Jack Terwilliger
- Automotive Engineering top 10%
- Computer Vision and Pattern Recognition top 10%
- Social Psychology
- Safety, Risk, Reliability and Quality top 10%
- Artificial Intelligence
- Co-authors
- Lex FridmanBryan ReimerLi DingBruce MehlerMichael GlazerLinda AngellSean SeamanAlea Mehler
- Topics
- Autonomous Vehicle Technology and Safety (3 papers)Action Observation and Synchronization (1 paper)Retinal Imaging and Analysis (1 paper)
- Cited by
- Automotive EngineeringSafety, Risk, Reliability and QualityComputer Vision and Pattern Recognition
- Partner nations
- United StatesUnited KingdomAustria
In The Last Decade
Jack Terwilliger
7 papers receiving 241 citations
Peers
Comparison fields: 5 of 69
- Automotive Engineering 92
- Computer Vision and Pattern Recognition 82
- Social Psychology 77
- Safety, Risk, Reliability and Quality 50
- Artificial Intelligence 42
Countries citing papers authored by Jack Terwilliger
This map shows the geographic impact of Jack Terwilliger'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 Jack Terwilliger with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jack Terwilliger more than expected).
Fields of papers citing papers by Jack Terwilliger
This network shows the impact of papers produced by Jack Terwilliger. 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 Jack Terwilliger. The network helps show where Jack Terwilliger may publish in the future.
Co-authorship network of co-authors of Jack Terwilliger
This figure shows the co-authorship network connecting the top 25 collaborators of Jack Terwilliger. A scholar is included among the top collaborators of Jack Terwilliger based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jack Terwilliger. Jack Terwilliger is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 3 | |
| 3 | 0 | |
| 4 | 11 | |
| 5 | 17 | |
| 6 | 155 | |
| 7 | DeepTraffic: Driving Fast through Dense Traffic with Deep Reinforcement Learning. | 11 |
| 8 | MIT Autonomous Vehicle Technology Study: Large-Scale Deep Learning Based Analysis of Driver Behavior and Interaction with Automation | 56 |
About Jack Terwilliger
Jack Terwilliger is a scholar working on Developmental Biology, Automotive Engineering and Pharmacy, having authored 8 papers that have together received 258 indexed citations. Recurring topics across this work include Autonomous Vehicle Technology and Safety (3 papers), Action Observation and Synchronization (1 paper) and Retinal Imaging and Analysis (1 paper). The work is most often cited by research in Automotive Engineering (92 citations), Safety, Risk, Reliability and Quality (50 citations) and Computer Vision and Pattern Recognition (82 citations). Jack Terwilliger has collaborated with scholars based in United States, United Kingdom and Austria. Frequent co-authors include Lex Fridman, Bryan Reimer, Li Ding, Bruce Mehler, Michael Glazer, Linda Angell, Sean Seaman, Alea Mehler, Bobbie Seppelt and Hillary Abraham. Their work appears in journals such as PLoS ONE, Philosophical Transactions of the Royal Society B Biological Sciences and IEEE Access.
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.