Nivetha Karthikeyan Awarded Chang Career Exploration Prize


Caltech has awarded the third annual Milton and Rosalind Chang Career Exploration Prize to alumna Nivetha (Niv) Karthikeyan (BS ’20) for her proposed project “Intersections: Building Solidarity Through Community Archives,” which intends to construct and share a new online community archive recording how people of color have historically created alliances, coalitions, and communities with other racial minorities in the United States.

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Undergraduate Fellowship Winner Will Study Artificial Intelligence and Machine-learning Applications for Health Care


Meera Krishnamoorthy, a senior in electrical engineering, has received a National Physical Science Consortium (NPSC) Fellowship that will fund up to six years of graduate training. Krishnamoorthy will be enrolling in a computer science PhD program at the University of Michigan, studying artificial intelligence and machine-learning applications for health care, such as turning complex medical data into actionable knowledge that ultimately improves patient care. "Engineering is a great way to solve problems in multiple disciplines," she says. Krishnamoorthy's interest in machine learning was sparked by coursework and a research project she worked with Professor Yisong Yue, and her academic advisor has been Professor Steven Low. [Caltech story]

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Undergrad Weighs in on Privacy Laws


Computer science junior Rona Yu has embarked on a yearlong project to answer the question: “What should the nation be doing, right now, to draft a privacy regulation?" She has written a paper that covers the points that new privacy legislation should be prioritizing, as well as the potential unintended consequences of the legislation that has been proposed. She is also preparing a document describing her findings that I will submit to the Federal Trade Commission. [Caltech story]

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2019 Caltech Distinguished Alumni


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]

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As artificial intelligence becomes mainstream, who will guide it?


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]

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Alumnus to Exploring Ways to Tackle California’s Housing Crisis


Caltech has awarded the inaugural Milton and Rosalind Chang Career Exploration Prize to EAS undergraduate alumnus, Sean McKenna (BS ’17, ACM) for his proposed project “Exploring Ways to Tackle California’s Housing Crisis.” McKenna plans to spend the next year connecting with residents, housing developers, homeless shelters, technology innovators, and policymakers in California and Washington, DC to learn more about the roots of the housing crisis. He is grateful for the “incredible amount of freedom" the Chang Prize will give him "to figure out how the skills and passions I developed at Caltech might translate into making a difference in the housing crisis, a problem that is very real for me, other Techers, and all residents of California.” [Alumni Association story]

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Learning Directly From Data Rather Than Human-Provided Expertise


Alumnus Yong Sheng Soh (PhD ’18, ACM), advised by Professor Venkat Chandrasekaran, has won the 2018 INFORMS Optimization Society Student Prize for his paper entitled Learning Semidefinite-Representable Regularizers. Regularization-based algorithms are widely used in the solution of data-driven inverse problems arising in statistics, operations research, signal processing, and machine learning. These approaches typically require a great deal of prior domain-specific expertise about the structure of the underlying problem. Such expertise is especially challenging to obtain in the modern era of 'Big Data' in which our ability to sense all manner of phenomena and produce massive datasets far exceeds our ability to understand the underlying mechanisms governing the phenomena. In his award-winning work, which has been accepted for publication at the Journal of the Foundations of Computational Mathematics, Yong Sheng has developed a new framework for learning suitable regularization methods directly from data rather from human-provided expertise. [INFORMS Optimization Society Award] [Read the paper]

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Alumna Wins Woman of the Year Award


CMS alumna, Ashley Williams, was named 2018 Woman of the Year by the Aerospace Corporation. Dr. Williams received her Caltech PhD in 2011 and was advised by Professors Jerry Marsden, Richard Murray, and Mathieu Desbrun. Currently she is the director of the Studies and Analyses Office at the Aerospace Corporation. [Dr. Williams’ Caltech thesis]

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A Network of Support


Early in his freshman year CMS and BEM alumnus Ramsathwick “Sathwick” Pathireddy (BS ’17) realized just how challenging a Caltech workload could be and turned to his housemates and friends for help. “When I had questions about time management, what classes to take, or what internships to go for, I always had someone to talk to,” Sathwick says. [Breakthrough story]

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For the Record


CMS alumnus Ramruthwick “Ruthwick” Pathireddy (BS ’17) is described as curious, ambitious, and rigorous. “When people talk about Caltech, they think of students studying really hard,” Ruthwick says. “While we do study hard, there’s more to it than that. I don’t think people realize the social opportunities that are available here, how enriching the activities are, and how close the entire undergraduate community is. It’s really like a family.” [Breakthrough story]

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