Undergraduate students Hongsen Qin, Emma Qian, Thomas Hoffmann, and Alexander Zlokapa (advised by Professors Aaron Ames, Erik Winfree, Jonathan Katz, Maria Spiropulu, and Yaser Abu-Mostafa) have won the Citadel Data Open International Data Science Competition. This winning team chose to investigate the optimal way to spend $1 billion to save lives from malaria and sanitation-related diseases, allocating funds for different prevention methods and optimizing budget breakdowns country by country. To quantify the socioeconomic impacts of their policy proposal, they modeled a variety of aspects from mosquito feeding cycles to climate change using techniques ranging from causal discovery methods to interpretable machine learning. The Caltech team was among 24 teams that were evaluated and questioned by a panel of experts including the former Chief Scientist of AI at Microsoft, a Princeton professor, and the chief of equities at Citadel. The Caltech team was chosen as the first place winner based on the depth, rigor, and comprehensiveness of their analysis.
Caltech has recognized alumnus William Dally (PhD ’86, Computer Science) with the Distinguished Alumni Award, the highest honor regularly bestowed by the Institute. Dally was recognized “for his significant contributions to the architecture of interconnection networks. He developed much of the technology found in modern interconnection networks including wormhole routing, virtual-channel flow control, global adaptive routing, modern network topology, deadlock analysis, performance analysis, fault-tolerance methods, and equalized high-speed signaling.” [Caltech story] [Distinguished Lecture at Caltech]
The Amazon Fellows program is the result of a partnership between Caltech and Amazon AWS around Machine Learning and Artificial Intelligence (AI). The 2018 Amazon fellows are Ehsan Abbasi, Gautam Goel, Jonathan Kenny, Palma London, and Xiaobin Xiong. Abbasi is interest in contributing to a deeper understanding of convex and non-convex learning methods in AI and is an Electrical Engineering graduate student working with Professor Babak Hassibi. Goel’s research interest is at the interface of the theory and practice of machine learning and is advised by Professor Adam Wierman. London is also working with Professor Wierman. She is developing efficient algorithms for solving extremely large optimization problems. The methods are applicable to distributed and parallel optimization. For example in a distributed data center setting, the algorithms are robust to unreliable data transfer between data centers and take into account privacy concerns. Kenny is a Computation & Neural Systems graduate student working with Professor Thanos Siapas on deep neural networks to identify and classify brain states. Xiong is a mechanical engineering graduate student who enjoys working on real physical robots, to make them walk, jump, and run in real life. He is advised by Professor Aaron Ames and their research is focused on robotic bipedal locomotion
In a recent Techer interview Electrical Engineering alumna Fei-Fei Li (PhD ’05) explains, “As we see artificial intelligence impacting the real world, it’s no longer a niche computer science, technical field. Policymakers, business leaders, educators, social scientists—they all need to take part and guide the future of A.I.” [Check out the full interview]
Thanks to Professor Pietro Perona and his graduate students including Grant Van Horn and Sara Beery, the next wildlife photo you snap might set you on a path to helping map life on Earth. “The whole web, this huge repository of wonderful information, is indexed by words,” Perona says. “But when we have an image—a visual query—we don’t know what to do unless there is an expert next to us. We’ve gotten so numb to the idea that we’ll never find the answer out.” [Breakthrough story]
Starting in fall 2018, EAS will offer students a new undergraduate degree option in a field that is at the forefront of computer science: information and data sciences (IDS). Mathematics will form the backbone of the new option. Students in IDS will take core courses focusing on machine learning, information theory, probability, statistics, linear algebra, and signal processing. After that, they will have the opportunity to branch out with electives that cover applications of data sciences to science and engineering. Professor Adam Wierman hopes the creation of this new option will prepare both students and Caltech for the future. "It almost doesn't matter what you're interested in. If you want to make discoveries and be on the cutting edge of your field, you're going to need the skills to analyze and manipulate large collections of information," he says. [Caltech story] [Degree option details]
In a letter to the Caltech community during National Postdoc Appreciation Week, the Caltech President emphasizes the role this key group plays at the Institute. He stated, “Caltech's mission of world-leading research and education depends crucially on our postdoctoral scholars. Although their time at Caltech may be short, they quickly become vital parts of the Institute's intellectual fabric.” [President’s Letter] [EAS Postdoc Resource Page]
Carver Mead, one of the fathers of modern computing, combines memoir and instruction in new video series. "My feeling is that these days, if it's not on the web, it doesn't exist," Professor Mead says of the decision to launch the new video channel. The video series is available for free on YouTube, and aims to provide a better understanding of the birth and evolution of modern computing, as told by one of its key participants and witnesses. [Caltech story]
Graduate student Grant Van Horn and postdoctoral scholars Oisin Mac Aodha, working with Professor Pietro Perona, started the iNaturalist Challenge last year, to see how much they could push machine-learning technology. The competition is now in its second year and the dataset contains over 8,000 species, with a combined training and validation set of 450,000 images that have been collected and verified by multiple users from iNaturalist. This year's competition promise to be much more challenging because there are more species and less examples for the computer to learn from. The top submissions will be invited to give talks at CVPR, which is the premier annual computer vision event. [Enter the competition]
Four graduate students from the Computing and Mathematical Sciences (CMS) Department and one from the Electrical Engineering (EE) Department have been selected as 2017 Amazon Fellows. This fellows program is the result of a partnership between Caltech and Amazon AWS around Machine Learning and Artificial Intelligence. The EE fellow is Srikanth Tenneti who is exploring the potential of deep learning for Direction of Arrival applications, and extending Ramanujan Sums based techniques for multi-dimensional periodicity extraction. CMS graduate student Navid Azizan Ruhi is researching faster optimization algorithms for machine learning. He is looking forward to visiting Amazon AI as a fellow and exchanging ideas with their researchers. Computer science graduate student Hoang Le is developing methods for efficient and intelligent sequential decision making in realistic systems. Florian Schaefer, whose focus is applied and computational mathematics, is researching the interface of statistical estimation and the design of fast algorithms. Control and dynamical systems graduate student Ellen Feldman, working with Professor Joel Burdick, has used part of the funding to present her research at the Society for Neuroscience annual meeting and looking forward to other future opportunities to share her research.