Papers

2025

  • Kumar, C., Herrera-Gerena, J., Just, J., Darr, M., Jannesari, A. (2026). A Novel Unsupervised Contrastive Learning Approach for Efficient Object Lookup and Retrieval. In: Arai, K. (eds) Intelligent Systems and Applications. IntelliSys 2025. Lecture Notes in Networks and Systems, vol 1660. Springer, Cham. https://doi.org/10.1007/978-3-032-07109-5_36

  • Kumar, C., Herrera-Gerena, J., Just, J., Darr, M., Jannesari, A. (2026). Learning Location-Aware Visual Representations Through Anchor-Based Contrastive Learning. In: Arai, K. (eds) Intelligent Systems and Applications. IntelliSys 2025. Lecture Notes in Networks and Systems, vol 1660. Springer, Cham. https://doi.org/10.1007/978-3-032-07109-5_18

  • KUMAR, C., 2025. Learning to Detect Objects with Unsupervised Learning. Order No. 31998925 ed. United States – Iowa: Iowa State University Dissertations & Theses @ Iowa State University; ProQuest Dissertations & Theses Global. ISBN 9798286430598.

2024

  • Khan, Inzamam, Wajid Shakeel Ahmed, Shafqat Shad, Chandan Kumar, Muhammad Usman, Milad Jasemi, and Khuarm Shafi. “Determine Intraday Trading Currency’s Trend Framework Evidence From Machine Learning Techniques.” International Journal of Business Intelligence Research (IJBIR) 15, no. 1 (2024): 1-15.

  • Khan, Inzamam, Wajid Shakeel Ahmed, Shafqat Shad, Chandan Kumar, Muhammad Usman, Milad Jasemi, and Khuarm Shafi. “Determine Intraday Trading Currency’s Trend Framework Evidence From Machine Learning Techniques.” International Journal of Business Intelligence Research (IJBIR) 15, no. 1 (2024): 1-15.

  • Kumar, Chandan, Ali Jannesari, and Matthew Darr. “Discerning self-supervised learning and weakly supervised learning.” In The Second Tiny Papers Track at ICLR 2024. 2024.

2023

  • Kumar, Chandan, and Ali Jannesari. “Optimal deep learning model for uavs: A case study.” In 2023 26th International Symposium on Wireless Personal Multimedia Communications (WPMC), pp. 51-57. IEEE, 2023.

2022

  • Kumar, Chandan, Yamini Mathur, and Ali Jannesari. “Efficient volume estimation for dynamic environments using deep learning on the edge.” In 2022 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), pp. 995-1002. IEEE, 2022.

  • J. K. Francis, C. Kumar, J. Herrera-Gerena, K. Kumar and M. J. Darr, “Deep Learning and Pattern-based Methodology for Multivariable Sensor Data Regression,” 2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA), Nassau, Bahamas, 2022, pp. 748-753, doi: 10.1109/ICMLA55696.2022.00125. keywords: {Training;Deep learning;Computer vision;Computational modeling;Crops;Computer architecture;Pattern recognition;artificial intelligence;neural networks;Regression analysis;agriculture},

  • Kumar, Chandan. “Efficient volume analysis for dynamic environments using Deep Learning.” Master’s thesis, Iowa State University, 2022.

2021

  • Vaddi, Subrahmanyam, Dongyoun Kim, Chandan Kumar, Shafqat Shad, and Ali Jannesari. “Efficient Object Detection Model for Real-time UAV Application.” Computer and Information Science 14, no. 1 (2021).