Emma Brunskill

8.1k citations
100 papers · 2.4k indexed · 1 hit paper · h-index 25

Impact in

Papers in

    • Online Learning and Analytics 18
    • Reinforcement Learning in Robotics 31
    • Intelligent Tutoring Systems and Adaptive Learning 28
    • Machine Learning and Algorithms 16
    • AI-based Problem Solving and Planning 10
    • Topic Modeling 9

Emma Brunskill

96 papers receiving 2.3k citations

Hit Papers

Global and regional hearing impairment prevalence: an analysis of 42 studies in 29 countries 2011 · 508 citations
5082011202620162021100200300400500

Peers

Emma Brunskill
Comparison fields: 5 of 145
  • Computer Science Applications 538
  • Sensory Systems 281
  • Artificial Intelligence 1.0k
  • Speech and Hearing 199
  • Health Informatics 32
Replace Mark Weal with:
Mark Weal United Kingdom
Myra Spiliopoulou Germany
J. C. R. Licklider United States
Xiaojuan Ma Hong Kong
Gheorghiță Ghinea United Kingdom
Krzysztof Z. Gajos United States
Giulio Jacucci Finland
Kshitij Sharma Norway
Jan Noyes United Kingdom
Margaret Mitchell United States
Emma Brunskill relative to Mark Weal United Kingdom Mark Weal's profile →
Citations per field
00.5×11.2×
Mark Weal · 1×
Citations per year

Countries citing papers authored by Emma Brunskill

Since Specialization
Citations

This map shows the geographic impact of Emma Brunskill's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Emma Brunskill with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Emma Brunskill more than expected).

Fields of papers citing papers by Emma Brunskill

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Emma Brunskill. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Emma Brunskill. The network helps show where Emma Brunskill may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Emma Brunskill, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Emma Brunskill Line = papers co-authored together Emma Brunskill links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20256
2 20250
3 20247
4 20240
5 20242
6
Provably Good Batch Off-Policy Reinforcement Learning Without Great Exploration
20206
7
Fake It Till You Make It: Learning-Compatible Performance Support.
20193
8
Learning Procedural Abstractions and Evaluating Discrete Latent Temporal Structure
20188
9
Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement Learning
201720
10
Questimator: generating knowledge assessments for arbitrary topics
201617
11 20163
12
Sequence Matters but How Exactly? A Method for Evaluating Activity Sequences from Data.
20168
13
Latent contextual bandits and their application to personalized recommendations for new users
20161
14
Sample complexity of episodic fixed-horizon reinforcement learning
20159
15
From Predictive Models to Instructional Policies.
201521
16
Predicting player moves in an educational game: A hybrid approach
201312
17
Partially Observable Sequential Decision Making for Problem Selection in an Intelligent Tutoring System.
201111
18
Estimating Prerequisite Structure From Noisy Data.
201114
19
Learning to Identify Locally Actionable Health Anomalies
20101
20
Routing for Rural Health: Optimizing Community Health Worker Visit Schedules
20108

About Emma Brunskill

Emma Brunskill is a scholar working on Computer Science Applications, Artificial Intelligence, Management Science and Operations Research, Computational Mathematics and General Decision Sciences, having authored 100 papers that have together received 2.4k indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (31 papers), Intelligent Tutoring Systems and Adaptive Learning (28 papers), Online Learning and Analytics (18 papers), Advanced Bandit Algorithms Research (17 papers), Machine Learning and Algorithms (16 papers), AI-based Problem Solving and Planning (10 papers), Topic Modeling (9 papers) and Advanced Causal Inference Techniques (6 papers). The work is most often cited by research in Computer Science Applications (538 citations), Sensory Systems (281 citations), Artificial Intelligence (1.0k citations), Speech and Hearing (199 citations) and Health Informatics (32 citations). Emma Brunskill has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Maya Mascarenhas, Mariel M. Finucane, Seth Flaxman, Colin Mathers, Gretchen A Stevens, Shayan Doroudi, Nicholas Roy, William Thies, Nicholas Roy and Zoran Popović. Their work appears in journals such as Journal of the American Statistical Association, European Journal of Public Health, Management Science, Proceedings of the Royal Society B Biological Sciences and Machine Learning.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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