Thursday, May 5th, 2022

Complex Networks

Dima Fayyad

Applications of AI in the context of complex networks are ubiquitous in our world and throughout our daily lives. We see them in recommendation systems when our friends suggest a restaurant to visit and in fraud detection systems that flag anomalous financial transactions. 

They are prevalent in drug discovery systems when searching for a match in the 3D structure of proteins and epidemic modeling systems used to predict the spread of Covid-19. We even see them in the social networks we use for online dating or to make new friends.

Complex networks can model so many human-based processes that the applications of AI in practice are innumerable. The Institute for Experiential AI works with network scientists to develop predictive and descriptive models to help understand the phenomena associated with these types of networks.

Latest Research

Responsible AI

AI Ethics and Responsible AI aim for AI systems that benefit individuals, societies, and the environment. It encompasses all the ethical, legal, and technical aspects of developing and deploying beneficial AI technologies. It includes making sure your AI system does not cause harm, interfere with human agency, discriminate, or waste resources.  AI Ethics and Responsible […]

Natural Language Processing

  GFT (General Fine-Tuning) Recently, deep nets have demonstrated significant progress with exciting results. Much of this work has been reported in leading media outlets and academic conferences such as ACL and NeurIPS. We have developed a “little” language, GFT, that makes deep nets look like regression. GFT is approachable to a broad audience, and […]


At the Institute for Experiential AI, we care about people’s health and wellness. We have several core faculty members with AI health expertise who cover AI for healthcare from multiple scales and various heterogeneous data sources. They work closely with scientists, clinicians, and healthcare providers in designing and developing AI algorithms over a wide range […]

Life Sciences

We live in the Golden Age of Life Sciences, driven in part by transformative advances across multiple fronts in our understanding of biological systems and their applications.  However, we are still only at the beginning of this new chapter.  A systematic strategy that includes humans and AI/ML-based approaches can accelerate the “exponentialization” of this value […]

Climate, Sustainability, and Environment

From climate science and water sustainability to urban resilience and disaster preparedness, Artificial Intelligence has shown significant potential to inform and enable transformative action in the areas of climate, sustainability, and the environment. For example, machine learning, graph analytics, agent-based models, and human-AI systems have shown potential with predictive understanding in earth systems science and […]