BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Halıcıoğlu Data Science Institute - UC San Diego - ECPv6.16.2//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:Halıcıoğlu Data Science Institute - UC San Diego
X-ORIGINAL-URL:https://datascience.ucsd.edu
X-WR-CALDESC:Events for Halıcıoğlu Data Science Institute - UC San Diego
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/Los_Angeles
BEGIN:DAYLIGHT
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
TZNAME:PDT
DTSTART:20230312T100000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
TZNAME:PST
DTSTART:20231105T090000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
TZNAME:PDT
DTSTART:20240310T100000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
TZNAME:PST
DTSTART:20241103T090000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
TZNAME:PDT
DTSTART:20250309T100000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
TZNAME:PST
DTSTART:20251102T090000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240722T140000
DTEND;TZID=America/Los_Angeles:20240722T150000
DTSTAMP:20260530T183802
CREATED:20240717T171423Z
LAST-MODIFIED:20240717T171423Z
UID:10000488-1721656800-1721660400@datascience.ucsd.edu
SUMMARY:Mayank Garg | Tackling Acute Respiratory Distress Syndrome (ARDS) : Integrated and Holistic Approaches
DESCRIPTION:When Monday July 22nd 2:00pm\nWhere: HDSI MPR 123\nZoom Info: http://bit.ly/HDSI-Seminars \nTitle: “Tackling Acute Respiratory Distress Syndrome (ARDS) : Integrated and Holistic Approaches” \nAbstract: ARDS is a complex heterogenous disorder which forms a significant health care burden. Pathophysiologically\, ARDS is caused by multiple aetiologies which can lead to the diversity in clinical presentation seen. In our work with preclinical rodent models\, we investigate the role of host mitochondrial factors in skewing the inflammation resolution pathways leading to an aggravated and exaggerated state of inflammation and possibly increased mortality. This work elicits another instance of how endotype identification is essential in ARDS (and other diseases)\, to improve translation of basic research. A potential solution for this could be integration of data driven approaches to derive biological insights which would serve as essential context for preclinical disease models. \nMayank Garg Bio: Mayank is a physician scientist who completed his medical graduation and clinical training from IPGME&R and SSKM Hospital\, Kolkata\, India. He gained brief experience in intensive care before switching to experimental research at CSIR-Institute of Genomics and Integrative Biology (CSIR-IGIB)\, Delhi\, India. He is affiliated with Ashoka University as a Simons Ashoka Early Career fellow. \nMayank is currently pursuing quantitative health research to explore the heterogeneity of ICU disorders like Sepsis and ARDS. Realising the importance of context in biomedical research\, he aims to derive mechanisms to leverage data science in a clinically relevant manner\, and to validate them using contextual application of experimental models. \nHe also believes in the potential of digital transformation in personal empowerment\, for improving health-care\, sick-care\, and clinical research. He is collaborating on a project to develop a digital framework to assist data collection and aid analysis for personalized lifestyle medicine. He plans to leverage the power of LLMs integrated with such digital frameworks for healthcare and healthcare research. He strongly advocates for collaborative growth and strict ethical standards as the foundation for advancing science.
URL:https://datascience.ucsd.edu/event/mayank-garg-tackling-acute-respiratory-distress-syndrome-ards-integrated-and-holistic-approaches/
LOCATION:Halıcıoğlu Data Science Institute (HDSI)\, Room 123\, 3234 Matthews Ln\, La Jolla\, CA\, 92093\, United States
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://datascience.ucsd.edu/wp-content/uploads/2024/01/cropped-HDSI-UCSD-Image-e1712856546428.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240724T100000
DTEND;TZID=America/Los_Angeles:20240724T110000
DTSTAMP:20260530T183802
CREATED:20240717T171141Z
LAST-MODIFIED:20240717T171141Z
UID:10000489-1721815200-1721818800@datascience.ucsd.edu
SUMMARY:HDSI/TILOS Seminar | Rob Nowak | What Kinds of Functions do Neural Networks Learn? Theory and Practical Applications
DESCRIPTION:When Wednesday July 24th 10:00am *Updated\nWhere: HDSI 123 * Updated\nZoom Info: https://ucsd.zoom.us/j/99334315002 *Updated \nTitle: What Kinds of Functions do Neural Networks Learn?  Theory and Practical Applications \nAbstract:  This talk presents a theory characterizing the types of functions neural networks learn from data. Specifically\, the function space generated by deep ReLU networks consists of compositions of functions from the Banach space of second-order bounded variation in the Radon transform domain. This Banach space includes functions with smooth projections in most directions. A representer theorem associated with this space demonstrates that finite-width neural networks suffice for fitting finite datasets. The theory has several practical applications. First\, it provides a simple and theoretically grounded method for network compression. Second\, it shows that multi-task training can yield significantly different solutions compared to single-task training\, and that multi-task solutions can be related to kernel ridge regressions. Third\, the theory has implications for improving implicit neural representations\, where multi-layer neural networks are used to represent continuous signals\, images\, or 3D scenes. This exploration bridges theoretical insights with practical advancements\, offering a new perspective on neural network capabilities and future research directions.\nBio: Robert Nowak is the Grace Wahba Professor of Data Science and Keith and Jane Nosbusch Professor in Electrical and Computer Engineering at the University of Wisconsin-Madison. His research focuses on machine learning\, optimization\, and signal processing. He serves on the editorial boards of the SIAM Journal on the Mathematics of Data Science and the IEEE Journal on Selected Areas in Information Theory.meeting with him. If…
URL:https://datascience.ucsd.edu/event/hdsi-tilos-seminar-rob-nowak-what-kinds-of-functions-do-neural-networks-learn-theory-and-practical-applications/
LOCATION:Halıcıoğlu Data Science Institute (HDSI)\, Room 123\, 3234 Matthews Ln\, La Jolla\, CA\, 92093\, United States
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://datascience.ucsd.edu/wp-content/uploads/2023/10/TILOS-Square_HDSI-Website-e1712854679822.png
END:VEVENT
END:VCALENDAR