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VERSION:2.0
PRODID:-//Memento EPFL//
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SUMMARY:IC Colloquium: Beyond General-Purpose Fuzzing: Low-Cost Customizat
 ion for Testing the AI Systems Stack
DTSTART:20260518T101500
DTEND:20260518T111500
DTSTAMP:20260916T063759Z
UID:306f341ae1663e06ecea04e692d87d16d721f236f39e299151841972
CATEGORIES:Conferences - Seminars
DESCRIPTION:By: Miryung Kim - UCLA\nVideo of her talk\n\nAbstract\nThe ra
 pid evolution of AI-accelerated hardware and specialized AI/ML compilers h
 as outpaced our ability to check their correctness using traditional softw
 are testing. To improve developer productivity and maximize heterogeneous 
 hardware utilization\, we must rethink how we discover edge cases within A
 I compiler stacks. In this talk\, I will reflect on my group’s experienc
 e designing domain-aware testing engines for compute-intensive systems. I 
 will argue that traditional fuzzing is insufficient for the rapidly evolvi
 ng requirements of extensible Multi-Level Intermediate Representations (ML
 IR). Specifically\, I will address the high manual effort required to spec
 ialize a fuzzer—namely\, the labor-intensive process of encoding domain-
 specific constraints and custom mutation operators.\nTo lower this barrier
  to entry\, I will discuss techniques to automate this specialization\, su
 ch as custom mutation synthesis from examples and rule-based repair for be
 spoke fuzzing. I will conclude by discussing the need to shift fuzzing tow
 ard Property-Based Testing (PBT) to bridge the gap between the scale of ra
 ndom fuzzing and the rigor of formal methods\, enabling the validation of 
 domain-specific invariants and properties.\n\nBio\nMiryung Kim is a Profes
 sor and Vice Chair of Graduate Studies in UCLA’s Computer Science Depart
 ment. A pioneer in data-intensive software engineering\, she led research 
 defining the role of data scientists in software teams. Her current resear
 ch focuses on developer tools for data and compute-intensive systems\, add
 ressing scale and complexity challenges that traditional debugging and tes
 ting cannot meet. For her contributions to data-driven software analytics 
 and establishing the significance of code clones in software evolution\, s
 he received the IEEE TCSE New Directions Award.  Her research demonstrate
 d how recurring patterns could be analyzed to automate bug fixes and refac
 toring---insights that now inform modern\, AI-driven developer tools. Dedi
 cated to mentoring\, she was honored with the ACM SIGSOFT Influential Educ
 ator Award\; eight of her former students and postdocs now hold faculty po
 sitions at institutions such as Columbia\, Purdue\, and Virginia Tech. She
  served as Program Co-Chair of FSE\, delivered keynotes at ASE and ISSTA\,
  and is currently an Amazon Scholar at AWS.\n\nMore information
LOCATION:BC 420 https://plan.epfl.ch/?room==BC%20420 https://epfl.zoom.us/
 j/61263924697
STATUS:CONFIRMED
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