Earlier this year, as the global pandemic started shutting down much of the world, medical researchers quickly moved to better understand the virus and work on a vaccine. Researchers from UCI’s Donald Bren School of Information and Computer Sciences (ICS) took a different approach. As Assistant Professor of Computer Science Sameer Singh explains, “work started as an outlet for the students to positively contribute to the fight against COVID-19 the one way we know how — by throwing machine learning at it!”

Can emerging technologies help alleviate water reliability concerns in various communities by minimizing water waste, supporting conservation and providing a resilient supply of safe drinking water? This is the question researchers in the Donald Bren School of Information and Computer Sciences (ICS) are working to address with a $1.5 million grant from the National Science Foundation (NSF) through its Smart and Connected Communities (S&CC) program.

At the Sixth IEEE International Conference on Smart Computing (SMARTCOMP 2020), a trio of researchers from the Donald Bren School of Information and Computer Sciences (ICS) received the Best Paper Award. Ph.D. student Praveen Venkateswaran co-authored the work with Computer Science Professors Nalini Venkatasubramanian and Sharad Mehrotra, in collaboration with Associate Professor Cheng-Hsin Hsu of National Tsing Hua University, Taiwan. Their paper, “REAM: Resource Efficient Adaptive Monitoring of Community Spaces at the Edge Using Reinforcement Learning,” presents a framework for combining Internet of Things (IoT) technologies with machine learning techniques to better support smart infrastructure.

Two computer science researchers from the Donald Bren School of Information and Computer Sciences (ICS) are co-authors of a paper selected as the Editor’s Choice for the October issue of the Lasers in Surgery and Medicine journal. Computer science Ph.D. student Gregor Urban and his adviser, Distinguished Professor Pierre Baldi, are part of the multidisciplinary team behind “Combining Deep Learning with Optical Coherence Tomography Imaging to Determine Scalp Hair and Follicle Counts.” Urban and Baldi worked with dermatology physicians Natasha Mesinkovska and Chloe Ekelem, and with undergraduate students Ella Csuka and Kiana Hashemi, medical student Nate Feil, and M.D. resident Franchesca Choi.