Elias Khalil

lyes[at]gatech.edu

Follow @lyeskhalil

I am on the job market for academic tenure-track positions and industry research roles!
Check out my résumé (research & teaching statements coming soon).
Please get in touch if you have an interesting role for me!

I am a Ph.D. candidate in Computational Science and Engineering at Georgia Tech.

My research interests are in the areas of machine learning and discrete optimization.

In particular, my goal is to improve discrete optimization solvers and algorithms by using machine learning.

Recently, I have been also working on discrete problems that arise in deep learning, where continuous optimization methods fail and combinatorial algorithms are more natural.

I am advised by Professor Bistra Dilkina. I also collaborate with Prof. George Nemhauser and Prof. Le Song.

Prior to GT, I studied for my bachelor's at the American University of Beirut, Lebanon.

News:

• October 2018: Presenting a poster on Combinatorial Attacks on Binarized Neural Networks at the workshop on the Theoretical Foundation of Deep Learning (TFDL 2018) at Georgia Tech.

• June-July 2018: Giving a Master Class on learning algorithms for combinatorial optimization at CPAIOR 2018 in Delft, and attending/presenting at ISMP 2018 in Bordeaux!

• October 2017: Best Poster Award at the INFORMS Annual Meeting 2017! Check out the poster on "Learning in Discrete Optimization"

• September 2017: Paper accepted to NIPS 2017 for a Spotlight presentation (top 4% of submissions)!

• July 2017: Check out this 3-minute CompSust-2017 lightning talk summarizing my current research: Youtube link.

• May 2017: I have received the Outstanding Poster award for discrete optimization at the NemFest Workshop 2017!

• April 2017: Two papers accepted to IJCAI 2017 (see below)!

• March 2017: I have received an IBM PhD Fellowship for 2017-2018. Thanks IBM!

Education:

• August 2014 - Present
  Ph.D. in Computational Science and Engineering
  Research Areas: machine learning, algorithms, discrete optimization
  Advised by Professor Bistra Dilkina
  Georgia Institute of Technology


• August 2012 - May 2014
  M.S in Computer Science
  Specialization: Machine Learning
  Thesis: Optimizing the Structure of Diffusion Networks: Theory and Algorithms
  Georgia Institute of Technology


• September 2009 - July 2012
  B.S in Computer Science
  American University of Beirut

Research Experience:

• Fall 2017 and Summer 2016
  Research Intern
  IBM Research
  IBM T.J. Watson Research Center - Yorktown Heights, NY


• August 2012 - May 2014
  Graduate Research Assistant
  Working with Prof. Polo Chau on graph mining
  algorithms and applications of big data analytics.
  Georgia Institute of Technology - Atlanta, GA


• Summer 2013
  Ph.D-Level Intern
  Symantec Research Labs
  Symantec Corporation - Culver City, CA

Publications:

