In the News
One day, self-propelling liquids could be used to create a class of liquid drugs that are injected into the bloodstream and then autonomously flow toward a specific group of cells or organs. Because the swirl is made from components already in our cells, it wouldn’t be rejected by our bodies.This is another important step towards understanding the swirl’s overall motion. Read the full article here in BrandeisNow.
On November 20, 2020, the department hosted a special guest speaker, Adam Cheyer, '88, who presented “A Brandeisian Entrepreneur’s Journey.” Adam is the co-founder of Siri and Bixby, and founder of change.org. He spoke about harnessing what he learned at Brandeis to make a profound and positive impact on the world.
Associate Professor, Chuxu Zhang's research interests include data science, applied machine learning and artificial intelligence. Upon receiving his master’s from Rutgers University in 2017, he joined the Department of Computer Science and Engineering at the University of Notre Dame where he recently received his PhD Recent projects include developing machine learning tools to solve recommendation problems in heterogeneous networks, and applying artificial intelligence to natural language processing and to synthetic chemistry.
With support from the Robust Intelligence program in the Division of Intelligent and Information Systems (IIS) and the NSF 2026 Fund Program in the Office of Integrated Activities, investigators at Boston College and Professor James Pustejovsky's team at Brandeis University are addressing the challenge of creating Artificial General Intelligence by synthesizing symbolic or logical reasoning, learning through interaction with the environment, as well as state-of-the-art neural networks. Inspired by the structure of natural (e.g., human) intelligence, the resulting mental architecture deploys each of these strategies for the problems they excel at (the "Best of All Worlds?, or BAW, approach). Successful completion of this project will facilitate a range of research projects in AI and psychology/neuroscience. Long-term, the development of AGI is expected to have significant benefits to society, by enabling computers to develop abstract concepts grounded in experience with the world, and to generate novel ideas and inventions. This project will also help broaden student training and participation of women and underrepresented minorities. Read Professor Pustejvosky's interview with BrandeisNow!
This project aims to prototype a new architecture and test it against an open-ended task that is difficult for artificial intelligence but mastered by human toddlers everywhere: uncovering the affordances of blocks, containers, and other small objects. The primary aims are to build a virtual world that a simulated infant can explore, manipulate, and learn from; build a working prototype of a simulated infant incorporating key aspects of the BAW mental architecture; and evaluate the performance of the agent on several difficult, open-ended tasks. This architecture facilitates incorporation of key concepts from the study of natural intelligence that are infrequently used in artificial intelligence: mental models, exploratory play, and chunking.
Computer science and linguistics professor James Pustejovsky is leading a Brandeis team in creating an artificial intelligence platform called Semantic Visualization of Scientific Data — or SemViz — that can sort through the growing mass of published work on coronavirus and help biologists who study the disease gain insights and notice patterns and trends across research that could lead to a treatment or cure. Read the full article in BrandeisNow as well as a feature story in the Brandeis Magazine.
Cracking the Genetic Code: Two Brandeis computer scientists are using machine learning and artificial intelligence to analyze the genomes of COVID-19, other relevant corona- and avian-influenza viruses and Ebola. Professor of computer science Pengyu Hong and assistant professor of computer science Hongfu Liu want to identify the small and crucial bit of COVID-19's genetic code that may give rise to two of its most lethal and unique attributes. The advanced machine learning and artificial intelligence techniques the scientists are using can help sift through massive amounts of data to learn which nucleotide patterns are shared and which might be specific to COVID-19. According to Hong and Liu, artificial intelligence may also be able to predict emerging variations in the genomes of future viruses. Read the full article on BrandeisNow.
Brandeis University was a finalist in the Northeast North American Regional Final of the International Collegiate Programming Contest (ICPC). More than 50,000 students from 3,000 universities around the world competed in the annual programming contest. Student teams were from Brandeis and 19 other colleges and universities that included RIT, Brown University, University at Buffalo, Concordia University, Harvard University, Massachusetts Institute of Technology, McGill University, Mount Allison University, Northeastern University and University of Rochester. Congratulations to our undergraduate team, Jianfei Xue, Seeing Hu, Zhaonan Li for coming in 9th out of 20.
In the contest, each team of three students had five hours to solve a set of 10 complex, real-world problems. The top regional team will advance to the World Finals in Moscow. More information is available on the International Collegiate Programming Contest website.
WGBH announced today The Andrew W. Mellon Foundation’s renewed support for WGBH with a two-year, $750,000 grant, which will enhance usability of the American Archive of Public Broadcasting (AAPB). The AAPB is a collaboration between WGBH and the Library of Congress that aims to digitize and preserve thousands of hours of broadcasts and previously inaccessible programs from the more than 60-year legacy of public radio and public television. Over the next two years, the grant will support a two-pronged effort to make the AAPB an even more valuable resource for researchers, educators, academics and the public. The AAPB will work with Brandeis University’s Lab for Linguistics and Computation, headed by Professor James Pustejovsky, which uses machine learning and artificial intelligence to develop open-source tools and workflows, to capture detailed metadata from AAPB radio and television programs. This metadata, descriptive information about the people, places, dates and conversations in the archive, is a powerful way to improve access and discoverability of content. Read more here.
Brandeis University received a major grant to enhance the Language Application (LAPPS) Grid Project and EU’s CLARIN Platform to provide access to NLP-enabled tools to quickly analyze huge amounts of language for digital humanities to create Smart Archives. Brandeis was awarded a 16-month $673,000 grant from the Andrew W. Mellon Foundation to expand and deploy the LAPPS Grid Project which connects open-source computer programs to analyze texts from diverse sources and genres. The programs analyze any language content, determine the overall meaning, and help uncover hidden relationships embedded in the data. According to James Pustejovsky, the Project Director, the Mellon Foundation support will allow Brandeis and its collaborators from around the world to extend the range of the LAPPS Grid platform by linking it to a similarly broad and extensive one known as the European Common Language Resources and Technology Infrastructure (CLARIN). Read more here.
Olga Papaemmanouil, Associate Professor of Computer Science, has received a prestigious AmazonResearch Award (ARA) for her proposal "Query Performance Modeling via Deep Learning" which argues for the confluence of machine learning and data management. Professor Papaemmanouil's project focuses on leveraging deep learning methods for predicting the performance of database queries, offering flexible predictive models that automatically adapt to changes in the data distributions, workload characteristics and operational capabilities of hardware resources. The ARA awards are granted to foster innovation and collaboration with major research institutions around the globe. The annual award offers up to $80,000 in funding to faculty members at academic institutions worldwide and $20,000 in Amazon Web Service credits to support research in a variety of Artificial Intelligence areas such as computer vision, natural language processing, robotics, security