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

Interactive Robotics for Agriculture

Friday, February 23, 2018 - 10:00am to 11:00am
Rogers 226

Speaker Information

Joe Davidson
Postdoctoral Research Associate
Newman Lab for Biomechanics and Human Rehabilitation
Massachusetts Institute of Technology

Abstract

The United Nations (U.N.) predicts that the world’s population will exceed 9 billion by the year 2050. To support the increased consumption expected to coincide with urbanization and rising incomes in the developing world, the U.N. estimates that food production must grow by 70% from current levels. However, increasing uncertainty surrounding the future availability of labor is causing rising concern in agricultural sectors heavily dependent on seasonal workforces. While advances in sensor technologies have advanced precision agriculture, there has been limited success in developing robotic systems for tasks requiring physical interaction with delicate crops in unstructured environments (e.g. harvesting, pruning, and thinning). In this presentation, I will discuss recent work on robotic apple harvesting in modern orchard systems. Topics covered will include the general approach, system design, field evaluation results, and opportunities for performance improvement. I will also talk about recent work to develop new actuator technologies for rehabilitation robots and how research themes from the field of physical human-machine interaction could advance agricultural robotics. 

Automated Semantics-Based Malware Detection through Program Analysis and Program Synthesis

Monday, February 26, 2018 - 9:00am to 10:00am
KEC 1007

Speaker Information

Yu Feng
Ph.D. candidate
Computer Science
UT Austin

Abstract

Due to the enormous popularity of Android as a mobile platform, the number of Android malware has skyrocketed. In this talk, I will focus on techniques for performing semantics based malware detection through program analysis and program synthesis.

In the first part of my talk, I will present Apposcopy, a new semantics-based approach for identifying a prevalent class of Android malware that steals private user information. Apposcopy incorporates (i) a high-level language for specifying signatures that describe semantic characteristics of malware families and (ii) a static analysis for deciding if a given application matches a malware signature. To reduce the manual effort of writing malware signatures in Apposcopy, in the second part of my talk, I will present a technique for automatically synthesizing malware signatures from very few samples of a malware family. The key idea underlying our technique is to look for a maximally suspicious common subgraph (MSCS) that is shared between all known instances of a malware family.

Speaker Bio

Yu Feng is a Ph.D. candidate in Computer Science at UT Austin. His research to date focuses on developing automated programming techniques that combine program synthesis and program analysis to improve software usability, reliability, and security. Yu has developed systems for tackling security vulnerabilities (FSE'14, NDSS'17, CCS'17), automating complex programming tasks (PLDI'17, POPL'17, PLDI'18), and challenging the limits of existing program analysis (OOPSLA'15, APLAS'15).

Enabling Complete and Efficient Attack Provenance at Scale

Monday, February 26, 2018 - 4:00pm to 4:50pm
LPSC 125

Speaker Information

Adam Bates
Assistant Professor
Computer Science
University of Illinois at Urbana-Champaign

Abstract

In a provenance-aware system, mechanisms gather and report metadata that
describes the history of each data object being processed, allowing users
to understand how objects came to exist in their present state.
Excitingly, we can also use provenance to trace the actions of system
intruders, enabling smarter and faster incident response. In this talk, I
will detail our efforts to achieve trustworthy data provenance in
malicious distributed environments. These efforts have led to the design
and implementation of a provenance-aware operating systems anchored in
trusted hardware, a mechanism that leverages the confinement properties
provided by Mandatory Access Controls to perform efficient policy-based
provenance collection, and most recently an efficient distributed
provenance management framework. Using these architectures, I will
demonstrate that provenance is an invaluable tool for combating critical
security threats including data exfiltration, SQL injection, and even
binary exploitation. By addressing key security and performance
challenges, this work is paving the way for the further proliferation of
provenance capabilities.

Speaker Bio

Adam Bates is an Assistant Professor in the Computer Science Department at
the University of Illinois at Urbana-Champaign. He is also an Affiliate
Assistant Professor in the Electrical & Computing Engineering Department.
He received his PhD from the University of Florida, where he was advised
by Professor Kevin Butler in the study of computer systems and cyber
security, and completed multiple internships at MIT Lincoln Laboratory.
Adam has conducted research on a variety of security topics, including
SSL/TLS, cloud computing, USB attack vectors, financial services, and
telephony infrastructure. He is best known for his work in the area of
data provenance, particularly the construction of secure provenance-aware
systems. He received the NSF CISE Research Initiation Initiative award in
2017, and served as Program Chair for the 2017 Workshop on the Theory and
Practice of Provenance (TaPP).

