Once every week while school is in session, EECS invites a distinguished researcher or practitioner in a computer science or electrical and computer engineering-related field to present their ideas and/or work. Talks are generally targeted to electrical engineering and computer science graduate students. This colloquium series is free and open to everyone.

Upcoming Colloquia

Advancing Energy Testing of Android

Monday, March 18, 2019 - 10:00am to 11:00am
KEC 1005

Speaker Information

Reyhaneh Jabbarvand
PhD Candidate
Donald Bren School of Information and Computer Sciences
University of California, Irvine


The utility of a smartphone is limited by its battery capacity and the ability of its hardware and software to efficiently use the device’s battery. To properly characterize the energy consumption of an app and identify energy defects, it is critical that apps are properly tested, i.e., analyzed dynamically to assess the app’s energy properties. However, currently there is a lack of testing tools for evaluating the energy properties of apps. As a result, for energy testing, developers are relying on tests intended for evaluating the functional correctness of apps. Are such tests adequate for revealing energy defects in apps? If not, what are the properties of tests that can effectively find energy inefficiencies in apps? How can we automatically generate such tests? Answers to these questions are the subject of my presentation.

In the first part of this talk, I will introduce μDroid, a mutation testing technique that can be used by developers to assess the adequacy of their test suite for revealing energy-related defects. Applying μDroid to real-world Android apps with available test suites showed that current Android testing tools are in fact ineffective at finding energy defects. Based on the insights from this study, I identified characteristics of tests that can effectively find energy issues in Android apps. In the second part of this talk, I will present COBWEB, a search-based energy testing technique that automatically generates energy tests. Experimental results on real-world Android apps demonstrate not only COBWEB's ability to effectively and efficiently test energy behavior of apps, but also its superiority over prior techniques by finding a wider and more diverse set of energy defects.

Speaker Bio

Reyhaneh Jabbarvand is a PhD candidate in the Donald Bren School of Information and Computer Sciences at the University of California, Irvine (UCI). Her research interests include analysis and testing of mobile apps to address security and energy issues. She has been awarded the Google PhD Fellowship in Programing Technology and Software Engineering for her work on advancing energy testing of Android. She is the lead author of several publications that have appeared in top software engineering venues, including ICSE, FSE, and ISSTA. More info about her can be found at: https://www.ics.uci.edu/~jabbarvr/

Automated Support for Improving Software Quality Before and After Release

Wednesday, March 20, 2019 - 10:00am to 11:00am
KEC 1007

Speaker Information

Mattia Fazzini
Ph.D. candidate
School of Computer Science
Georgia Institute of Technology


Due to the importance of software quality, companies invest a great number of resources in software verification, and in particular in testing. It is therefore crucial to develop and use testing approaches that are both effective and efficient. At the same time, because exhaustive testing is not generally possible, software is released with bugs and these bugs will translate into field failures. The ability to react effectively to field failures is therefore also essential to resolve bugs, but the support for this task is still limited and based on mostly manual, human-intensive approaches. The overarching goal of my research is to improve software quality by devising novel techniques that account for software bugs before and after release.

In particular, this talk will present the work I did towards my goal in the context of mobile applications (or simply apps). I will first provide an overview of my research in this domain and then discuss in detail two of the techniques I developed: Yakusu and AppEvolve. Yakusu automatically translates natural-language bug reports into test cases, so that developers can use the generated tests to focus their attention on debugging failures and quickly fix their apps. AppEvolve prevents failures by accounting for changes to the environment in which apps operate; it automatically updates API usages (i.e., interactions with the underlying environment) in an app by analyzing how developers of other apps performed corresponding changes. I will conclude my talk with a discussion of open challenges and future research directions.

Speaker Bio

Mattia Fazzini is a Ph.D. candidate in the School of Computer Science at the Georgia Institute of Technology. His research interests lie primarily in the area of software engineering, with emphasis on techniques for improving software quality. The central theme of his research is the development of techniques for testing and maintenance of mobile applications. He is also interested in defining techniques for improving the security of software.

Quality of Time: A New Perspective to Design Cyber-Physical Systems

Friday, March 22, 2019 - 10:00am to 11:00am
KEC 1005

Speaker Information

Fatima Anwar
Ph.D. candidate
Electrical & Computer Engineering


Unprecedented Cyber-Physical Systems (CPS) applications such as health care, connected vehicles and augmented/virtual reality are revolutionizing smart spaces. These applications span the cloud and edge devices with a critical dependence on temporal use cases. As such, cloud services are expected to provide ‘timely responses’ and ‘schedulable demands’, while edge devices are required to ‘synchronize observations’ and ‘choreograph actions’ across distributed entities. The goal of my research is to design new systems that enable time awareness and meet consistency, causality and scheduling demands of underlying CPS applications running on commodity platforms. In particular, I design trustworthy systems centered around extensible time abstractions in the presence of timing variations and vulnerabilities.

