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Daniel Khashabi (دانیال خشابی)
Young Investigator
Allen Institute for Artificial Intelligence
2157 N Northlake Way Suite 110, Seattle, WA 98103


My research focuses on the computational foundations of intelligent behavior, through the lens of natural language. I mostly identify with natural language processing (ACL, NAACL, EMNLP) and artificial intelligence communities (AAAI, IJCAI) and, to some extent, with the machine learning community (NourIPS, ICML).

My goal is to explore the different ways in which we can develop and evaluate systems that understand and reason with (and about) natural language in different contexts. My thesis focused on different analyses related to construction of knowledge-aware language comprehension systems that can make effective use of background information from different sources. Parts of my work focused on the Science Exam challenges of the Aristo project (IJCAI 16). Just earlier this year, Aristo reached its milestone by achieving over 90% in Science 8th grade – a milestone for AI and NLP.

I tend to worry a lot about the unintended consequences of technology in all areas of our lives. These include, but are not limited to, algorithmic biases, echo chambers in digital spaces, and the contamination of information gateways. More recently, in an effort to mitigate the effect of echo-chambers, we explore ways to organize ideas about controversial issues in ways that allows people to see alternative views and help them have a more open mindset (NAACL 19).

Outside the academic spaces, I am interested in writing for a wider audience, especially on issues at the intersection of policy + AI/tech, and beyond.

I was a doctoral student at Computer and Information Sciences at the University of Pennsylvania (2017-2019) and at the University of Illinois, Urbana-Champaign (2012-2016), under Prof. Dan Roth. I have a bachelor's degree from Amirkabir University of Technology, Tehran Polytechnic (2008-2012). I was greatly fortunate to work with Prof. Hamid Sheikhzadeh during my undergraduate studies.


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  • Not All Claims are Created Equal: Choosing the Right Approach to Assess Your Hypotheses
    Erfan Sadeqi Azer, Daniel Khashabi, Ashish Sabharwal and Dan Roth
    arXiv preprint, 2019
    Paper, Software

  • From ‘F’ to ‘A’ on the N.Y. Regents Science Exams: An Overview of the Aristo Project
    Peter Clark, Oren Etzioni, Daniel Khashabi, Tushar Khot, Bhavana Dalvi Mishra, Kyle Richardson, Ashish Sabharwal, Carissa Schoenick, Oyvind Tafjord, Niket Tandon, Sumithra Bhakthavatsalam, Dirk Groeneveld, Michal Guerquin, Michael Schmitz
    arXiv preprint, 2019
    Paper, Media coverage: NYTimes, GeekWire, Vox, Forbes

  • “Going on a vacation” takes longer than “Going for a walk”: A Study of Temporal Commonsense Understanding
    Ben Zhou, Daniel Khashabi, Qiang Ning and Dan Roth
    EMNLP, 2019
    Paper, Dataset, Leaderboard, Slides

  • PerspectroScope: A Window to the World of Diverse Perspectives
    Sihao Chen, Daniel Khashabi, Chris Callison-Burch, and Dan Roth
    ACL - Demos, 2019
    Paper, Video, Code, Poster

  • Seeing Things from a Different Angle: Discovering Diverse Perspectives about Claims
    Sihao Chen, Daniel Khashabi, Wenpeng Yin, Chris Callison-Burch, and Dan Roth
    NAACL, 2019
    Paper, Dataset, Code, Poster, Video

  • On the Capabilities and Limitations of Reasoning for Natural Language Understanding
    Daniel Khashabi, Erfan Sadeqi Azer, Tushar Khot, Ashish Sabharwal and Dan Roth
    arXiv preprint, 2019

  • Zero-Shot Open Entity Typing as Type-Compatible Grounding
    Ben Zhou, Daniel Khashabi, Chen-Tse Tsai and Dan Roth
    EMNLP, 2018
    Paper, Code, Poster

  • Looking Beyond the Surface: A Challenge Set for Reading Comprehension over Multiple Sentences
    Daniel Khashabi, Snigdha Chaturvedi, Michael Roth, Shyam Upadhyay and Dan Roth
    NAACL, 2018
    Paper, Dataset, Poster

  • CogCompNLP: Your Swiss Army Knife for NLP
    Daniel Khashabi, Mark Sammons, Ben Zhou, Tom Redman, Christos Christodoulopoulos, Vivek Srikumar, Nicholas Rizzolo, Lev Ratinov, Guanheng Luo, Quang Do, Chen-Tse Tsai, Subhro Roy, Stephen Mayhew, Zhili Feng, John Wieting, Xiaodong Yu, Yangqiu Song, Shashank Gupta, Shyam Upadhyay, Naveen Arivazhagan, Qiang Ning, Shaoshi Ling, Dan Roth
    LREC, 2018
    Paper, Code, Poster

  • Question Answering as Global Reasoning over Semantic Abstractions
    Daniel Khashabi, Tushar Khot, Ashish Sabharwal and Dan Roth
    AAAI, 2018
    Paper, Code, Slides-1, Slides-2

