Jyotirmaya Ijaradar Master of Science
Person

Affiliations

Chair of Traffic Process Automation
- Academic Staff
- jyotirmaya.ijaradar@tu-dresden.de

Identification Numbers

ORCID	0000-0002-8450-4550
Scopus author ID	58022143700

Data-Driven Anomaly Detection in Urban Traffic Data: A Deep Learning Approach

Ijaradar, J., Pape, S., Tan, C., Körner, M. & Wang, M., 8 Sept 2025, 2025 9th International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS). p. 1-6

Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed › peer-review

Local differences in feature importance for the prediction of PM₁₀, O₃ and NO_x using Dresden as example

Teichmann, S., Ninnemann, L., Schanze, J., Ijaradar, J. & Herold, H., 4 May 2025, 28th AGILE Conference on Geographic Information Science - Poster Track, Dresden, Germany. 4 p.

Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed › peer-review

A Survey on Multivariate Time Series Imputation using Adversarial Learning

Richter, A., Ijaradar, J., Wetzker, U., Jain, V. & Frotzscher, A., 3 Oct 2024, In: IEEE access. 12, p. 148167 - 148189 23 p.

Research output: Contribution to journal › Research article › Contributed › peer-review

An Imputation-Enhanced Hybrid Deep Learning Approach for Traffic Volume Prediction in Urban Networks: A Case Study in Dresden

Yan, P., Li, Z., Ijaradar, J., Pape, S., Körner, M. & Wang, M., 13 Sept 2024, In: Data Science for Transportation. 6 (2024), 3, 16 p., 22.

Research output: Contribution to journal › Research article › Contributed › peer-review

Unlocking the Potential of Lignin: Towards a Sustainable Solution for Tire Rubber Compound Reinforcement

Hait, S., Kumar, L., Ijaradar, J., Ghosh, A. K., De, D., Chanda, J. & Ghosh, P. & 5 others, Gupta, S. D., Mukhopadhyay, R., Wießner, S., Heinrich, G. & Das, A., 27 Jul 2024, In: Journal of cleaner production. 470 (2024), 14 p., 143274.

Research output: Contribution to journal › Research article › Contributed › peer-review

View all research output (6)

Research Portal of the TU Dresden

Jyotirmaya Ijaradar Master of Science
Person

Affiliations

Identification Numbers

Related content

Data-Driven Anomaly Detection in Urban Traffic Data: A Deep Learning Approach

Local differences in feature importance for the prediction of PM₁₀, O₃ and NO_x using Dresden as example

A Survey on Multivariate Time Series Imputation using Adversarial Learning

An Imputation-Enhanced Hybrid Deep Learning Approach for Traffic Volume Prediction in Urban Networks: A Case Study in Dresden

Unlocking the Potential of Lignin: Towards a Sustainable Solution for Tire Rubber Compound Reinforcement