Hardik Gohel

Hardik Gohel, , Ph.D., Senior Member - IEEE
Assistant Professor & Director of Research, Department of Computer Science
Director of Applied AI Research Laboratory
Phone: (361) 570-4219
Office: UHV- North, Room No. 212P

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Ph.D. in Computer Science, University of Hertfordshire, United Kingdom, 2015

Subjects Area of Specialization

Artificial Intelligence and Cybersecurity

Research Disciplines

Data Science (Bigdata, Machine Learning, Deep Learning)

Digital Health

Virtualization

Social Media

Dr. Gohel has extensive research experience in artificial intelligence and his research projects have involved cyber test automation and monitoring, smart bandages for wound monitoring, bigdata for security intelligence, trustworthy cyberspace for security and privacy of social media, predictive maintenance for nuclear infrastructure, and database and mobile forensics infrastructure. Dr. Gohel is also working on how to prepare quality diversified workforce with artificial intelligence in science, technology, engineering and mathematics (STEM) education.

His independent research program is inspired from his graduate and postdoc studies. He is interested to design and develop robust artificial intelligence and cybersecurity solutions to make human life better. Dr. Gohel is actively working with United States Federal funding agencies and national labs for research collaborations. He is also interested in linkages, and MOUs with government, academia and industry to foster individual and institutional partnerships in a natural and sustainable manner.

Dr. Gohel welcomes motivated undergraduate and graduate students to join his research team and contact him.

Selected Publications

M.A. Mujawar, H. Gohel, S.K.Bhardwaj, S. Srinivasan, N. Hickman, A. Kaushik, "Nano-enabled biosensing systems for intelligent healthcare: towards COVID-19 management", Elsevier journal of Materialstoday Chemistry, 2020, doi: 10.1016/j.mtchem.2020.100306
H.Gohel, H.Upadhyay, L.Lagos, K. Cooper, A. Sanzetenea, "Predictive maintenance architecture development for nuclear infrastructure using machine learning", Elsevier journal of Nuclear Engineering & Technology., 2020 doi: 10.1016/j.net.2019.12.029
S. Bhardwaj, H. Gohel and S. Namuduri, "A Multiple Input Deep Neural Network Architecture for Solution of One-Dimensional Poisson Equation," in IEEE Antennas and Wireless Propagation Letters. doi: 10.1109/LAWP.2019.2933181
Gohel H., Upadhyay H. Developing Security Intelligence in Big Data. Knowledge Computing and Its Applications. Springer Publications, 2018, pp. 25-50, doi: 10.1007/978-981-10-6680-1_2
H. Upadhyay, H. Gohel, A. Pons and L. Lagos, "Windows Virtualization Architecture For Cyber Threats Detection," IEEE Conference on Data Intelligence and Security, 2018, pp. 119-122. doi: 10.1109/ICDIS.2018.00025
D. Levy, H. Gohel, H. Upadhyay, A. Pons and L. E. Lagos, "Design of Virtualization Framework to Detect Cyber Threats in Linux Environment," IEEE Conference on Cyber Security and Cloud Computing, 2017, pp. 316-320. doi: 10.1109/CSCloud.2017.18
Gohel H., Sharma P. Intelligent Web Security Testing with Threat Assessment and Client Server Penetration. Springer Advances in Intelligent Systems and Computing, 2016, pp. 555-567 doi:10.1007/978-981-10-0135-2_54