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José's Research

I currently work as a Data Science Manager at Chegg's Writing Tools team. I conduct research in Artificial Intelligence; my work has been recognized by the scientific community and the popular media. For example, I have presented at Artificial Intelligence & Statistics, an honor for only 6% of the submissions of the conference (out of 400+ papers). I have also been nominated for best paper awards in the International Educational Data Mining and the Special Interest Group of Dialogue Systems conferences. I am the happy first-prize winner of a Kaggle competition against 350+ international teams predicting sudden traffic changes .

Education

Carnegie Mellon University

Ph.D. in Language Technologies (Computer Science) • 2013

National Tsing Hua University

IMBA in Technology Management • 2007

Instituto Tecnológico de Costa Rica

BSc in Computer Science• 2003

Client Testimonials

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You can download my bibtex .

Book Chapters

I have published in machine learning, data science and education venues
  1. Bayesian Networks
    González-Brenes, José P., Behrens, John T., Mislevy, Robert J., Levy, Roy, DiCerbo, Kristen E.  •  2016
    Rupp, Andre A. and Leighton, Jacqueline P. (eds)
    The Wiley Handbook of Cognition and Assessment: Frameworks, Methodologies, and Applications
    pdf

Long Papers

Conferences involve three stringent peer reviews of the full paper — not just the abstract — including suggested revisions. Publication in these proceedings is considered archival. For example, EDM2014 accepted only 17% (24 out of 142) of the full paper submissions
  1. Beyond Word Embeddings: Dense Representations for Multi-Modal Data Deep Learning
    Armona, Luis, Edezhath, Ralph, González-Brenes, José P.  •  2019
    Rupp, Andre A. and Leighton, Jacqueline P. (eds)
    Proceedings of the Thirty-Second International Florida Artificial Intelligence Research Society Conference
    pdf slides code
  2. A data-driven approach for inferring student proficiency from game activity logs
    Falakmasir, Mohamad, González-Brenes, José P., Gordon Geoffrey, DiCerbo, Kristen  •  2016
    Learning at Scale
    pdf
  3. Joint Discovery of Skill Prerequisite Graphs and Student Models
    Chen, Yetian, González-Brenes, José P., Tian, Jin  •  2016
    The 9th International Conference on Educational Data Mining
    pdf
  4. A Framework for Multifaceted Evaluation of Student Models
    Huang, Yun, González-Brenes, José P., Kumar, Rohit, Brusilovsky, Peter  •  2015
    Boticario, Jesus G. and Santos, Olga C. and Romero, Cristobal and Pechenizkiy, Mykola (eds)
    Proceedings of the 8th International Conference on Educational Data Mining
    pdf
  5. Your model is predictive— but is it useful? Theoretical and Empirical Considerations of a New Paradigm for Adaptive Tutoring Evaluation
    González-Brenes, José P., Huang, Yun  •  2015
    Boticario, Jesus G. and Santos, Olga C. and Romero, Crist\"obal and Pechenizkiy, Mykola (eds)