  • Relational Learning and Feature Extraction by Querying over Heterogeneous Information Networks
    Parisa Kordjamshidi, Sameer Singh, Daniel Khashabi, Christos Christodoulopoulos, Mark Summons, Saurabh Sinha, and Dan Roth
    Seventh International Workshop on Statistical Relational AI (StarAI), 2017
    Paper, Code, Poster

  • Learning What is Essential in Questions
    Daniel Khashabi, Tushar Khot, Ashish Sabharwal and Dan Roth
    CoNLL, 2017
    Paper, Code, Poster, Spotlight

  • Better call Saul: Flexible Programming for Learning and Inference in NLP
    Parisa Kordjamshidi, Daniel Khashabi, Christos Christodoulopoulos, Bhargav Mangipudi, Sameer Singh and Dan Roth
    COLING, 2016
    Paper, Slides, Code

  • Question Answering via Integer Programming over Semi-Structured Knowledge
    Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Peter Clark, Oren Etzioni and Dan Roth
    IJCAI, 2016
    Paper, Code, Demo, UW talk, IJCAI talk, Poster

  • EDISON: Feature Extraction for NLP, Simplified
    Mark Sammons, Christos Christodoulopoulos, Parisa Kordjamshidi, Daniel Khashabi, Vivek Srikumar, Paul Vijayakumar, Mazin Bokhari, Xinbo Wu, Dan Roth
    LREC, 2016
    Paper, Poster

  • Combining Retrieval, Statistics, and Inference to Answer Elementary Science Questions
    Peter Clark, Oren Etzioni, Tushar Khot, Ashish Sabharwal, Oyvind Tafjord, Peter Turney, Daniel Khashabi
    AAAI, 2016

  • Online Learning with Adversarial Delays
    Kent Quanrud, Daniel Khashabi
    NourIPS, 2015
    Paper, Poster

  • Clustering With Side Information: From a Probabilistic Model to a Deterministic Algorithm
    Daniel Khashabi★, John Wieting★, Jeffrey Yufei Liu★, Feng Liang★
    arXiv preprint, 2015
    Paper, Relevant: A list of constrained clustering algorithms

  • Illinois-Profiler: Knowledge Schemas at Scale
    Zhiye Fei, Daniel Khashabi, Haoruo Peng, Hao Wu and Dan Roth
    IJCAI Workshop on Cognitive Knowledge Acquisition and Applications (Cognitum 2015)
    Paper, Slides, Poster

  • Solving Hard Co-reference Problems
    Haoruo Peng★, Daniel Khashabi★ and Dan Roth
    NAACL, 2015
    Paper, Slides, Poster

  • Adaptive Tiled Neural Networks
    Mohammad Nokhbeh-Zaeem, Daniel Khashabi, Heidar-Ali Talebi, Shiva Navabi and Faramarz Jabbarvaziri
    in IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2011
    Paper, Code


  • Image demosaicing
    Sebastian Nowozin, Daniel Khashabi, Jeremy Jancsary, Bruce Lindbloom, Andrew Fitzgibbon, Microsoft Technology Licensing LLC
    United States patent US 9,344,690. 2016 May 17.


  • Reasoning-Driven Question-Answering for Natural Language Understanding
    PhD Thesis, University of Pennsylvania, 2019
    PDF, Slides

  • Analysis and Implementation of Bayesian Methods to Model Correlated Information (Multitask Learning)
    BSc Thesis, Tehran Polytechnic, 2012 (in Persian.)
    PDF, Slides

Select Talks


  • Guest Lecturer: CS446 (Machine Learning) @ UPenn, Spring 2018.

  • Guest Lecturer: CS446 (Machine Learning) @ UPenn, Fall 2018: Lecture 1 Lecture 2

  • Guest Lecturer: CS446 (Machine Learning) @ UIUC, Spring 2016: Lecture 1

  • Guest Lecturer: CS446 (Machine Learning) @ UIUC, Fall 2015: files Lecture 1 Lecture 2

  • Teaching Assistant: CS446: Machine Learning, Dan Roth, UIUC (Fall, 2015).

  • Teaching Assistant: CS473: Fundamental Algorithms, Jeff Erikson, UIUC (Fall, 2013).

  • Teaching Assistant: CS473: Fundamental Algorithms, Sariel Har-Peled and Alexandra Kolla, UIUC (Spring, 2013).

  • Teaching Assistant: “Probability and Statistics”, Instructor: Dr. Gholamreza Moradi, AUT (Spring, 2012).

  • Teaching Assistant: “Digital Signal Processing”, Instructor: Dr. Hamid Sheikhzadeh, AUT (Spring 2012).

  • Teaching Assistant: “C++ II : Numerical C++ Programming”, Instructor: Dr.Bahram Taheri, Joint program with University of Birmingham and AUT (Fall, 2011).

  • Teaching Assistant: “Introduction to Computers and Programming(C++)”, Instructor: Dr.Hassan Taheri (Spring, 2011).

Past Projects and Resources