Dr. Margaret Anne Schedel

Biography:

Forging vital connections between classical music, audio data research, and innovative computational arts education Dr. Margaret Anne Schedel cultivates new possibilities at the boundaries where disciplines meet. Her diverse creative output includes multimedia operas, virtual reality experiences, sound art, video game scores, compositions for classical instruments with interactive electronics, and the development of custom interactive controllers. Honored with NIME’s Pamela Z Innovation Award, Schedel is set to release her solo CD, "Signal through the Flames," in 2025. 

Her fascination with data sonification caught NPR's Science Friday's attention, where she showed how sound can unveil hidden patterns in everything from nanomaterials to the movement of people with Parkinson's Disease. This same innovative spirit led her to co-found Lyrai, where she's using AI to capture the acoustic essence of architectural spaces. She is a Professor of Music and core faculty of the Institute of Advanced Computational Science at Stony Brook University, and formerly served as the Chair of Art. Her research ventures into unexpected territory, from the meeting point of Hip-hop and electroacoustic music to the challenge of making technological art sustainable. As co-author of "Electronic Music" (Cambridge University Press) and regional editor of "Organised Sound," she helps shape conversations about the future of music while nurturing the next generation of creators. 

Laura Lindenfeld, PhD

Biography:

Laura Lindenfeld, PhD, is the Executive Director of the Alda Center, Dean of the School of Communication and Journalism, Vice Provost for Academic Strategy and Planning, and a professor of journalism. She holds a PhD in cultural studies from the University of California, Davis.

As the Alda Center director, she oversees a dynamic organization that has trained 15,000 scientists from around the world. The Center provides international leadership in conducting and connecting research and practice to advance effective science communication. As dean of the School of Communication and Journalism, she oversees a team of dedicated faculty and staff, including Pulitzer Prize winners, to educate and train the next generation of multimedia journalists and communication professionals.

Vivian Zhang

Biography:

Vivian Zhang is the Chief Technology Officer and School Director of NYC Data Science Academy and Chief Technology Officer of SupStat. With her extensive experience working in the data science field, she developed expertise in multiple programming languages, including R, Python, Hadoop, and Spark. Her tenure has been marked by pioneering applications of AI across various sectors, including healthcare, finance, and education. In 2013, she created the NYC Open Data Meetup group, which stands as one of the largest data science communities offering meetups, conferences, and a weekly newsletter.

She has launched several AI companies, including GoDental.AI and Intrinsica.AI, which leverage advanced machine learning techniques to transform industry practices.

In August 2016, Forbes ranked her amongst one of the nine women leading the pack in data analytics.

Steven Skiena, PhD

Biography:

Steven Skiena, PhD is Distinguished Teaching Professor of Computer Science and Interim Director of the AI Innovation Institute at Stony Brook University.  His research interests include data science, bioinformatics, and algorithms.  He is the author of six books, including "The Algorithm Design Manual",   "The Data Science Design Manual", and "Who's Bigger: Where Historical Figures Really Rank", and over 200 technical papers. 

Skiena received his B.S. in Computer Science from the University of Virginia and his Ph.D. in Computer Science from the University of Illinois under Herbert Edelsbrunner in 1988.   He is a Fellow of the American Association for the Advancement of Science (AAAS), a current and former Fulbright scholar, and recipient of the University of Virginia Engineering Distinguished Alumni Award (WahooWa!), the ONR Young Investigator Award and the IEEE Computer Science and Engineer Teaching Award.   His paper on the DeepWalk approach to graph representation learning received the ten year Test of Time Award at KDD 2024.