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BEGIN:VEVENT
SUMMARY:IC Colloquium: Language theory into practice\, a play in three act
 s
DTSTART:20220228T100000
DTEND:20220228T110000
DTSTAMP:20260406T052236Z
UID:411c7ac1382053c607642b80122b732239fa25f8b9e9dee30f8309cf
CATEGORIES:Conferences - Seminars
DESCRIPTION:By: Ningning Xie - University of Cambridge\nIC Faculty candida
 te\n\nAbstract\nComputer development has come a long way. Along with the e
 volution of computers\, advances in high-level programming languages allow
  us to write large-scale software systems easily. While new language featu
 res significantly extend the language expressive power\, they often lack t
 heoretical development and lead to subtle implementation bugs. Moreover\, 
 while high-level languages abstract over low-level aspects and thus elimin
 ate many sources of errors\, the abstraction often comes with a runtime pe
 nalty that results in inefficient low-level code.\n\nIn this talk\, I will
  show how to apply programming language theory to practical programming to
  offer strong static safety and efficiency guarantees in three\ndomains: l
 anguage design\, runtime systems\, and machine learning systems. First\, I
  will demonstrate a type-theoretical formalization of language features\,\
 nfocusing on type inference for dependent types in algebraic datatype decl
 arations. The formalization has guided real-world language implementations
 .\nThen\, I will show that programming language theory reaps benefits beyo
 nd safety. I will present Perceus\, a garbage-free reference counting algo
 rithm with reuse\, that supports high-level programming while preserving l
 ow-level efficiency. Perceus delivers competitive performance compared to 
 state-of-the-art memory reclamation implementations. Finally\, as part of 
 a vision to make programming languages broadly applicable\, I will discuss
  my efforts to apply programming language techniques to machine learning s
 ystems\, by presenting a program synthesis framework that accelerates larg
 e-scale distributed machine learning on hardware platforms.\n\nBio\nNingni
 ng Xie is a research associate at the University of Cambridge. She receive
 d her Ph.D. in Computer Science at the University of Hong Kong in 2021.\nH
 er research interests are in the field of programming languages\, where sh
 e applies programming language theory to a variety of domains\, including 
 language design\, runtime and compiler systems\, and machine learning syst
 ems. In the last two years of her Ph.D. study\, Ningning had research visi
 ts at Microsoft Research Redmond and DeepMind London. Her research has bee
 n recognized by ACM SIGPLAN Distinguished Paper awards at the Symposium on
  Principles of Programming Languages (POPL 2020) and the Conference on Pro
 gramming Language Design and\nImplementation (PLDI 2021).\n\nMore informat
 ion
LOCATION:BC 420 https://plan.epfl.ch/?room==BC%20420 https://epfl.zoom.us/
 j/68222054795?pwd=eVZRdHNpRmxoZWdpZzdIQ1E2Q3ROUT09
STATUS:CONFIRMED
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