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University Calendar
Events for September
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Interested in starting a company while at USC?
Wed, Sep 04, 2024 @ 12:00 PM - 01:00 PM
Viterbi Technology Innovation and Entrepreneurship
University Calendar
Come & hear about programs with over 100k in prizes! Hear from program alumni on their student co founder journey and experience in participating in USC's innovation programming. Hear specicially about the Min Family Challenge and the Maseeh Entrepreneurship Prize Competition. Min Family Challenge - Engineering solutions for Social Impact with a 50k prizeMaseeh Entrepreneurship Prize Competition- Deep Tech 50k prize competition RSVP
Location: Michelson Center for Convergent Bioscience (MCB) - 101
Audiences: Everyone Is Invited
Contact: Viterbi TIE
Event Link: https://cglink.me/2nB/r397841
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AI4Health – Computational Epidemiology During the COVID-19 Pandemic
Mon, Sep 16, 2024 @ 11:00 AM - 12:00 PM
Information Sciences Institute
University Calendar
Abstract: In this talk, Professor Majumder will discuss her recent work in computational epidemiology (comp epi): an interdisciplinary field at the intersection of machine learning, digital data, and public health. With a focus on the COVID-19 pandemic, topics covered will include agent-based models for health policy simulation; smartphone mobility data for health policy evaluation; and search query & news media data for monitoring health misinformation. In particular, the health policies and digital data considered will showcase the role of social justice and social networks in Prof. Majumder’s research. Host: Abigail Horn, Research Assistant Professor of Industrial and Systems Engineering You may sign up here to speak with Professor Majumder via Zoom between 9 am and 10:30 am, and 12 pm and 2 pm. All times Pacific Speaker Bio Dr. Maimuna (Maia) Majumder (she/they) is an Assistant Professor and Inaugural Peter Szolovits Distinguished Scholar in the Computational Health Informatics Program at Harvard Medical School and Boston Children’s Hospital. Her research applies artificial intelligence & machine learning methods to public health problems, with a focus on infectious disease surveillance using search query, mobile phone, and news & social media data. Since January 2020, Maia and her team have been actively responding to the ongoing COVID-19 pandemic.
Location: ONLINE ONLY
Audiences: Everyone Is Invited
Contact: Tricia Olmedo
Event Link: https://usc.zoom.us/j/93936022035?pwd=Ot1rjLPcXteolnG18eVVPJhnrdiBtr.1&from=addon
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Panel Discussion: Intersection of societal needs and innovation
Wed, Sep 18, 2024 @ 12:00 PM - 01:00 PM
Viterbi Technology Innovation and Entrepreneurship
University Calendar
Join us for an inspiring panel discussion at USC, where 5 NGO leaders passionate about Sustainable Development Goals (SDGs) will share their insights and support for emerging entrepreneurs and engineers. This event is designed to bridge the gap between innovation and real-world impact, offering students a unique opportunity to engage directly with those who understand real world needs.
Through this collaboration, students will gain valuable early access to perspectives that can shape their entrepreneurial journeys, helping them develop solutions that address critical challenges and make a positive difference in communities worldwide. Don’t miss this chance to connect with leaders driving change and learn how you can contribute to a more sustainable future!Audiences: Everyone Is Invited
Contact: Viterbi TIE
Event Link: https://cglink.me/2nB/r397960
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PhD Thesis Proposal - Jesse Zhang
Tue, Sep 24, 2024 @ 05:00 PM - 06:00 PM
Thomas Lord Department of Computer Science
University Calendar
Title: Scalable Robot Adaptation with Large Pre-trained Models
Date and Time: 09/24/24 - 5:00p - 6:00p
Location: RTH 114
Committee Members: Erdem Biyik, Jesse Thomason, Joseph Lim, Daniel Seita, Somil Basil
Abstract: General robots deployed in the real world need to respond to dynamic environments and constantly learn new tasks. However, current approaches lack the ability to enable them to adapt to these ever-changing environments and tasks at scale, i.e., without extensive human supervision. My thesis proposal aims to tackle this problem by utilizing vast general knowledge stored in Large Pre-trained Models (LPTMs) to enable scalable and efficient robot adaptation. I will cover 3 fundamental paradigms in enabling robot adaptation: using LPTMs to (1) label offline data, (2) guide robots in learning new tasks online, and finally (3) adapt to new agent settings. Through extensive research in the first two paradigms and future thesis work proposed in the third, my proposal aims to produce general algorithms that will lead to robots mastering new tasks in unfamiliar environments with little human supervision.Location: Ronald Tutor Hall of Engineering (RTH) - 114
Audiences: Everyone Is Invited
Contact: Jesse Zhang