Although Stephen McAleer first became interested in artificial intelligence after reading the book Gödel, Escher, Bach: An Eternal Golden Braid, it wasn’t until Google’s AI program AlphaGo beat the world champion of the game Go that he decided to switch careers from finance to AI research. Now, as a Ph.D. student working with Chancellor’s Professor Pierre Baldi in the Donald Bren School of Information and Computer Sciences (ICS), he has helped tackle a new deep-learning challenge.
UCI Professor of Computer Science Aditi Majumder’s, Ph.D., journey into the virtual/augmented reality world stems back to a young girl growing up in Kolkata, India around her mother, a professional musician and her father, a civil engineer. Both parents unknowingly planted the hybrid seed of art and science, which led Majumder to pursue a blossoming career in virtual/augmented reality that intertwines with her deep appreciation for art and music.
Read the full story at UCI Applied Innovation Tech Currents.
In chess, by contrast, there is a relatively large search space but each move can be evaluated and rewarded accordingly. That just isn’t the case for the Rubik’s Cube.
Enter Stephen McAleer and colleagues from the University of California, Irvine. These guys have pioneered a new kind of deep-learning technique, called “autodidactic iteration,” that can teach itself to solve a Rubik’s Cube with no human assistance. The trick that McAleer and co have mastered is to find a way for the machine to create its own system of rewards.
Read the full story at MIT Technology Review.
Researchers from the University of California, Irvine developed a deep learning-based approach to accelerate drug discovery and cancer research.
“We have developed a convolutional neural network to improve the data analysis processes for high-throughput drug screening using our microphysiological system (MPS),” the researchers stated in their paper.
Read the full story at NVIDIA Developer News Center.
At UCI’s graduation, 49 students will wear a blue and gold shoulder cord with their commencement regalia, indicating that they are recipients of the 2018 Chancellor’s Award of Distinction. The UCI Alumni Association honors outstanding graduating seniors with this award to acknowledge their “exceptional academic achievement and commitment to cutting-edge research, leadership and service to UCI.” Two students from the Donald Bren School of Information and Computer Sciences (ICS) have been honored this year with this distinction: Christian Morte and Ayesha Syed.
For the second time in just three years, Ramesh Jain, Bren Professor of Computer Science, has won the IEEE MultiMedia “Best Department Article” award. This year, he received the award for “Social-Sensed Multimedia Computing,” which he co-authored with Peng Cui and Wenwu Zhu of Tsinghua University, China, and Tat-Seng Chua of the National University of Singapore.
Distinguished Professor of Computer Science Vijay Vazirani recently received a grant of $500,000 from the National Science Foundation (NSF) for his proposal, “Algorithms for Matching, Markets, and Matching Markets.” All three problem areas — matching, markets, and matching markets — have deep and rich algorithmic theories and numerous applications. For example, applications of matching markets range from assigning interns to hospitals, to assigning query keywords to advertisers in the multibillion-dollar online ads markets of search engine companies such as Google. Over the years, Vazirani has made foundational contributions to all three problem areas, and in the current proposal, he has identified several new problems.
UCI Applied Innovation has recognized Chancellor’s Professor of Computer Science Michael Franz as its inaugural Innovator of the Year. The new award aims to recognize researchers who have developed a breakthrough idea, process or technology and demonstrated its transformational potential to improve lives and create economic value.
Whether examining tweets to better understand crime levels, or monitoring comments posted on public forums to identify health trends, researchers need methods and tools specifically designed for social media analytics. That is why Computer Science Professor Chen Li decided to organize UCI’s first SoCal Social Analytics Workshop on May 11, 2018. Sponsored by the UCI Data Science Initiative and the UC Institute for Prediction Technology (UCIPT), the goal was to bring together people from different disciplines to exchange ideas regarding social media as a data source.