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.

A Coordinated Approach to Cyber-Situation Awarness Based on Traffic Anomaly Detection

This project aims at developing a suite of anomaly detection algorithms and tools monitoring network traffic and operating both at the local (resource) level and the wider (global) network level. It will leverage recent work by the PIs on statistical temporal anomaly detection using random and Markovian models and on detecting wider network spatial anomalies […]

Refinement Methods for Protein Docking based on Exploring Multi-Dimensional Energy Funnels

All successful state-of-the-art protein docking methods employ a so called multistage approach. At the first stage of such approaches a rough energy potential is used to score billions of conformations. At a second stage, thousands of conformations with the best scores are retained and clustered based on a certain similarity metric. Cluster centers correspond to putative predictions/models. Recent work […]

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 […]

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 […]

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 […]