Microsoft Student Partners program

Microsoft Student Partners (MSPs) are student technology leaders, empowered to build Microsoft communities on their campus and share their deep knowledge and passion for technology with their fellow classmates.  See here for more information. Apply by 15 July 2016.

UMBC students demonstrate smartphone applications, 12:30-2:30 Tue 5/10


7919_New Faculty 2009 Nilanjan Banerjee Computer Science and Computer Engineering

Student groups drawn from two UMBC classes will demonstrate twelve mobile applications they developed as projects from 12:30 to 2:30 on Tuesday, 10 May 2016 in the UC Ballroom. Pizza will be provided.

The projects are a result of an innovative collaboration between a computer science class lead by Professor Nilanjan Banerjee (CMSC 678 Mobile Computing) and a visual arts class lead by Professor Viviana Chacon (ART 434 Advanced Interface Design).

The two faculty were awarded a grant from the fall 2015 round of the Hrabowski Fund for Innovation competition to develop and evaluate the collaboration between the two courses. The classes held regular joint sessions and each project group comprised students from both Engineering and Visual Arts.

In ART 434 Prof. Cordova concentrated on the visual experience of the interface in mobile and desktop applications, while in CMSC 628 Prof.  Banerjee provided the tools necessary to design and implement mobile applications.  Specific mobile development topics such as user interface design and implementation, accessing and displaying sensor and location data, and mobile visual design were co-­‐taught by both instructors.  Teams comprising Engineering and Visual Arts students designed and built mobile applications for local clients in Baltimore and Washington DC area.

poster describing the event has brief descriptions of the twelve class projects.

NSF CyberCorps: Scholarship For Service, May 15 deadline

UMBC undergraduate and graduate students interested in cybersecurity can apply for an Federal CyberCorps: Scholarship For Service scholarship by 15 May 2016. This application deadline will be the last one under the current NSF grant, which ends August 2017.

The Federal CyberCorps: Scholarship For Service program is designed to increase and strengthen the cadre of federal information assurance professionals that protect the government’s critical information infrastructure. This program provides scholarships that may fully fund the typical costs incurred by full-time students while attending a participating institution, including tuition and education and related fees. Participants also receive stipends of $22,500 for undergraduate students and $34,000 for graduate students.

Applicants must be be full-time UMBC students within two years of graduation with a BS or MS degree; a student within three years of graduation with both the BS/MS degree; a student participating in a combined BS/MS degree program; or a research-based doctoral student within three years of graduation in an academic program focused on cybersecurity or information assurance. Recipients must also be US citizens or permanent residents; meet criteria for Federal employment; and be able to obtain a security clearance, if required.

For more information and instructions on how to apply see the UMBC CISA site (use old application form, and be sure to include the cover sheet).

talk: Down the rabbit hole: An Android system call study, 10:30 Mon 3/28


Down the rabbit hole: An Android system call study

Prajit Kumar Das

10:30 am, Monday, March 28, 2016 ITE 346

App permissions and application sandboxing are the fundamental security mechanisms that protects user data on mobile platforms. We have worked on permission analytics before and come to a conclusion that just studying an app’s requested access rights (permissions) isn’t enough to understand potential data breaches. Techniques like privilege escalation have been previously used to gain further access to user and her data on mobile platforms like Android. Static code analysis and dynamic code execution may be studied to gather further insight into an app’s behavior. However, there is a need to study such a behavior at the lowest level of code execution and that is system calls. The system call is the fundamental interface between an application and the Linux kernel. In our current project, we are studying system calls made by apps for gathering a better understanding of their behavior.

HackUMBC 24 -hour student hackathon, 5-6 March 2016 at UMBC


HackUMBC is a 24 hour student hackathon that will take place on Saturday and Sunday, March 5-6, 2016 at UMBC. It’s an opportunity to learn new skills, make friends, create your wildest idea, and share it with the world. Build an app, a website, a robotic arm, a game, anything. It’s free and food, beverages, swag, workspaces, and sleeping areas will be provided. All undergraduate, graduate, and high school students are welcome, but pre-registration is required. Get more information and apply at

PhD defense: Infrastructure-less Group Data Sharing using Smart Devices

Ph.D. Dissertation Defense

Infrastructure-less Group Data
Sharing using Smart Devices

Ahmed Shahin

2:30 Tuesday, 8 December 2015, ITE-346

Advances in pervasive communication technology have enabled many unconventional applications that facilitate and improve the safety and quality of life in modern society. Among emerging applications is situational awareness where individuals and first-responders receive timely alerts about serious events that could have caused the interruption of the services provided by the communication infrastructure such as cellular networks, Wi-Fi hotspots, etc. Another example is when exchanging road conditions between peer-to-peer networked vehicles without the involvement of roadside units. The popularity of smart portable devices such as iPhone and Android powered phones and tablets has made them an attractive choice that can play a role in the realization of these emerging applications. These devices support multiple communication standards and thus enable Device-to-Device (D2D) data exchange at an increased level of convenience. By using technologies such as Bluetooth, Wi-Fi ad-hoc mode and Wi-Fi Direct, these devices are able to communicate without the need for any communication infrastructures. In addition, many of these devices are equipped with sensors that can provide a wealth of information about the surroundings once their readings are aggregated.

