Professional

Oreilly Publishing

Summer 2021 - Technical Reviewer

Google

Summer 2018 - Software Engineering Intern

Microsoft

Fall 2017 - Research Intern

Google

Summer 2017 - Software Engineering Intern

Silicon Labs

Summer 2016 - Software Engineering Intern

Imagitas

Summer 2015 - Software Engineering Intern


Publications

Conferences and Journals

  1. Charles Lovering*, Jessica Forde*, Ellie Pavlick, Michael Littman. Where, When & Which Concepts Does AlphaZero Learn? AAAI, RLG Workshop, 2022. (*Equal contribution.)
  2. Charles Lovering, Rohan Jha, Tal Linzen, Ellie Pavlick. Predicting Inductive Biases of Pre-Trained Models. ICLR, 2021. Github.
  3. Rodica Neamtu, Ramoza Ahsan, Cuong Dinh Tri Nguyen, Charles Lovering, Elke A. Rundensteiner, and Gabor Sarkozy. "A General Approach For Supporting Time Series Matching using Multiple-Warped Distances." IEEE Transactions on Knowledge and Data Engineering (2020).
  4. Charles Lovering, Anqi Lu, Cuong Nguyen, Huyen Nguyen, David Hurley, Emmanuel Agu. Fact or Fiction: ACM CSCW 2018.
  5. Rodica Neamtu, Ramoza Ahsan, Elke Rundensteiner, Gabor Sarkozy, Eamonn Keogh, Cuong Nguyen, Charles Lovering: Generalized Dynamic Time Warping. IEEE International Conference on Data Engineering (ICDE) 2018.
  6. Neamtu, R., Ahsan, R., Lovering, C., Nguyen, C., Rundensteiner, E., & Sarkozy, G. (2017, May). Interactive Time Series Analytics Powered by ONEX. In Proceedings of the 2017 ACM International Conference on Management of Data (pp. 1595-1598). ACM.
  7. Nguyen, C., Lovering, C., & Neamtu, R. Ranked Time Series Matching by Interleaving Similarity Distances. 4th Workshop on Advances in Software and Hardware for Big Data to Knowledge Discovery 2017. IEEE Big Data 2017.

PrePrints

  1. Rohan Jha, Charles Lovering, Ellie Pavlick. Does Data Augmentation Improve Generalization in NLP? 2020. PREPRINT.
  2. Charles Lovering, Ellie Pavlick. Self-play for Data Efficient Language Acquisition. 2020. PREPRINT.

Unpublished Work

Posters

  1. Rohan Jha, Charles Lovering, Ellie Pavlick. Do Adversarial Counterexamples help Generalization? New York Symposium for Natural Language Processing (2019).
  2. Charles Lovering, Ellie Pavlick. Emergent Communication with Selfplay. New York Symposium for Natural Language Processing (2019).
  3. Charles Lovering, Jake Whitehill. Why did they cite that? New England Machine Learning Day (NEML) 2018.
  4. Cuong Nguyen, Charles Lovering. Ranked Time Series Matching by Interleaving Similarity Distances. New England Database Day (NEDB) 2018. MIT.
  5. Charles Lovering, Cuong Nguyen. INSIGHT. Interactive Time Series Analytics System. MIT IEEE Undergraduate Conference for Research 2016.

Academics

Doctorate, 2018+ (Brown) - Natural Language Understanding

I am pursuing my PhD at Brown University (2018) working with Professor Pavlick.

Masters, 2017-18 (WPI) - Natural Language Understanding

Working with my master thesis advisor Professor Whitehill we developed machine learning models to find (extract) evidence for claims made in academic papers.

Undergraduate, 2016-18 (WPI) - Time Series Analysis

We developed a series of theoretical frameworks for time series analysis and search. We further implemented efficient systems demonstrating these concepts