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.
Collaborative Research: TRIPODS Institute for Optimization and Learning
This Phase I project forms an NSF TRIPODS Institute, based at Lehigh University and in collaboration with Stony Brook and Northwestern Universities, with a focus on new advances in tools for machine learning applications. A critical component for machine learning is mathematical optimization, where one uses historical data to train tools for making future predictions […]
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 […]
CAREER: Algorithms and Fundamental Limitations for Sparse Control
The proposal is to study the design of feedback control strategies which stabilize and steer systems by affecting them in only a few variables. The motivation comes from applications which are either large-scale or geographically distributed and therefore cannot be feasibly affected in many places. A primary motivating application is the control of metabolic chemical […]
CAREER: Specification-Guided Imitation Learning
Imitation learning (IL) is a powerful learning paradigm that enables machines, such as robots or artificial intelligence (AI) systems, to learn from demonstrations provided by human experts or expert agents. However, in practice, human demonstrations can be inadequate, partial, imperfect, environment-specific, or suboptimal. To address these challenges, this project introduces a novel framework that allows […]
CISE Hosts Pivotal ‘AI for Understanding Earthquakes’ Workshop
On Friday, November 10, 2023, CISE organized a first of its kind workshop, drawing in a diverse gathering of experts hailing from all over the US and Italy to explore the intersection of artificial intelligence and earthquake sciences. The workshop was presented alongside an AI Challenge, where participants were challenged to predict earthquake timing and […]
New Artificial Intelligence Program Could Help Treat Hypertension
High blood pressure is a major risk factor for heart disease and stroke, two leading causes of death in the U.S, and it is on the rise in this country. Nearly one in two adults have high blood pressure according to the Center for Disease Control. While hypertension is a treatable medical condition, it can be […]
Learning From Animal Behaviors to Inform Control Systems
You may be familiar with the term “blind as a bat”, which is used to describe someone who has poor eyesight. However, recent research on animal behavior by CISE affiliate and Distinguished Professor of Engineering John Baillieul (ME, ECE, SE) found that this phrase is a misconception and many species of bats rely on visual […]
Collaborative Research: CNS Core: Small: A New Architecture for Petabyte-scale File Transfer Evaluated in FABRIC
File transfer is a fundamental operation of the Internet. Important scientific instruments, such as the James Webb Space Telescope and the Large Hadron Collider, generate massive files daily. As files increase in size, it is more likely errors are introduced during their transfer, such as the ones not caught by the checksum process. Reliability is […]
GCR: COLLABORATIVE RESEARCH: MICRO-BIO-GENETICS FOR PROGRAMMABLE ORGANOID FORMATION
This project aims at defining a new area of dynamically-controlled, robot-assisted biological design. A convergent research team consisting of experts in microrobotics, machine learning, and synthetic biology will focus on developing a radically new approach towards analyzing and replicating intricate cellular patterning in mammalian tissues. Not only will this research result in new biological rules, […]
Collaborative Research: Elements: Discrete Simulation of Flexible Structures and Soft Robots
From carbon nanotubes to human-size soft robots, flexible and deformable structures are present throughout the next generation of promising engineering disciplines. However, simulation of these mechanical systems is often slow, and simulation software is challenging to use. In addition, there is little support for simulating flexible structures in common robotics research and education software, limiting […]