Theory & Algorithms

Most CISE research projects include elements of theoretical analysis and algorithm development. These projects study the capabilities and fundamental limitations of algorithms to better understand the computational tools utilized in various research fields. Researchers apply this knowledge to machine learning, data structures, optimization, computational biology, cryptography,geometric modeling, and other fields. Theory and algorithms anticipates the growing quantity and power of data and works to use algorithms to their full capacity. Research areas include: designing efficient data structure and algorithms, understanding the complexity of computational problems, and designing secure cryptographic systems.

CNS Core: Small: Building Resilience into Blockchains

Blockchains and cryptocurrencies have emerged as disruptive technologies with profound financial and societal impact. This state of affairs makes it imperative to gain better understanding of the dynamics and resilience of the underlying peer-to-peer networks on which blockchains operate. To this end, this project researches novel measurement methodologies, statistical modeling, and design approaches for distributed […]

Stealth Driverless Cars without Visible Light?

CISE Faculty Affiliate Professor Vivek Goyal (ECE) recently received a Defense Advanced Research Projects Agency (DARPA) subaward for his work in connection with the agency’s Invisible Headlights program. Professor Goyal is working under an award to MIT entitled, Super Headlights: Superconducting Nanowire Detectors for Passive Infrared Sensing.  The DARPA Invisible Headlights program has a very […]

Cars that learn how to drive themselves by watching other cars

Self-driving cars are powered by machine learning algorithms that require vast amounts of driving data in order to function safely. But if self-driving cars could learn to drive in the same way that babies learn to walk—by watching and mimicking others around them—they would require far less compiled driving data. That idea is pushing Boston […]

Creating Safe, Energy-Efficient Buildings in a Post-Covid World

Smart building technology has been a growing trend in the commercial real estate sector to help building owners and other stakeholders automate processes, reduce costs, boost energy efficiency, and improve the comfort of tenants.  In a post-covid world, its adoption is expected to increase as safety amenities top the list of concerns of tenants planning […]

Ali Siahkamari Ties for First Place in the 2021 CISE Best Student Paper Award

Ali Siahkamari, Boston University PhD candidate (ECE), tied for first place in the 2021 CISE Best Student Paper Award Competition. His winning paper, entitled “Piecewise Linear Regression via a Difference of Convex Functions,” was published in Proceedings of the 37th International Conference on Machine Learning. This paper was co-authored with his advisor, CISE Faculty Affiliate, Associate Professor Brian […]

Francesco Orabona Wins NSF CAREER Award

CISE Faculty Affiliate, Assistant Professor Francesco Orabona (ECE, SE, CS) recently received a prestigious Faculty Early Career Development Program (CAREER) award from the National Science Foundation (NSF) for his work on new, more automated, machine learning algorithms. Machine learning has begun to take over our digital lives. It can be found in automatic text suggestions […]