News

WNCG professor Edison Thomaz is part of a team exploring the use of wearable technology to prevent kidney stones. The team received a five year, $2.97 million grant from the National Institute of Diabetes and Digestive and Kidney Diseases to address this problem. The team includes David Conroy, professor of kinesiology and human development and family studies, Necole Streeper, assistant professor of surgery at the College of Medicine, both from Penn State University, as well as Nilam Ram, professor of communications and psychology at Stanford University.

R. Srikant (University of Illinois at Urbana-Champaign) Date: Friday, October 16, 2020Time: 11:00 AM – 12:00 PM (CDT; UTC -5) Title: The Role of Regularization in Overparameterized Neural Networks

WNCG professor Atlas Wang received a Data Science Research Award from Adobe for his work on “Towards Automated Design of Efficient Deep Multi-Modal Recommendation Models.” Every year, Adobe funds a university faculty research program to “promote the understanding and use of data science in the area of marketing with the goal “to encourage both theoretical and empirical development of solutions to problems in marketing.”

WNCG professor Aryan Mokhtari has received a grant from the National Science Foundation (NSF) to study Computationally Efficient Second-Order Optimization Algorithms for Large-Scale Learning. The project “lays out an agenda to develop a class of memory efficient, computationally affordable, and distributed friendly second-order methods for solving modern machine learning problems.”

WNCG professor Todd Humphreys and postdoctoral fellow Peter Iannucci of the Radionavigation Laboratory have developed a system using the constellation of SpaceX satellites to potentially deliver a low-cost, more accurate, and highly secure alternative to GPS. Their work was recently featured in the MIT Technology Review:

The application of supervised learning techniques for the design of the physical layer of a communication link is often impaired by the limited amount of pilot data available for each device; while the use of unsupervised learning is typically limited by the need to carry out a large number of training iterations. In this talk, meta-learning, or learning-to-learn, is introduced as a tool to alleviate these problems.

A defining characteristic of federated learning is the presence of heterogeneity, i.e., that data and compute may differ significantly across the network. In this talk I show that the challenge of heterogeneity pervades the machine learning process in federated settings, affecting issues such as optimization, modeling, and fairness. In terms of optimization, I discuss FedProx, a distributed optimization method that offers robustness to systems and statistical heterogeneity.

WNCG professor Al Bovik has received the University Co-operative Society’s Career Research Excellence Award for 2019-2020. The award acknowledges a faculty member or staff researcher “who has maintained superior research programs over many years.” The award is one of three research accolades that are part of the University Co-op Hamilton Book Author Awards. In addition to the Career Research Excellence Award, the Co-op also designates a Best Research Paper Award and the Creative Research Award.

WNCG professor José del R. Millán has been elected as a Fellow to the International Academy of Medical and Biological Engineering (IAMBE) for his outstanding contributions to the profession of medical and biological engineering.  Election to the Academy is highly selective, initiated by nominations which are involved with at least 3 current Fellows and screened by the Membership Committee of the Academy. The election is conducted by a vote of all Fellows of the Academy. There are currently less than 200 Fellows world-wide.

AMD announced a second round of high-performance technology contributions to assist in the global fight against the COVID-19 pandemic.