CSEE at Undergraduate Research and Creative Achievement Day

CSEE students at UMBC’s 23nd Annual Undergraduate Research and Creative Achievement Day

Congratulations to the 49 undergraduate majors from our computer engineering and computer science programs who are presenting their research at the 23nd Annual Undergraduate Research and Creative Achievement Day on Wednesday, 24 April 2019.

  • Devon Adams | Computer Science and Electrical Engineering
    Development Of An Autonomous Vehicle For The Micromouse Competition
    Mentor(s): E F Charles LaBerge
    UC Ballroom | 1 – 2:30 p.m.
  • Aileiwaer Airexiati | Computer Science and Electrical Engineering
    Development Of An Autonomous Vehicle For The Micromouse Competition
    Mentor(s): E F Charles LaBerge
    UC Ballroom | 1 – 2:30 p.m.
  • Rashed Mohamed Salem Ali Alhefeiti | Computer Science and Electrical Engineering
    Development Of An Autonomous Vehicle For The Micromouse Competition
    Mentor(s): E F Charles LaBerge
    UC Ballroom | 1 – 2:30 p.m.
  • Ahmed Ali Almehrzi | Computer Science and Electrical Engineering
    Micromouse-X : UMBC Capstone Project
    Mentor(s): E.F. Charles LaBerge
    UC Ballroom | 10 – 11:30 a.m.
  • Trevor Ancona | Computer Science and Electrical Engineering
    UMBC Game Developers Club 2018-2019 Game Projects
    Mentor(s): Marc Olano
    UC Ballroom Lounge | 10 – Noon
  • Ryan Apt | Computer Science and Electrical Engineering
    Development Of An Autonomous Vehicle For The Micromouse Competition
    Mentor(s): E F Charles LaBerge
    UC Ballroom | 1 – 2:30 p.m.
  • Courtney Bohn | Computer Science and Electrical Engineering
    Creating A Quadruped Robot With Walking And Wheeled Capabilities
    Mentor(s): Fow-Sen Choa
    UC Ballroom | 1 – 2:30 p.m.
  • Cameron Blomquist | Computer Science and Electrical Engineering
    UMBC Game Developers Club 2018-2019 Game Projects
    Mentor(s): Marc Olano
    UC Ballroom Lounge | 10 – Noon
  • Maxwell Breitmeyer | Computer Science and Electrical Engineering
    Virtual Reality And Photogrammetry For Improved Reproducibility Of Human-Robot Interaction Studies
    Mentor(s): Don Engel
    UC Ballroom | 10 – 11:30 a.m.
  • Elwin Brown | Computer Science and Electrical Engineering
    Thirst: A Quest To Restore The Oasis
    Mentor(s): Marc Olano
    UC Ballroom Lounge | 10 – Noon
  • Elwin Brown | Computer Science and Electrical Engineering
    Toward The Application Of SVM’s For Text-Based Replication Of CATME Peer Evaluations
    Mentor(s): Don Engel
    UC Ballroom | 1 – 2:30 p.m.
  • Erin Cannon | Computer Science and Electrical Engineering
    Thirst: A Quest To Restore The Oasis
    Mentor(s): Marc Olano
    UC Ballroom Lounge | 10 – Noon
  • Noah Carver | Computer Science and Electrical Engineering
    Modular Solvers For Partially Continuous Abstract Markov Decision Processes
    Mentor(s): Cynthia Matuszek
    UC Ballroom | 1 – 2:30 p.m.
  • Dan Castellano | Computer Science and Electrical Engineering
    Brain Guitar-Pedal Interface
    Mentor(s): E. F. Charles LaBerge
    UC Ballroom | Time
  • Caroline Cocca | Computer Science and Electrical Engineering
    Investigating Teamwork Quality Through Neural Networks And Text Analysis
    Mentor(s): Don Engel
    UC Ballroom | 10 – 11:30 a.m.
  • Adam Der | Computer Science and Electrical Engineering
    Fabrication Of A Wearable Temperature Sensing System For CIPA Patients
    Mentor(s): Gymama Slaughter
    UC 312 | 3:45 – 4 p.m.
  • Debora Diaz Diestra | Computer Science and Electrical Engineering
    Micromouse-X : UMBC Capstone Project
    Mentor(s): E.F. Charles LaBerge
    UC Ballroom | 10 – 11:30 a.m.
  • Anthony Ellis | Computer Science and Electrical Engineering
    UMBC Game Developers Club 2018-2019 Game Projects
    Mentor(s): Marc Olano
    UC Ballroom Lounge | 10 – Noon
  • Carllie Foley | Computer Science and Electrical Engineering
    Escape To Planet Earth
    Mentor(s): Marc Olano
    UC Ballroom Lounge | 10 – Noon
  • Charles Fox | Computer Science and Electrical Engineering
    Investigating Teamwork Quality Through Neural Networks And Text Analysis
    Mentor(s): Don Engel
    UC Ballroom | 10 – 11:30 a.m.
  • Jaylan Hall | Computer Science and Electrical Engineering
    Creating A Quadruped Robot With Walking And Wheeled Capabilities
    Mentor(s): Fow-Sen Choa
    UC Ballroom | 1 – 2:30 p.m.
  • Edward Hanson | Computer Science and Electrical Engineering
    Brain Guitar-Pedal Interface
    Mentor(s): E. F. Charles LaBerge
    UC Ballroom | 10 – 11:30 a.m.
  • Brian D. Hanson, Jr. | Computer Science and Electrical Engineering
    Fabrication Of A Wearable Temperature Sensing System For CIPA Patients
    Mentor(s): Gymama Slaughter
    UC 312 | 3:45 – 4 p.m.
  • Kit Heckman | Computer Science and Electrical Engineering
