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Daniel Khashabi (دانیال خشابی)
Post-doctoral fellow
Computer and Information Science
University of Pennsylvania


About

I am thrilled to have Prof. Dan Roth as my advisor. I was greatly fortunate to work with Prof. Hamid Sheikhzadeh as my undergraduate advisor.

I do research on theoretical and empirical analysis of information, for learning, inference and decision making. More specifically, I focus on Artificial Intelligence, in the context of natural languages.

Publication

Disclaimer: This material is presented to ensure timely dissemination of scholarly works. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms invoked by each author's copyright.
★ shows equal contribution!

  • 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

  • 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

  • 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
    Paper

  • 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
    Paper

  • 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

  • Haar wavelet for function approximation and solving ordinary differential equations
    Sayed Mohsen Moosavi Dezfooli and Daniel Khashabi
    in 13th Iranian Student Conference on Electrical and Computer Engieering, 2010 (In Persian)
    Paper

  • Design and Optimizing Digital Combinational Logic Circuits Using Genetic Algorithm
    Sayed Mohsen Moosavi Dezfooli and Daniel Khashabi
    in 13th Iranian Student Conference on Electrical and Computer Engieering, 2010 (in Persian), Best Paper Award!
    Paper, Source and demo

  • C++ Programming and Numerical Methods
    Daniel Khashabi, Mohammad Motamedi, Shiva Navabi and Bahram Taheri
    2009 (in Persian.)
    Website

Patents

  • 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.
    PDF

Theses

  • 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

Select Talks

Teaching

  • 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

Notes