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University Calendar
Events for April
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W.V.T. Rusch Engineering Honors Program Colloquium
Fri, Apr 01, 2016 @ 01:00 PM - 01:50 PM
USC Viterbi School of Engineering, Viterbi School of Engineering Student Affairs
University Calendar
Join us for a presentation by Helen Park, from WET Design, titled "When Engineering Meets Design."
Location: Seeley G. Mudd Building (SGM) - 123
Audiences: Everyone Is Invited
Contact: Ramon Borunda/Academic Services
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PhD Defense - Thanh Nguyen
Fri, Apr 08, 2016 @ 10:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
University Calendar
Title: Combating Adversaries under Uncertainties in Real-world Security Problems: Advanced Game-theoretic Behavioral Models and Robust Algorithms
Location: EEB 248
Date: April 8th
Time: 10am-12pm
Phd Candidate: Thanh Nguyen
Committee members:
Prof. Milind Tambe (Chair)
Prof. David Kempe
Prof. Jonathan Gratch
Prof. William Halfond
Prof. Richard John
Prof. Ariel Procaccia
Abstract:
Security is a global concern. Real-world security problems range from domains such as the protection of ports and airports from terrorists to protecting forests and wildlife from smugglers and poachers. A key challenge in solving these security problems is that security resources are limited; not all targets can be protected all the time. Therefore, security resources must be deployed intelligently, taking into account responses of attackers and potential uncertainties over their types, preference, and knowledge. Stackelberg Security Games (SSG) have drawn a significant amount of interest from security agencies. SSG-based decision aids are in widespread use for the protection of assets such as major ports in the US and airport terminals.
My research focuses on addressing uncertainties in SSGs --- one recognized area of weakness in SSGs. For example, adversary payoff values can be extremely difficult to assess and are generally characterized by significant uncertainty. My thesis provides innovative techniques and significant advances in addressing these uncertainties in SSGs. First, in many security problems, human adversaries are known to be boundedly rational, and often choose targets with non-highest expected value to attack. I introduce novel behavioral models of adversaries which significantly advance the state-of-the-art models in capturing the adversaries' decision making. More specifically, my new model for predicting poachers'behavior in wildlife protection is the first game-theoretic model which takes into account key domain challenges including the imperfect poaching data and complex temporal dependencies in the poachers' behavior. The superiority of my new models over the existing ones is demonstrated via extensive experiments based on the biggest real-world poaching dataset collected in a national park in Uganda over 12 years. Second, my research also focuses on developing new robust algorithms which address uncertainties in real-world security problems. I present the first unified maximin-based robust algorithm - a single algorithm -to handle all different types of uncertainties explored in SSGs. Furthermore, I propose a less conservative decision criterion; minimax regret for generating new, candidate defensive strategies that handle uncertainties in SSGs. In fact, this is the first time minimax regret has ever been used for addressing uncertainties in SSGs. I then present novel robust algorithms to compute minimax regret for addressing payoff uncertainty.
A contribution of particular significance is that my work is deployed in the real-world; I have deployed my robust algorithms and behavioral models for the PAWS system, which is currently being used by NGOs (Panthera and Rimba) in a conservation area in Malaysia.
Location: 248
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
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W.V.T. Rusch Engineering Honors Program Colloquium
Fri, Apr 08, 2016 @ 01:00 PM - 01:50 PM
USC Viterbi School of Engineering, Viterbi School of Engineering Student Affairs
University Calendar
Join us for a presentation by Farbod Shoraka, from Bloom Nation, titled "Bootstrapping a Technical Startup."
