Cyber Law

The goal of Artificial Intelligence (AI) is to understand intelligence by constructing computational models of intelligent behavior. This entails developing and testing falsifiable algorithmic theories of (aspects of) intelligent behavior, including sensing, representation, reasoning, learning, decision-making, communication, coordination, action, and interaction. AI is also concerned with the engineering of systems that exhibit intelligence. Machine learning is concerned with the scientific study, exploration, design, analysis, and applications of algorithms that learn concepts, predictive models, behaviors, action policies, etc. from observation, inference, and experimentation and the characterization of the precise conditions under which classes of concepts and behaviors are learnable. Learning algorithms can also be used to model aspects of human and animal learning. Machine learning integrates and builds on advances in algorithms and data structures, statistical inference, information theory, signal processing as well as insights drawn from neural, behavioral, and cognitive sciences. Data mining is concerned with the applications of statistical machine learning for exploratory analysis and predictive modeling from large data sets. Causal discovery is concerned with algorithms for eliciting the underlying causal (as opposed to the merely predictive) relationships from observational and experimental data.

2. Why did you select PhD in Information Technology? Why did you select University of the Cumberlands?

Information Technology (IT) allows me to take my career in number of different directions. To Become a computer network architect, a computer programmer, a computer systems analyst, a database administrator, an information security analyst, an information architect, a web developer and data scientist so much more. University of the Cumberland’s even offers specializations in Data science and Information Systems Security, Network Administration and Management.

3. As an individual, what are your strengths and weaknesses and how will they impact you as a PhD IT student?

I’m naturally shy. From high school and into my early professional interactions, it prevented me from speaking up. After being a part of a workgroup that didn’t meet our strategic goals two quarters in a row, I knew I owed it to my team and myself to confidently share my ideas. I joined an improv acting class—it’s fun and has really helped me overcome my shyness. I learned practical skills around leading discussions and sharing diverse perspectives. Now, in group settings, I always start conversations with the quieter folks. I know exactly how they feel, and people can be amazing once they start talking.”

4. Where do you see the future of Information Technology going and where do you see yourself in this mix after obtaining PhD in Information Technology from UC? 

The Future of Information Technology is Artificial Intelligence and machine learning.

The biggest challenge to IT in the future is security. Security could negatively impact connectivity to public networks. If these problems cannot be successfully addressed, I envision a time of closed, private networks and less information sharing. The risks now are so great and getting worse every day that we even see foreign governments toppling superpowers the way Russia toppled the US and put its puppet in charge because of weak controls and poor security.