BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Workshops @ UCLA - ECPv6.17.4.1//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:Workshops @ UCLA
X-ORIGINAL-URL:https://workshops.ucla.edu
X-WR-CALDESC:Events for Workshops @ UCLA
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:20250309T100000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
TZNAME:PST
DTSTART:20251102T090000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
TZNAME:PDT
DTSTART:20260308T100000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
TZNAME:PST
DTSTART:20261101T090000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
TZNAME:PDT
DTSTART:20270314T100000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
TZNAME:PST
DTSTART:20271107T090000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260808T160000
DTEND;TZID=America/Los_Angeles:20260808T170000
DTSTAMP:20260808T195157Z
CREATED:20260724T172152Z
LAST-MODIFIED:20260808T195157Z
UID:10003792-1786204800-1786208400@workshops.ucla.edu
SUMMARY:Sriram Sankararaman\, Professor of Computer Science\, Human Genetics and Computational Medicine – UCLA
DESCRIPTION:“Insights into the evolutionary and genetic architecture of human complex traits from biobank-scale data” \nThe quest to understand the interplay between evolution\, genes and traits has  been revolutionized by the collection of rich phenotypic and genetic data across millions of individuals in diverse populations.  However analyses of these Biobank-scale datasets present substantial statistical and computational challenges. I will present new statistical and computational techniques that aim to provide a deeper understanding of the role of archaic admixture in human evolution and the genetic architecture of complex traits. While multiple instances of interbreeding between modern and archaic humans (Neanderthals and Denisovans) have been documented\, our understanding of the structure and functional impact of archaic introgression remains limited. I will discuss how we combine maps of introgressed archaic DNA with biobank-scale data to assess the contribution of introgressed alleles to complex traits. In the second part of my talk\, I will describe our efforts to understand the genetic architecture underlying complex traits. Our current picture of genetic architecture is largely one of additive models due\, in part\, to the computational challenges involved in fitting even the simplest models at scale. I will describe a new class of algorithms that can learn non-additive(context-dependent) models of genetic architecture while scaling to biobanks with millions of individuals. By applying these methods to data from the UK Biobank\, we obtain novel insights into the contributions of additive\, dominance\, gene-environment\, and gene-gene interaction effects to complex trait variation.
URL:https://workshops.ucla.edu/workshop/sriram-sankararaman-professor-of-computer-science-human-genetics-and-computational-medicine-ucla/
LOCATION:Boyer Hall 159
CATEGORIES:QCBio Seminar Series,Research Seminars
ATTACH;FMTTYPE=image/jpeg:https://workshops.ucla.edu/wp-content/uploads/2026/07/Sriram-clNixd.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260731T160000
DTEND;TZID=America/Los_Angeles:20260731T170000
DTSTAMP:20260731T195144Z
CREATED:20260724T172152Z
LAST-MODIFIED:20260731T195144Z
UID:10003791-1785513600-1785517200@workshops.ucla.edu
SUMMARY:Aaron Meyer\, Associate Professor\, Department of Bioengineering – UCLA
DESCRIPTION:“Building an Integrative View of Immunity with Data Tensors” \nHigh-throughput technologies now allow us to characterize immune responses with comprehensive scale and detail. While profiling cells across parameters like time\, perturbations\, and genetics yields rich data\, these multidimensional datasets challenge conventional analysis. Standard workflows typically flatten data into two-dimensional matrices\, sacrificing the essential context provided by the experimental structure. Instead\, I will show how tensor decompositions can preserve the structure of multidimensional studies. Choosing the right mathematical representation allows us to derive robust insights—from utilizing in vitro characterization to optimize engineered cytokines\, to identifying single-cell features that define autoimmunity. Furthermore\, these approaches enable integrative analysis that links cellular states to alterations at the tissue\, organ\, and individual scales.
URL:https://workshops.ucla.edu/workshop/aaron-meyer-associate-professor-department-of-bioengineering-ucla/
LOCATION:Boyer Hall 159
CATEGORIES:QCBio Seminar Series,Research Seminars
ATTACH;FMTTYPE=image/png:https://workshops.ucla.edu/wp-content/uploads/2026/07/Meyer-8.19.53-AM-XAGxwv.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260724T160000
DTEND;TZID=America/Los_Angeles:20260724T170000
DTSTAMP:20260724T193617Z
CREATED:20260721T172201Z
LAST-MODIFIED:20260724T193617Z
UID:10003790-1784908800-1784912400@workshops.ucla.edu
SUMMARY:Amy Goldberg\, Associate Professor\, Human Genetics\, UCLA
DESCRIPTION:TITLE: “Evolutionary perspectives on malaria” \nPathogen genomics increasingly guides public health decisions\, yet organisms with complex life cycles can produce genealogies that violate assumptions of standard population genetic methods. Similarly\, despite decades of population-genetic methods to infer population or adaptive histories in humans\, allele frequencies are often modeled to be roughly constant on short timescales relevant for public health. Here I discuss computational methods to leverage the growing amounts of genomic data from both host and pathogen perspectives. In particular\, I consider genomic evolution on ecologically and epidemiologically relevant timescales\, with implications for public health and basic biology.
URL:https://workshops.ucla.edu/workshop/amy-goldberg-associate-professor-human-genetics-ucla/
LOCATION:Boyer Hall 159
CATEGORIES:QCBio Seminar Series,Research Seminars
ATTACH;FMTTYPE=image/jpeg:https://workshops.ucla.edu/wp-content/uploads/2026/07/PhotoHandler-ZT2lTs.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260717T160000
DTEND;TZID=America/Los_Angeles:20260717T170000
DTSTAMP:20260717T193215Z
CREATED:20260713T170243Z
LAST-MODIFIED:20260717T193215Z
UID:10003789-1784304000-1784307600@workshops.ucla.edu
SUMMARY:Neil Lin Assistant Professor\,  Mechanical and Aerospace Engineering  –  UCL
DESCRIPTION:“Unraveling Signaling Pathway Crosstalk Using LLMs” \nLiving cells do not process information through isolated\, linear pathways. Instead\, they rely on an intricate network of signaling crosstalk to make critical fate decisions. Deciphering this hidden cellular conversation remains one of the greatest challenges in targeted oncology and regenerative medicine. Yet traditional mechanistic models struggle to capture its complexity\, while the scale of modern single-cell datasets exceeds what can be analyzed manually. My lab asks a simple question: Can large language models\, designed to understand human language\, be repurposed to decode the language of cellular signaling? In this talk\, I will describe our efforts to develop LLMs as specialized\, locally deployed biological reasoning engines. By grounding these models in both the biomedical literature and high-dimensional single-cell data\, we show how they can identify key regulatory nodes where signaling pathways converge. Finally\, I will discuss how integrating biological knowledge with empirical data enables prediction of nonlinear cellular responses\, providing a scalable\, mechanistically informed framework for discovering novel therapeutic combinations.
URL:https://workshops.ucla.edu/workshop/neil-lin-assistant-professor-mechanical-and-aerospace-engineering-ucl/
LOCATION:Boyer Hall 159
CATEGORIES:QCBio Seminar Series,Research Seminars
ATTACH;FMTTYPE=image/jpeg:https://workshops.ucla.edu/wp-content/uploads/2026/07/neil_lin_headshot.jpg-copy-wIXzh5.jpg
END:VEVENT
END:VCALENDAR