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  2018 (1)
Combinatorial Attacks on Binarized Neural Networks. Khalil, E. B.; Gupta, A.; and Dilkina, B. In arXiv:1810.03538 [cs.LG], 2018.
paper   bibtex
@inproceedings{KhaGupDil18,
  title={Combinatorial Attacks on Binarized Neural Networks},
  author={Khalil, Elias B. and Gupta, Amrita and Dilkina, Bistra},
  booktitle = {arXiv:1810.03538 [cs.LG]},
  year={2018},
  url_Paper={https://arxiv.org/abs/1810.03538},
  keywords={deep learning,neural networks,integer programming}
}
  2017 (5)
Learning Combinatorial Optimization Algorithms over Graphs. Dai, H.; Khalil, E. B.; Zhang, Y.; Dilkina, B.; and Song, L. In Advances in Neural Information Processing Systems (NIPS), 2017.
paper   bibtex
@inproceedings{DaiKhaYuyetal17,
  title={Learning Combinatorial Optimization Algorithms over Graphs},
  author={Dai, Hanjun and Khalil, Elias B. and Zhang, Yuyu and Dilkina, Bistra and Song, Le},
  booktitle={Advances in Neural Information Processing Systems (NIPS)},
  year={2017},
  url_Paper={https://papers.nips.cc/paper/7214-learning-combinatorial-optimization-algorithms-over-graphs},
  keywords={machine learning,deep learning,embedding,optimization,search,reinforcement learning}
}
CP-ORTHO: An Orthogonal Tensor Factorization Framework for Spatio-Temporal Data. Afshar, A.; Ho, J. C.; Dilkina, B.; Perros, I.; Khalil, E. B.; Xiong, L.; and Sunderam, V. In Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2017.
paper   bibtex
@inproceedings{AfsHoDiletal17,
  title={CP-ORTHO: An Orthogonal Tensor Factorization Framework for Spatio-Temporal Data},
  author={Afshar, Ardavan and Ho, Joyce C. and Dilkina, Bistra and Perros, Ioakeim and Khalil, Elias B. and Xiong, Li and Sunderam, Vaidy},
  booktitle={Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems},
  year={2017},
  url_Paper={https://dl.acm.org/citation.cfm?id=3139958.3140047},
  keywords={machine learning,tensor factorization}
}
Learning to Run Heuristics in Tree Search. Khalil, E. B.; Dilkina, B.; Nemhauser, G.; Ahmed, S.; and Shao, Y. In 26th International Joint Conference on Artificial Intelligence (IJCAI), 2017.
paper   bibtex
@inproceedings{KhaDilNemetal17,
  title={Learning to Run Heuristics in Tree Search},
  author={Khalil, Elias B. and Dilkina, Bistra and Nemhauser, George and Ahmed, Shabbir and Shao, Yufen},
  booktitle = {26th International Joint Conference on Artificial Intelligence (IJCAI)},
  year={2017},
  url_Paper={pdfs/KhaDilNemetal17.pdf},
  keywords={machine learning,optimization,integer programming,search}
}
Learning Feature Engineering for Classification. Nargesian, F.; Samulowitz, H.; Khurana, U.; Khalil, E. B.; and Turaga, D. In 26th International Joint Conference on Artificial Intelligence (IJCAI), 2017.
paper   bibtex
@inproceedings{NarSamKhuetal17,
 title={Learning Feature Engineering for Classification},
  author={Nargesian, Fatemeh and Samulowitz, Horst and Khurana, Udayan and Khalil, Elias B. and Turaga, Deepak},
  booktitle = {26th International Joint Conference on Artificial Intelligence (IJCAI)},
  year={2017},
  url_Paper={https://www.ijcai.org/proceedings/2017/352},
  keywords={machine learning,deep learning,feature engineering,classification}
}
Fake News Mitigation via Point Process Based Intervention. Farajtabar, M.; Yang, J.; Ye, X.; Xu, H.; Trivedi, R.; Khalil, E. B.; Li, S.; Song, L.; and Zha, H. International Conference on Machine Learning. 2017.
paper   bibtex
@article{FarYanYeetal17,
  title={Fake News Mitigation via Point Process Based Intervention},
  author={Farajtabar, Mehrdad and Yang, Jiachen and Ye, Xiaojing and Xu, Huan and Trivedi, Rakshit and Khalil, Elias B. and Li, Shuang and Song, Le and Zha, Hongyuan},
  journal={International Conference on Machine Learning},
  url_Paper={http://proceedings.mlr.press/v70/farajtabar17a/farajtabar17a.pdf},
  year={2017},
  keywords={machine learning,optimization,reinforcement learning}
}
  2016 (3)
Machine Learning for Integer Programming. Khalil, E. In Proceedings of the Doctoral Consortium at the Twenty-Fifth International Joint Conference on Artificial Intelligence (IJCAI), 2016.
paper   bibtex
@inproceedings{Khalil16,
