Dr. Fei Huang is Chief Scientist and Senior Director of Language Technologies Lab, DAMO Academy. 

He led natural language processing (NLP) team to develop one of the first Chinese Large Language Models (LLM): PLUG and  AliceMind, which evolve into Tongyi Qianwen, Alibaba's ChatGPT system, and achieved results surpassing human performances for the first time  in tasks such as machine reading comprehension (MRC), visual question answering (VQA) and Chinese understanding (CLUE). He led teams building AliNLP,  the NLP service platform that supports dozens of BUs within the Alibaba Group with trillions of calls per day. His team also developed AI products to empower judicial, e-commerce, health, customs and other industry partners, resulting in tens of millions of revenue. Before joining DAMO Academy, he led machine translation effort at Facebook, was a senior research scientist at IBM Watson before obtaining  Ph.D. at Carnegie Mellon University in Computer Sciences. He has published   60+ articles in top artificial intelligence conferences and journals, tens of patents in US and China, and served as PC Chair, Senior Area Chair, reviewers in numerous industrious and academic conferences. 

Email: feirhuang[at]gmail.com

WORK EXPERIENCE

Alibaba   DAMO Academy                                                                                                                          2018-present

Chief Scientist and Senior Director of Language Technology Lab, DAMO Academy

"Make Language Local, Make Business Global"

• Developed one of the first Chinese Large Language Models (LLM): PLUG and  AliceMind, which evolve into Tongyi Qianwen, Alibaba's ChatGPT system, and achieved results surpassing human performances for the first time  in tasks such as machine reading comprehension (MRC), visual question answering (VQA) and Chinese understanding (CLUE), which were highlighted in Alibaba's  financial reports twice.

• Applied LLMs in various Alibaba business scenarios and product, such as  Dingtalk (Slack), Tmall Genie (Alexa), customer service chatbots, search, advertisement, translation, etc. and generated tens of millions of dollars in revenue

• Built AliNLP,  the NLP service platform that supports dozens of BUs within the Alibaba Group with trillions of calls per day, providing information extraction, sentimental analysis, natural language understanding, machine translation, OCR, language generation, embedding, etc.

• Developed AI products to empower judicial, e-commerce, health, customs and other industry partners, enable clients with advanced AI solutions. 

• Led the development of ModelScope open source AI model community, the largest and fastest growing AI model community in China. Within 6 months of launch, it already hosted 800+ models, 2million users and 20 million model downloads.

Zhejiang University 2020-present 

Adjunct Full Professor in Computer Science

Meta (Facebook)                                                                                                                            2014-2018

Senior Tech Leader/Staff Research Scientist in Machine Translation, Applied Machine Learning and Places Data, Local

"Connect the world in everyone's language"

• Develop cutting-edge technologies in machine translation, confidence estimation, language detection, user language modeling and natural language understanding, Reduce language barriers for  20 Billion people, built the best social media translation systems among 45+ languages.

• Lead the research effort on machine translation and machine learning for Places Data, setting vision and agenda for the team, help oversee the execution and make sure the delivery of strong results with high impact. 

• Mentor junior team members; provide technical guidance to the team, and collaborate/communicate with cross-functional teams within the company and external collaborators so that the technologies developed at the translation team can have impact to other products and organizations. 

IBM T. J. Watson Research Center                                                                      2006-2014

Senior Research Staff Member in Statistical Machine Translation 

"Make  Watson multilingual"

• Develop cutting-edge technologies in statistical natural language processing and data mining to significantly improve IBM SMT system performances. 

• Drastically improved the accuracy of the IBM English-Chinese SMT system by 46% via better modeling of phrase translations. 

• Technical lead for the MT between Arabic and English in Meedan project, where MT technologies are used to help the communication between Arabic-speaking and Englishspeaking communities. 

• Lead contributor in the IBM RTTS real time machine translation Platform to offer high quality, multilingual (English<>Spanish, English<>Chinese etc.) chat and web translations services. 

• Major contributor in the IBM-led Rosetta team (including CMU, Stanford, JHU and UMD etc.) in the government-funded GALE project, responsible for improving word alignment accuracy, MT system performance and system combination. 

EDUCATION

CARNEGIE MELLON UNIVERSITY                                                                      

LANGUAGE TECHNOLOGY INSTITUTE, SCHOOL OF COMPUTER SCIENCE 

Ph.D. in Language and Information Technologies

CARNEGIE MELLON UNIVERSITY                                                                   

LANGUAGE TECHNOLOGY INSTITUTE, SCHOOL OF COMPUTER SCIENCE

M.S. in Language Technologies

CHINESE ACADEMY OF SCIENCES                                                                    

M.S. in Pattern Recognition and Intelligent System

TIANJIN UNIVERSITY                                                                                                     

B.E. (major) in Electrical Engineering and Automation with High Honors 

B.A. (minor) in English for Science and Technology 

Research and Publications

I have published 150+ articles in top artificial intelligence conferences and journals, tens of patents in US and China, and served as PC Chair, Senior Area Chair, reviewers in numerous industrious and academic conferences, with  H-index 50 (about 10K citations by 07/2024).

google scholar: https://scholar.google.com/citations?hl=en&user=9r98PpoAAAAJ

PATENTS

• Machine translation output reranking  Patent number: 10067936

• Analyzing language dependency structures. Patent number: 9830404

• Universal translation.  Patent number: 10346537. Patent number: 9734142

• Determining trending topics in social media Patent number: 9830386

• OPTIMIZING MACHINE TRANSLATIONS FOR USER ENGAGEMENT Publication number: 20170371868

• Translation confidence scores Patent number: 10133738

• Language independent representations Patent number: 9990361

• Optimizing machine translations for user engagement Patent number: 10114819

• Machine learning dialect identification Patent number: 9477652

• Machine learning dialect identification Patent number: 10410625

• Identifying multiple languages in a content item Patent number: 10180935

• Predicting future translations Patent number: 9747283

• Machine learning dialect identification Patent number: 9899020

• User feedback for low-confidence translations Patent number: 9922029

• Predicting future translations Patent number: 9805029

• Predicting future translations Patent number: 10289681l

• 20+ under review

Professional Services

Chairperson of Forum on Large Language Models,  CNCC 2022 

Senior Area Chair, Area Chair, PC Member, ACL, NAACL, EMNLP, AAAI, IJCAI, NLPCC, 

Reviewer  TACL, TASLP, TALLIP