Location: Seeley G. Mudd Building (SGM) - 123
Audiences: Everyone Is Invited
Contact: Ramon Borunda/Academic Services
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PhD Defense - Fei Fang
Fri, Apr 08, 2016 @ 01:00 PM - 03:00 PM
Thomas Lord Department of Computer Science
University Calendar
Title: Towards Addressing Spatio-Temporal Aspects in Security Games
PhD Candidate: Fei Fang
Committee members: Milind Tambe (advisor), Leana Golubchik, Jelena Mirkovic, Suvrajeet Sen, Shaddin Dughmi
Location: RTH 526
Time: April 8, 1pm-3pm
Abstract:
Game theory has been successfully used to handle complex resource allocation and patrolling problems in security and sustainability domains. More specifically, real-world applications have been deployed for different domains based on the framework of ``security games'', where the defender (e.g., security agency) has a limited number of resources to protect a set of targets from an adversary (e.g., criminal, terrorist). Whereas the first generation of security games research provided algorithms for optimizing security resources in mostly static settings, my thesis advances the state-of-the-art to a new generation of security games, handling massive games with complex spatio-temporal settings and leading to real-world applications that have fundamentally altered current practices of security resource allocation. My thesis provides the first algorithms and models for advancing key aspects of spatio-temporal challenges in security games, including (i) continuous time; (ii) continuous space; (iii) frequent and repeated attacks; (iv) complex spatial constraints.
First, focusing on games where actions are taken over continuous time (for example games with moving targets such as ferries and refugee supply lines), I propose a new game model that accurately models the continuous strategy space for the attacker and provide an efficient solution that uses compact representation for both the defender and the attacker's strategy space. Second, for games where actions are taken over continuous space (for example games with forest land as a target), I provide an algorithm computing the optimal distribution of patrol effort. Third, my work addresses challenges with one key dimension of complexity -- frequent and repeated attacks. Motivated by the repeated interaction of players in domains such as preventing poaching and illegal fishing, I introduce a novel game model that deals with frequent and repeated attacks and provide algorithms to plan effective sequential defender strategies. Furthermore, I handle complex spatial constraints that arise from the problem of designing optimal patrol strategy given complex topographical information.
My thesis work has led to two applications which have been deployed in the real world and have fundamentally altered previously used tactics, including one used by the US Coast Guard for protecting the Staten Island Ferry in New York City in past few years and another deployed in a protected area in Southeast Asia to combat illegal poaching.
Location: Ronald Tutor Hall of Engineering (RTH) - 526
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
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PhD Defense - Chao Zhang
Mon, Apr 11, 2016 @ 02:00 PM - 04:00 PM
Thomas Lord Department of Computer Science
University Calendar
Title: Opportunistic Crime Security Games: Assisting Police to Control Urban Crime Using Real World Data
Location: THH 119
Time: 2 p.m. April 11th, 2016
PhD Student: Chao Zhang
Committee members:
Prof. Milind Tambe (Chair)
Prof. Cyrus Shahabi
Prof. Kevin Knight
Prof. Najmedin Meshkati
Abstract:
Crime in urban areas plagues every city in all countries. A notable characteristic of urban crime, distinct from organized terrorist attacks, is that most urban crimes are opportunistic in nature, i.e., criminals do not plan their attacks in detail, rather they seek opportunities for committing crime and are agile in their execution of the crime. In order to deter such crimes, police officers conduct patrols with the aim of preventing crime. However, by observing on the spot the actual presence of patrol units, the criminals can adapt their strategy by seeking crime opportunity in less effectively patrolled location. The problem of where and how much to patrol is therefore important.
My thesis focuses on addressing such opportunistic crime by introducing a new game-theoretic framework and algorithms. I first introduce the Opportunistic Security Game (OSG), a computational framework to recommend deployment strategies for defenders to control opportunistic crimes. I propose a new exact algorithm EOSG to optimize defender strategies given our opportunistic adversaries. Then I develop a fast heuristic algorithm to solve large-scale OSG problems, exploiting a compact representation. The next contribution in my thesis is a Dynamic Bayesian Network (DBN) to learn the OSG model from real-world criminal activity. Standard Algorithm such as EM can be applied to learn the parameters. Also, I propose a sequence of modifications that allows for a compact representation of the model resulting in better learning accuracy and increased speed of learning of the EM algorithm. Finally, I propose a game abstraction framework that can handle opportunistic crimes in large-scale urban areas. I propose a planning algorithm that recommends a mixed strategy against opportunistic criminals in this abstraction framework. As part of our collaboration with local police departments, we apply our model in two large scale urban problems: USC campus and the city of Nashville. Our approach provides high prediction accuracy in the real datasets; furthermore, we project significant crime rate reduction using our planning strategy compared to current police strategy.
