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Welcome to the National University Data Science Ph.D Program. Our program equips students with practical analytics, machine learning, and AI skills to solve real-world problems and make data-driven decisions. With hands-on training and a flexible online structure, students gain experience in critical areas like data engineering and predictive modeling. We prepare graduates to apply data science across industries and drive innovation in a data-centric world.
Welcome to the National University Data Science Ph.D Program. Our program equips students with practical analytics, machine learning, and AI skills to solve real-world problems and make data-driven decisions. With hands-on training and a flexible online structure, students gain experience in critical areas like data engineering and predictive modeling. We prepare graduates to apply data science across industries and drive innovation in a data-centric world.
We operate under the Department of Engineering, Computer Science, and Data Science and we belong to the CoBET—College of Business, Engineering, and Technology.
If you have questions, contact the Academic Program Director or our School email, SOTE Administration. Please do not hesitate to ask questions, express your concerns, or give suggestions.
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For updates, lectures, discussions, and announcements. Please ensure that you are registered, set up your notifications, and your profile.
Join us every Thursday at 4 PM PST at our Community meetings. |
Welcome aboard, and let’s make an impact together.
Sincerely,
Irene Tsapara, PhD
Academic Program Director - PhD Data Science Program
Professor Data Science
College of Business, Engineering, and Technology
School of Technology & Engineering
National University | www.nu.edu
ITsapara@nu.edu
Office hours: Friday 9:00 AM – 11:00 AM PST (First come first served)
Schedule an appointment: Appointments
Welcome to the EDSCS Symposium on Data Science and Artificial Intelligence. We are honored to bring together a diverse group of presenters—professors, researchers, and students—who are actively shaping the future of intelligent systems, data-driven innovation, and interdisciplinary inquiry.
This symposium celebrates the breadth and depth of work taking place within our department, showcasing original research, applied projects, and exploratory ideas at the intersection of statistics, machine learning, computational theory, and domain-specific problem solving. From theoretical advancements to practical applications in fields such as healthcare, cybersecurity, sustainability, and education, today's presentations reflect both academic rigor and real-world relevance.
Our goal is to foster dialogue, spark collaboration, and highlight the exceptional talent emerging from our academic community. Whether you are here to share your work, support your peers, or discover new directions in the evolving landscape of Data Science and AI, we thank you for your participation and look forward to a day of meaningful exchange and inspiration.
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Location: |
Zoom Webinar Link: https://nu.zoom.us/s/91835063659 |
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Date: |
June 21st, 2025 |
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Time: |
10:00 – 3:30 PM PST |
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Facilitators: |
Irene Tsapara/Daniel Johnston |
Welcome and Opening Remarks
10:00 AM: Opening Remarks and Welcome
Presentations
10:05 AM: Educating with AI: New Frontiers in Learning
Mark Otis, Ms.
10:30 AM: Open-Source LLMOps and MLOps Platform on Kubernetes
Nate Lebel, Ms. (Ph.D. Candidate)
11:05 AM: Digital Twin Representation of Foliage –
Dr. Hashim Shaik
11:40 AM: Multimodal LLM and Smartphones for BP Monitoring –
Dr. Mohammad Yavarimanesh
12:05 PM: Bayesian Network Model for Predicting Gout Attacks –
Dr. Seyedmohsen Hosseini
12:30 PM: URLAgent: Reasoning and Acting in LLMs –
Dr. Mohammed Nabeel
12:55 PM: Kernel Landmarks: An Empirical Statistical Approach to Detect Covariate Shift
Dr. Yuksel Karahan
1:20 PM: Accelerating Legacy Code Migration with Artificial Intelligence
Dr. Amir Schur
1:45 PM: Quantum Computing: A New Computational Paradigm
Dr. Alexander Watt
Student Presentations
2:10 PM: Integrating QAOA with Deep Learning to Detect Protein Folding Disruptions in Liver Cancer Patients
Dr. Mousumi Chakrabarty
2:25 PM: Transformer-Based Prediction of Emerging Research Themes
Viktoria Popova, Ms. (Ph.D. Candidate)
2:40 PM: Entity Resolution Approaches for Aircraft Type Matching
Karna Bryan, Ms. (Ph.D. Candidate)
Tutorials
2:55 PM: GitHub Tutorial –
Dr. Amir Schur
3:20 PM: Smart Insights with Tableau –
Dr. Jenny Du
** All times are in Pacific Time Zone
Participants:
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