About Me

I am currently a Ph.D. student at Florida Atlantic University, member of the CA-AI group. I am advised by Professor Georgios Sklivanitis .


  • B.S. in Computer Science with a minor in Mathematics, Winthrop Univeristy, Department of Computer Science and Quantitative Methods, Rock Hill, SC, United States.
    • Selected by the faculty as the top graduate from the program.
  • Ph.D. in Computer Science, Florida Atlantic University, Department of CEECS, Boca Raton, FL, United States. (2021 - present)
Curriculum Vitae

Curriculum Vitae (CV)


  • Undergraduate Researcher at Cornell University
  • Utilizing Machine Learning (ML) and Natural Language Processing (NLP) techniques we develop a fact-checking tool that will assist authors and reviewers of scientific papers to identify inconsistencies and potential errors. To train our model we are creating multiple datasets depending on what type of errors we aim to capture using scientific papers from multiple and diverse disciplines. Finally, we are using the task specific dataset to fine-tune the state of the art for NLP tasks model (BERT).

  • Undergraduate Researcher at North Carolina State University
  • Development of an inovative approach for Effective Public Outreach for Transportation Projects Using Geospatial Analytics and Online Advertising.

    More Information for this project

  • The Cornell, Maryland, Max Planck Pre-doctoral Research School 2020
  • Outstanding undergraduate and Masters students are invited to learn about cutting-edge research in computer science, including databases and data analysis, distributed systems, security and privacy, Internet measurement and network architecture, large-scale machine learning, and theory of deep learning. Leading researchers will engage with attendees in their areas of expertise: the curriculum will include lectures and interaction with faculty from participating institutions.

Academic Interest

My undergraduate research experiences have fostered my passion for Machine Learning and Artificial Intelligence. I am excited and intrigued by those areas and the way they promise to transform our lives. I understand that there is a prevailing opinion that they will define the fourth industrial revolution, as revolutionary for humanity as the steam engine, electricity, and the Internet. I am very much looking forward to becoming part of this new revolution. I am also captivated by the content of the Machine Learning and Knowledge Extraction book presenting advances in the ML field by the 2019 IFIP Organization members. Issues such as the development of models to explore, compare and contrast the ways in which humans and machines explain, the study of the trade-off between predictive accuracy and interpretability, or the deployment of fact-checking in the development of physiological indicators for user trust in Machine Learning, are cutting-edge as much as feasible predictions for the years to come. I look forward to witnessing all the transformations that the new technologies and the new way of thinking promise us.