Data Mining Competition
Chengdu, China, April 2012

NIPS travel grant
Sponsored by Winton Capital, etc.
The 25th Annual Conference on Neural Information Processing Systems
Granada, Spain, December 2011

DAAD STIBET scholarship
Sponsored by German Academic Exchange Service (DAAD)
Marburg University Research Academy
Marburg, Germany, April 2011

Nomination for best student paper award [pic]
The 7th Conference of the European Society for Fuzzy Logic and Technology
Aix-les-Bains, France, July 2011

UNESCO ECMLPKDD conference grant
Sponsored by UNESCO Chair in Data Privacy
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
Barcelona, Spain, September 2010

ICML scholarship [link]
Sponsored by IBM, National Science Foundation (NSF), etc.
The 27th International Conference on Machine Learning
Haifa, Israel, June 2010

China national award [pic][link de1 de2 zh1 zh2 zh3][video CCTV CRIOnline]
Chinese Government Award for Outstanding Self-Financed Students Abroad
Ministry of Education of China
Berlin, Germany, June 2010

Best paper award [pic][video]
Machine Learning Journal Best Student Paper Award
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
Bled, Slovenia, September 2009

ICML scholarship [link]
Sponsored by National Science Foundation (NSF), etc.
The 26th International Conference on Machine Learning
Montreal Canada, June 2009

Best graduate award [pic]
Best graduate 2007/2008 in Master of Data and Knowledge Engineering
Otto von Guericke University Magdeburg
Magdeburg, Germany, October 2008

MLSS scholarship
Sponsored by Predict & Control and Lille's Computer Science Laboratory
The 10th Machine Learning Summer School
Ile De Re, France, September 2008

Nomination for best paper award
The 9th European Conference on Case-Based Reasoning
Trier, Germany, September 2008

Outstanding international student scholarship [pdf]
Ministry of Education and Cultural Affairs of Saxony-Anhalt
Magdeburg, Germany, October 2006

Best debater award [pic]
The 1st Henan Universities Debating Championship
Zhengzhou, China, April 2003

Speech contest award [pic]
The 3rd prize in Speech Contest "The 50 Years"
Anqing, China, August 1999

Supervised Interns & Students

Yahui Liu, University of Trento
Continuous pre-training with in-domain data and curriculum learning for fine-tuning QA models
2021

Sean Chung, University of Wisconsin-Madison
Improving retrieval for product questions using search log data
2020

Jamin Shin, Hong Kong University of Science & Technology
Model-agnostic meta learning for question answering
2019

Sven Buechel, Friedrich-Schiller University Jena
Speeding up BERT by pruning
2019

Ida Szubert, University of Edinburgh
Evidence aggregation for question answering
2019

Michael Schlichtkrull, University of Edinburgh
Generating diverse questions from text with variational autoencoder
2018

Joachim Bingel & Mareike Hartmann, University of Copenhagen
Joint question and answer generation from Amazon customer reviews
2017

Arthur Bražinskas, University of Amsterdam
Neural open information extraction
2017

Nam Khanh Tran, L3S Research Center & Leibniz University Hannover
Multiplicative tree-structured LSTMs
2017

Nedelina Teneva, University of Chicago
Keyphrase extraction with topic modeling
2016

Rebecca Knowles, Johns Hopkins University (co-supervised with György Szarvas)
Helpfulness estimation of Amazon customer reviews
2015

Links