Location: Mark Taper Hall Of Humanities (THH) - 119
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
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Remote Sensing with Multiple Satellite Sensors for Interdisciplinary Science Investigation of Arctic Sea Ice and Halogen Chemical Processes
Wed, Apr 13, 2016 @ 05:30 PM - 07:30 PM
Viterbi School of Engineering Student Organizations
University Calendar
Interested in geosciences and/or remote sensing? The local section of the IEEE Geosciences and Remote Sensing Society Chapter invites you to our first meeting of the year at 5:30pm on Wed 13-Apr-2016 on the Caltech campus in Pasadena. In this distinguished lecture event, Dr Son Nghiem of JPL will talk about remote sensing with multiple satellite sensors for interdisciplinary science investigation of Arctic sea ice and halogen chemical processes. The event is also an opportunity to get to know engineers from JPL, local industry, and other local universities. For details please see .
More Information: 2016-GRSS-4-13-16-AGENDA_v2.pdf
Location: Sharp Lecture Hall Caltech Campus Pasadena, California
Audiences: Everyone Is Invited
Contact: Institute of Electrical and Electronics Engineers
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ASBME GM 10: The Biomedical Cowgirl
Wed, Apr 13, 2016 @ 07:00 PM - 08:00 PM
Viterbi School of Engineering Student Organizations
University Calendar
With hair dyed blue and pink, stand-out clothes, and an eccentric personality, Samantha Huynh is not your typical biomedical engineer. She's done everything from racing cars in the desert, working at Tesla, and SpaceX, and now researching on ways to build better exoskeletons for those who can't walk. Don't miss out on this opportunity to come to ASBME's GM 10 to listen to her fascinating story, her research, and maybe absorb some of her swagger by simply being in her presence. As always, free food will be provided in the form of delicious Chik-Fil-A entrees!
Location: Kaprielian Hall (KAP) - 156
Audiences: Everyone Is Invited
Contact: Associated Students of Biomedical Engineering
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USC Viterbi Robotics Open House
Thu, Apr 14, 2016
USC Viterbi School of Engineering, Viterbi School of Engineering K-12 STEM Center
University Calendar
USC Viterbi's annual Robotics Open House invites everyone to visit the labs where demonstrations of the robotics research will be given. More info here: http://www.viterbi.usc.edu/k-12/robotics-open-house.htm Free but reservations required for groups > 10.
Location: Ronald Tutor Hall of Engineering (RTH) - Outside in patio facing McClintock Ave.
Audiences: Everyone Is Invited
Contact: Katie Mills
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PhD Defense - Yundi Qian
Thu, Apr 14, 2016 @ 02:00 PM - 04:00 PM
Thomas Lord Department of Computer Science
University Calendar
Title: Handling Attacker's Preference in Security Domains: Robust and Learning Approaches
PhD Candidate: Yundi Qian
Location: VKC 252
Time: 2pm, April 14th, Thursday
Committee members:
Milind Tambe
Aram Galstyan
Jonathan Gratch
Maged Dessouky (Outside Member)
Yilmaz Kocer (Outside Member)
Abstract:
Stackelberg security games (SSGs) are now established as a powerful tool in security domains. In order to compute the optimal strategy for the defender in SSG model, the defender needs to know the attacker's preferences over targets so that she can predict how the attacker would react under a certain defender strategy. Uncertainty over attacker preferences may cause the defender to suffer significant losses. Motivated by that, my thesis focuses on addressing uncertainty in attacker preferences using robust and learning approaches.
In security domains with one-shot attack, e.g., counter-terrorism domains, the defender is interested in robust approaches that can provide performance guarantee in the worst case. The first part of my thesis focuses on handling attacker's preference uncertainty with robust approaches in these domains. My work considers a new dimension of preference uncertainty that has not been taken into account in previous literatures: the risk preference uncertainty of the attacker, and propose an algorithm to efficiently compute defender's robust strategy against uncertain risk-aware attackers.
