Andrew Silva

472 citations
19 papers · 221 · h-index 9

Impact in

Papers in

Andrew Silva

17 papers receiving 215 citations

Peers

Andrew Silva
Comparison fields: 5 of 54
  • Health Informatics 13
  • Artificial Intelligence 129
  • Safety Research 23
  • Social Psychology 37
  • Computer Vision and Pattern Recognition 25
Replace Ranganath Krishnan with:
Ranganath Krishnan United States
Hengshuai Yao Canada
Serena Booth United States
Shahin Atakishiyev Canada
Bruno Castro da Silva United States
Mehdi Mekni United States
Rahul Iyer United States
Yasaman Khazaeni United States
Éloi Zablocki France
Yao Rong Germany
Andrew Silva relative to Ranganath Krishnan United States Ranganath Krishnan's profile →
Citations per field
00.5×2.8×
Ranganath Krishnan · 1×
Citations per year

Countries citing papers authored by Andrew Silva

Since Specialization
Citations

This map shows the geographic impact of Andrew Silva'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 Andrew Silva with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrew Silva more than expected).

Fields of papers citing papers by Andrew Silva

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andrew Silva. 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 Andrew Silva. The network helps show where Andrew Silva may publish in the future.

Co-authors

The 23 scholars most cited alongside Andrew Silva, 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 Andrew Silva Line = papers co-authored together Andrew Silva links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 202253
2 202134
3 202230
4 202123
5
Optimization Methods for Interpretable Differentiable Decision Trees Applied to Reinforcement Learning
202018
6 202114
7 201812
8 202411
9 20229
10 20245
11 20234
12
ProLoNets: Neural-encoding Human Experts' Domain Knowledge to Warm Start Reinforcement Learning.
20193
13
Personalized Apprenticeship Learning from Heterogeneous Decision-Makers.
20191
14 20231
15 20191
16 20251
17 20251
18 20250
19 20250

About Andrew Silva

Andrew Silva is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Safety Research and Pediatrics, Perinatology and Child Health, having authored 19 papers that have together received 221 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (6 papers), Explainable Artificial Intelligence (XAI) (5 papers), Topic Modeling (4 papers), Artificial Intelligence in Games (2 papers), Ethics and Social Impacts of AI (2 papers), Machine Learning and Data Classification (2 papers), Color Science and Applications (1 paper) and Adversarial Robustness in Machine Learning (1 paper). The work is most often cited by research in Health Informatics (13 citations), Artificial Intelligence (129 citations), Safety Research (23 citations), Social Psychology (37 citations) and Computer Vision and Pattern Recognition (25 citations). Andrew Silva has collaborated with scholars based in United States, Canada and Australia. Frequent co-authors include Matthew Gombolay, Nakul Gopalan, Pradyumna Tambwekar, Mariah Schrum, Sonia Chernova, Siddhartha Banerjee, Grace Gombolay, Yuchen Cui, Joanna Black and David G. Cory. Their work appears in journals such as IEEE Robotics and Automation Letters, Journal of Vision, International Journal of Human-Computer Interaction, Annals of Clinical and Translational Neurology and Translational Vision Science & Technology.

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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