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Events for March 07, 2023
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Element Materials Technology's Tabling Session
Tue, Mar 07, 2023 @ 11:00 AM - 03:00 PM
Viterbi School of Engineering Career Connections
Workshops & Infosessions
Element Materials Technology is one of the world leading providers of testing, inspection and certification services. When failure in use is not an option, we help customers make certain that their products, materials, processes, and services are safe, compliant and fit for purpose. We have labs nationwide and several local in California. We have entry level jobs all the way to Engineering careers!
We will have 2 Reps on site, HR and a recruiter! We are going to table and to get our name out there! We have entry level job openings to Engineers.
What majors and class levels are you interested in connecting with? Graduating students, Seniors. Majors: Engineers
Are you recruiting for internships, full-time, or both? Full time
Can you offer Visa sponsorship? We do not
Are you able to hire a student on CPT or OPT? We do notLocation: Epstein Family Plaza
Audiences: Everyone Is Invited
Contact: RTH 218 Viterbi Career Connections
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CS Colloquium: Matus Telgarsky (University of Illinois, Urbana-Champaign) - Searching for the implicit bias of deep learning
Tue, Mar 07, 2023 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Matus Telgarsky, University of Illinois, Urbana-Champaign
Talk Title: Searching for the implicit bias of deep learning
Series: CS Colloquium
Abstract: What makes deep learning special --- why is it effective in so many settings where other models fail? This talk will present recent progress from three perspectives. The first result is approximation-theoretic: deep networks can easily represent phenomena that require exponentially-sized shallow networks, decision trees, and other classical models. Secondly, I will show that their statistical generalization ability --- namely, their ability to perform well on unseen testing data --- is correlated with their prediction margins, a classical notion of confidence. Finally, comprising the majority of the talk, I will discuss the interaction of the preceding two perspectives with optimization: specifically, how standard descent methods are implicitly biased towards models with good generalization. Here I will present two approaches: the strong implicit bias, which studies convergence to specific well-structured objects, and the weak implicit bias, which merely ensures certain good properties eventually hold, but has a more flexible proof technique.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Matus Telgarsky is an assistant professor at the University of Illinois, Urbana-Champaign, specializing in deep learning theory. He was fortunate to receive a PhD at UCSD under Sanjoy Dasgupta. Other highlights include: co-founding, in 2017, the Midwest ML Symposium (MMLS) with Po-Ling Loh; receiving a 2018 NSF CAREER award; and organizing two Simons Institute programs, one on deep learning theory (summer 2019), and one on generalization (fall 2024).
Host: Vatsal Sharan
Location: Olin Hall of Engineering (OHE) - 132
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Epstein Institute - ISE 651 Seminar
Tue, Mar 07, 2023 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Abdullah Alibrahim, Assistant Professor, Dept. of Industrial & Management Systems Engineering, Kuwait University
Talk Title: TBD
Host: Dr. Shinyi Wu
Location: Ethel Percy Andrus Gerontology Center (GER) - GER 206
Audiences: Everyone Is Invited
Contact: Grace Owh
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CAIS Seminar: Andrew Zolli (Planet) - Using Space and AI to Help Life on Earth: How AI and Satellites Are Transforming Our Stewardship of the Planet
Tue, Mar 07, 2023 @ 04:00 PM - 05:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Andrew Zolli, Planet
Talk Title: Using Space and AI to Help Life on Earth: How AI and Satellites Are Transforming Our Stewardship of the Planet
Series: CS Colloquium
Abstract: We're in the middle of two concurrent and convergent technological revolutions. The first is a sensor revolution, in which new streams of real-time data from the ground, the air, and space are making the change on Earth more transparent than ever before. New generations of satellites monitor every crop, every forest, every city, everywhere, every day - and provide unprecedented transparency. The second revolution is an AI summer, in which the wide availability of machine learning, cloud storage and computing are enabling the extraction of real-time indicators from these data sets. This is revealing real-time feedback loops that can show us how our actions impact the world -“ both positively and negatively - and enabling entirely new ways of seeing, analyzing, and responding to planetary change.
In this talk, Planet's Chief Impact Officer Andrew Zolli will share how these breakthrough approaches are transforming our stewardship of the planet, and where they are likely to go next.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: I currently oversee Sustainability and Global Impact initiatives at Planet, a breakthrough space and AI organization that has deployed the largest constellation of Earth-observing satellites in history. These satellites image our whole planet every day in high resolution, and my team makes sure this data is ethically used to its highest and best purposes to accelerate climate action, monitor the world's ecosystems, improve humanitarian action and disaster response, protect human rights, transform sustainable development, advance scientific discovery and artistic expression. We're even exploring how these tools can inform the next iteration of capitalism, where social and environmental externalities are more effectively measured and valued. I also currently serve on the International Board of Directors of Human Rights Watch.
Host: USC Center for Artificial Intelligence in Society (CAIS)
Location: Seeley G. Mudd Building (SGM) - 124
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