    UMBC Game Developers Club 2018-2019 Game Projects
    Mentor(s): Marc Olano
    UC Ballroom Lounge | 10 – Noon
  • Phillip Hilliard | Computer Science and Electrical Engineering
    Annotating And Predicting Contextual Sentiment In Text
    Mentor(s): Frank Ferraro
    UC Ballroom | 1 – 2:30 p.m.
  • Mark Horton | Computer Science and Electrical Engineering
    Brain Guitar-Pedal Interface
    Mentor(s): E. F. Charles LaBerge
    UC Ballroom | 10 – 11:30 a.m.
  • Mark Horton | Computer Science and Electrical Engineering
    Autoencoder Implementation For Embedded Reinforcement Learning
    Mentor(s): Tinoosh Mohsenin
    UC Ballroom | 10 – 11:30 a.m.
  • Ben Ireland | Computer Science and Electrical Engineering
    UMBC Atmospheric Lidar Group DATA: Distributed Systems & Cyber-Security Of Remote Sensing Profiling Network Testbed
    Mentor(s): Ruben Delgado
    UC 312 | 4 – 4:15 p.m.
  • Zachary Jones | Computer Science and Electrical Engineering
    Brain Guitar-Pedal Interface
    Mentor(s): E. F. Charles LaBerge
    UC Ballroom | 10 – 11:30 a.m.
  • Thomas Kohler | Computer Science and Electrical Engineering
    Micromouse-X : UMBC Capstone Project
    Mentor(s): E.F. Charles LaBerge
    UC Ballroom | 10 – 11:30 a.m.
  • Alex Leger | Computer Science and Electrical Engineering
    UMBC Game Developers Club 2018-2019 Game Projects
    Mentor(s): Marc Olano
    UC Ballroom Lounge | 10 – Noon
  • Josh Ludlow | Computer Science and Electrical Engineering
    UMBC Game Developers Club 2018-2019 Game Projects
    Mentor(s): Marc Olano
    UC Ballroom Lounge | 10 – Noon
  • Lucas McCullum | Computer Science and Electrical Engineering
    Development Of An Autonomous Vehicle For The Micromouse Competition
    Mentor(s): E F Charles LaBerge
    UC Ballroom | 1 – 2:30 p.m.
  • Andrew McLamb | Computer Science and Electrical Engineering
    Escape To Planet Earth
    Mentor(s): Marc Olano
    UC Ballroom Lounge | 10 – Noon
  • Stephanie Milani | Computer Science and Electrical Engineering
    A Hierarchical Framework For Norm-Aware Planning And Reinforcement Learning
    Mentor(s): Marie desJardins
    UC Ballroom | 10 – 11:30 a.m.
  • Shawn Oppermann | Computer Science and Electrical Engineering
    UMBC Game Developers Club 2018-2019 Game Projects
    Mentor(s): Marc Olano
    UC Ballroom Lounge | 10 – Noon
  • Nicholas Potteiger | Computer Science and Electrical Engineering
    Archiving Workflows In Cloud Based Storage
    Mentor(s): Douglas Thain
    UC Ballroom | 1 – 2:30 p.m.
  • Ben Przysucha | Computer Science and Electrical Engineering
    UMBC Game Developers Club 2018-2019 Game Projects
    Mentor(s): Marc Olano
    UC Ballroom Lounge | 10 – Noon
  • Zhou Qin | Computer Science and Electrical Engineering
    Micromouse-X : UMBC Capstone Project
    Mentor(s): E.F. Charles LaBerge
    UC Ballroom | 10 – 11:30 a.m.
  • Brendan Robison | Computer Science and Electrical Engineering
    Wizards
    Mentor(s): Marc Olano
    UC Ballroom Lounge | 10 – Noon
  • Shea Sandifer | Computer Science and Electrical Engineering
    UMBC Game Developers Club 2018-2019 Game Projects
    Mentor(s): Marc Olano
    UC Ballroom Lounge | 10 – Noon
  • Matthew Schweiss | Computer Science and Electrical Engineering
    Creating A Quadruped Robot With Walking And Wheeled Capabilities
    Mentor(s): Fow-Sen Choa
    UC Ballroom | 1 – 2:30 p.m.
  • Danielle Sherrod | Computer Science and Electrical Engineering
    Creating A Quadruped Robot With Walking And Wheeled Capabilities
    Mentor(s): Fow-Sen Choa
    UC Ballroom | 1 – 2:30 p.m.
  • Levan Sulimanov | Computer Science and Electrical Engineering
    Virtual Reality Mirror Therapy Rehabilitation For Post-Stroke Patients
    Mentor(s): Marc Olano
    UC Ballroom Lounge | 10 – Noon
  • Danilo Symonette | Computer Science and Electrical Engineering
    Toward The Application Of SVM’s For Text-Based Replication Of CATME Peer Evaluations
    Mentor(s): Don Engel
    UC Ballroom | 1 – 2:30 p.m.
  • Jordan Troutman | Computer Science and Electrical Engineering
    Understanding Machine Learning Bias Without A Ground Truth
    Mentor(s): Anand Sarwate
    UC Ballroom | 10 – 11:30 a.m.
  • Liam Upton | Computer Science and Electrical Engineering
    UMBC Game Developers Club 2018-2019 Game Projects
    Mentor(s): Marc Olano
    UC Ballroom Lounge | 10 – Noon
  • Jenna Westfall | Computer Science and Electrical Engineering
    Automatization Of Characterization Of Atmospheric Particles With Machine Learning
    Mentor(s): Ruben Delgado
    UC Ballroom | 1 – 2:30 p.m.
  • Brendan Witt | Computer Science and Electrical Engineering
    Using Augmented Reality And Smart Home Devices to Better Sense Users
    Mentor(s): Reynold Bailey
    UC Ballroom | 1 – 2:30 p.m.

