Erin Grant

Ph.D. Candidate, UC Berkeley

UC Berkeley, EECS Department, CS Graduate Student
396 Soda Hall, #1776
Berkeley, CA 94720-1776

currently

pursuing a doctoral degree (Ph.D.) in Computer Science at UC Berkeley

affiliated with

the Berkeley Artificial Intelligence Research (BAIR) Lab and Princeton’s Computational Cognitive Science Lab

interested in

understanding black-box systems in machine learning and cognitive science

education

May 2022 (Expected) Ph.D. in Computer Science, UC Berkeley

June 2016 Honours B.Sc. in Computer Science & Statistics with High Distinction, University of Toronto

research appointments

2021 Research Scientist Intern, DeepMind, London

2019—2020 Research Intern then Student Researcher, Brain Team, Google Research, Montréal

2018 Research Intern, OpenAI, San Francisco

2016— Graduate Student Researcher (GSR), UC Berkeley

2014—2016 Undergraduate Student Researcher (USR), University of Toronto

teaching appointments

2018 Graduate Student Instructor (GSI) for CS194/294-129: Deep Learning, UC Berkeley

2016 Teaching Assistant (TA) for CSC401/2511: Natural Language Computing, University of Toronto

2015 Teaching Assistant (TA) for CSC411/2515: Introduction to Machine Learning, University of Toronto

publications

preprints

  1. 2021 “Distinguishing rule- and exemplar-based generalization in black-box systems.”
    Ishita Dasgupta*, Erin Grant*, Thomas L. Griffiths.
    In preparation.

  2. 2021 “Passive attention in artificial neural networks predicts human visual selectivity.”
    Thomas A. Langlois*, Charles Zhao*, Erin Grant, Ishita Dasgupta, Thomas L. Griffiths, Nori Jacoby.
    arXiv: 2107.07013.

  3. 2020 “Connecting context-specific adaptation in humans to meta-learning.”
    Rachit Dubey, Erin Grant, Michael Luo, Karthik Narasimhan, Thomas L. Griffiths.
    arXiv: 2011.13782.

refereed journal articles

2019 “Doing more with less: Meta-reasoning and meta-learning in humans and machines.”
Thomas L. Griffiths, Frederick Callaway, Michael B. Chang, Erin Grant, Paul M. Krueger, Falk Lieder.
Current Opinion in Behavioral Sciences 29.

refereed conference publications

  1. 2021 “Are Convolutional Neural Networks or Transformers more like human vision?”
    Shikhar Tuli, Ishita Dasgupta, Erin Grant, Thomas L. Griffiths.
    Annual Meeting of the Cognitive Science Society (CogSci).

  2. 2020 “Universal linguistic inductive biases via meta-learning.”
    R. Thomas McCoy, Erin Grant, Paul Smolensky, Thomas L. Griffiths, Tal Linzen.
    Annual Meeting of the Cognitive Science Society (CogSci).

  3. 2020 “Tracing the emergence of gendered language in childhood.”
    Ben Prystawski, Erin Grant, Aida Nematzadeh, Spike W.S. Lee, Suzanne Stevenson, Yang Xu.
    Annual Meeting of the Cognitive Science Society (CogSci).

  4. 2019 “Reconciling meta-learning and continual learning with online mixtures of tasks.”
    Ghassen Jerfel*, Erin Grant*, Thomas L. Griffiths, Katherine Heller.
    Conference on Neural Information Processing Systems (NeurIPS).

  5. 2019 “Learning deep taxonomic priors for concept learning from few positive examples.”
    Erin Grant, Joshua C. Peterson, Thomas L. Griffiths.
    Annual Meeting of the Cognitive Science Society (CogSci).

  6. 2018 “Recasting gradient-based meta-learning as hierarchical Bayes.”
    Erin Grant, Chelsea Finn, Sergey Levine, Trevor Darrell, Thomas L. Griffiths.
    International Conference on Learning Representations (ICLR).

  7. 2018 “Evaluating theory of mind in question answering.”
    Aida Nematzadeh, Kaylee Burns, Erin Grant, Alison Gopnik, Thomas L. Griffiths.
    Conference on Empirical Methods in Natural Language Processing (EMNLP).