However, most existing protocols for data sharing among devices either require an internet connection, which may not be available and may incur extra costs in some cases, or suffer from the device’s operating system limitations. Actually there is no existing solution that allows a set of devices to start sharing data dynamically without forcing the users to apply an elaborate procedure for setting up a group. These shortcomings render existing solutions unsuitable for emergency cases. In this dissertation proposal, we tackle such a problem by developing a framework for enabling data exchange in a cost-effective and timely manner through the establishment of peer-to-peer links among smart devices. In addition, our framework opts to minimize the user required interaction for setting up a connection and overcome the limitations of the operating system.

Our framework consists of a set of protocols for group data exchange using Wi-Fi Direct on Android devices. First we present an Efficient and Lightweight protocol for peer-to-peer Networking of Android smart devices over Wi-Fi Direct (ELN). ELN main goal is to overcome the Wi-Fi Direct support limitations in Android, thus allowing the devices in one Wi-Fi Direct group to communicate together. The ELN protocol is validated by implementing a group chatting application. In addition, we present a protocol for Alert Dissemination using Service discovery (ADS) in Wi-Fi Direct. ADS uses the service discovery feature of Wi-Fi Direct for distributing alerts to nearby devices without requiring any prior connections and thus avoids the setup delay in creating Wi-Fi Direct groups and the limitations of multi-group connectivity in Android. ADS is validated by implementing a hazard propagation application for Android. Finally, we present an Efficient Multi-group formation and Communication (EMC) protocol for Wi-Fi Direct. EMC exploits the battery specifications of the devices to qualify potential group owners and enable dynamic formation of efficient groups. Moreover, EMC allows data exchange between different Wi-Fi direct groups. Part of our implementation of EMC in Android involves the modification of the Android source code to allow multi-group support. A chat application is developed to validate EMC.

To complete the dissertation, we plan to extend EMC by replacing the static assignment of devices’ addresses in our current implementation with an IP address negotiation protocol that runs before creating groups. Such an extension would give greater flexibility in adapting EMC. In addition, we plan to define some criteria for selecting proxy members in order to allow maximum coverage and allow the D2D communication to span a larger geographical area. In addition, we will develop a simulator to do large scale testing for the proposed framework. Finally, we would like to explore the use of dual transceivers in order to increase the robustness of D2D connections when the wireless channels are subject to varying level of interference; particularly we like to investigate the integration of Bluetooth Low Energy within our framework to enable group membership of nodes that do not have Wi-Fi Direct or suffer interference that makes the Wi-Fi Direct links unstable.

Committee: Drs. Mohamed Younis (Chair), Charles Nicholas, Chintan Patel, Tinoosh Mohsenin

MS defense, Budhraja: Neuroevolution-Based Inverse Reinforcement Learning


M.S. Thesis Defense

Neuroevolution-Based Inverse Reinforcement Learning

Karan K. Budhraja

9:00am Wednesday, 2 December 2015, ITE 346

Motivated by such learning in nature, the problem of Learning from Demonstration is targeted at learning to perform tasks based on observed examples. One of the approaches to Learning from Demonstration is Inverse Reinforcement Learning, in which actions are observed to infer rewards. This work combines a feature based state evaluation approach to Inverse Reinforcement Learning with neuroevolution, a paradigm for modifying neural networks based on their performance on a given task. Neural networks are used to learn from a demonstrated expert policy and are evolved to generate a policy similar to the demonstration. The algorithm is discussed and evaluated against competitive feature-based Inverse Reinforcement Learning approaches. At the cost of execution time, neural networks allow for non-linear combinations of features in state evaluations. These valuations may correspond to state value or state reward. This results in better correspondence to observed examples as opposed to using linear combinations.

This work also extends existing work on Bayesian Non-Parametric Feature construction for Inverse Reinforcement Learning by using non-linear combinations of intermediate data to improve performance. The algorithm is observed to be specifically suitable for a linearly solvable non-deterministic Markov Decision Processes in which multiple rewards are sparsely scattered in state space. Performance of the algorithm is shown to be limited by parameters used, implying adjustable capability. A conclusive performance hierarchy between evaluated algorithms is constructed.