Meet Your Professor: Dr. Cynthia Matuszek, 12-1 Mon 4/15, ITE231

Meet Your Professor: Dr. Cynthia Matuszek

On April 15th, come join the Computer Science Education Club for the third installment of its Spring 2019 Meet Your Professor series featuring Dr. Cynthia Matuszek. The Meet Your Professor events provide students with the opportunity to learn more about their professors, including how they achieved their position, what they believe makes an effective teacher, what research they conduct, and more!

Dr. Matuszek’s areas of research include robotics, natural language processing, human-robot interaction, and artificial intelligence. At UMBC she heads the Interactive Robotics and Language lab She has taught courses in robotics, artificial intelligence, advanced AI, human-robot interaction, and ethics in computing.

If you want to learn from Dr. Matuszek’s experience in academia, come to ITE 231 on April 15th from 12pm-12:50pm.

talk: Learning to Ground Instructions to Plans, 2:30 Thr 3/21, ITE346

Learning to Ground Natural Language Instructions to Plans

Nakul Gopalan, Brown University

2:30-3:30pm Thursday, 21 March 2019, ITE 346, UMBC

In order to easily and efficiently collaborate with humans, robots must learn to complete tasks specified using natural language. Natural language provides an intuitive interface for a layperson to interact with a robot without the person needing to program a robot, which might require expertise. Natural language instructions can easily specify goal conditions or provide guidances and constraints required to complete a task. Given a natural language command, a robot needs to ground the instruction to a plan that can be executed in the environment. This grounding can be challenging to perform, especially when we expect robots to generalize to novel natural language descriptions and novel task specifications while providing as little prior information as possible. In this talk, I will present a model for grounding instructions to plans. Furthermore, I will present two strategies under this model for language grounding and compare their effectiveness. We will explore the use of approaches using deep learning, semantic parsing, predicate logic and linear temporal logic for task grounding and execution during the talk.

