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
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
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