Nan Li

Ph.D. Student
School of Computer Science
Carnegie Mellon University
nli1 [at] cs [dot] cmu [dot] edu

 

 

 

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Journal Articles

 

  1. Li, N., Cohen, W., & Koedinger, K. (2013). Problem order implications for learning transfer. (Under Review).

  2. Li, N., Matsuda, N., Cohen, W., & Koedinger, K. (2012). Integrating representation learning and skill learning in a human-like intelligent agent. (Under Review).

  3. Li, N., Matsuda, N., Cohen, W., & Koedinger, K. (2012). SimStudent: An agent architecture for simulating student learning. (Under Review).

  4. Li, N., Schreiber, A., Cohen, W., & Koedinger, K. (2012). Efficient complex skill acquisition through representation learning. Advances in Cognitive Systems. (Accepted).

  5. Li, N., Cushing, W., Kambhampati, S., & Yoon, S. (2012). Learning probabilistic hierarchical task networks as probabilistic context-free grammars to capture user preferences. ACM Transactions on Intelligent Systems and Technology. (Accepted).

  6. Li, N., Stracuzzi, D.J., & Langley, P. (2012). Improving acquisition of teleoreactive logic programs through representation change. Advances in Cognitive Systems. (Accepted).

  7. Stracuzzi, D.J., Fern, A., Ali, K., Hess, R., Pinto, J., Li, N., Konik, T. & Shapiro, D. (2011). An application of transfer to American football: From observation of raw video to control in a simulated environment. AI Magazine, 32 (2).  [PDF preprint]

 

Conference Proceedings

 

  1. Li, N., Stampfer, E., Cohen, W., & Koedinger, K. (2013). Efficient cross-domain cognitive model discovery using a simulated student. Proceedings of the 35th annual meeting of the Cognitive Science Society. Berlin, Germany. 

  2. Li, N., Tian, Y., Cohen, W., & Koedinger, K. (2013). Integrating perceptual learning with external world knowledge in a simulated student. Proceedings of the 16th International Conference on Artificial Intelligence in Education. Memphis, TN. 

  3. Li, N., Cohen, W., & Koedinger, K. (2013). Discovering student models with a clustering algorithm using problem content. Proceedings of the 6th International Conference on Educational Data Mining. Memphis, TN.  (Best Student Paper Finalist)

  4. Li, N., Schreiber, A., Cohen, W., & Koedinger, K. (2012). Efficient complex skill acquisition through representation learning. Proceedings of the 1st Annual Conference on Advances in Cognitive Systems. Palo Alto, CA.  [PDF]

  5. Li, N., Cohen, W., & Koedinger, K. (2012). Learning to perceive two-dimensional displays using probabilistic grammars. Proceedings of the 22nd European Conference on Machine Learning. Bristol, UK.  [PDF]

  6. Li, N., Schreiber, A., Cohen, W., & Koedinger, K. (2012). Creating features from a learned grammar in a simulated student. Proceedings of the 20th European Conference on Artificial Intelligence. Montpellier, France.  [PDF]

  7. Li, N., Cohen, W., & Koedinger, K. (2012). Efficient cross-domain learning of complex skills. Proceedings of the 11th International Conference on Intelligent Tutoring Systems. Chania, Greece.  [PDF]

  8. Li, N., Cohen, W., & Koedinger, K. (2012). Problem order implications for learning transfer. Proceedings of the 11th International Conference on Intelligent Tutoring Systems. Chania, Greece.  [PDF]

  9. Li, N., Stracuzzi, D., & Langley, P. (2011). Improving acquisition of teleoreactive logic programs through representation change. Proceedings of the AAAI 2011 Fall Symposium on Advances in Cognitive Systems. Arlington, VA.  [PDF]

  10. Li, N., Cohen, W., Koedinger, K., & Matsuda, N. (2011). A machine learning approach for automatic student model discovery. Proceedings of the 4th International Conference on Educational Data Mining. Eindhoven, Netherlands.  [PDF]

  11. Li, N., Cohen, W., Koedinger, K., & Matsuda, N. (2010). Towards a computational model of why some students learn faster than others. Proceedings of the AAAI 2010 Fall Symposium on the Cognitive and Metacognitive Educational Systems. Arlington, VA.  [PDF]

  12. Li, N., Cohen, W., & Koedinger, K. (2010). A computational model of accelerated future learning through feature recognition. Proceedings of the 10th International Conference on Intelligent Tutoring Systems. Pittsburgh, PA.  [PDF]