  title={Machine Learning for Integer Programming},
  author={Khalil, Elias},
  booktitle = {Proceedings of the Doctoral Consortium at the Twenty-Fifth International Joint Conference on Artificial Intelligence (IJCAI)},
  year={2016},
  url_Paper={http://www.ijcai.org/Proceedings/16/Papers/576.pdf},
  keywords={machine learning,optimization,integer programming,search}
}
Generating Graph Snapshots from Streaming Edge Data (Poster). Soundarajan, S.; Tamersoy, A.; Khalil, E. B.; Eliassi-Rad, T.; Chau, D. H.; Gallagher, B.; and Roundy, K. In International World Wide Web Conference (WWW), 2016.
paper   bibtex
@inproceedings{SouTamKhaetal16,
  title={Generating Graph Snapshots from Streaming Edge Data (Poster)},
  author={Soundarajan, Sucheta and Tamersoy, Acar and Khalil, Elias B. and Eliassi-Rad, Tina and Chau, Duen Horng and Gallagher, Brian and Roundy, Kevin},
  booktitle={International World Wide Web Conference (WWW)},
  year={2016},
  url_Paper={pdfs/SouTamKhaetal16.pdf},
  keywords={networks}
}
Learning to Branch in Mixed Integer Programming. Khalil, E. B.; Le Bodic, P.; Song, L.; Nemhauser, G.; and Dilkina, B. In Proceedings of the 30th AAAI Conference on Artificial Intelligence, 2016.
paper   bibtex
@inproceedings{KhaBodSonNemDil16,
  title={Learning to Branch in Mixed Integer Programming},
  author={Khalil, Elias B. and Le Bodic, Pierre and Song, Le and Nemhauser, George and Dilkina, Bistra},
  booktitle = {Proceedings of the 30th AAAI Conference on Artificial Intelligence},
  year={2016},
  url_Paper={pdfs/KhaLebSonNemDil16.pdf},
  keywords={machine learning,optimization,integer programming,search}
}
  2014 (3)
Scalable Diffusion-Aware Optimization of Network Topology. Khalil, E. B.; Dilkina, B.; and Song, L. In Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014.
paper   bibtex   33 downloads
@inproceedings{KhaDilSon14,
  title={Scalable Diffusion-Aware Optimization of Network Topology},
  author={Khalil, Elias B. and Dilkina, Bistra and Song, Le},
  booktitle = {Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining},
  year={2014},
  url_Paper={pdfs/KhaDilSon14.pdf},
  keywords={optimization,supermodularity,diffusion,linear threshold model}
}
Large Scale Insider Trading Analysis: Patterns and Discoveries. Tamersoy, A.; Khalil, E. B.; Xie, B.; Lenkey, S.; Routledge, B.; Chau, D. H.; and Navathe, S. In Social Network Analysis and Mining, 2014. Springer
paper   bibtex
@inproceedings{TamKhaXieLenetal14,
  title={Large Scale Insider Trading Analysis: Patterns and Discoveries},
  author={Tamersoy, Acar and Khalil, Elias B. and Xie, Bo and Lenkey, Stephen and Routledge, Bryan and Chau, Duen Horng and Navathe, Shamkant},
  booktitle = {Social Network Analysis and Mining},
  Publisher = {Springer},
  year={2014},
  url_Paper={pdfs/TamKhaXieLenetal14.pdf},
  keywords={finance,insider trading,network analysis}
}
Optimizing the Structure of Diffusion Networks: Theory and Algorithms. Khalil, E. Master's Thesis, Georgia Institute of Technology, April 2014.
paper   bibtex   2 downloads
@mastersthesis{Khalil14,
  author = {Elias Khalil},
  title = {Optimizing the Structure of Diffusion Networks: Theory and Algorithms},
  school = {Georgia Institute of Technology},
  year = {2014},
  month = {April},
  url_Paper={https://smartech.gatech.edu/bitstream/handle/1853/55481/KHALIL-THESIS-2014.pdf},
  keywords={optimization,supermodularity,diffusion,linear threshold model}
}
  2013 (1)
CuttingEdge: Influence minimization in networks. Khalil, E. B.; Dilkina, B.; and Song, L. In Workshop on Frontiers of Network Analysis: Methods, Models, and Applications at NIPS, 2013. Best Paper Award.
paper   bibtex   22 downloads
@inproceedings{KhaDilSon13,
  title={CuttingEdge: Influence minimization in networks},
  author={Khalil, Elias B. and Dilkina, Bistra and Song, Le},
  booktitle = {Workshop on Frontiers of Network Analysis: Methods, Models, and Applications at NIPS},
  year={2013},
  url_Paper={pdfs/CuttingEdge.pdf},
  bibbase_note = {<font color="green"><b>Best Paper Award</b>.</font>},
  keywords={optimization,supermodularity,diffusion,linear threshold model}
}
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