In this talk, I will first discuss the challenges faced by time-aware applications. I will then motivate and present the necessary timing abstractions that treat time as a controllable operating system primitive while taking into account the uncertainty arising from hardware and network variations. Further, I will discuss timing vulnerabilities in trusted execution technologies and network security mechanisms; and present my design of secure global clocks. While my abstractions and system designs can be applied to many CPS applications, my talk will focus on autonomous driving use cases.

Speaker Bio

Fatima Anwar is a Ph.D. candidate in the Electrical & Computer Engineering department at UCLA. Her research interests lie in the intersection of system design, security, and quality of time in distributed Cyber-Physical Systems. Specifically, she designs trustworthy systems around abstractions to provide key services to the Internet of Things applications running on commodity platforms and operating systems. Earlier, she used to work at Samsung Electronics on the Smart Health project (SHealth) and developed a sensor service framework for mobile devices. She was Qualcomm Innovation Fellowship finalist in 2018 and was Anita Borg scholar in 2017. Fatima is also committed to broadening participation and volunteers for Los Angeles Computing Circle (LACC) and Engineering day for Girls at UCLA.

Defending Memory Vulnerabilities Latent in Production Software

Friday, April 5, 2019 - 2:00pm to 3:00pm
KEC 1005

Speaker Information

Tongping Liu
Assistant Professor
University of Texas at San Antonio


Memory vulnerabilities can be exploited for security attacks, such as data corruption, control-flow hijacks, and information leakage. The intermittent reports of security attacks indicate the wide existence of memory vulnerabilities, and the lack of effective systems to defend such vulnerabilities in reality. This talk will present two of our research efforts aiming to defend memory vulnerabilities latent in the production software.

First, I will present a novel heap allocator--Guarder--that could make heap-based security attacks harder to succeed. Randomization is the conventional wisdom to achieve this. However, existing secure allocators face with two serious issues that prevent their wide adoptions, the significant performance overhead, and the unstable randomization entropy that can vary on different execution phases. Due to the second fact, attackers may breach the system at the weakest point. Guarder ensures the reliable randomization entropy, and provides an unprecedented level of security guarantee by providing all security features of existing allocators, but without compromising the performance, which has an overhead less than 3% on average comparing to performance-oriented allocators. This project was supported by Mozilla Company.

Second, I will present an efficient tool--iReplayer--that could report memory vulnerabilities precisely. The key insight is that it is possible to ensure that the evidence of memory vulnerabilities remains for the later detection. Therefore, instead of detecting memory vulnerabilities in the original execution, which may impose prohibitive performance overhead, the proposed approach only invokes the detection when the evidence of vulnerabilities is found. More specifically, it only performs the detection based on the found evidence, which avoids the significant performance overhead for common cases that do not have vulnerabilities and makes it applicable for the production environment. iReplayer further unlocks numerous possibilities in security forensics, failure diagnosis, and online error remediation.

Speaker Bio

Tongping Liu is an Assistant Professor at the University of Texas at San Antonio. He received his Ph.D. from the University of Massachusetts Amherst in 2014. His primary research goal is to practically improve the security and reliability of software. His work appeared in most prestigious system and security conferences, such as SOSP, OSDI, USENIX Security, CCS, and PLDI. He has been awarded the 2015 Google Faculty Research Award, and multiple grants from NSF. More information can be seen at http://www.cs.utsa.edu/~tongpingliu/.

Run-time computation for enhanced integrated circuits and systems

Monday, April 8, 2019 - 4:00pm to 4:50pm
Weniger Hall 151

Speaker Information

Visvesh Sathe
Assistant professor
University of Washington


For over half a century, Integrated Circuits have been designed and developed (rather successfully) toward the goal of enhancing computing performance and efficiency.  During this time, the relationship between circuit design and computing has remained largely one-directional: Careful, detailed circuit design is performed in the service of building computing systems. Notwithstanding a post-Moore and post-Dennard reality, the impressive strides made by digital computing thus far spurs an important question that re-examines the traditional circuit-computing relationship: Can runtime computing itself be used to enhance circuit and system capabilities? If so, under which conditions and to what extent?


