I am a Ph.D. candidate in Information Science with a concentration in Data Science. I can also say that I am the recipient of both the UNT Golden Eagle and Outstanding academic achievement awards of 2021. I work as a teaching fellow for a graduate-level course, Information retrieval Systems, in the Department of Information Science. I received the Dewey E. Carroll Graduate Fellowship and The Mark E. Rorvig Endowed Graduate Fellowship.
My Ph.D. journey started with Physics, my primary major for Bachelor's and Masters' degrees. Successfully passing my first semester in the UNT physics department, I decided to make a challenging and exciting change to better peruse my expectations and needs toward my academic life dreams. I wanted to choose a multidisciplinary field that could allow me to cross the borders between different disciplines and investigate their connectivity while solving information problems. Being encouraged by my academic advisor at that time, Dr. Zavallina, I was confident that Information science with a concentration in Data Science was the most suitable choice.
During the two first years of my new journey, my job responsibilities, research, and course works were beyond expectations. My curiosity to explore Information Science theories and principles led me to explore research areas that can solve information-related issues using statistical physics. Thus, I did some preliminary studies with professor O'Connor about the idea of modeling browsing in library science using the concept of a complex temporal system borrowed from statistical physics. The result turns out to be my first presentation in the IS field, the ICKM 2018 conference.
As data science was still in its primary stages in the department of Information Science and worldwide, I needed to explore this field through coherence research to gain a deep understanding of its criteria and applications. Thus, in a class project with Dr. Suliman Hawamdeh, I explored gaps between Data Science jobs and Graduate Programs in the US. The class project continued as I was working as a GSA for the department. The outcome of that then became a paper presentation at the ALICE conference 2019.
In summer 2019, I had the opportunity to work as an RA for an REU program under Dr. Ding, Dr. Chen, and Dr. Palmer's supervision. An NSF grant supported the project, and it was mainly involved with Information Retrieval and Data Analysis. The outcome was highly significant to me as I gained a lot of experience in leading student projects and technical skills such as machine learning and data mining. In the next step, I took advanced computer science courses to develop those skills better. I ended up taking Natural Language Processing, Machine learning, and a Special Problem with Dr. Ting Xiao. This extreme interest in Data Mining and machine learning resulted in a paper published in the Knowledge-based system journal, one of the most prestigious journals in AI.
After a lot of hardworking and exploration, I became more confident in the field and started making connections with other researchers to share knowledge and learn more. I assisted a Ph.D. candidate, Tara Zimmerman, in her projects' analysis and results and then her dissertation. This great collaboration added another Conference presentation as the second author, iConference 2020, to my accomplishments. Tara and I could also present our research in the IS brown bag in Fall 2019.
Currently, I am working on my dissertation project, which is pre-training deep neural networks using efficient coding. In this regard, I have had various accomplishments so far. For example, I had a presentation at the ACM-TAPIA conference in 2020, one of the well-known computing conference venues. Good to mention that I was honored to receive the NSF scholarship for attending this conference. Also, our paper got accepted for publication in the AI Review, a Q1 journal with an impact factor of 8. In that study, we have made an accessible Jupyter notebook for applying efficient coding to various datasets, from natural and non-natural images to sounds and video.
In collaboration with Professors Mark Albert, Michele Spector, and Lin Lin, I am honored to write a book chapter, Understanding machine learning through data-oriented concepts. The book is entitled Bridging Human and Artificial Intelligence, and it will be showcased in Sep 2021 during the Tapia Conference.