    Proceedings of the 8th International Conference on Educational Data Mining
    pdf slides code
  6. Modeling Skill Acquisition Over Time with Sequence and Topic Modeling 6% acceptance rate for presentations
    González-Brenes, José P.  •  2015
    Guy Lebanon and S.V.N. Vishwanathan (eds)
    Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics AISTATS 2015
    pdf
  7. General Features in Knowledge Tracing: Applications to Multiple Subskills, Temporal Item Response Theory, and Expert Knowledge Nominated to Best Paper Award
    González-Brenes, José P., Huang, Y., Brusilovsky, P.  •  2014
    Manolis Mavrikis and Bruce M. McLaren (eds)
    Proceedings of the 7th International Conference on Educational Data Mining
    pdf slides code
  8. Dynamic Cognitive Tracing: Towards Unified Discovery of Student and Cognitive Models
    González-Brenes, José P., Mostow, Jack  •  2012
    Kalina Yacef and Osmar R. Za\"\iane and Arnon Hershkovitz and Michael Yudelson and John C. Stamper (eds)
    Proceedings of the 5th International Conference on Educational Data Mining
    pdf
  9. How to Classify Tutorial Dialogue? Comparing Feature Vectors vs. Sequences
    González-Brenes, José P., Mostow, Jack  •  2011
    M. Pechenizkiy and T. Calders and C. Conati and S. Ventura and C. Romero and J. Stamper (eds)
    Proceedings of the 4th International Conference on Educational Data Mining
    pdf
  10. Learning Classifiers from a Relational Database of Tutor Logs
    Mostow, Jack, González-Brenes, José P. , Tan, Bao Han  •  2011
    M. Pechenizkiy and T. Calders and C. Conati and S. Ventura and C. Romero and J. Stamper (eds)
    Proceedings of the 4th International Conference on Educational Data Mining
    pdf
  11. Classifying dialogue in high-dimensional space
    González-Brenes, José P., Mostow, Jack  •  2011
    ACM Trans. Speech Lang. Process.
    pdf
  12. What System Differences Matter? Using ℓ1/ℓ2-regularization to Compare Dialogue Systems Nominated to Best Paper and Best Student Paper Awards
    González-Brenes, José P., Mostow, Jack  •  2011
    Proceedings of the 12th Annual SIGdial Meeting on Discourse and Dialogue
    pdf
  13. How to Classify Tutorial Dialogue? Comparing Feature Vectors vs. Sequences
    González-Brenes, José P. , Mostow, Jack , Duan, Weisi  •  2011
    Mykola Pechenizkiy and Toon Calders and Cristina Conati and Sebastián Ventura and Cristóbal Romero and John C. Stamper (eds)
    Proceedings of the 4th International Conference on Educational Data
    pdf
  14. A Better Reading Tutor That Listens
    Mostow, Jack, Aist, Greg, Bey, Juliet, Chen, Wei, Corbett, Al, Duan, Weisi, Duke, Nell, Duong, Minh, Gates, Donna, González-Brenes, José P, Juarez, Octavio, Kantorzyk, Martin, Li, Yuanpeng, Liu, Liu, McKeown, Margaret, Trotochaud, Christina, Valeri, Joe, Weinstein, Anders, Yen, David  •  2010
    Aleven, Vincent and Kay, Judy and Mostow, Jack (eds)
    Intelligent Tutoring Systems
    pdf
  15. Describing Spoken Dialogue Systems Differences
    González-Brenes, José P., Black, Alan W., Eskenazi, Maxine.  •  2009
    International Workshop on Spoken Dialogue Systems
    pdf