  8. 2017 “How can memory-augmented neural networks pass a false-belief task?”
    Erin Grant, Aida Nematzadeh, Thomas L. Griffiths.
    Annual Meeting of the Cognitive Science Society (CogSci).

  9. 2016 “The interaction of memory and attention in novel word generalization: A computational investigation.”
    Erin Grant, Aida Nematzadeh, Suzanne Stevenson.
    Annual Meeting of the Cognitive Science Society (CogSci).

  10. 2015 “A computational cognitive model of novel word generalization.”
    Aida Nematzadeh, Erin Grant, Suzanne Stevenson.
    Conference on Empirical Methods in Natural Language Processing (EMNLP).

refereed workshop publications

  1. 2020 “Generalization in planning by metalearning to metareason.”
    Frederick Callaway, Bas van Opheusden, Erin Grant, Thomas L. Griffiths.
    AAAI Workshop on Generalization in Planning.

  2. 2018 “Exploiting attention to reveal shortcomings in memory models.”
    Kaylee Burns, Aida Nematzadeh, Erin Grant, Alison Gopnik, Thomas L. Griffiths.
    EMNLP Workshop on BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP.

  3. 2017 “Concept acquisition through meta-learning.”
    Erin Grant, Chelsea Finn, Joshua C. Peterson, Joshua T. Abbott, Sergey Levine, Trevor Darrell, Thomas L. Griffiths.
    NeurIPS Workshop on Cognitively Informed Artificial Intelligence.

awards

international

Conference on Neural Information Processing Systems (NeurIPS)

2019 Best Reviewer (top 8.5%): free conference registration valued at 750 USD

2018 Best Reviewer (top 6.9%): free conference registration valued at 750 USD

Conference on Empirical Methods in Natural Language Processing (EMNLP)

2015 Student Travel Grant: 1000 USD, awarded by merit

national

Natural Sciences and Engineering Research Council of Canada (NSERC)
(Canadian federal granting agency, equivalent to the National Science Foundation (NSF))

2020 Canada Graduate Scholarship, Doctoral (CGS-D): 35 000 CAD per year
Ranked 3rd out of 166 (top 1.8%) of applicants in “Computing Sciences” nationally; declined for the PGS-D due to tenure at a non-Canadian institution.

2020 Postgraduate Scholarship, Doctoral (PGS-D): 21 000 CAD per year

2014, 2015 Undergraduate Student Research Award (USRA): 6000 CAD per year

provincial

Ontario Ministry of Colleges and Universities

2011 Queen Elizabeth II Aiming for the Top Tuition Scholarship: 1000 CAD

institutional

UC Berkeley

2016 EECS Excellence Award: 5000 USD

2016 EECS Departmental Fellowship

2016 UC Berkeley Microsoft Research Women’s Fellow: 20 000 USD

University of Toronto

2012—2016 Dean’s List Scholar

2012—2016 Innis College Exceptional Achievement Award: 3000 CAD

2011 President’s Entrance Scholarship: 2000 CAD

presentations

invited talks

  1. May 2021 “Using meta-learning as a tool to investigate human inductive biases.”
    Workshop on Learning-to-Learn, virtually collocated with the International Conference on Learning Representations (ICLR).

  2. December 2019 “Meta-learning as hierarchical modelling.”
    Workshop on Meta-Learning, collocated with the Conference on Neural Information Processing Systems (NeurIPS), Vancouver.

  3. December 2019 “Taxonomic structure in learning from few positive examples.”
    Workshop on Shared Visual Representations in Human & Machine Intelligence (SVHRM), collocated with the Conference on Neural Information Processing Systems (NeurIPS), Vancouver.

professional service

conference chairing

2019 Session Chair for “Skill Acquisition,” Annual Meeting of the Cognitive Science Society (CogSci), Montréal

workshop chairing

2018, 2020, 2021 Organizer, Workshop on Meta-Learning (MetaLearn), collocated with the Conference on Neural Information Processing Systems (NeurIPS), Montréal

2020 General Chair, Women in Machine Learning Workshop (WiML), virtually collocated with the Conference on Neural Information Processing Systems (NeurIPS)

