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Events for March 25, 2024
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Gas Turbine Engine Accident Investigation GTAI 24-2Mon, Mar 25, 2024 @ 08:00 AM - 04:00 PM
Aviation Safety and Security Program
University Calendar
This specialized accident investigation course is directed to fixed-wing turbojet and turboprop as well as turbine-powered rotary-wing aircraft. The course examines specific turbine engine investigation methods and provides technical information related to material factors and metallurgical failure investigation. This is a fundamental accident investigation course. Individuals with many years of engine investigations may find this course too basic. It is assumed that the attendee has a basic understanding of jet engines.
Location: Century Boulevard Building (CBB) - 960
Audiences: Everyone Is Invited
Contact: Daniel Scalese
Event Link: https://avsafe.usc.edu/wconnect/CourseStatus.awp?&course=24AGTAI2
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Helicopter Accident Investigation HAI 24-2
Mon, Mar 25, 2024 @ 08:00 AM - 04:00 PM
Aviation Safety and Security Program
University Calendar
The course examines the investigation of helicopter accidents to include processes used to determine the cause. The course includes interactive lectures, various case studies, examination of component wreckage in the classroom, and helicopter wreckage examination in the laboratory. The course includes an examination of helicopter rotor systems, controls, performance variables, flight hazards, and material characteristics involved in helicopter operations and accidents. Although Aircraft Accident Investigation (AAI) is not a prerequisite, it is assumed that the attendee has either completed AAI or has some previous experience in aircraft accident investigation.
Location: Century Boulevard Building (CBB) - 920
Audiences: Everyone Is Invited
Contact: Daniel Scalese
Event Link: https://avsafe.usc.edu/wconnect/CourseStatus.awp?&course=24AHAI2
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USC Symposium on Frontiers of Generative AI Models in Science and Society
Mon, Mar 25, 2024 @ 08:30 AM - 06:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Various, USC Machine Learning Center
Talk Title: USC Symposium on Frontiers of Generative AI Models in Science and Society
Abstract: The USC Machine Learning Center and Computer Science Department is excited to host the syposium on "Frontiers of Generative AI Models in Science and Society". Experts in generative AI models will discuss recent progresses and their applications in science and soceity.
Keynote Speakers: Alessandro Vespignani (Northeastern University), Nitesh Chawla (Notre Dame), Yizhou Sun (UCLA), & Jian Ma (CMU)
Spotlight Speakers: Jieyu Zhao, Robin Jia, Yue Wang, Vatsal Sharan, & Ruishan Liu (USC Thomas Lord Department of Computer Science)
Host: USC Machine Learning Center
More Info: https://www.eventbrite.com/e/usc-symposium-on-frontiers-of-generative-ai-models-in-science-and-society-tickets-860269668737?aff=oddtdtcreator
Location: Michelson Center for Convergent Bioscience (MCB) - 101
Audiences: Everyone Is Invited
Contact: Thomas Lord Department of Computer Science
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EiS Communications Hub Drop-In Hours
Mon, Mar 25, 2024 @ 10:00 AM - 01:00 PM
Viterbi School of Engineering Student Affairs
Workshops & Infosessions
Viterbi Ph.D. students are invited to stop by the EiS Communications Hub for one-on-one instruction for their academic and professional communications tasks. All instruction is provided by Viterbi faculty at the Engineering in Society Program.
Location: Ronald Tutor Hall of Engineering (RTH) - 222A
Audiences: Viterbi Ph.D. Students
Contact: Helen Choi
Event Link: https://sites.google.com/usc.edu/eishub/home?authuser=0
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EiS Communications Hub Drop-In Hours
Mon, Mar 25, 2024 @ 10:00 AM - 01:00 PM
Engineering in Society Program
Student Activity
Drop-in hours for writing and speaking support for Viterbi Ph.D. students
Location: Ronald Tutor Hall of Engineering (RTH) - 222
Audiences: Everyone Is Invited
Contact: Helen Choi
Event Link: https://sites.google.com/usc.edu/eishub/home
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CS Colloquium: Junzhe Zhang - Towards Causal Reinforcement Learning
Mon, Mar 25, 2024 @ 10:00 AM - 11:00 AM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Junzhe Zhang, Columbia University
Talk Title: Towards Causal Reinforcement Learning
Abstract: Causal inference provides a set of principles and tools that allows one to combine data and knowledge about an environment to reason with questions of a counterfactual nature - i.e., what would have happened if the reality had been different - even when no data of this unrealized reality is currently available. Reinforcement learning provides a collection of methods that allows the agent to reason about optimal decision-making under uncertainty by trial and error - i.e., what would the consequences (e.g., subsequent rewards, states) be had the action been different? While these two disciplines have evolved independently and with virtually no interaction, they operate over various aspects of the same building block, i.e., counterfactual reasoning, making them umbilically connected. This talk will present a unified theoretical framework, called causal reinforcement learning, that explores the nuanced interplays between causal inference and reinforcement learning. I will discuss a recent breakthrough in partial identification that allows one to infer unknown causal effects from a combination of model assumptions and available data. Delving deeper, I will then demonstrate how this method could be applicable to address some practical challenges in classic reinforcement learning tasks, including robust off-policy evaluation from confounded observations and accelerating online learning with offline data. This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Junzhe Zhang is a postdoctoral research scientist in the Causal AI lab at Columbia University. He obtained his doctoral degree in Computer Science at Columbia University, advised by Elias Bareinboim. His research centers on causal inference theory and its applications in reinforcement learning, algorithmic fairness, and explainability. His works have been selected for oral presentations in top refereed venues such as NeurIPS.
Host: Sven Koenig
Location: Olin Hall of Engineering (OHE) - 132
Audiences: Everyone Is Invited
Contact: CS Faculty Affairs
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ECE Seminar: Dr. Guanghan Meng, "Capturing Life: Optical Microscopy for in vivo Deep Tissue Imaging at High Spatiotemporal Resolution"
Mon, Mar 25, 2024 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Guanghan Meng, Postdoctoral Scholar, Dept of EECS, UC Berkeley
Talk Title: Capturing Life: Optical Microscopy for in vivo Deep Tissue Imaging at High Spatiotemporal Resolution
Abstract: Optical microscopy has become an indispensable tool for non-invasive, high-resolution in vivo imaging of living organisms. Its capability to provide insights into real-time physiological and pathological processes within the body underscores its significance in bioscience and medicine. However, conventional optical microscopy methods have certain limitations. For instance, multiphoton fluorescence microscopy, the method of choice for in vivo imaging through scattering tissue such as the mammalian brains, delivers excellent resolution but falls short in speed for capturing rapid biological activities, such as blood flow dynamics. On the other hand, optical coherence tomography (OCT), a label-free deep-tissue imaging method, stands as a powerful instrument in contemporary optometry clinics, but its high cost limits its broad use, especially in lower-income communities. In this presentation, I will share my research on the development of high-speed multiphoton fluorescence microscopy and cost-effective OCT for brain and eye imaging, respectively, through the utilization of both optical engineering and computational methods.
Biography: Dr. Guanghan Meng, currently a postdoctoral scholar in the Department of Electrical Engineering and Computer Science at the University of California, Berkeley, focuses on advancing high-speed, high-resolution fluorescence, and label-free microscopy technologies for deep tissue imaging in vivo. Having earned her PhD from the same university, her doctoral research spanned the disciplines of Molecular and Cell Biology and Physics, primarily concentrating on enhancing two-photon fluorescence microscopy for mouse brain imaging. At present, she is working on computational label-free imaging with a specific interest in the human eye. Guanghan has been recognized with various best presentation awards at scientific conferences and is a recipient of the Berkeley Center for Innovation in Vision and Optics (CIVO) postdoctoral fellowship. Guanghan is also an invited lecturer at the 17th Edition of the Frontiers in Neurophotonics Summer School in Quebec City, Canada in 2024.
Host: Dr. Justin Haldar, jhaldar@usc.edu
Webcast: https://usc.zoom.us/j/96234786783?pwd=eXF0NnlvNEhPRHllS1NDUEFZWklSdz09Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
WebCast Link: https://usc.zoom.us/j/96234786783?pwd=eXF0NnlvNEhPRHllS1NDUEFZWklSdz09
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
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CSC/CommNetS-MHI Seminar: Chandra Murthy
Mon, Mar 25, 2024 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Chandra Murthy, Professor, Department of Electrical Communication Engineering | Indian Institute of Science, Bangalore, India
Talk Title: Sparsity-aware Bayesian Inference and its Applications
Series: CSC/CommNetS-MHI Seminar Series
Abstract: This talk presents a set of tools based on a Bayesian framework to address the general problem of sparse signal recovery, and discusses the challenges associated with them. Bayesian methods offer superior performance compared to convex optimization-based methods and are largely parameter tuning-free. They also have the flexibility necessary to deal with a diverse range of measurement modalities and structured sparsity in signals than hitherto possible. We discuss recent developments towards providing rigorous theoretical guarantees for these methods. Further, we show that, by re-interpreting the Bayesian cost function as a technique to perform covariance matching, one can develop new and ultra-fast Bayesian algorithms for sparse signal recovery. As example applications, we discuss the utility of these algorithms in the context of (a) 5G communications with several case studies such as wideband time-varying channel estimation, low-resolution ADCs, etc, and (b) controllability and observability of linear dynamical systems under sparsity constraints.
Biography: Chandra R. Murthy is a professor in the department of Electrical Communication Engineering at the Indian Institute of Science, Bangalore, India. His research interests are in sparse signal recovery, energy harvesting-based communication, performance analysis, and optimization of 5G and beyond communications. Papers coauthored by him have received Student/Best Paper Awards at the NCC 2014, IEEE ICASSP 2018, IEEE ISIT 2021, IEEE SPAWC 2022, and NCC 2023. He is a senior area editor for the IEEE Transactions on Signal Processing and the IEEE Transactions on Information Theory. He is an elected member of the IEEE SPS SAM Technical Committee. He is an IEEE Fellow (Class of 2023), and a fellow of the Indian National Academy of Engineering (2023).
Host: Dr. Urbashi Mitra, ubli@usc.edu
More Information: 2024.03.25 CSC Seminar - Chandra Murthy.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 132
Audiences: Everyone Is Invited
Contact: Miki Arlen
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Ph.D. Thesis Defense - Ali Omrani
Mon, Mar 25, 2024 @ 02:00 PM - 04:00 PM
Thomas Lord Department of Computer Science
University Calendar
Ph.D. Thesis Defense - Ali Omrani
Committee: Morteza Dehghani (Chair), Xiang Ren, Robin Jia, Payam Piray, and Jeffrey Sorensen
Title: Countering Problematic Content in Digital Space: Bias Reduction and Dynamic Content Adaptation
Abstract: Problematic content, such as hate speech, poses a significant challenge to society, leading to discrimination and exclusion while undermining inclusivity and well-being. This thesis proposal outlines my efforts to create adaptable solutions for combating problematic content in digital space through a theory-motivated approach that bridges language technology and social sciences. I will begin by presenting an innovative group-agnostic method for bias mitigation in language models, which is grounded in a deep understanding of stereotyping from social psychology. Subsequently, I will introduce a novel continual learning framework for problematic content detection that captures the ever-evolving nature of this issue. Afterward, I discuss my work that extends this framework to multilingual settings, with a specific emphasis on two key aspects: 1. Harnessing cultural diversity for cross-lingual transfer of offensive language detection and 2. Investigating the challenges posed by disparities in data quality across various languages.Date and Time: March 25th, 2:00 PM - 4:00 PM
Location: Room 266, USC Brain and Creativity Institute 605, 3620 McClintock Ave, Los Angeles, CA 90089
Location: Dornsife Neuroscience Imaging Center (DNI) - 266
Audiences: Everyone Is Invited
Contact: CS Events
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How to Search for a Job in Today’s Digital Age
Mon, Mar 25, 2024 @ 04:00 PM - 05:00 PM
Viterbi School of Engineering Career Connections
Workshops & Infosessions
THIS EVENT WILL BE HOSTED HYBRID: IN-PERSON & ONLINE SIMULTANEOUSLY Zoom link: https://usc.zoom.us/meeting/register/tJYtduquqT8pHtJvtZs8at8XEZCbaNBjyFzd Learn about how recruitment has changed in this virtual environment and review best practices by attending this professional development Q&A moderated by Viterbi Career Connections staff or Viterbi employer partners. For more information about all workshops, please visit viterbicareers.usc.edu/workshops.
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: All Viterbi
Contact: RTH 218 Viterbi Career Connections
Event Link: https://usc.zoom.us/meeting/register/tJYtduquqT8pHtJvtZs8at8XEZCbaNBjyFzd
