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Events for the 2nd week of March

  • BME Seminar Speaker Dr. Donghui Zuo

    Mon, Mar 06, 2023 @ 11:00 AM - 12:00 PM

    Alfred E. Mann Department of Biomedical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Donghui Zhu , SUNY Empire Innovation Professor, Department of Biomedical Engineering and Neuroscience, Stony Brook University, SUNY

    Talk Title: ZINC: a novel bioresorbable and bioactive material

    Host: BME Professor Stacey Finley

    More Info: Zoom Available Upon Request

    Location: Corwin D. Denney Research Center (DRB) - 145

    Audiences: Everyone Is Invited

    Contact: Michele Medina

    Event Link: Zoom Available Upon Request

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  • AME Seminar

    Mon, Mar 06, 2023 @ 03:30 PM - 04:30 PM

    Aerospace and Mechanical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Wen Chen, University of Massachusetts Amherst

    Talk Title: Additive Manufacturing of Emerging Complex Alloys with Engineered Structures

    Abstract: The increasing demands for materials serving under extreme environments call for the development of emerging classes of metal alloys with increasingly complex compositions. However, synthesis and processing of complex alloys via traditional routes are challenging. Additive manufacturing, also called 3D printing, is a disruptive technology for creating materials and components in a single print. Harnessing the vast compositional space of complex alloys and the far-from-equilibrium processing conditions (e.g., large thermal gradients and high cooling rates) of additive manufacturing provides a paradigm-shifting pathway for material design. In this talk, I will present the potential of utilizing laser additive manufacturing and direct ink writing to produce metal alloys with engineered structural hierarchy across multiple length scales. These unique microstructures give rise to exceptional mechanical and functional properties that extend far beyond those accessible by conventional manufacturing. In addition, I will discuss the abundant opportunities enabled by additive manufacturing for high-throughput materials discovery to accelerate the pace of future materials search for a wide range of applications in aerospace, biomedical, and renewable energy.

    Biography: Wen Chen is an Assistant Professor in the Department of Mechanical and Industrial Engineering at University of Massachusetts Amherst. He completed his Ph.D. degree in Mechanical Engineering and Materials Science at Yale University in 2016. After his Ph.D., he worked as a postdoctoral research scientist at Lawrence Livermore National Laboratory, where he studied a variety of additive manufacturing techniques such as projection stereolithography, direct ink writing, and laser powder bed fusion. Dr. Chen's current research interests include advanced manufacturing, mechanical behavior of materials, physical metallurgy, and architected materials. He is the recipient of several prestigious awards including the SME Outstanding Young Manufacturing Engineer Award and NSF CAREER Award. He has served as an editorial board member of Scientific Reports since 2018.

    Host: AME Department

    More Info: https://ame.usc.edu/seminars/

    Webcast: https://usc.zoom.us/j/95805178776?pwd=aEtTRnQ2MmJ6UWE4dk9UMG9GdENLQT09

    Location: John Stauffer Science Lecture Hall (SLH) - 102

    WebCast Link: https://usc.zoom.us/j/95805178776?pwd=aEtTRnQ2MmJ6UWE4dk9UMG9GdENLQT09

    Audiences: Everyone Is Invited

    Contact: Tessa Yao

    Event Link: https://ame.usc.edu/seminars/

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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 not

    Location: 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

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  • BME Seminar Speaker, Dr. Andy Tay Kah Ping

    Wed, Mar 08, 2023 @ 11:00 AM - 12:00 PM

    Alfred E. Mann Department of Biomedical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Andy Tay , Assistant Professor, College of Design and Engineering, National University of Singapore

    Talk Title: Mechano-enhancement of wound regeneration and nanomedicine delivery

    Host: Eun Ji Chung

    More Information: bme seminar speaker andy tay.pdf

    Location: Corwin D. Denney Research Center (DRB) - 145

    Audiences: Everyone Is Invited

    Contact: Michele Medina

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  • Computer Science General Faculty Meeting

    Wed, Mar 08, 2023 @ 12:00 PM - 02:00 PM

    Thomas Lord Department of Computer Science

    Receptions & Special Events


    Bi-Weekly regular faculty meeting for invited full-time Computer Science faculty only. Event details emailed directly to attendees.

    Location: Ronald Tutor Hall of Engineering (RTH) - 526- Hybrid

    Audiences: Invited Faculty Only

    Contact: Assistant to CS chair

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  • NL Seminar - • Enhancing Machine Translation with Large Language Models via Optimizing In Context Examples and Dictionary Based Prompting

    Thu, Mar 09, 2023 @ 11:00 AM - 12:00 PM

    Information Sciences Institute

    Conferences, Lectures, & Seminars


    Speaker: Marjan Ghazvininejad, FAIR, Facebook AI Research

    Talk Title: Enhancing Machine Translation with Large Language Models via Optimizing In Context Examples and Dictionary Based Prompting

    Abstract: REMINDER:
    This Talk will be a Live Broadcast Only, It "Will Not" be recorded.

    Meeting hosts only admit guests that they know to the Zoom meeting. Hence, you are highly encouraged to use your USC account to sign into Zoom.

    If you are an outside visitor, please inform us at nlg DASH seminar DASH host AT isi DOT edu beforehand so we will be aware of your attendance and let you in.