In security domains with repeated attacks, e.g., green security domain of protecting natural resources, the attacker ``attacks'' (illegally extracts natural resources) frequently, so it is possible for the defender to learn attacker's preference from their previous actions and then to use this information to better plan her strategy. The second part of my thesis focuses on learning attacker's preferences in these domains. My thesis models the preferences from two different perspectives: (i) the preference is modeled as payoff and the defender learns the payoffs from attackers' previous actions; (ii) the preference is modeled as a markovian process and the defender learns the markovian process from attackers' previous actions.
Location: Von Kleinsmid Center For International & Public Affairs (VKC) - 252
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
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W.V.T. Rusch Engineering Honors Program Colloquium
Fri, Apr 15, 2016 @ 01:00 AM - 01:50 PM
USC Viterbi School of Engineering, Viterbi School of Engineering Student Affairs
University Calendar
Join us for a presentation by Dr. Steve A. Kay, from the Scripps Research Institute, titled "The Rise of the Machines: How High Throughput Biology Enables Translation of Basic Biomedical Research."
Location: Seeley G. Mudd Building (SGM) - 123
Audiences: Everyone Is Invited
Contact: Ramon Borunda/Academic Services
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W.V.T. Rusch Engineering Honors Program Colloquium
Fri, Apr 22, 2016 @ 01:00 PM - 01:50 PM
USC Viterbi School of Engineering, Viterbi School of Engineering Student Affairs
University Calendar
Join us for a presentation by Justin Fuisz, from Fuisz Media, titled "Building a Tech Startup in LA."
Location: Seeley G. Mudd Building (SGM) - 123
Audiences: Everyone Is Invited
Contact: Ramon Borunda/Academic Services
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PhD Defense - Christian Potthast
Thu, Apr 28, 2016 @ 10:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
University Calendar
PhD Defense - Christian Potthast
Thursday, April 28, 2016 @ 10:00 am - 12:00 pm
Computer Science
Title: Information Theoretical Action Selection
Location: RTH 406
Time: 10:00am - 12:00pm , April 28th, 2016
PhD Candidate: Christian Potthast
Committee members:
Prof. Gaurav S. Sukhatme (Chair)
Prof. Stefan Schaal
Prof. Sandeep K. Gupta
Abstract:
For robots to become one day fully autonomous and assist us in our daily life's, they need to be able to self reliantly acquire information about their environment. Challenges arise from limited energy budget to operate the robot, occlusion as well as uncertainty in data captured by noisy sensor. To cope with such challenges, the robot needs to be able to rely on a system that enables him to capture efficiently information and stay well within its constraints. Furthermore, information acquisition should be reactive to sensor measurement, incorporate uncertainty and tradeoff information gain with energy usage.
In my thesis we look at the realization of such systems using well established information theoretical quantities to formulate a framework as general and versatile as possible. Specifically, we look at the task of defining objective functions that enable us to tradeoff information with acquisition cost, enabling the robot to gather as much useful information as possible, but at the same time keep energy consumption to a minimum. We address this challenge for a variety of different tasks.
First, we look at the problem of 3d data acquisition which is of outmost importance to a robotic system since the robot needs to know the environment it is operating in. In this work I propose a framework that enables the robot to quickly acquire information by sequentially choosing next observation positions that maximize information. Next, we look at adaptive action selection in the context of object recognition on robots with limited operating capabilities. I propose an information-theoretic framework that combines and unifies two common techniques: view planning for resolving ambiguities and occlusions and online feature selection for reducing computational costs. Concretely, this framework adaptively chooses two strategies: utilize simple-to-compute features that are the most informative for the recognition task or move to new viewpoints that optimally reduce the expected uncertainties on the identity of the object. Lastly, I present an online trajectory optimization approach that optimizes a trajectory such that object recognition performance is improved. With the idea in mind that the robot needs to make progress towards a goal a cost function is formulated formulated the that allows the robot to improve recognition performance, reduces information acquisition time while simultaneously moving towards the goal point.
Location: Ronald Tutor Hall of Engineering (RTH) - 406
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
