Part ten of our AI Researcher Profile series invites Professor Dimitris Samaras, SUNY Empire Innovation Professor and Director of the Computer Vision Lab at the Department of Computer Science, Stony Brook University, to discuss his research interests and knowledge surrounding human behavior and its role in artificial intelligence.
Conversational AI has come a long way from the basic chatbots that provided scripted responses, only to cause inconvenience and later connect you with a live agent. Today, the technology has evolved tremendously, owing to the advent of neural networks, the transformer model, and OpenAI’s GPT-4. These complex systems, which have found significant usage across several industries, including education, healthcare, finance, and voice assistant technologies, among others, are becoming increasingly helpful in everyday life.
Misinformation can harm people’s health as they find and act on information designed to trick and mislead them online. Worse still, misinformation generated by artificial intelligence (AI) is becoming more prevalent and harder to detect, exacerbating the negative effects of human-generated misinformation.
And racial groups whose health is already vulnerable, including Black and Hispanic populations, are most likely to be harmed as AI-generated misinformation is created particularly to engage — and mislead — them.
All of this seems clear from a growing body of research. What is less clear is what can be done about it.
Stony Brook researchers collaborated with academic centers and AI labs from around the world to advance machine learning, robotics, and computer vision. Their upcoming research is being presented at the 37th edition of the Conference on Neural Information Processing Systems, or NeurIPS—the most cited AI conference in the world.
The conference, which is being held in New Orleans from Sunday, Dec 10 through Saturday, Dec 16, is a multi-track interdisciplinary annual meeting including invited talks, demonstrations, symposia, and oral and poster presentations of refereed papers, creating space for a less formal setting for the exchange of ideas.
Cerebral Blood Flow (CBF), which is crucial for maintaining energy supply to support synaptic activity, is known to be a strong indicator of brain function. Therefore, CBF, along with other factors, is used to link blood oxygenation signals to cellular activity in the brain.
This year’s International Conference on Computer Vision (ICCV) showcased several SBU’s AI researchers, sharing their notable milestones in the field of Computer Vision. Their contributions to a variety of fields—including robotics, machine learning, and augmented reality, among others—were presented at the premier international computer vision conference, which is regarded as one of the top conferences in computer vision, alongside CVPR and ECCV.
The annual conference, which was held in Paris between October 2nd and 6th, comprises the main conference along with several co-located workshops and tutorials. Researchers from around the world are invited to present their findings.
Some of SBU’s notable contributions include:
What goes through screenwriters’ minds when they’re paging through a novel? Do they care more about the time limits of the film they want to make, or do they focus on capturing the content and the spirit of the story? What about dialogue, or narration? The relationship between a novel and its film adaptation has repeatedly been a subject of interest within the research community. As AI experts continue to analyze and help improve the screenwriting process, demand for generative applications like ChatGPT that can help automate creative tasks is on the rise.
Empirical Methods in Natural Language Processing, or EMNLP, is a leading conference in the fields of Artificial Intelligence and Natural Language Processing. Organized by the ACL Special Interest Group on Linguistic Data (SIGDAT) and started in 1996, EMNLP was recently recognized as the 2nd most mentioned in Natural Language Processing.