James Tu

6 papers and 86 indexed citations i.

About

James Tu is a scholar working on Artificial Intelligence, Automotive Engineering and Materials Chemistry. According to data from OpenAlex, James Tu has authored 6 papers receiving a total of 86 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Artificial Intelligence, 3 papers in Automotive Engineering and 1 paper in Materials Chemistry. Recurrent topics in James Tu’s work include Autonomous Vehicle Technology and Safety (3 papers), Adversarial Robustness in Machine Learning (2 papers) and Anomaly Detection Techniques and Applications (2 papers). James Tu is often cited by papers focused on Autonomous Vehicle Technology and Safety (3 papers), Adversarial Robustness in Machine Learning (2 papers) and Anomaly Detection Techniques and Applications (2 papers). James Tu collaborates with scholars based in Canada, Australia and United States. James Tu's co-authors include Raquel Urtasun, Mengye Ren, Sivabalan Manivasagam, Jingkang Wang, Sergio Casas, Abbas Sadat, Bin Yang, Robert Smee, Simon Su and Kelvin K. L. Wong and has published in prestigious journals such as Neurosurgery, Materials science forum and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

In The Last Decade

Co-authorship network of co-authors of James Tu i

Fields of papers citing papers by James Tu

Since Specialization
EngineeringComputer SciencePhysics and AstronomyMathematicsEarth and Planetary SciencesEnergyEnvironmental ScienceMaterials ScienceChemical EngineeringChemistryAgricultural and Biological SciencesVeterinaryDecision SciencesArts and HumanitiesBusiness, Management and AccountingSocial SciencesPsychologyEconomics, Econometrics and FinanceHealth ProfessionsDentistryMedicineBiochemistry, Genetics and Molecular BiologyNeuroscienceNursingImmunology and MicrobiologyPharmacology, Toxicology and Pharmaceutics

This network shows the specialization of papers citing the papers produced by James Tu. Nodes represent fields, and links connect fields that are likely to share authors. The network helps show where James Tu may publish in the future.

Countries citing papers authored by James Tu

Since Specialization
Citations

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

Rankless by CCL
2025