    Large language models LLMs have revolutionized natural language processing by demonstrating impressive abilities to perform a wide range of tasks, including machine translation MT. However, the quality and domain of the in-context examples used to prompt these models can significantly impact their performance for specific tasks. In this talk, I will discuss two recent papers that propose to optimize in-context examples and leverage bilingual dictionaries to enhance the quality and controllability of MT with LLMs. First, I will explore the impact of in-context examples on the translation quality of LLMs and highlight the challenges of selecting good examples in both in-domain and out-of-domain settings. Then, I will discuss how we can leverage bilingual dictionaries to provide fine-grained phrase-level control hints in the prompts of LLMs.

    Biography: Marjan Ghazvininejad is a senior research scientist at Facebook AI Research. She received her Ph.D. at the University of Southern California on neural creative language generation. Her research interests include text representation, language generation, and machine translation. Her recent research has focused on how to optimize the use of large language models in various applications.


    Host: Jon May and Justin Cho

    More Info: https://nlg.isi.edu/nl-seminar/

    Webcast: https://usc.zoom.us/j/96863901584

    Location: Information Science Institute (ISI) - Virtual and ISI-Conf Rm#689

    WebCast Link: https://usc.zoom.us/j/96863901584

    Audiences: Everyone Is Invited

    Contact: Pete Zamar

    Event Link: https://nlg.isi.edu/nl-seminar/

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  • CS Colloquium: Alexander Rodríguez (Georgia Tech) - AI for Public Health: Epidemic Forecasting Through a Data-Centric Lens

    Thu, Mar 09, 2023 @ 11:00 AM - 12:00 PM

    Thomas Lord Department of Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Alexander Rodríguez , Georgia Tech

    Talk Title: AI for Public Health: Epidemic Forecasting Through a Data-Centric Lens

    Series: CS Colloquium

    Abstract: Epidemic forecasting is a crucial tool for public health decision making and planning. There is, however, a limited understanding of how epidemics spread, largely due to other complex dynamics, most notably social and pathogen dynamics. With the increasing availability of real-time multimodal data, a new opportunity has emerged for capturing previously unobservable facets of the spatiotemporal dynamics of epidemics. In this regard, my work brings a data-centric perspective to public health via methodological advances in AI at the intersection of time series analysis, spatiotemporal mining, scientific ML, and multi-agent systems. Toward realizing the potential of AI in public health, I addressed multiple challenges stemming from the domain such as data scarcity, distributional changes, and issues arising from real-time deployment to enable our support of CDC's COVID-19 response. This talk will cover methods to address these challenges with novel deep learning architectures for real-time response to disease outbreaks and new techniques for end-to-end learning with mechanistic epidemiological models-”based on differential equations and agent-based models-”that bridge ML advances and traditional domain knowledge to leverage individual merits. I will conclude by discussing challenges and opportunities in public health for data and computer scientists.


    This lecture satisfies requirements for CSCI 591: Research Colloquium

    Biography: Alexander Rodríguez is a PhD candidate in the College of Computing at Georgia Tech, advised by Prof. B. Aditya Prakash. His research is at the intersection of machine learning, time series, and scientific modeling, and his main application domains are public health and community resilience. He has published at top venues such as AAAI, NeurIPS, ICLR, KDD, WWW, AAMAS, PNAS and has organized workshops and tutorials at AAAI and KDD. His work won the best paper award at ICML AI4ABM 2022 and was awarded the 1st place in the Facebook/CMU COVID-19 Challenge and the 2nd place in the C3.ai COVID-19 Grand Challenge. He was also invited to the Heidelberg Laureate Forum in 2022, and named a 'Rising Star in Data Science' by the University of Chicago Data Science Institute in 2021 and a 'Rising Star in ML & AI' by the University of Southern California in 2022.


    Host: Bistra Dilkina

    Location: Olin Hall of Engineering (OHE) - 132

    Audiences: Everyone Is Invited

    Contact: Assistant to CS chair

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  • BME Seminar Speaker, Dr. Nathan Shaner

    Fri, Mar 10, 2023 @ 11:00 AM - 12:00 PM

    Alfred E. Mann Department of Biomedical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Nathan Shaner, Associate Professor, Neurosciences, UCSD

    Talk Title: Fluorescent protein engineering

    Host: BME Chair Peter Wang - ZOOM link available on request

    More Information: BMEseminar Nathan Shaner.pdf

    Location: Corwin D. Denney Research Center (DRB) - 145

    Audiences: Everyone Is Invited

    Contact: Michele Medina

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  • Spring Break Writing Retreat for Viterbi Ph.D. Students

    Fri, Mar 10, 2023 @ 11:00 AM - 04:00 PM

    Viterbi School of Engineering Student Affairs

    Workshops & Infosessions


    Spring Break Writing Retreat

    Join us at the Hub for a Spring Break Writing Retreat for concentrated writing time!

    Quiet writing space, lunch, and optional one-on-one writing consultations with Hub staff provided.

    RSVP by March 1 here. Space is very limited.

    When: Friday, March 10 (11am to 4pm) and Monday, March 13 (11am to 4pm)

    Where: RTH 222

    More Information: Hub Spring Writing Retreat.pdf

    Location: Ronald Tutor Hall of Engineering (RTH) - 222

    Audiences: Ph.D. Students with RSVP

    Contact: Helen Choi

    Event Link: https://sites.google.com/usc.edu/eishub/writing-retreat

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