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Events for March 19, 2019
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CS Colloquium: ShiQing Ma (Purdue University) - Transparent Computing Systems Enabled by Program Analysis
Tue, Mar 19, 2019 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: ShiQing Ma, Purdue University
Talk Title: Transparent Computing Systems Enabled by Program Analysis
Series: CS Colloquium
Abstract: Modern computing systems are complex and opaque, which is the root cause of many security and software engineering problems. In enterprise level system operations, this leads to inaccurate and hard-to-understand attack forensics results. In deep learning systems, such opaqueness prevents us from understanding the misclassifications and improving the model accuracy. Hence, there is a pressing need for improving the transparency of these systems to help us solve the corresponding security and software engineering problems.
In this talk, I will focus on my research efforts of developing novel program analysis techniques to improve the transparency of such systems and their applications in attack forensics and deep learning systems. For attack forensics, I will first describe a compiler-based execution partitioning technique MPI which helps accomplish accurate, semantics-rich and multi-perspective attack forensics. For deep learning systems, I will introduce novel state differential analysis and input selection techniques to analyze deep learning model internals for addressing the misclassification problem. Finally, I will briefly present my ongoing and future work on intelligent systems (i.e., systems that combine traditional computing components and artificial intelligent components).
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Shiqing Ma is a Ph.D. candidate in the Department of Computer Science at Purdue University, co-advised by Professors Xiangyu Zhang and Dongyan Xu. His research interests lie in solving security and software engineering problems via program analysis techniques with a focus on improving the transparency of modern computing systems. He is the recipient of two Distinguished Paper Awards at ISOC NDSS 2016 and USENIX Security 2017
Host: Muhammad Naveed
Location: Olin Hall of Engineering (OHE) - 132
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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PhD Defense - Abdulmajeed Alameer
Tue, Mar 19, 2019 @ 11:00 AM - 01:30 PM
Thomas Lord Department of Computer Science
University Calendar
PhD Candidate:
Abdulmajeed Alameer
Committee:
William G.J. Halfond (Chair)
Nenad Medvidovic
Sandeep Gupta
Chao Wang
Jyotirmoy V. Deshmukh
Dissertation Title:
Detection, Localization, and Repair of Internationalization Presentation Failures in Web Applications
Time and Location:
3/19 from 11am to 1:30pm - Room PHE 223.
Abstract:
Web applications can be easily made available to an international audience by leveraging frameworks
and tools for automatic translation and localization. However, these automated changes
can introduce Internationalization Presentation Failures (IPFs) - an undesired distortion of the
web page's intended appearance that occurs as HTML elements expand, contract, or move in
order to handle the translated text. It is challenging for developers to design websites that can
inherently adapt to the expansion and contraction of text after it is translated to different languages.
Existing web testing techniques do not support developers in debugging these types of
problems and manually testing every page in every language can be a labor intensive and error
prone task.
In my dissertation work, I designed and evaluated two techniques to help developers in debugging
web pages that have been distorted due to internationalization efforts. In the first part of
my dissertation, I designed an automated approach for detecting IPFs and identifying the HTML
elements responsible for the observed problem. In evaluation, my approach was able to detect
IPFs in a set of 70 web applications with high precision and recall and was able to accurately
identify the underlying elements in the web pages that led to the observed IPFs. In the second
part of my dissertation, I designed an approach that can automatically repair web pages that
have been distorted due to internationalization efforts. My approach models the correct layout
of a web page as a system of constraints. The solution to the system represents the new and
correct layout of the web page that resolves its IPFs. The evaluation of this approach showed
that it could more quickly produce repaired web pages that were rated as more attractive and
more readable than those produced by a prior state-of-the-art technique. Overall, these results
are positive and indicate that both my detection and repair techniques can assist developers in
debugging IPFs in web applications with high effectiveness and efficiency.
Time and Location:
3/19 from 11am to 1:30pm - Room PHE 223.
Location: Charles Lee Powell Hall (PHE) - 223
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
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CS Colloquium: Protiva Rahman (Ohio State University) - Amplifying Domain Expertise in Data Pipelines
Tue, Mar 19, 2019 @ 04:00 PM - 05:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Protiva Rahman, Ohio State University
Talk Title: Amplifying Domain Expertise in Data Pipelines
Series: Computer Science Colloquium
Abstract: Digitization of forms and electronic health records (EHR) has made data from diverse domains available for analysis. The specialized nature of the data require domain expert input at every step of the data analysis pipeline, including entry, cleaning, and analysis. Since domain experts (e.g. physicians) are highly skilled in their fields, their time is very valuable and expensive. Moreover, they often do not have any training in computer science or statistics, making it difficult for them to effectively interact with data. Thus, it is crucial that we make data interaction easy, efficient and effortless for experts. This involves amplifying or generalizing their inputs to multiple data points, reducing their time and effort.
In this talk, I will present Icarus, a system that leverages the database schema to amplify domain expert input during data cleaning. Icarus optimizes a weighted sum to guide the user to high-impact edits. Once a user fills in a cell, the system leverages the many-to-one relations in the database to suggest generalized update queries in the form of rules. These rules apply to a larger number of cells, amplifying the user's single edit.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Protiva Rahman is a fourth-year Ph.D. student in the Department of Computer Science and Engineering at the Ohio State University, advised by Professor Arnab Nandi. Her research interests include databases, human-computer interaction, visualization, and clinical informatics. Besides data cleaning, she has also worked on optimizing data entry interfaces for constrained interaction, guidelines for evaluating interactive systems and visualizations for domain expert consensus.
Host: Computer Science Department
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Computer Science Department
