Wednesday May 20, 2026
13th Annual NJBDA Symposium

Building Accessible & Sustainable AI Ecosystems:
People, Data, Ethics, & Infrastructure

Host: Rowan University

201 Mullica Hill Rd, Glassboro, NJ 08028

The New Jersey Big Data Alliance Symposium is a collaborative forum for information sharing, networking, research, and discovery of the importance of a sustainable AI ecosystem. This dynamic event will delve into strategies and considerations for creating a long-term, balanced AI environment that aligns human, technological, and ethical dimensions.

Achieving this goal requires collaboration among academia, government, and industry to ensure that AI innovation remains inclusive, responsible, and environmentally conscious. Outstanding keynote speakers, industry and academia expert panels, research workshops and more will offer innovative and insightful information!

Don’t miss this opportunity to connect, learn, and lead the charge in building a future where balanced and sustainable AI ecosystems can contribute to remarkable success for all!

Keynote Speakers

Dr. Khalifeh Al Jadda

Director of Data Science, Google and Co-Founder & VP at ATLytiCS

Dr. Khalifeh Al Jadda

Khalifeh AlJadda holds a Ph.D. in computer science from the University of Georgia (UGA), with a specialization in machine learning. He has experience implementing large scale, distributed machine learning algorithms to solve challenging problems in domains ranging from Bioinformatics to search and recommendation engines. He is the lead data scientist on the search data science team at CareerBuilder, which is one of the largest job boards in the world. He leads the data science effort to design and implement the backend of CareerBuilder’s language-agnostic semantic search engine leveraging Apache Spark and the Hadoop ecosystem. He is also the founder and chairman of the Data Science Council at CareerBuilder, which organizes events and hosts prominent speakers to promote data science in the Atlanta community.

Dr. Jeannette M. Wing

Executive Vice President for Research & Professor of Computer Science at Columbia University

Dr. Jeannette M. Wing

Jeannette M. Wing is the Executive Vice President for Research and Professor of Computer Science at Columbia University. She joined Columbia in 2017 as the inaugural Avanessians Director of the Data Science Institute. From 2013 to 2017, she was a Corporate Vice President of Microsoft Research. She is an Adjunct Professor of Computer Science at Carnegie Mellon where she twice served as the Head of the Computer Science Department and had been on the faculty since 1985. From 2007-2010 she was the Assistant Director of the Computer and Information Science and Engineering Directorate at the National Science Foundation. She received her S.B., S.M., and Ph.D. degrees in Computer Science, all from the Massachusetts Institute of Technology. She holds an honorary doctorate of technology from Linkoping University, Sweden. Professor Wing’s current research focus is on trustworthy AI.

Event highlights

• Academic research sessions with presentations
• Industry panel on AI impacts across sectors
• Hands-on student workshop
• Workforce development panel on advanced technologies
• Poster presentations
• Networking
• Exhibit opportunities

Strategic themes

• People: Invest in human capital. Build AI literacy, retrain existing workers, and create diverse talent pipelines.
• Data: Promote access to quality, representative, and responsibly governed data. Further provide frameworks that govern secure access to data and the supporting systems and networks.
• Ethics: Integrate fairness, transparency, and accountability into every stage of AI design and deployment.
• Infrastructure: Build equitable and energy-efficient computing and connectivity resources that enable broad participation.
• Sustainability: Balance environmental and social responsibility with technological progress.

Expected outcomes

• Cross-sector partnerships linking education, research, and commercialization.
• Ethical and environmental standards embedded into AI lifecycle design.
• Shared data and compute infrastructure accessible to researchers and communities.
• A model for continuous, responsible AI development that benefits both industry and society.

Call for Research Proposals

We invite researchers from academia, industry & government to submit extended abstracts or full papers for presentation at the symposium. This is a great opportunity to share your latest work, engage with peers, and contribute to the growing community of AI research.