Computational Biology & Medicine
With the increasing availability of data and the improved understanding of system-level interactions in biological systems, computational methods have found many applications in biology and medicine. Research in CISE develops algorithms for long-standing problems in computational biology, such as predicting and characterizing protein interactions, optimizing metabolic networks, and developing computational neuroscience models. Another line of research develops computational methods to advance experimental observation techniques used in biology, from imaging methods to atomic force microscopy. A burgeoning area of research applies Artificial Intelligence (AI) methods to medical data, leading to disease/outcome prediction models and medical decision-making tools.
How Computational Imaging is Helping to Advance In-Vivo Studies of Brain Function
New BU-developed wearable device integrates miniature optics and computational algorithms to enable cortex-wide, cellular resolution imaging of the brain in freely moving animals The ability to study and learn about the brain hinges on what technology is available. Current wearable brain imaging technologies are limited by a small field of view. An interdisciplinary team at […]
Paschalidis Shares Health Data Findings in DeLisi Lecture
CISE Director Professor Yannis Paschalidis (ECE, SE, BME, CDS) discussed data-driven reasoning—which he calls “the backbone of engineering systems”—and predictive health analytics as he delivered the Charles DeLisi Distinguished Lecture May 6 to an online audience of about 100 members of the Boston University community. The DeLisi Award and Lecture honors a senior faculty member […]
Machine, Meet Stem Cells
Model organs grown from patients’ own cells may one day revolutionize how diseases are treated. A person’s cells, coaxed into heart, lung, liver, or kidney in the lab, could be used to better understand their disease or test whether drugs are likely to help them. But this future relies on scientists’ ability to form complex […]
Collaborative Research: A Workshop on Pre-emergence and the Predictions of Rare Events in Multiscale, Complex, Dynamical Systems
Although pandemics have threatened human civilization since ancient times, how to predict and prevent them remains one of the most pressing challenges, calling out for innovative insights and practices. Pandemics emerge through incidental ‘perfect storms’: molecular changes in pathogens, gradual trends in climate, subtle shifts in ecological interactions among potential hosts, and even individual behavioral […]
Advancing COVID-19 Drug Development via Network Analysis
CISE Faculty Affiliate Mark Crovella (Prof., CS, Bioinformatics) has teamed up with Simon Kasif (Prof., BME, CS, Bioinformatics) and other CS researchers from across the U.S. to advance COVID-19 drug development via Network Analysis. The researchers are co-developing a machine learning methodology to analyze viral and human protein-protein interaction networks. Through this work, the researchers […]
PLOS Computational Biology: Learning from Animals: How to Navigate Complex Terrains
PLOS Computational Biology issued a press announcement on a paper that it published today authored by Boston University CISE Director Yannis Paschalidis (Professor ECE, SE, BME), PhD candidate Henghui Zhu (SE), former CISE post-doctoral associate Armin Ataei, former CISE visiting student scholar Hao Liu (Zhejiang University), along with University of Washington collaborators Professor Thomas Daniel (BIO, […]
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 […]
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 […]
A Computational Miniature Mesoscope for Large-Scale Brain Mapping in Behaving Mice
Scale is a fundamental obstacle in linking neural activity to behavior. While perception and cognition arise from interactions between diverse brain areas separated by long distances, neural codes and computations are implemented at the scale of individual neurons. An integrative understanding of brain dynamics thus requires cellular-resolution measurements across sensory, motor, and executive areas spanning […]