Design and Evaluation of Everyday Interactive Robots

Tuesday, February 27, 2018 - 10:00am to 11:00am
Rogers 226

Speaker Information

Naomi Fitter
Postdoctoral Scholar
Robotics and Autonomous Systems Center
University of Southern California

Abstract

As robots appear in more everyday environments, they will have new opportunities to enhance the lives of the people around them. Despite this potential gain, modern robots lack many of the necessary skills to effectively interact with people. In particular, almost all robots lack the kinds of social touch capabilities that help human beings to learn about the world and connect with one another. My goal is to improve the social-physical human-robot interaction (spHRI) capabilities of robots in everyday environments to make them effective agents for supporting the communication, health, and learning of individuals.

This talk covers the ways I have combined physical human-robot interaction and social robotics to help people understand robot capabilities, form connections with support robots, and feel socially embedded in a remote environment. In collaborative manufacturing settings, I aim to use spHRI to improve trust and performance in human-robot teamwork. Previously, I investigated ways that human-robot hand-clapping games could serve as an icebreaker activity in this type of collaboration. Using similar social touch abilities, I also designed and evaluated human-robot exercise games to help older adults stay active. Currently, I research telepresence robots for education. Such telepresence platforms might have the ability to preserve the educational and social experiences of children who miss extended amounts of school, but only if these systems improve in their ability to interact with remote environments. Overall, this interdisciplinary research combines principles from control theory, signal processing, machine learning, psychology, design, mechatronics, and other areas. My ongoing and future research will yield everyday robotic systems with the potential to help people live more productive, healthy, and enriching lives.

AI For Societally Relevant Problems: Influence Maximization in an Uncertain World

Wednesday, February 28, 2018 - 9:00am to 10:00am
KEC 1007

Speaker Information

Amulya Yadav
Ph.D. Candidate
Computer Science Department
USC Viterbi School of Engineering

Abstract

The potential of Artificial Intelligence to tackle challenging problems that afflict society is enormous, particularly in the areas of healthcare, conservation and public safety and security. Many problems in these domains involve harnessing social networks of under-served communities to enable positive change, e.g., using social networks of homeless youth to raise awareness about HIV (and other STDs). Unfortunately, most of these real-world problems are characterized by uncertainties about social network structure and influence models, and previous research in AI fails to sufficiently address these uncertainties, as they make several unrealistic simplifying assumptions for these domains. In this talk, I will describe my research on algorithmic interventions in social networks. In the first part of my talk, I will describe my work on developing new influence maximization algorithms which can handle various uncertainties in social network structure, influence models, etc., that commonly exist in real-world social networks. I will discuss how my algorithms utilize techniques from sequential planning problems and computational game theory to develop new kinds of algorithms in the sub-fields of multi-agent systems and reasoning under uncertainty. In the second part of my talk, I will discuss the real-world deployment of my algorithms to spread awareness about HIV among homeless youth in Los Angeles. This represents one of the first-ever deployments of computer science based influence maximization algorithms in this domain. I will discuss the challenges that I aced, and the lessons that can be gleaned for future deployment of AI systems. Finally, I will also talk about other kinds of societally relevant problems that I have worked on, e.g., raising grievances of low literate farmers to government agencies in emerging market countries, etc. All these problems illustrate the enormous potential of AI in addressing societally relevant problems. 

Speaker Bio

Amulya Yadav is a Ph.D. Candidate in the Computer Science Department of the USC Viterbi School of Engineering, where he is also a part of the USC Center for Artificial Intelligence in Society. His research interests include Artificial Intelligence, Multi-Agent Systems, Computational Game-Theory and Applied Machine Learning. His work in the field of Artificial Intelligence for Social Good focuses on developing theoretically grounded approaches to real-world problems that can have an impact in the field. His algorithms have been deployed in the real-world, particularly in the field of public health and social justice. Amulya is a recipient of the AAMAS 2016 Best Student Paper Award, the AAAI 2017 Best Video and Best Student Video Award, the IDEAS 2016 Most Visionary Paper Award, and the AAMAS 2017 Best Paper Award nomination. His work has also been highlighted by Mashable.com as one of 26 incredible innovations that improved the world in 2015. He was also awarded the Best Research Assistant Award at USC in 2016. 

Past Colloquia

David Hendrix
Monday, October 10, 2016 - 4:00pm to 4:50pm
Robert Adams
Monday, October 3, 2016 - 4:00pm to 4:50pm
Kofi A.A. Makinwa
Monday, June 13, 2016 - 4:00pm to 4:50pm
Nan Sun
Monday, May 9, 2016 - 4:00pm to 4:50pm
Alan Hui Zhao
Monday, April 25, 2016 - 4:00pm to 4:50pm
David J. Allstot
Monday, April 25, 2016 - 9:00am to 10:00am
Subhasish Mitra
Monday, April 18, 2016 - 4:00pm to 4:50pm
Jacob Crandall
Friday, April 15, 2016 - 10:00am to 11:00am

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