Exploring the Evolving Partnership Between Humans and Artificial Intelligence
Inaugural Stevens Institute of Technology AI Research Summer (AIRS) Fellowship Program empowers students to advance innovative research
Stevens Institute for Artificial Intelligence
Combating Bias with a Human-Centered Approach to Artificial Intelligence
Stevens Institute of Artificial Intelligence director says the key to addressing algorithmic bias is prioritizing awareness, education and integrity — both in data and in humans.
Faking Videos is Easy, Deep Nostalgia Shows
Deep Nostalgia is a new program that allows you to animate old photos. The technology shows just how easy it is to create videos of people doing things they actually haven’t done in real life.
The Stevens Institute for Artificial Intelligence (SIAI) is an interdisciplinary, tech-driven collaboration of engineering, business, systems and design experts working toward solving pressing global problems in industry and the world.
Stevens Institute for Artificial Intelligence is composed of more than 65 faculty members from all academic units at Stevens (engineering, business, systems and arts & music) researching a variety of applications in AI and machine learning. SIAI hopes to amplify the impact of its research and analysis through collaborations with industry, government, foundations and academic partners.
Vision
Artificial intelligence is transforming the world and industry as we know it, and the future of AI remains seemingly limitless. In a world where AI-enabled innovation continues to rapidly evolve, SIAI and its Stevens collaborators will synergistically develop solutions to real-world problems.
Founded on that premise, the SIAI envisions the exploration of opportunities to advance AI and machine learning to serve humanity and to improve disciplines such as healthcare, business operations, the workplace and education.
This vision will flourish through the convergence of faculty research, the positive impact of partner organizations and agencies, foundational research sponsors like the National Science Foundation, National Institutes for Health and the Department of Defense; and the deployment of AI and machine learning solutions for business advantage, social good, and national security.
Experience and Expertise
Cross-disciplinary collaboration among faculty and research experts from Stevens’ Schaefer School of Engineering and Science, School of Business, School of Systems and Enterprises and College of Arts and Letters gives SIAI a forward-thinking, holistic approach to exploring complex problems and creative new solutions that impact society while advancing the engineering and science of artificial intelligence and machine learning.
A History of Developing Impactful AI Applications
Our researchers continually develop AI and machine learning-powered innovations that address key challenges in healthcare, finance, cybersecurity, robotics, sustainability and other critical fields.
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Professors K.P. Subbalakshmi and R. Chandramouli have built an AI-fueled application that has demonstrated it can detect early-warning signs of Alzheimer's disease, dementia and aphasia by analyzing text and voice based communications.
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Stevens professor Negar Tavassolian develops new ways of imaging the surface of the skin and sensing our heartbeats, then processes those signals with new algorithms curated to intelligently detect skin cancer tumors and irregular heartbeats.
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Dr. Giuseppe Ateniese's team has developed a powerful password cracker by using the power of GANs to learn commonly used password patterns. It's promising for its applications to law enforcement in cracking terrorist communications and other uses.
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Professor German Creamer has introduced boosting as a proper method to combine and select financial indicators and generate algorithmic trading rules-including social network indicators-to forecast asset price trends.
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Professor Samantha Kleinberg uses machine learning to analyze sensor data from stroke patients in medical centers, research that will better inform stroke diagnosis and treatment.
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Professor Brendan Englot, a robotics expert, uses machine learning to teach remotely operated underwater vehicles (ROVs) to build better maps in real time as they navigate in murky, changing conditions inspecting bridges, piers, pipes and ships.
SIAI News
