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Events Calendar

22 Oct
Rising Stars
Computer Science Building, Room 150/151
Tuesday, 10/22/2019 2:30pm to 3:30pm

Abstract:  Privacy and security concerns are growing rapidly thanks to ubiquitous data collections by IoT devices. One way to alleviate such concerns is to design privacy assistants that provide users with transparency...

06 Nov
Rising Stars
Computer Science Building, Room 150/151
Wednesday, 11/06/2019 12:15pm to 1:15pm

Abstract:  Interactive theorem provers make it possible to prove that a program satisfies a specification. This provides a high degree of certainty that the program is trustworthy. The last two decades have marked a new...

13 Nov
Rising Stars
Computer Science Building, Room 150/151
Wednesday, 11/13/2019 12:15pm to 1:15pm

Abstract: Software bugs, leading to correctness or security issues, are pervasive in modern software. Fuzzing or fuzz testing is a method to find such bugs automatically by sending many random-looking inputs to the...

03 Dec
Rising Stars
Computer Science Building, Room 150/151
Tuesday, 12/03/2019 4:00pm to 5:00pm

Abstract:

Detecting concurrency bugs can be challenging due to the intricacies associated with their manifestation. These intricacies correspond to identifying the methods that need to be invoked concurrently, the...

01 Jan
Academic Calendar
Wednesday, 01/01/2020 (All day)

Winter Session: Holiday Break

01 Jan
Academic Calendar
Wednesday, 01/01/2020 (All day)

Holiday - New Year's Day

Campus Closed
02 Jan
Academic Calendar
Thursday, 01/02/2020 (All day)

Fall 2020 Final grades due by midnight

02 Jan
Academic Calendar
Thursday, 01/02/2020 (All day)

Classes resume - Winter Session

09 Jan
Academic Calendar
Thursday, 01/09/2020 (All day)

Winter Session: Last day to drop with "W" or "DR" and select "P/F"

13 Jan
PhD Dissertation Proposal Defense
CS 343
Monday, 01/13/2020 2:00pm to 5:00pm

Abstract:

A long-standing assumption common in algorithm design is that any part of the input is accessible at any time for unit cost. However, as we work with increasingly large data sets, or as we build smaller...

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