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Registration Link: https://forms.office.com/Pages/ResponsePage.aspx?id=RlcpEyVylUyUF5RnGheJ-Jl31AMLM_9Im2OfkToGRUdUQzhKSFRUOE5VR1ZPT0pDMUVSOVYySjlFNC4u
Questions: itsapara@nu.edu
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, airspace, 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: |
Saturday, June 21st |
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Time: |
10:00 – 3:30 PM PST |
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Facilitators: |
Irene Tsapara / Daniel Johnston |
| Program: | https://resources.nu.edu/ld.php?content_id=81265416 |
Presentations - Schedule
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 (Alumni)
11:40 AM: Multimodal LLM and Smartphones for BP Monitoring –
Dr. Mohammad Yavarimanesh (Faculty)
12:05 PM: Bayesian Network Model for Predicting Gout Attacks –
Dr. Seyedmohsen Hosseini (Faculty)
12:30 PM: URLAgent: Reasoning and Acting in LLMs –
Dr. Mohammed Nabeel (Faculty)
12:55 PM: Kernel Landmarks: An Empirical Statistical Approach to Detect Covariate Shift
Dr. Yuksel Karahan (Faculty)
1:20 PM: Accelerating Legacy Code Migration with Artificial Intelligence
Dr. Amir Schur (Faculty)
1:45 PM: Quantum Computing: A New Computational Paradigm
Dr. Alexander Watt (Faculty)
Student Presentations
2:10 PM: Integrating QAOA with Deep Learning to Detect Protein Folding Disruptions in Liver Cancer Patients
Dr. Mousumi Chakrabarty (Ph.D. Candidate)
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 (Faculty)
3:20 PM: Smart Insights with Tableau –
Dr. Jenny Du (Faculty)
** All times are in Pacific Time Zone
Participants:
