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Events for December 05, 2024
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OKRA Forum: Ranjit Singh Atwal
Thu, Dec 05, 2024 @ 10:00 AM - 11:00 AM
Alfred E. Mann Department of Biomedical Engineering, USC Viterbi School of Engineering
Conferences, Lectures, & Seminars
Speaker: Ranjit Singh Atwal, Moderna Global Fellow and Research Assistant Professor in Kelley Laboratories at Northwestern University Feinberg School of Medicine
Talk Title: LeaPFrog: Highly Scalable Cell Profiling for Druggable Target Discovery and Therapeutics Development
Abstract: Registration is required for this event: https://northwestern.zoom.us/webinar/register/8017315250267/WN_6P8qnb64Qn-VQM84m3tbXA
Large-scale genetic perturbation and cell profiling technologies have revolutionized the field of molecular biology and has the potential to transform many aspects of healthcare and biotechnology in the coming decade. Nowadays, CRISPR/Cas9-based genome-scale functional genetic screens are being routinely used to identify key genetic regulators of a phenotype of interest. However, the identification of genetic modifications that lead to a phenotypic change requires sorting large numbers of cells, which increases operational times and costs and often limits cell viability. To fully realize the potential of whole-genome CRISPR screening, advances in high-throughput cell sorting technologies are needed. Over the last 5 years, our research group has developed the use of immunomagnetic cell sorting facilitated by microfluidic chips as a rapid and scalable screening platform (termed LeaPFroG) for efficiently and accurately analyzing large numbers of CRISPR-edited cells. I will present how we have leveraged the high-throughput cell sorting capabilities of our LeaPFroG platform as a discovery engine to identify and validate novel checkpoint inhibitors for modulating tumor cell/immune cell interactions and elucidating allele-specific functional regulators of previously undruggable proteins. Lastly, I will outline how the experiences and lessons from these functional studies are being applied to the identification of cellular determinants impacting the mesangial cells in IgA Nephropathy.
Biography: Dr. Ranjit Singh Atwal is a Moderna Global Fellow and Research Assistant Professor in Kelley Laboratories at Northwestern University Feinberg School of Medicine in the Department of Biochemistry and Molecular Genetics. Dr. Atwal received his Ph.D. from McMaster University (Canada) and was a postdoctoral fellow at the Center for Genomic Medicine and faculty member at Massachusetts General Hospital and Harvard Medical School. His research investigations are focused on expanding the use of large-scale phenotypic screening technologies to address unmet needs across diverse biological realms. Current research investigations include the identification of functional regulators of undruggable proteins, rare-cell enrichment based in vivo phenotypic CRISPR screening to identify genetic regulators of metastasis and the use of tissue-selective delivery systems for therapeutic genome editing applications. He is also a founding scientist of a pre-seed startup focused on translating findings at the bench towards the development of targeted therapeutics. As part of the NU-OKRA/NUGokidney Resource Development Core, he is supporting the adaptation of the LeaPFroG platform to enable rapid enrichment of disease-relevant population of kidney cells to empower functional studies to better understand the mechanisms of kidney disease.
Host: Northwestern University & University of Southern California George M. O'Brien Kidney Resource Center
More Info: https://northwestern.zoom.us/webinar/register/8017315250267/WN_6P8qnb64Qn-VQM84m3tbXA
Webcast: https://northwestern.zoom.us/webinar/register/8017315250267/WN_6P8qnb64Qn-VQM84m3tbXAMore Information: Webinar graphic - 12.05.24.png
WebCast Link: https://northwestern.zoom.us/webinar/register/8017315250267/WN_6P8qnb64Qn-VQM84m3tbXA
Audiences: Everyone Is Invited
Contact: Greta Harrison
Event Link: https://northwestern.zoom.us/webinar/register/8017315250267/WN_6P8qnb64Qn-VQM84m3tbXA
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NL Seminar-The Duality of Bias in Large Language Models: Leveraging Community Perspectives and Uncovering Ideological Vulnerabilities
Thu, Dec 05, 2024 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Zihao He, USC/ISI
Talk Title: The Duality of Bias in Large Language Models: Leveraging Community Perspectives and Uncovering Ideological Vulnerabilities
Series: NL Seminar
Abstract: REMINDER: Meeting hosts only admit on-line guests that they know to the Zoom meeting. Hence, you’re highly encouraged to use your USC account to sign into Zoom. If you’re an outside visitor, please inform us at (nlg-seminar-host(at)isi.edu) to make us aware of your attendance so we can admit you. Specify if you will attend remotely or in person at least one business day prior to the event. Provide your: full name, job title and professional affiliation and arrive at least 10 minutes before the seminar begins. If you do not have access to the 6th Floor for in-person attendance, please check in at the 10th floor main reception desk to register as a visitor and someone will escort you to the conference room location. Join Zoom Meeting https://usc.zoom.us/j/98068942358?pwd=MYU6jzrZIjaIYPEuIHG0C61g3BTEXB.1 Meeting ID: 980 6894 2358 Passcode: 716186
Large language models (LLMs) have demonstrated remarkable capabilities in understanding and generating human-like text. As these models become increasingly integrated into various applications, it is crucial to understand their potential for both beneficial and problematic impacts on society. In this talk, I will explore the dual nature of bias in LLMs through two recent studies that employ similar methodologies but reveal contrasting implications. First, I will discuss COMMUNITY-CROSS-INSTRUCT, an innovative framework that aligns LLMs with online community perspectives to create “digital twins” for efficient public opinion analysis. Then, I will present findings on LLMs’ susceptibility to ideological influences through targeted instruction tuning.
By examining these complementary perspectives, I aim to showcase the innovative potential of LLMs in social science research while also highlighting the importance of understanding their malleability. This presentation will contribute to the ongoing dialogue on responsible AI development, illustrating how careful application of LLM capabilities can lead to valuable insights while also emphasizing the need for awareness of their limitations and vulnerabilities.
Biography: Zihao He is a final-year PhD candidate in computer science at University of Southern California (USC). He is advised by Prof. Kristina Lerman. His research interests lie at the intersection of natural language processing and computational social science. Specifically, Zihao has been focusing on evaluating the societal impacts of large language models (LLMs) and investigating their vulnerability to ideological influences. His work has been published in top-tier conferences like ACL, EMNLP, and ICWSM.
Previously, Zihao received his undergraduate degree from Beijing University of Posts and Telecommunications (BUPT). He spent one year of master’s studies at Tsinghua University. He has interned at TikTok, Amazon, and DiDi Global.
If speaker approves to be recorded for this NL Seminar talk, it will be posted on the USC/ISI YouTube page within 1-2 business days: https://www.youtube.com/user/USCISI. Subscribe here to learn more about upcoming seminars: https://www.isi.edu/events/ For more information on the NL Seminar series and upcoming talks, please visit: https://www.isi.edu/research-groups-nlg/nlg-seminars/
Host: Jonathan May and Katy Felkner
More Info: https://www.isi.edu/research-groups-nlg/nlg-seminars/
Webcast: https://usc.zoom.us/j/98068942358?pwd=MYU6jzrZIjaIYPEuIHG0C61g3BTEXB.1Location: Information Science Institute (ISI) - Conf Rm#689
WebCast Link: https://usc.zoom.us/j/98068942358?pwd=MYU6jzrZIjaIYPEuIHG0C61g3BTEXB.1
Audiences: Everyone Is Invited
Contact: Pete Zamar
Event Link: https://www.isi.edu/research-groups-nlg/nlg-seminars/
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PhD Dissertation Defense - Jingyao Ren
Thu, Dec 05, 2024 @ 11:00 AM - 01:00 PM
Thomas Lord Department of Computer Science
University Calendar
Title: Advancements in Understanding the Empirical Hardness of the Multi-Agent Pathfinding Problem
Date: December 5TH, 11:00 AM to 1:00 PM
Location: EEB 110
Committee: T.K. Satish Kumar (Chair), Stefanos Nikolaidis, Feifei Qian, Sven Koenig
Abstract: Multi-Agent Path Finding~(MAPF) involves finding collision-free paths for agents in shared environments and is crucial for applications like automated warehouses and swarm control. While solving MAPF optimally is NP-hard, many real-world instances are solvable efficiently, though factors affecting instance hardness remain unclear. This dissertation explores MAPF empirical hardness, addressing what makes instances hard, how to predict hardness, and ways to generate challenging instances. Key contributions include formalizing empirical hardness research in MAPF, introducing the MAPFAST algorithm selection framework, identifying map connectivity as a critical factor, and demonstrating methods to generate instances with varying hardness.Location: Hughes Aircraft Electrical Engineering Center (EEB) - 110
Audiences: Everyone Is Invited
Contact: Jingyao Ren
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Is Data All You Need?: Large Robot Action Models and Good Old Fashioned Engineering
Thu, Dec 05, 2024 @ 03:00 PM - 05:15 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Ken Goldberg, Ph.D., William S. Floyd Distinguished Chair of Engineering - UC Berkeley
Talk Title: Is Data All You Need?: Large Robot Action Models and Good Old Fashioned Engineering
Abstract: Enthusiasm has been skyrocketing for humanoids based on recent advances in "end-to-end" large robot action models. Initial results are promising, and several collaborative efforts are underway to collect the needed demonstration data. But is data really all you need?
Although end-to-end Large Vision, Language, Action (VLA) Models have potential to generalize and reliably solve all problems in robotics, initial results have been mixed[1]. It seems likely that the size of the VLA state space and dearth of available demonstration data, combined with challenges in getting models to generalize beyond the training distribution and the inherent challenges in interpreting and debugging large models, will make it difficult for pure end-to-end systems to provide the kind of robot performance that investors expect in the near future.
In this presentation, I share my concerns about current trends in robotics, including task definition, data collection, and experimental evaluation. I propose that to reach expected performance levels, we will need "Good Old Fashioned Engineering (GOFE)" – modularity, algorithms, and metrics. I'll present MANIP[2], a modular systems architecture that can integrate learning with well-established procedural algorithmic primitives such as Inverse Kinematics, Kalman Filters, RANSAC outlier rejection, PID modules, etc. I’ll show how we are using MANIP to improve performance on robot manipulation tasks such as grasping, cable untangling, surgical suturing, motion planning, and bagging, and propose open directions for research.
Presented at:
>Stanford Robotics Seminar, 19 April, 2024 4-min video clip
>Berkeley AI Research (BAIR) Seminar, 24 April, 2024
>IEEE ICRA Workshop, Yokohama Japan, 16 May 2024
>Berkeley Sky Lab Retreat Keynote, Santa Cruz, 29 May 2024
>Amazon Lab 126, Sunnyvale, CA, 18 June 2024
>Apple Park, Cupertino, CA, 24 July 2024
>Toyota Research Lab, San Jose, CA, 31 July 2024
>ICRA@40 Keynote, Rotterdam, 23 Sept 2024
>WAFR Keynote, Chicago, 7 Oct 2024
>Univ of Southern California (USC) Computer Science Distinguished Lecture Seminar, 5 Dec 2024
[1] Nishanth J. Kumar. Will Scaling Solve Robotics? The idea of solving the biggest robotics challenges by training large models is sparking debate. IEEE Spectrum. 28 May 2024.
[2] MANIP: A Modular Architecture for iNtegrating Iteractive Perception into Long-Horizon Robot Manipulation Systems. Justin Yu*, Tara Sadjadpour*, Abby O’Neill, Mehdi Khfifi, Lawrence Yunliang Chen, Richard Cheng, Ashwin Balakrishna, Thomas Kollar, Ken Goldberg. IEEE/RSJ International Conference on Robots and Systems (IROS), Abhu Dhabi, UAE. Oct 2024. Paper
**LOCATION CHANGE**
GINSBURG COMPUTATION HALL (GCS)
AUDITORIUM
This lecture satisfies requirements for CSCI 591: Research Colloquium.
This lecture will be presented as a HYBRID presentation, but will not be recorded.
Zoom details below: https://usc.zoom.us/j/94205149719?pwd=LjETcnHLvCzyDbB6LjjxfknZaab3Dm.1
Meeting ID: 942 0514 9719 | Passcode: 400232
Biography: Ken Goldberg is William S. Floyd Distinguished Chair of Engineering at UC Berkeley and Chief Scientist of Ambi Robotics and Jacobi Robotics. Ken leads research in robotics and automation: grasping, manipulation, and learning for applications in warehouses, industry, homes, agriculture, and robot-assisted surgery. He is Professor of IEOR with appointments in EECS and Art Practice. Ken is Chair of the Berkeley AI Research (BAIR) Steering Committee (60 faculty) and is co-founder and Editor-in-Chief emeritus of the IEEE Transactions on Automation Science and Engineering (T-ASE). He has published ten US patents, over 400 refereed papers, and presented over 600 invited lectures to academic and corporate audiences.
http://goldberg.berkeley.edu
Host: USC Thomas Lord Department of Computer Science
More Info: https://forms.gle/w1r6Yo3se3WU8Bou7
Webcast: https://usc.zoom.us/j/94205149719?pwd=LjETcnHLvCzyDbB6LjjxfknZaab3Dm.1Location: Ginsburg Hall (GCS) - Auditorium
WebCast Link: https://usc.zoom.us/j/94205149719?pwd=LjETcnHLvCzyDbB6LjjxfknZaab3Dm.1
Audiences: Everyone Is Invited
Contact: USC Thomas Lord Department of Computer Science
Event Link: https://forms.gle/w1r6Yo3se3WU8Bou7