2019 Lead Organizer, Workshop on Structure & Priors in RL (SPiRL), collocated with the International Conference on Learning Representations (ICLR), New Orleans

conference committee

2021 Reviewer, Conference on Uncertainty in Artificial Intelligence (UAI)

2020, 2021 Reviewer, AAAI Conference on Artificial Intelligence (AAAI)

2019—2021 Reviewer, International Conference on Artificial Intelligence and Statistics (AISTATS)

2016—2021 Reviewer, Annual Meeting of the Cognitive Science Society (CogSci)

2019—2022 Reviewer, International Conference on Learning Representations (ICLR)

2018—2021 Reviewer, International Conference on Machine Learning (ICML)

2018—2021 Reviewer, Conference on Neural Information Processing Systems (NeurIPS)

2019, 2020 Reviewer, Annual Meeting of the Association for Computational Linguistics (ACL)

2019, 2020 Reviewer, SIGNLL Conference on Computational Natural Language Learning (CoNLL)

2019, 2020 Reviewer, IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

2019 Reviewer, Conference on Empirical Methods in Natural Language Processing (EMNLP)

2019 Reviewer, International Conference in Computer Vision (ICCV)

2017 Reviewer, IEEE/RSJ International Conference on Intelligent Robots & Systems (IROS)

workshop committee

2021 Reviewer, From Shallow to Deep: Overcoming Data Adversity, collocated with the International Conference on Learning Representations (ICLR)

2019, 2020 Reviewer, Workshop on Shared Visual Representations in Human and Machine Intelligence (SVHRM), collocated with the Conference on Neural Information Processing Systems (NeurIPS)

2019, 2020 Reviewer, Workshop for New in Machine Learning (NewInML), collocated with the Conference on Neural Information Processing Systems (NeurIPS)

2020 Reviewer, Workshop on Bridging AI and Cognitive Science (BAICS), collocated with the International Conference on Learning Representations (ICLR)

2019 Reviewer, Workshop on Generative Modeling & Model-Based Reasoning for Robotics & AI, collocated with the International Conference on Machine Learning (ICML)

2019 Reviewer, Workshop on Adaptive & Multitask Learning: Algorithms & Systems (AMTL), collocated with the International Conference on Machine Learning (ICML)

2018 Reviewer, Women in Computer Vision Workshop (WiCV), collocated with the International Conference on Machine Learning (ICML)

2018, 2019 Reviewer, International Workshop on Automatic Machine Learning (AutoML), collocated with the International Conference on Machine Learning (ICML)

2017, 2019 Reviewer, Workshop on Meta-Learning (MetaLearn), collocated with the Conference on Neural Information Processing Systems (NeurIPS)

institutional committee

2021 Organizer, BAIR Research Experience for Undergraduates (REU) Summer Program, UC Berkeley

2020 Organizer, Equal Access to Application Assistance (EAAA) Program, UC Berkeley

2018 President, Women in Computer Science & Engineering (WiCSE), UC Berkeley

2017 Coordinator of weekly lunches with invited speakers, Women in Computer Science & Engineering (WiCSE), UC Berkeley

2017, 2018 Student Reader on the Ph.D. Application Review Committee, EECS Department, UC Berkeley

diversity, equity, & inclusion (DEI)

2021 Organizer, BAIR Research Experience for Undergraduates (REU) Summer Program, UC Berkeley

2020 General Chair, Women in Machine Learning Workshop (WiML), virtually collocated with the Conference on Neural Information Processing Systems (NeurIPS)

2020 Organizer, Equal Access to Application Assistance (EAAA) Program, UC Berkeley

2020 Mentor for a first-year Ph.D. student, Berkeley AI Research (BAIR) Ph.D. Buddy Program, UC Berkeley

2018 President, Women in Computer Science & Engineering (WiCSE), UC Berkeley

2019 Organizer, 7th Annual Berkeley-Stanford Meetup for women in computer science & electrical engineering, UC Berkeley

2017, 2018 Mentor for undergraduate groups who are underrepresented in AI, Berkeley AI Research (BAIR) Mentoring Program, UC Berkeley

2017 Coordinator of weekly lunches with invited speakers, Women in Computer Science & Engineering (WiCSE), UC Berkeley