Our expert faculty receive a number of prestigious grant awards and collaborate with students on research projects.

Research Grant Projects

Project TitleSponsorAmountPrincipal Investigator
Collaborative Research: SaTC: CORE: Small: UAV-NetSAFE.COM: UAV Network Security Assessment and Fidelity Enhancement through Cyber-attack-ready Optimized Machine-learning PlatformsNational Science Foundation$200,000 (2020-2023)Khair Al Shamaileh
Collaborative Research: FW-HTF-P: IntelEUI: Artificial Intelligence and Extended Reality to Enhance Workforce Productivity for the Energy and Utilities IndustryNational Science Foundation$79,000 (2021-2022)Xiaoli Yang (PI), Quamar Niyaz (Co-PI)
Collaborative Research: IUSE: EHR: CyberMUG: Cybersecurity Modules aligned with UG Computer Science and Engineering CurriculumNational Science Foundation$140,500 (2020-2022)Quamar Niyaz (PI), Xiaoli Yang (PI)
SaTC: EDU: Collaborative: INteractive VIsualization and PracTice basEd Cybersecurity Curriculum and Training (InviteCyber) Framework for Developing Next-gen Cyber-Aware WorkforceNational Science Foundation$231,400 (2019-2022)Xiaoli Yang (PI), Quamar Niyaz (PI)
Early Concept Exploratory Summer Research: Improvement of Arcelor Mittal Mill Operation through Incorporation of Data Fusion and Machine LearningArcelorMittal USA$10,000 (2019-2020)Colin Elkin (PI)
Deep Learning Methods with Bio-signals for Control of RoboticsIndiana Space Grant Consortium $11,726 (2020-2021)Lizhe Tan (PI), Jean Jiang (PI)

Journal Publications

  • O. Hussein, K. Al Shamaileh, H. Sigmarsson, S. Abushamleh, N. Aboserwal, and V. Devabhaktuni, “A Half-mode substrate integrated waveguide filtering power divider with Fourier-varying via holes,” Microwave and Optical Technology Letters, vol. 63, no. 12, pp. 2964–2968, December 2021.
  • U. Khan, S. Paheding, C. Elkin, and V. Devabhaktuni, “Trends in deep learning for medical hyperspectral image analysis,” IEEE Access, vol. 9, pp. 79534-79548 (2021)
  • N. Siddique, S. Paheding, C. Elkin, and V. Devabhaktuni, “U-net and its variants for medical image segmentation: A review of theory and applications,” IEEE Access, vol. 9, pp. 82031 – 82057 (2021)
  • Akshay Mathur, Laxmi Podilla, Keyur Kulkarni, Quamar Niyaz, and Ahmad Y. Javaid, “NATICUSdroid: A Malware Detection System in Android using Native and Custom Permissions,” Elsevier Journal of Information Security and Applications, Vol. 58, No. 102696, 2021, Impact Factor: 3.872
  • P.C. Srinivasa Rao, A. J. Sravan Kumar, Quamar Niyaz, Sidike Paheding, and Vijay Devabhaktuni, “A Chemical Reaction Optimization based Feature Selection Technique for Machine Learning Classification Problems,” Elsevier Expert Systems and Applications, Vol. 167, No. 114169, 2021, Impact Factor: 6.954.
  • Kyle Greene, Deven Rodgers, Henry Dykhuizen, Quamar Niyaz, Khair Al Shamaileh, and Vijay Devabhaktuni, “A Defense Mechanism Against Replay Attack in Remote Keyless Entry Systems Using Timestamping and XOR Logic,” IEEE Consumer Electronics Magazine, Vol. 10, Issue 1, pp. 101─108, 2021, Impact Factor: 3.789.
  • A. Lendek, L. Tan, “Mitigation of derivative kick using time-varying fractional-order PID control,” IEEE Access, vol. 9, pp. 55974-55987, April 2021.
  • J. Chen, J, J. Jiang, X. Guo, L. Tan, “An efficient CNN with tunable input-size for bearing fault diagnosis,” International Journal of Computational Intelligence Systems, vol. 14, no. 1, pp. 625–634, 2021.
  • J. Chen, J. Jiang, X. Guo, L. Tan, “A self-Adaptive CNN with PSO for bearing fault diagnosis,” Systems Science & Control Engineering, vol. 8, no. 1, pp. 11-22, 2021.
  • J. Chen, J. Jiang, X. Guo, L. Tan, “Bit-error aware lossless image compression with 2D-layer-block coding,” Journal of Sensors, vol. 2021, November, 2021.
  • F. Tian, M. Hua, W. Zhang, Y. Li , X. Yang, (2021) Emotional arousal in 2D versus 3D virtual reality environments. PLoS ONE 16(9): e0256211.

Conference Proceedings

  • H. Jaradat, N. Dib, and K. Al Shamaileh, “A miniaturized ultra-wideband Wilkinson power divider using non-uniform coplanar waveguide,” International Congress on Engineering Technologies, September 2021.
  • J. Pawlak, Y. Li, J. Price, M. Wright, K. Al Shamaileh, Q. Niyaz, and V. Devabhaktuni, “A machine learning approach for detecting and classifying jamming attacks against OFDM-based UAVs,” ACM Workshop on Wireless Security and Machine Learning, Abu Dhabi, UAE, July 2021.
  • Doga Ozgulbas, and N. Houshangi, “Autonomous Navigation and Room Categorization for an Assistant Robot”, 7th International Conference on Engineering and Emerging Technologies, Istanbul, Turkey, October 2021.
  • Akshay Mathur, Ethan Ewoldt, Quamar Niyaz, Xiaoli Yang, and Ahmad Javaid, “Permission Educator: App for Educating Users about Android Permissions,” at 13th International Conference on Intelligent Human-Computer Interaction, December 20-22, 2021, Kent, Ohio, USA.
  • Y. Cai, L. Tan, J. Chen, “Evaluation of deep learning neural networks with input processing for bearing fault diagnosis,” 2021 IEEE International Conference on Electro/Information Technology, pp. 140-145, Mt. Pleasant, MI, May 2021.
  • Y. Song, Y. Cai, L. Tan, “Video-audio emotion recognition based on feature fusion deep learning method,” 2021 IEEE International Midwest Symposium on Circuits and Systems (MWSCAS), pp. 611-616, Lansing, MI, August 2021.
  • J. Rogers, M. Baker, X. Yang, A. R. Angulo, Y. Luo, “Cultivating the Future of Graduate Nurses’ Knowledge Acquisition of Pathophysiology through Multifarious Innovative Gamification Techniques,” the 2021 Signa Nursing, Indianapolis, Indiana, USA, November 6-10, 2021.
  • J. Rogers, M. Baker, X. Yang, A. R. Angulo, Y. Luo, “Creating a Future in Nurse Education Using 3-D Interactive Visualizations to Mind Map Disease,” the 2021 Signa Nursing, Indianapolis, Indiana, USA, November 6-10, 2021.
  • M. Baker, J. Rogers, X. Yang, A. R. Angulo, Y. Luo, “Creating Learning Experiences Using Serious Games: Skill Competency Development for Future Nurses,” the 2021 Signa Nursing, Indianapolis, Indiana, USA, November 6-10, 2021.