Data Science, AI & Machine Learning
Data Science, artificial intelligence (AI) and machine learning involve making accurate predictions, data mining, machine learning, and more to guide business decisions. Research areas include: bio inspired control using data from animals, computational biology, computational imaging, cyber security, medical informatics, simulation, and video analytics.
Abraham Matta Wins NSF Grant for Application Software Project
CISE Faculty Affiliate Abraham Matta, Professor (CS, SE) and a Hariri Research Fellow received a grant from the Division of Computer and Network Systems, National Science Foundation for his proposal titled “CNS Core: Small: Collaborative Research: HEECMA: A Hybrid Elastic Edge-Cloud Application Management Architecture”. This project will examine how application software can be partitioned and deployed over different parts of […]
SCH: INT: Distributed Analytics for Enhancing Fertility in Families
The demands of modern life, education and career choices, as well as the availability of assisted reproductive technologies, are leading many individuals and couples to delay childbearing. This has contributed to infertility and sub-fertility emerging as significant public health problems in the U.S., affecting about 15% of couples, involving both men and women, and resulting […]
AF: Small: Collaborative Research: New Representations for Learning Algorithms and Secure Computation
Recent success of machine learning is due in part to the availability of large datasets for training and testing purposes. However, the training process is computationally intensive and collected datasets are often privacy sensitive. This has led to providing Machine Learning as a Service (MLaaS), where data providers store their data in the cloud and […]
Optimizing and Learning Strategies for Protein Docking
Protein docking is defined as predicting the three-dimensional structure of the docked complex based on knowledge of the structure of the components. Experimental techniques for this purpose are often expensive, time-consuming, and in some cases, not feasible; hence the need for computational docking methods. The problem of finding the docked conformation is generally formulated as […]
Neuro-Autonomy: Neuroscience-inspired Perception, Navigation, and Spatial Awareness for Autonomous Robots
State-of-the-art Autonomous Vehicles (AVs) are trained for specific, well-structured environments and, in general, would fail to operate in unstructured or novel settings. This project aims at developing next-generation AVs, capable of learning and on-the-fly adaptation to environmental novelty. These systems need to be orders of magnitude more energy efficient than current systems and able to pursue complex goals in […]
CISE Faculty Affiliate Venkatesh Saligrama (ECE) Appointed BU Data Science Faculty Fellow
The Data Science Faculty Fellows Program was created in 2017 by Provost Jean Morrison as a part of the BU Data Science Initiative, to help build on the University’s vision for research and education in this strategically important area. Candidates are selected through an evaluation of their current research portfolio, demonstrated contributions, a track record […]
Know What’s Good for Your Health? Artificial Intelligence
Every day, it becomes a little harder to find a corner of healthcare not being touched in some fundamental way by data analytics. That Fitbit on your wrist may soon send your resting heart rate to Google, where it would join the electronic health records of millions of others, and where algorithms could yield comprehensive […]
EAGER: SaTC: Early-Stage Interdisciplinary Collaboration: Multi-regulation computation
This interdisciplinary project investigates whether existing cryptographic techniques for analyzing siloed data comport with participants’ legal restrictions on data disclosure. Secure multi-party computation (MPC) is a technique from cryptography that allows several participants, each with sensitive information, to analyze their data collectively without ever sharing it. Several companies, governments, and non-profit organizations have adopted MPC […]
How to Make Self-Driving Vehicles Smarter, Bolder
With $7.5M DOD grant, BU researchers head international team developing bioinspired control systems for self-navigated vehicles Autonomous vehicles that can maneuver themselves around any city are already out on our public roads, says Yannis Paschalidis, but operating off-road remains a challenge. “These vehicles are designed for very structured environments, within roads and lanes,” says Paschalidis, a […]
BU-led Research Team Wins Competitive $7.5 million MURI Grant to Create Neuro-Autonomous Robots
By Maureen Stanton, CISE Dream Team of Engineers, Computer Scientists, and Neuroscientists from BU, MIT, and Australia to develop neuro-inspired capabilities for Land, Sea, and Air-based Autonomous Robots A Boston University-led research team was selected to receive a $7.5 million Multidisciplinary University Research Initiative (MURI) grant from the U.S. Department of Defense (DoD). With this […]