Committee: Drs. Tim Oates, Cynthia Matuszek and Tim Finin

PhD defense: R. Holder, Plan Adaptation Through Offline Analysis of Potential Plan Disruptors

Ph.D. Dissertation Defense
Computer Science and Electrical Engineering
University of Maryland, Baltimore County

Rapid Plan Adaptation Through Offline
Analysis of Potential Plan Disruptors

Robert H. Holder, III

9:00am Wednesday, 9 December 2015, ITE 325b

Computing solutions to intractable planning problems is particularly problematic in dynamic, real-time domains. For example, visitation planning problems, such as a delivery truck that must deliver packages to various locations, can be mapped to a Traveling Salesman Problem (TSP). The TSP is an NP-complete problem, requiring planners to use heuristics to find solutions to any significantly large problem instance, and can require a lengthy amount of time. Planners that solve the dynamic variant, the Dynamic Traveling Salesman Problem (DTSP), calculate an efficient route to visit a set of potentially changing locations. When a new location becomes known, DTSP planners typically use heuristics to add the new locations to the previously computed route. Depending on the placement and quantity of these new locations, the efficiency of this adapted, approximated solution can vary significantly. Solving a DTSP in real time thus requires choosing between a TSP planner, which produces a relatively good but slowly generated solution, and a DTSP planner, which produces a less optimal solution relatively quickly.

Instead of quickly generating approximate solutions or slowly generating better solutions at runtime, this dissertation introduces an alternate approach of precomputing a library of high-quality solutions prior to runtime. One could imagine a library containing a high-quality solution for every potential problem instance consisting of potential new locations, but this approach obviously does not scale with increasing problem complexity. Because complex domains preclude creating a comprehensive library, I instead choose a subset of all possible plans to include. Strategic plan selection will ensure that the library contains appropriate plans for future scenarios.

Committee: Drs. Marie desJardins (co-chair), Tim Finin (co-chair), Tim Oates, Donald Miner, R. Scott Cost

New spring course: Principles of Human-Robot Interaction

Principles of Human-Robot Interaction

CSEE professor Cynthia Matuszek will teach a new special topics course this spring on Principles of Human-Robot Interaction. The graduate level course (CMSC 691-08) will meet on Tuesday and Thursdays from 4:00 to 5:30pm in 013 Sherman Hall.


Principles of Human-Robot Interaction

An introduction to robots in our daily lives

CMSC691-08, 4:00-5:15pm Tue/Thr, starting 26 January 2016, UMBC

Robots are becoming ubiquitous. From Roombas in our homes, to surgical robots in hospitals, to giant manipulators that assemble cars, robots are everywhere. In the past, robots have only ever interacted with highly trained experts. Now, as they are being deployed more widely, we must address new questions about how our robots can interact day-to-day with end users — non-experts — safely, usefully, and pleasantly. This new area of research is called Human-Robot Interaction, or HRI.

This 3-credit special topics course aims to introduce students to current research in HRI and provide hands-on experience with HRI research. Students will explore the diverse range of research topics in this area, learn to identify HRI problems in their own research, and carry out a collaborative project involving human-robot interactions. Topics to be covered include:

  • Social robots: how can robots be social beings? When do we want them to?
  • Human-robot collaboration: humans and robots working together on tasks
  • Natural-language interactions with robots and human-robot dialog
  • Telerobotics: the uses of remote presence and teleoperation
  • Expressive robots: how can robots express emotion – and should they?

Students may benefit from having some previous coursework or experience in AI, machine learning, or robotics, but none are necessary. Undergraduate students can enroll with the instructor’s permission. For more information, contact Dr. Matuszek at cmat at

Apply to CRA-W 2016 Grad Cohort Workshop by Nov. 30


CRA-W is now accepting applications for Grad Cohort 2016, a two-day workshop during which participants will learn graduate school survival skills, receive mentoring, and develop networks with senior female computing researchers. This is a great opportunity for female graduate students to build mentoring relationships and develop peer networks to form the foundation of their graduate career and beyond.p

Female graduate students in their first three years are eligible to apply. Reasonable travel expenses, meals, and lodging will be provided for students chosen to participate in this program.

The Grad Cohort 2016 workshop will be held at the Hilton San Diego Bayfront in San Diego, California, on April 15-16, 2016. The application deadline is 30 November 2015. Apply online here and get more information at the Grad Cohort 2016 Workshop site.

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