Nakul Gopalan is a graduate student in the H2R lab at Brown University. His interests are in the problems of language grounding for robotics, and abstractions within reinforcement learning and planning. He has an MSc. in Computer Science from Brown University (2015) and an MSc. in Information and Communication Engineering from T.U. Darmstadt (2013) in Germany. He completed a Bachelor of Engineering from R.V. College of Engineering in Bangalore, India (2008). His team recently won the Brown-Hyundai Visionary Challenge for their proposal to use Mixed Reality and Social Feedback for Human-Robot collaboration.

Host: Prof. Cynthia Matuszek (cmat at umbc.edu)

talk: Algorithms for Weakly Supervised Denoising of EEG Data, 6:30pm Feb 28

The February meeting of the Data Works MD Meetup features a talk by UMBC Professor Tim Oates on  Two Algorithms for Weakly Supervised Denoising of EEG Data, 6:30-9pm Thursday, February 28, 2019 at UMBC’s South Campus.  Join the meetup and register to attend this free talk and network with members of the Maryland data science community.  The talk abstract and Dr. Oates’s biosketch are given below.

Electroencephalogram (EEG) data is used for a variety of purposes, including brain-computer interfaces, disease diagnosis, and determining cognitive states. Yet EEG signals are susceptible to noise from many sources, such as muscle and eye movements, and motion of electrodes and cables. Traditional approaches to this problem involve supervised training to identify signal components corresponding to noise so that they can be removed. However, these approaches are artifact specific. In this talk, I will discuss two algorithms for solving this problem that uses a weak supervisory signal to indicate that some noise is occurring, but not what the source of the noise is or how it is manifested in the EEG signal. In the first algorithm, the EEG data is decomposed into independent components using Independent Components Analysis, and these components form bags that are labeled and classified by a multi-instance learning algorithm that can identify the noise components for removal to reconstruct a clean EEG signal. The second algorithm is a novel Generative Adversarial Network (GAN) formulation. I’ll present empirical results on EEG data gathered by the Army Research Lab, and discuss pros and cons of both algorithms.

Dr. Tim Oates is an Oros Family Professor in the Computer Science Department at the University of Maryland, Baltimore County. His Ph.D. from the University of Massachusetts Amherst was in the areas of artificial intelligence and machine learning with a focus on situated language learning. After working as a postdoctoral researcher in the MIT Artificial Intelligence Lab, he joined UMBC where he has taught extensively in core areas of Computer Science, including data structures, discrete math, compiler design, artificial intelligence, machine learning, and robotics. Dr. Oates has published more than 150 peer-reviewed papers in areas such as time series analysis, natural language processing, relational learning, and social media analysis. He has developed systems to determine operating room state from video streams, predict the need for blood transfusions and emergency surgery for traumatic brain injury patients based on vital signs data, detect seizures from scalp EEG, and find story chains (causal connections) joining news articles, among many others. Recently Dr. Oates served as the Chief Scientist of a Virginia-based startup where he developed architectures and algorithms for managing contact data, including entity linking, fuzzy record matching, and connected components on billion node graphs stored in a columnar database. He has extensive knowledge of machine learning algorithms, implementations, and usage.

talk and demo: Exploiting IoT Vulnerabilities, 11:45-1:00pm Mon 2/18

Exploiting IoT Vulnerabilities

Dr. Yatish Joshi, Senior Engineer, Cisco Systems

11:45am-1:00pm Monday, 18 February 2019, ITE 325-B

The past decade has seen explosive growth in the use and deployment of IoT (Internet of Things) devices. According to Gartner there will be about 20.8 billion IoT devices in use by 2020. These devices are seeing wide spread adoption as they are cheap, easy to use and require little to no maintenance. In most cases, setup simply requires using a web or phone app to configure Wi-Fi credentials. Digital home assistants, security cameras, smart locks, home appliances, smart switches, toys, vacuum cleaners, thermostats, leakage sensors etc are examples of IoT devices that are widely used and deployed in home and enterprise environments.

The threat landscape is constantly evolving and threat actors are always on the prowl for new vulnerabilities they can exploit. With traditional attack methods yielding fewer exploits   due to the increased focus on security testing, frequent patches, increased user awareness, Threat actors have turned their attention on IoT devices and are exploiting inherent vulnerabilities in these devices. The vulnerabilities, always ON nature, and autonomous mode of operation allow attackers to spy on users, spoof data, or leverage them as botnet infrastructure to launch devastating attacks on third parties. Mirai, a well known IoT malware utilized hundreds and thousands of enslaved IoT devices to launch DDoS attacks on Dyn affecting access to Netflix, Twitter, Github and many other websites. With the release of the Mirai source code numerous variants of the malware are infecting IoT devices across the world and using them to carry out attacks.