  13. Konik, T., Ali, K., Shapiro D., Li, N., & Stracuzzi, D.J. (2010). Improving structural knowledge transfer with parametric adaptation. Proceedings of the 23rd Florida Artificial Intelligence Research Society (FLAIRS) Conference. Daytona Beach, FL.  [PDF]

  14. Danielescu, A., Stracuzzi, D., Li, N., & Langley, P. (2010). Learning from errors by counterfactual reasoning in a unified cognitive architecture. Proceedings of the Annual Meeting of the Cognitive Science Society. Portland, OR.  [PDF]

  15. Li, N., Cushing, W., Kambhampati, S., & Yoon, S. (2009). Learning user plan preferences obfuscated by feasibility constraints. Proceedings of the 19th International Conference on Automated Planning and Scheduling. Thessaloniki, Greece.  [PDF]

  16. Li, N., Kambhampati, S., & Yoon, S. (2009). Learning probabilistic hierarchical task networks to capture user preferences. Proceedings of the 21st International Joint Conference on Artificial Intelligence. Pasadena, CA.  [PDF]

  17. Li, N., Stracuzzi, D.J., Cleveland, G., Konik, T., Shapiro, D., Molineaux, M., Aha, D.W., & Ali, K. (2009). Constructing game agents from video of human behavior. Proceedings of the 5th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. Stanford, CA.  [PDF]

  18. Li, N., Stracuzzi, D.J., Cleveland, G., Langley, P., Konik, T., Shapiro, D., Ali, K., Molineaux, M., & Aha, D.W. (2009). Learning hierarchical skills for game agents from video of human behavior. Proceedings of the IJCAI 2009 Workshop on Learning Structural Knowledge From Observations. Pasadena, CA.  [PDF]

  19. Li, N., Stracuzzi, D., Langley, P., & Nejati, N. (2009). Learning hierarchical skills from problem solutions using means-ends analysis. Proceedings of the Annual Meeting of the Cognitive Science Society. Amsterdam, Netherlands.  [PDF]

  20. Stracuzzi, D., Li, N., Cleveland, Gary., & Langley, P. (2009). Representing and reasoning over time in a symbolic cognitive architecture. Proceedings of the Annual Meeting of the Cognitive Science Society. Amsterdam, Netherlands.  [PDF]

  21. Yang, D., Fang, X., Li, N., & Xue, G. (2009) A simple greedy algorithm for link scheduling with the physical interference model. Proceedings of IEEE Global Communications Conference. Hawaii, USA.  [PDF]

  22. Li, N., Stracuzzi, D., & Langley, P. (2008). Learning conceptual predicates for teleoreactive logic programs. Proceedings of the International Conference on Inductive Logic Programming. Prague, Czech Republic.  [PDF]

  23. Li, N., Choi, D., & Langley, P. (2007). Adding goal priorities to teleoreactive logic programs. Proceedings of the International Symposium on Skill Science. Tokyo, Japan.  [PDF]

 

Posters, Presentations and Other Publications

 

  1. Li, N., Khandelwal, A., Phan, T., Touretzky, D., Cohen, W., & Koedinger, K. (2013). Creating an educational robot by embedding a learning agent into a physical world. Proceedings of The 44th ACM Technical Symposium on Computer Science Education (SIGCSE). Denver, CO.  [PDF]

  2. Li, N., Cohen, W., & Koedinger, K. (2012). Integrating perceptual representation learning and skill learning in a simulated student. Proceedings of IEEE Conference on Development and Learning / EpiRob. San Diego, CA.  [PDF]

  3. Li, N., Schreiber, A., Cohen, W., & Koedinger, K. (2012). Automated creation of intelligent tutoring to support personalized online learning. Proceedings of NIPS Workshop on Personalizing Education with Machine Learning. Lake Tahoe, CA. 

  4. Li, N., Cohen, W., & Koedinger, K. (2010). Integrating transfer learning in synthetic students. Proceedings of AAAI10 Student Abstract and Poster Program. Atlanta, GA.  [PDF]

  5. Li, N. (2010). Hidden concept detection in graph-based ranking algorithm for personalized recommendation. Presented at the 2010 Key Scientific Challenges Graduate Student Summit. Sunnyvale, CA.  [PPT]

 

Patents

 

  1. Issued United States Patent: 8,316,019, Ainslie, A, & Li, N. Personalized query suggestions from profile trees.

  2. Issued United States Patent: 8,326,861, Ainslie, A, & Li, N. Personalized term importance evaluation in queries.

  3. Pending Patent: Li, N., & Graham, M. Aggregating product information for electronic product catalogs.

  4.