Daniel Lowd

30 papers and 878 indexed citations i.

About

Daniel Lowd is a scholar working on Artificial Intelligence, Information Systems and Signal Processing. According to data from OpenAlex, Daniel Lowd has authored 30 papers receiving a total of 878 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Artificial Intelligence, 4 papers in Information Systems and 4 papers in Signal Processing. Recurrent topics in Daniel Lowd’s work include Bayesian Modeling and Causal Inference (17 papers), Machine Learning and Algorithms (10 papers) and Adversarial Robustness in Machine Learning (6 papers). Daniel Lowd is often cited by papers focused on Bayesian Modeling and Causal Inference (17 papers), Machine Learning and Algorithms (10 papers) and Adversarial Robustness in Machine Learning (6 papers). Daniel Lowd collaborates with scholars based in United States, Belgium and China. Daniel Lowd's co-authors include Javid Ebrahimi, Pedro Domingos, Dejing Dou, Anyi Rao, Jesse Davis, Dejing Dou, Roberto González, Stanley Kok, Reza Rejaie and Walter Willinger and has published in prestigious journals such as Communications of the ACM, Machine Learning and Journal of Machine Learning Research.

In The Last Decade

Co-authorship network of co-authors of Daniel Lowd i

Fields of papers citing papers by Daniel Lowd

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 Daniel Lowd. Nodes represent fields, and links connect fields that are likely to share authors. The network helps show where Daniel Lowd may publish in the future.

Countries citing papers authored by Daniel Lowd

Since Specialization
Citations

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

Rankless by CCL
2025