These attacks are made possible because the devices are manufactured without security in mind!. In this talk I will demonstrate how one can hack a widely available off-the-shelf IP Camera and router by exploiting the vulnerabilities present in these devices to get on the network, steal personal data, spy on a user, disrupt operation etc. We will also look at what can be done to mitigate the dangers posed by IOT devices.

So attend hack & defend!

Dr. Yatish Joshi is a software engineer in the Firepower division at Cisco Systems where he works on developing new features for Cisco’s security offerings. Yatish has a PhD in Computer Engineering from UMBC. Prior to Cisco Yatish worked as a lecturer at UMBC, and was a senior software engineer developing TV software at Samsung Electronics. When not working, he enjoys reading spy thrillers and fantasy novels.

talk: OMI, Invisible Technology that will Revolutionize Supercomputing and AI; 3pm Thr Feb 14, ITE325

Distinguished Lecture Series

OMI: The Invisible Technology that will Revolutionize Supercomputing and AI

Prof. Harm Peter Hofstee
Delft University of Technology
Distinguished Research Staff, IBM Austin Research Laboratory

3:00pm Thursday 14 February, 2019, ITE325, UMBC

In this talk, we present some major trends in compute, memory/storage, and networking, and for each we will discuss how OpenCAPI Memory Interface (OMI) and related interface technologies are set to transform how we build, program, and think about our computer systems. For the first of these trends, it allows us to compensate for the reduced growth in processor performance (per dollar) and performance per Watt. Accelerators are sharing memory and other resources over NVLink or OpenCAPI with conventional IBM POWER cores and are driving performance in the world’s largest supercomputers and IBM’s systems are targeting AI and other workloads. The second addresses the reduced improvement in memory cost and capacity. OMI allows us to use technologies other than DRAM as memory, and because many of these technologies are nonvolatile, the line between memory and storage is becoming blurred. The third, OpenCAPI-based networking leverages the rapid improvements in cost per Gb/s and allows us to contemplate systems that extend memory beyond the node using commodity infrastructure.

Harm Peter Hofstee is a Dutch physicist and computer scientist who currently is a distinguished research staff member at the IBM Austin Research Laboratory, USA, and a part-time Professor in Big Data Systems at Delft University of Technology, Netherlands. Hofstee is best known for his contributions to Heterogeneous computing as the chief architect of the Synergistic Processor Elements in the Cell Broadband Engine processor used in the Sony PlayStation 3, and the first supercomputer to reach sustained Petaflop operation. His early research work on coherently attached reconfigurable acceleration on POWER7 paved the way for the new coherent attach processor interface on POWER8. Hofstee is an IBM Master Inventor with more than 100 issued patents and a member of the IBM Academy of Technology. Hofstee was born in Groningen and obtained his master’s degree in theoretical physics of the University of Groningen in 1988. He continued to study at the California Institute of Technology where he wrote a master’s thesis Constructing Some Distributed Programs in 1991 and obtained a Ph.D. with a thesis titled Synchronizing Processes in 1995. He joined Caltech as a lecturer for two years and moved to IBM in the Austin, Texas, Research Laboratory, where he had staff member, senior technical staff member and distinguished engineer positions.

MD-AI Meetup: An AI Enabled Vision of the Future, 6-8pm 2/12, UMBC

talk: Using Deep Learning in Identifying Network Intrusions, 10:30am Mon 2/11, UMBC

Maryland Data Science Conference, Fri. 1/25, UMBC (new date)

MD Data Science Conference
Friday, 25 January, PAH Concert Hall, UMBC

Miner & Kasch

, a AI and data science consulting firm founded by two UMBC alumni, will hold a one-day Data Science Conference at UMBC on Friday, January 25 in the Linehan Concert Hall of the UMBC Performing Arts & Humanities Building. A limited number of free tickets are available for current UMBC students. To attend, you need to register here.

The event was originally scheduled for January 14, but had to be rescheduled due to inclement weather. If you had registered and obtained a ticket earlier, you will need to re-register.

The event brings together local companies and professionals to share what new and exciting things they are doing with their data. It will be attended by business managers, startup founders, software engineers, data scientists, students, and other curious people that want to learn more about the cutting edge of data science, machine learning, and AI. See the conference website for topics and speakers.

Workshop on Usable Security, 10-4 Tue 12/18

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