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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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  • From ‘F’ to ‘A’ on the N.Y. Regents Science Exams: An Overview of the Aristo Project
    with Peter Clark and others
    AI Magazine, 2021
    Paper, Media coverage: NYTimes, GeekWire, Vox, Forbes

  • Text Modular Networks: Learning to Decompose Tasks in the Language of Existing Models
    with Tushar Khot and others
    arXiv, 2020
    Paper, Resources, Demo

  • UnQovering Stereotypical Biases via Underspecified Questions
    with Tao Li and others
    EMNLP - Findings, 2020
    Paper, Code, Demo

  • UnifiedQA: Crossing Format Boundaries With a Single QA System
    with Sewon Min, Tushar Khot, Ashish Sabharwal, Oyvind Tafjord, Peter Clark, Hannaneh Hajishirzi
    EMNLP - Findings, 2020
    Paper, Resources, Demo, Slides

  • Evaluating Models’ Local Decision Boundaries via Contrast Sets
    with Matt Gardner and others
    EMNLP - Findings, 2020
    Paper, Data

  • More Bang for Your Buck: Natural Perturbation for Robust Question Answering
    with Tushar Khot and Ashish Sabharwal
    EMNLP, 2020
    Paper, Data, Slides, Talk

  • Commonsense Knowledge Discovery from Linguistic Graphs
    with Hongming Zhang, Yangqiu Song and Dan Roth
    IJCAI, 2020
    Paper, Data

  • Temporal Common Sense Acquisition with Minimal Supervision
    with Ben Zhou, Qiang Ning and Dan Roth
    ACL, 2020
    Paper, Code, ACL slides

  • Not All Claims are Created Equal: Choosing the Right Approach to Assess Your Hypotheses
    with Erfan Sadeqi Azer, Ashish Sabharwal and Dan Roth
    ACL, 2020
    Paper, Software, Slides, Slides2, ACL slides

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

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

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

  • On the Possibilities and Limitations of Multi-hop Reasoning Under Linguistic Imperfections
    with Erfan Sadeqi Azer, Tushar Khot, Ashish Sabharwal and Dan Roth
    arXiv, 2019

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

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

  • CogCompNLP: Your Swiss Army Knife for NLP
    with Mark Sammons and others
    LREC, 2018
    Paper, Code, Poster

  • Question Answering as Global Reasoning over Semantic Abstractions
    with 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
    with Parisa Kordjamshidi, Sameer Singh, 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
    with Tushar Khot, Ashish Sabharwal and Dan Roth
    CoNLL, 2017
    Paper, Code, Poster, Spotlight

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

  • Question Answering via Integer Programming over Semi-Structured Knowledge
    with 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
    with Mark Sammons and others
    LREC, 2016
    Paper, Poster

  • Combining Retrieval, Statistics, and Inference to Answer Elementary Science Questions
    with Peter Clark and others
    AAAI, 2016

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

  • Illinois-Profiler: Knowledge Schemas at Scale
    with Zhiye Fei, 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
    with Haoruo Peng and Dan Roth
    NAACL, 2015
    Paper, Slides, Poster

  • Adaptive Tiled Neural Networks
    with Mohammad Nokhbeh-Zaeem and others
    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