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Over the past decade, the world has seen tremendous increases in the deployment of artificial intelligence (AI) technology. The main horsepower behind the success of AI systems is provided by deep learning models and machine learning (ML) algorithms. Recently, a new AI paradigm has emerged: Automated Machine Learning (AutoML) including its subfield Neural Architecture Search (NAS). State-of-the-art ML models consist of complex workflows with numerous design choices and variables that must be tuned for optimal performance.

WNCG professor Jon Tamir aims to leverage machine learning techniques to make brain scans faster and more informative. He received an Amazon Machine Learning Research Award in 2020 from Amazon Web Services (AWS) to support the work. A recent article on Amazon Science explored the details of Prof. Tamir's research on MRI scans.

Pneumonia has emerged as a life-threatening complication of COVID-19, accounting for nearly half of all patients who have died from the novel coronavirus in the U.S. since the beginning of the pandemic. Even before the onset of the COVID-19 pandemic, pneumonia was responsible for more than 43,000 deaths in 2019.

WNCG students Akash Doshi and Manan Gupta have been named winners in the 2021 Qualcomm Innovation Fellowship (QIF) North America Program. Doshi and Gupta proposed the project “Federated Generative Learning for Channel Estimation in mmWave and THz systems.” The pair was one of 16 winners chosen from 43 teams of finalists. “We are extremely honored to have been selected as the recipients of this prestigious fellowship,” Gupta said. “We look forward to working with Qualcomm to develop impactful and innovative wireless technology.”

IBM recently announced the awardees of this year’s IBM Ph.D. Fellowship Program. WNCG student Tianlong Chen was among only 16 students selected worldwide for 2021. According to IBM, the Fellowship Awards Program is “intensely competitive.” Awardees are exceptional Ph.D. students conducting research in promising and disruptive technologies, particularly: Hybrid Cloud; Quantum Computing / Quantum Systems; Artificial Intelligence; Cloud / Open Source Technologies; Security / Cyber Security; Data Science; and Systems.

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's Prof. Jeff Andrews has been named as a recipient of a 2021 Qualcomm Faculty Award. The Qualcomm Faculty Award (QFA) "supports key professors and their research through a $75,000 charitable donation to their university. The goal of the QFA funding is to strengthen Qualcomm’s engagement with faculty who are playing a key role in our recruiting of top graduate students."

A team of Texas ECE students has been named a winner of the Qualcomm Innovation Fellowship 2020 (North America) competition. The team of Khurram Mazher and Andrew Graff won for their project "Radar-to-radar Interference: System Level Analysis and Solutions." Khurram and Andrew were one of 13 winning teams selected from 42 finalists. The Qualcomm Innovation Fellowship began in 2009, and "has continued to grow with the addition of more universities, more candidates, and expansion to our research centers internationally."

The National Science Foundation has selected The University of Texas at Austin to lead the NSF AI Institute for Foundations of Machine Learning, bolstering the university’s existing strengths in this emerging field. Machine learning is the technology that drives AI systems, enabling them to acquire knowledge and make predictions in complex environments. This technology has the potential to transform everything from transportation to entertainment to health care.