Information Sciences
Information Sciences involves collecting, storing, retrieving, and analyzing the flow of information to improve efficiency. Research areas include: Computation over networks, human/animal decision making and perception, information theory, inverse problems, machine learning, medical imaging, signal and image processing, synthetic aperture radar imagery, video analytics, anomaly detection
CISE Faculty Recognized for Groundbreaking AI Research with AIRR Awards
Recognized for their cutting-edge research in artificial intelligence, 11 CISE faculty affiliates have been honored with AI Research Resource (AIRR) awards. This Hariri Institute program supports AI research at Boston University by giving researchers access to the New England Research Cloud (NERC), a regional computing infrastructure that provides cloud-based resources tailored to academic research. A […]
CISE Hosts 11th Annual Graduate Student Workshop (CGSW 11.0)
Over 100 student and faculty attendees gathered on January 24th, 2025, for the 11th Annual Graduate Student Workshop hosted by the Center of Information and Systems Engineering (CISE). The day-long symposium featured doctoral students from different disciplines across Boston University’s College of Engineering presenting their original research. “CGSW aims to bring together CISE students, faculty, […]
Collaborative Research: CAIG: A Large Foundational Model for Earthquake Understanding
Earthquakes are powerful and unpredictable forces of nature, capable of causing immense destruction and loss of life. Despite advances in understanding the Earth’s movements, predicting earthquakes remains a challenge. This project aims to revolutionize the field of earthquake science by using artificial intelligence (AI) to unravel the mysteries hidden within seismic data ? the vibrations […]
Innovative Energy Efficiency: Fisheye Cameras in Smart Spaces
Imagine a bustling corporate office building where energy consumption needs to be balanced with maintaining a comfortable environment for employees. In such settings, traditional methods of regulating air handling systems can lead to inefficiencies and waste energy in unoccupied areas. This is where the research of Boston University Professors and CISE affiliates Thomas Little, Janusz […]
Collaborative Research: Interferers in our midst
In the data-driven world that we live in, sharing digital information is a key component underpinning a vast body of technologies. Low-latency, high fidelity access to information is central to algorithms that impact how we work, are entertained, how we travel, and our healthcare. Systems that, in particular, rely on wireless communication to deliver their […]
The Future of Driving: Control Barrier Functions and the Internet of Vehicles
The National Highway Traffic and Safety Association reports that 94% of serious car crashes are due to human error. Christos Cassandras, Boston University Distinguished Professor of Electrical & Computer Engineering, Head of the Division of Systems Engineering, and a co-founder of the Center for Information & Systems Engineering (CISE), has made monumental contributions to the […]
Collaborative Research: IMR: MM-1C: Methods for Active Measurement of the Domain Name System
This project will investigate techniques for measuring the contents of the Domain Name System (DNS) toward the goal of producing a comprehensive census of all record types. The project will focus on developing methods for generating domain names that will be used in queries of the global DNS. Strategies for name generation that will be […]
Faculty across five BU research centers will work together to prevent future pandemics
A multidisciplinary team of researchers at Boston University will work towards predicting and preventing future pandemics as part of a new $1 million project funded by the National Science Foundation (NSF). Faculty members from the Rafik B. Hariri Institute for Computing and Computational Science & Engineering, the Center for Information & Systems Engineering (CISE), the […]
PIPP Phase I: Predicting and Preventing Epidemic to Pandemic Transitions
The COVID-19 pandemic and its effects, both in terms of the millions of lives lost and the trillions in estimated costs, are a recent example of the devastation pandemics can cause. Any discernible progress in the prediction, early detection, and rapid response would have significant impacts on human welfare. The overarching goal of this project […]
Could a Computer Diagnose Alzheimer’s Disease and Dementia?
It takes a lot of time—and money—to diagnose Alzheimer’s disease. After running lengthy in-person neuropsychological exams, clinicians have to transcribe, review, and analyze every response in detail. But researchers at Boston University have developed a new tool that could automate the process and eventually allow it to move online. Their machine learning–powered computational model can […]