Sarker Monojit Asish

Assistant Professor - 9
Sarker Monojit Asish

Phone 863-874-8581

Location Main Campus

Office BARC-1187

Directory Computer Science

Dr. Sarker Monojit Asish joined Florida Polytechnic University in August of 2023 as an assistant professor of computer science. Prior to this, he worked as a post-doc research assistant at the University of Louisiana at Lafayette where he also completed his Ph.D. and master’s degree. He also worked as a software engineer in Bangladesh for several years.

  • UL Lafayette Dissertation Completion Fellowship Award, Fall 2022
  • Honorable Mention for Best Paper Award ( ICAT-EGVE, 2021)
  • Three minute (3MT) thesis finalist Award for "Identifying distracted students in online learning environment", University of Louisiana at
  • Lafayette, LA, 2021
  • Curriculum Committee Members, Computer Science, Florida Poly, 2023-current
  • Ph.D. in Computer Science, University of Louisiana at Lafayette, 2023
  • M.S. in Computer Science, University of Louisiana at Lafayette, 2019
  • B.S. in Computer Science and Engineering, Shahjalal University of Science & Technology, Sylhet, Bangladesh, 2009
  • Human-Computer Interaction
  • Virtual Reality
  • Mixed Reality
  • Machine Learning/Deep Learning
  • Professional Member, Association of Computing Machinery (ACM), 2020-current
  • Professional Member, Institute of Electrical and Electronics Engineers (IEEE)
  • Asish, S. M., Kulshreshth, A. K., & Borst, C. (2023, August). Internal distraction detection utilizing EEG data in an educational VR environment. In ACM Symposium on Applied Perception 2023 (pp. 1-10). DOI: https://doi.org/10.1145/3605495.3605790
  • Asish, S. M., Kulshreshth, A. K., & Borst, C. W. (2023, March). Detecting Distracted Students in an Educational VR Environment Utilizing Machine Learning on EEG and Eye-Gaze Data. In 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW) (pp. 703-704). IEEE.  DOI: 10.1109/VRW58643.2023.00194
  • Nath, F., Asish, S., Sutradhar, S., Li, Z., Shahadat, N., Debi, H. R., & Hoque, S. S. (2023, June). Rock Thin-Section Analysis and Mineral Detection Utilizing Deep Learning Approach. In SPE/AAPG/SEG Unconventional Resources Technology Conference (p. D031S073R005). URTEC. DOI: https://doi.org/10.15530/urtec-2023-3865660 
  • Nath, F., Asish, S. M., Ganta, D., Debi, H. R., Aguirre, G., & Aguirre, E. (2022). Artificial Intelligence Model in Predicting Geomechanical Properties for Shale Formation: A Field Case in Permian Basin. Energies, 15(22), 8752. DOI: https://doi.org/10.3390/en15228752
  • Asish, S. M., Kulshreshth, A. K., & Borst, C. W. (2022). Detecting distracted students in educational VR environments using machine learning on eye gaze data. Computers & Graphics, 109, 75-87. DOI: https://doi.org/10.1016/j.cag.2022.10.007   
  • Asish, S. M., Kulshreshth, A. K., & Borst, C. W. (2022, September). User identification utilizing minimal eye-gaze features in virtual reality applications. In Virtual Worlds (Vol. 1, No. 1, pp. 42-61). MDPI. DOI: https://doi.org/10.3390/virtualworlds1010004
  • Asish, S. M., Hossain, E., AK, K., & Borst, C. W. (2021, January). Deep learning on eye gaze data to classify student distraction level in an educational vr environment. In International Conference on Artificial Reality and Telexistence Eurographics Symposium on Virtual Environments (ICAT-EGVE). DOI: https://doi.org/10.2312/egve.20211326
  • Rahman, Y., Asish, S. M., Fisher, N. P., Bruce, E. C., Kulshreshth, A. K., & Borst, C. W. (2020, March). Exploring eye gaze visualization techniques for identifying distracted students in educational VR. In 2020 IEEE Conference on Virtual Reality and 3D User Interfaces (VR) (pp. 868-877). IEEE. DOI: 10.1109/VR46266.2020.00009