In this talk, I will present an overview of recent efforts in my group as we examine the promising role of computing in augmenting circuit capabilities to (1) overcome limitations inherent in circuit design; (2) enable rapid, time-optimal control of integrated control systems; and (3) to perform low-complexity runtime system optimization. Each of these goals is examined a through a representative test-chip design. Applications include robust True-Random Number Generators (TRNGs) demonstrating the lowest measured energy-per-bit (2.58pJ/bit), All-digital PLLs (ADPLLs) for system clocking applications with the fastest demonstrated cold-start and re-lock times (16 Refclk cycles, mean), and an autonomous all-digital minimum energy-point (MEP) tracking system for a sub-threshold microprocessor.

Speaker Bio

Visvesh Sathe is an assistant professor at the University of Washington, where his group conducts research into digital, mixed-signal and power circuits and architectures. Prior to joining the University of Washington, he served as a Member of Technical Staff in the Low-Power Advanced Development Group at AMD, where his research focused on inventing and developing new technologies in clocking, voltage-noise mitigation and circuit-design for energy-efficient and high-performance computing. Dr. Sathe led the research and development effort at AMD that resulted in the first-ever resonant clocked commercial microprocessor.  Dr. Sathe received the B.Tech degree from the Indian Institute of Technology Bombay in 2001, and the M.S and Ph.D. degrees from the University of Michigan, Ann Arbor in 2004 and 2007, respectively. He has served as a chapter officer for the Denver Solid State Circuits Society, as has previously served as a technical program committee member at the Custom Integrated Circuits Conference as well as a JSSC guest editor.



Human-Centered AI through Scalable Visual Data Analytics

Wednesday, April 10, 2019 - 10:00am to 11:00am
KEC 1007

Speaker Information

Minsuk Kahng
Ph.D. Candidate
Computer Science
Georgia Institute of Technology


While artificial intelligence (AI) has led to major breakthroughs in many domains, understanding machine learning models remains a fundamental challenge. They are often used as "black boxes," which could be detrimental. How can we help people understand complex machine learning models, so that they can learn them more easily and use them more effectively?

In this talk, I present my research that makes AI more accessible and interpretable, through a novel human-centered approach, by creating novel data visualization tools that are scalable, interactive, and easy to learn and to use. I present my work in two interrelated topics. (1) Visualization for Industry-scale Models: I present how to scale up interactive visualization tools for industry-scale deep learning models that use large datasets. I describe how the ActiVis system helps Facebook data scientists interpret deep neural network models by visually exploring activation flows. ActiVis is patent-pending, and has been deployed on Facebook’s ML platform. (2) Interactive Understanding of Complex Models: I show how visualization helps novices interactively learn complex concepts of deep learning models. I describe how I developed GAN Lab, a visual education system for Generative Adversarial Networks (GANs), one of the most popular, but hard-to-understand models. GAN Lab has been open-sourced in collaboration with Google Brain and used by over 30,000 people from 140 countries. I conclude with my vision to make AI more human-centered, to promote actionability for AI, stimulate a stronger ethical AI workforce, and foster healthy impacts of AI on broader society.

Speaker Bio

Minsuk Kahng is a Ph.D. Candidate in Computer Science at Georgia Tech. His research focuses on building visual analytics tools for exploring, interpreting, and interacting with complex machine learning systems and large datasets. He publishes at premier venues spanning data visualization, data mining, databases, machine learning, and human-computer interaction. His research led to deployed and patent-pending technologies by Facebook (ActiVis, MLCube), and an open-sourced education tool for deep learning with Google Brain (GAN Lab). He received his Master's and Bachelor's degrees from Seoul National University in South Korea. He was named Graduate Teaching Assistant of the Year in Computer Science at Georgia Tech. He has been supported by a Google PhD Fellowship and an NSF Graduate Research Fellowship.
Website: https://minsuk.com

Past Colloquia

Hoi-To Wai
Monday, January 8, 2018 - 4:00pm to 4:50pm
Brian M. Kurkoski
Monday, November 20, 2017 - 4:00pm to 4:50pm
John Wager
Monday, November 6, 2017 - 4:00pm to 4:50pm
Danny Dig
Monday, October 16, 2017 - 4:00pm to 4:50pm
Sriraam Natarajan
Monday, October 9, 2017 - 4:00pm to 4:50pm
J.-C. Chiao
Monday, October 2, 2017 - 4:00pm to 4:50pm
Christopher Scaffidi
Monday, September 25, 2017 - 4:00pm to 4:50pm