Steeve Huang

CS PhD student, UIUC

Co-Founder, Rosetta.ai


Kung-Hsiang (Steeve) Huang is a third-year PhD student and an Amazon Fellow at the University of Illinois Urbana-Champaign. He is part of the BLENDER Lab, led by Professor Heng Ji. His research goal is to reduce false information around the world. To achieve this goal, he works towards three main research directions: fact-checking, fake news detection, and improving faithfulness for text generation models. Prior to joining UIUC, he obtained his master’s degree from the University of Southern California, where he was advised by Professor Nanyun Peng. Steeve earned his bachelor’s degree at the Hong Kong University of Science and Technology. In addition, he is a co-founder of Rosetta.ai, in charge of the core Deep Learning-based recommender system that empowers our clients with millions of online shoppers.


  • Fact-checking
  • Fake News Detection
  • Faithfulness


  • PhD in Computer Science, 2021 - 2024

    University of Illinois at Urbana-Champaign

  • MSc in Computer Science, 2020 - 2021

    University of Southern California

  • BEng in Computer Science, 2014 - 2018

    Hong Kong University of Science and Technlogy

  • Exchange Program, 2016

    Georgia Institute of Technology

Recent News

  • [Sep 2023] Selected as an Amazon Fellow at the Amazon-Illinois Center!
  • [May 2023] Two papers (paper 1,paper 2) accepted by ACL 2023!
  • [Jan 2023] One paper accepted by EACL 2023 (Findings)!
  • [Nov 2022] Gave a tutorial at AACL 2022!
  • [Aug 2022] One paper accepted by COLING 2022!
  • [Aug 2022] Gave a tutorial at KDD 2022!
  • [Apr 2022] Served as a reviewer for JAIR.



Research Intern


May 2023 – Aug 2023 CA, United States

Applied Scientist Intern


May 2022 – Aug 2022 NY, United States

Research Assistant

University of Illinois at Urbana-Champaign

Aug 2021 – Present IL, United States

Research Assistant

Information Sciences Institute

Jan 2020 – Jul 2021 CA, United States

Chief Technology Officer


Aug 2018 – Aug 2021 Taipei, Taiwan

Recent Publications

AMRFact: Enhancing Summarization Factuality Evaluation with AMR-driven Training Data Generation
Embrace Divergence for Richer Insights: A Multi-document Summarization Benchmark and a Case Study on Summarizing Diverse Information from News Articles
ManiTweet: A New Benchmark for Identifying Manipulation of News on Social Media
Zero-shot Faithful Factual Error Correction
Faking Fake News for Real Fake News Detection: Propaganda-loaded Training Data Generation


Amazon Fellowship

2023 Amazon Fellow at the Amazon-Illinois Center on AI for Interactive Conversational Experiences (AICE)

Dean’s Scholarship

Merit-based scholarship issued on admission.

4th Place, 2019 ACM RecSys Challenge

Build session-based, context-aware recommender systems for hotel metasearch.

Silver Medal, The 2nd YouTube-8M Video Understanding Challenge

Build a compact (< 1GB) video classification model for video understanding.

Competitions Master

Silver Medal, Avito Demand Prediction Challenge

Predict the demand for an online advertisement based on natural language metadata and context.

Bronze Medal, TalkingData AdTracking Fraud Detection Challenge

Detect fraudulent click traffic for mobile app ads.

Final List, IT Challenge

Create an innovative Chatbot solution.

Bronze Medal, 2018 Data Science Bowl

Create a model to identify the nuclei from an image, evaluated at the pixel-level.

Gold Medal, Toxic Comment Classification Challenge

Build multi-headed models that’s capable of detecting different types of of toxicity like threats, obscenity, insults, and identity-based hate.

Bronze Medal, Recruit Restaurant Visitor Forecasting

Construct a regression model for predicting the number of visitors a restaurant will receive.

Silver Medal, Statoil/C-CORE Iceberg Classifier Challenge

Build a classifier to distinuish between ship and iceberg from remotely shot images.

First Place, Smart City in Hong Kong

Second Place, Public Welfare Datathon (公益数据骇客马拉松)

First Runner-up, Imagine Cup Hong Kong Final

Reaching Out Award Scholarship

University Full Scholarship