Stephan Mandt, an assistant professor of computer science and statistics in UCI’s Donald Bren School of Information and Computer Sciences (ICS), received an unrestricted gift of $50,000 from Disney Research Los Angeles to support his work on generative modeling.

Mandt is exploring how to use machine learning under resource constraints — in particular, given a lack of relevant training data. “In other words, how might you train a deep learning algorithm to mimic speech when you don’t have massive amounts of available speech recordings?”

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If you’re a local student, you might already know senior Kazeem Salaam, a computer science major at UCI in the Donald Bren School of Information and Computer Sciences (ICS). Perhaps he helped you better understand Python or C++ through the 4.0 Club, a free tutoring service for ICS and engineering students at UCI. Or he might have introduced you to the MIT App Inventor as a K-12 web application instructor, or to Raspberry Pi as a volunteer for the National Society of Black Engineers (NSBE) youth program, Engineers of the Future. Or maybe you’ve watched his video on How to Use LeetCode. Because when Salaam isn’t studying software development at UCI or interning at Amazon, he’s often sharing his knowledge with others in the classroom or documenting his own experiences on his YouTube channel ZeemTheDream, encouraging students — especially those from underrepresented backgrounds — to explore careers in STEM.

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Sang-Woo Jun, an assistant professor of computer science in the Donald Bren School of Information and Computer Sciences (ICS), was pleased with the Best Paper Award announcement at the 31st International Conference on Field-Programmable Logic and Applications (FPL 21). The award went to “Eciton: Very Low-Power LSTM Neural Network Accelerator for Predictive Maintenance at the Edge,” a paper he co-authored that introduces a Long Short-Term Memory (LSTM) neural network accelerator for low-power edge sensor nodes. The work was a collaboration with ICS graduate students Jeffrey Chen and Sehwan Hong, Diamond Bar High School student Warrick He, and Professor Jinyeong Moon of Florida State University.

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Earlier this year, the Association for Computing Machinery (ACM) announced that Michael Franz, Chancellor’s Professor of Computer Science in UCI’s Donald Bren School of Information and Computer Sciences (ICS), had been selected to receive the ACM Charles P. “Chuck” Thacker Breakthrough in Computing Award. The award recognizes “individuals or groups who have made surprising, disruptive, or leapfrog contributions to computing ideas or technologies.” Franz is being recognized for his development of just-in-time (JIT) compilation techniques that enable fast and feature-rich web services on the internet — services now used by billions of people daily with applications such as Gmail and Facebook.

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A paper by Chancellor’s Professor of Computer Science David Eppstein, “Finding Relevant Points for Nearest-Neighbor Classification,” has won the best paper award of the 2022 SIAM Symposium on Simplicity in Algorithms (SOSA22), to be held in a hybrid online and in-person format in Virginia in January 2022, jointly with several other SIAM conferences.

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The Information and Computer Sciences Student Council (ICSSC) kicked off the fall quarter with WebJam 2021, a weeklong competition that was open to all UCI students who wanted to learn web development. 

Students had the option to participate in the competition individually or in teams of up to four students. Between Oct. 11-15, students learned the skills they needed to create fully functional web applications. 

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The U.S. Department of Energy (DOE) recently awarded $16 million to five research projects developing artificial intelligence and machine learning algorithms to enable greater scientific insight and new discoveries. “Disruptive technology changes are occurring across science applications, algorithms, architectures, and high-performance computing ecosystems,” said Barbara Helland, the DOE Office of Science’s associate director for advanced scientific computing research. “These projects explore potentially high-impact approaches in AI and machine learning to assist and automate scientific discovery and data analysis for increasingly complex problems.”

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