Please join me in congratulating our outstanding students for their achievements at the recent research symposium:
Hashim Shaik received the Poster Award for his exceptional study: 
A Study on Creating Digital Twin Foliage Representation Through Computer Vision, Aerial Image Analysis, and Machine Learning techniques to enhance the Network Planning and Deployment
Jovelyn De Quiton earned an Honorable Mention for her poster on:
Machine Learning Methods in Ankle Arthrodesis.
Alexander Watt was recognized with the COBET President's Award for his work on:
Interdisciplinary Approaches to Pulmonary Diagnostic Imaging: The Role of Quantum Computation and Three-Dimensional Convolutional Neural Networks in Assessing Lung Damage.

These awards reflect the rigor, innovation, and excellence our students continue to demonstrate in their research. 
We extend our deepest thanks to their dedicated mentors—Dr. Yavarimanesh, Dr. Schur, Dr. Fulton, and Dr. Nabeel, 
whose guidance and commitment were instrumental in helping the students reach this level of accomplishment.
Congratulations again to all!

To all our graduating students—congratulations on reaching this incredible milestone. Your perseverance, intellectual curiosity, and commitment to excellence have brought you to this moment, and we could not be prouder. Whether heading into research, industry, entrepreneurship, or continued academic pursuits, you carry the skills, knowledge, and resilience to lead and innovate. As you move forward, remember that you are always part of our academic community.
We look forward to seeing the impact you will make in the world.

Warm regards,
Dr. Tsapara

Data Scientists Group – National University
Our LinkedIn group is for current students, alumni, faculty, and collaborators of the Data Science programs at National University. This group serves as a hub for sharing knowledge, networking, and advancing professional development in data science, artificial intelligence, machine learning, and analytics.
Whether you're exploring innovative applications of data science, seeking career opportunities, or looking to connect with peers and mentors, this is the space to collaborate, exchange ideas, and grow together.
🔹 Engage with fellow data scientists across academia and industry
🔹 Share research, projects, job postings, and events
🔹 Discuss emerging tools, trends, and challenges in the field
🔹 Build a strong, supportive professional community
Join us as we transform data into insight—and insight into impact.

Register here: https://www.linkedin.com/groups/14664134/

If you would like to review and listen to any of the Past TILOS seminar talks or workshops, please visit:

https://tilos.ai/recorded-talks/

Recordings of past TILOS Seminars and other presentations are available at tilos.ai/recorded_talks.
Subscribe to our YouTube channel for updates.

Mini-Symposium on Data Science and AI

Registration Link: https://forms.office.com/Pages/ResponsePage.aspx?id=RlcpEyVylUyUF5RnGheJ-Jl31AMLM_9Im2OfkToGRUdUQzhKSFRUOE5VR1ZPT0pDMUVSOVYySjlFNC4u

Questions: itsapara@nu.edu

Mini Symposium on DSAI

The Zoom Webinar Link and the Schedule for both talks and Workshops will be posted here after June 15th. 

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.

Information for Presenters and Participants

Presenters:

• Deadline for Presenting: June 10th

• Please register to present at: https://forms.office.com/Pages/DesignPageV2.aspx?prevorigin=shell&origin=NeoPortalPage&subpage=design&id=RlcpEyVylUyUF5RnGheJ-Jl31AMLM_9Im2OfkToGRUdUQU1JVUxYVDhCNUxVTTBZVzUwSDJZWE5DWi4u

• Questions: Please email us at itsapara@nu.edu for any questions or concerns you may have.

Participants:

• Please Register at: https://forms.office.com/Pages/DesignPageV2.aspx?prevorigin=shell&origin=NeoPortalPage&subpage=design&id=RlcpEyVylUyUF5RnGheJ-Jl31AMLM_9Im2OfkToGRUdUQzhKSFRUOE5VR1ZPT0pDMUVSOVYySjlFNC4u

TILOS Industry Day 2025

( For more information, visit the TILOS Institute HomePage)

Our 4th Annual Industry Day will be June 2, 2025, at the Halıcıoğlu Data Science Institute at UC San Diego, the campus hub for data science. This year TILOS Industry Day will feature:

• Talks from invited industry speakers sharing their perspectives on challenges in AI + Optimization + Use Domains (chips, robotics, networking)
• Research highlights from TILOS team members
• Panel discussions on AI Challenges for Academia—An Industry Perspective and Building Deep Tech Companies
• Poster session featuring the work of TILOS trainees (students and postdoctoral scholars)

Date & Time

Monday, June 2, 2025
8:00 am - 7:30 pm PST

Registration

Registration is complementary but required as space is limited. Register HERE by Wednesday, May 28, 2025.

Venue

Halıcıoğlu Data Science Institute Room 123
University of California, San Diego
3234 Matthews Lane
La Jolla, CA 92093

Nate Lebel will be presenting  at ODSC East Conference on May 15th

For more information visit: ODSC East on May 15th.

Nate Lebel is a strategic leader in data-driven transformation with over 24 years of experience in transforming organizations through solution architecture, enterprise data strategy, and MLOps. 

His talk is on: 

Abstract:

In the rapidly evolving landscape of artificial intelligence (AI), effective operations management for machine learning (ML) and large language models (LLMs) is critical. While new models and methods improve LLMs and agentic systems, few platform-agnostic tools exist for unified system evaluation. We integrate our tools with widely used cloud services and choose open-source tools for portability. We offer a complete open-source LLMOps and MLOps platform for efficient Kubernetes deployment, streamlining AI workflow integration and management at scale.

Our platform promotes accelerated innovation by enabling faster experimentation and iteration cycles. Through enhanced productivity, teams can automate and streamline their end-to-end ML lifecycle processes, from data ingestion to model deployment. With improved decision-making facilitated by robust model monitoring and evaluation tools, stakeholders can gain deeper insights and make more informed choices. Additionally, our open-source approach opens up new opportunities for collaboration and customization, allowing organizations to tailor solutions to their unique needs.

Central to our modular architecture is an intuitive user interface that ushers users through the entire end-to-end MLOps cycle. Our platform integrates tools for AI asset discovery, registration, validation, evaluation, monitoring, and assessment to facilitate centralized ML management. Behind this UI is our platform-agnostic Kubernetes environment, allowing users to easily manage new datasets with LakeFS, run dataset and model validation pipelines with Kubeflow, and collect training and deployment metrics with MLFlow. To cover staging and deployment, our monitoring tools, coupled with KServe’s inference server and the Kubeflow training operator, complete a centralized end-to-end ML development and deployment ecosystem.

Attendees will learn the ease with which AI centralization can be achieved via the discovery and registration of datasets and models as they deploy this distribution via our GitHub repository. We’ll dive into our data and model monitoring ecosystems. Attendees will get experience with our data provenance tools like LakeFS and transparency-enhancing monitoring tools such as MLFlow and AIM. Join us if you are interested in using open-source technologies to build a strong, cost-effective MLOps and LLMOps infrastructure.