Other

Short Papers, Workshop papers, etc.
  1. Inferring Course Enrollment from Partial Data Deep Learning
    González-Brenes, José and Edezhath, Ralph  •  2018
    Artificial Intelligence in Education - 19th International Conference, AIED 2018, London, UK, June 27-30, 2018, Proceedings, Part II
    pdf
  2. The FAST toolkit for Unsupervised Learning of HMMs with Features
    Huang, Yun, González-Brenes, José P., Brusilovsky, Peter  •  2015
    The Machine Learning Open Source Software workshop at the 32nd International Conference on Machine Learning (ICML-MLOSS 2015)
  3. The Leopard Framework: Towards understanding educational technology interventions with a Pareto Efficiency Perspective
    González-Brenes, José P., Huang, Yun  •  2015
    The ICML 2015 Workshop on Machine Learning for Education (ICML4Ed 2015)
    slides
  4. Challenges of Using Observational Data to Determine the Importance of Example Usage
    Huang, Yun, González-Brenes, José P., Brusilovsky, Peter  •  2015
    Proceedings of 17th International theConference on Artificial Intelligence (AIED 2015)
    pdf
  5. Using Data from Real and Simulated Learners to Evaluate Adaptive Tutoring Systems
    González-Brenes, José P., Huang, Yun  •  2015
    Proceedings of the Workshops at the 18th International Conference on Artificial Intelligence in Education AIED 2015
  6. The White Method: Towards Automatic Evaluation Metrics for Adaptive Tutoring Systems
    González-Brenes, José P., Huang, Yun  •  2014
    Proceedings of NIPS 2014 Workshop on Human Propelled Machine Learning (NIPS 2014)
  7. Data-Driven Curriculum Design: Mining the Web to Make Better Teaching Decisions
    Moretti, Antonio, González-Brenes, J. .P, McKnight, Kathy  •  2014
    Manolis Mavrikis and Bruce M. McLaren (eds)
    Proceedings of the 7th International Conference on Educational Data Mining
    pdf
  8. Mining the Web to Discover Non-Cognitive Preferences of Students Non-Cognitive Factors & Personalization for Adaptive
    Moretti, Antonio, González-Brenes, José P, McKnight, Kathy  •  2014
    Workshop on Non-Cognitive Factors & Personalization for Adaptive Learning of the 7th International Conference on Educational Data Mining
    pdf
  9. Mining Student Ratings and Course Contents for Computer Science Curriculum Decisions
    Moretti, Antonio, González-Brenes, José .P, McKnight, Kathy, Salleb-Aouissi, Ansaf  •  2014
    Data Mining for Educational Assessment and Feedback Workshop from KDD 2014
  10. Integrating Knowledge Tracing and Item Response Theory: A Tale of Two Frameworks
    José P. González-Brenes, Mohammad M. Khajah, Yun Huang abd Michael C. Mozer, Peter Brusilovsky  •  2014
    Milos Kravcik and Olga C. Santos and Jesus G. Boticario (eds)
    4th International Workshop on Personalization Approaches in Learning Environments (PALE) in The 22nd Conference on User Modeling, Adaptation and Personalization
    pdf
  11. FAST: Feature-Aware Student Knowledge Tracing
    González-Brenes, José P, Huang, Yun, Brusilovsky, Peter  •  2013
    NIPS Workshop on Data Driven Education
  12. What and When do Students Learn? Fully Data-Driven Joint Estimation of Cognitive and Student Models
    González-Brenes, José P., Mostow, Jack  •  2013
    Andrew Olney and Philip Pavlik and Art Graesser (eds)
    Proceedings of the 6th International Conference on Educational Data Mining
    pdf
  13. Topical HMMs for Factorization of Input-Output Sequential Data
    González-Brenes, José P., Mostow, Jack  •  2012
    P. Bartlett and F.C.N. Pereira and C.J.C. Burges and L. Bottou and K.Q. Weinberger (eds)
    paper presented at Personalizing Education Workshop in Advances in Neural Information Processing Systems (NIPS'12)
  14. Predicting Travel Times for the M4 Highway in Sidney: How We Won Kaggle.com's First \$10,000 Data Mining Challenge Invited Talk
    González-Brenes, José P.  •  2012
    Joint Statistical Meetings 2012
  15. Topical Hidden Markov Models for Skill Discovery in Tutorial Data
    González-Brenes, José P., Mostow, Jack  •  2012
    NIPS-Workshop on Personalizing Education With Machine Learning
  16. Predicting Task Completion from Rich but Scarce Data
    González-Brenes, José P., Mostow, Jack  •  2010
    Ryan Shaun Joazeiro de Baker and Agathe Merceron and Philip I. Pavlik Jr. (eds)
    Proceedings of the 3rd International Conference on Educational Data Mining
  17. Speech Interfaces in the Context of the HealthLine Project
    González-Brenes, José P., Sherwani, Jahanzeb, Rose, Carolyn P., Rosenfeld, Roni  •  2009
    CHI Workshop on Human-centered computing in International Development
  18. Coreference resolution: Current trends and future directions
    Clark, Jonathan H, González-Brenes, José P  •  2008
    Technical Report
    pdf
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