Sustainable Wireless Communications and Networking for Internet of Things

Date/Time: Monday, April 16th from 11:00 a.m. - 11:50 a.m.
Location: Barnard Hall 347
Dr. Lina Pu

Abstract: Internet of Things (IoT) is the technology that will transform our world in the coming years. IoT-based devices are now ubiquitous (e.g., smartphone, tablet, and smart TVs, etc) in terrestrial, and will expand to the underwater world. Sustainable power supply and spectrum utilization are challenging issues for IoT systems (e.g., wearable devices, underwater sensor networks). Innovative Radio Frequency (RF) energy harvesting technology coupled with IoT is expected to have a broad impact on multiple sectors including healthcare, public safety, and surveillance. Cognitive acoustic technology combined with IoT is a promising solution to sharing acoustic spectrum with marine animals efficiently, friendly, and intelligently. In this talk, Dr. Pu will report her explorations of sustainable wireless communications and networking in terrestrial and underwater environments. First, she will discuss how to manage the energy harvested from ambient RF environment for efficient information transmission. Afterwards, she will introduce her recent work on the optimal energy request from dedicated energy sources for efficient energy utilization. Dr. Pu will also briefly introduce the cyclostationary-based spectrum sensing approach for marine animal detection in underwater cognitive acoustic networks.

Biosketch: Dr. Lina Pu is currently a visiting scientist in the Electrical and Computer Engineering Department, South Dakota School of Mines and Technology, where she initially joined as Research Engineer in August 2016. She received her Ph.D. degree from the Department of Computer Science and Engineering, University of Connecticut, in December 2015. Dr. Pu’s research interests include, but are not limited to: cyber-physical systems, cybersecurity, data analysis in smart health/grid/city, resilience and sustainable network design, wireless/underwater sensor networks, energy harvesting Internet of Things. Dr. Pu has published over 20 papers in prestigious journals and international conferences. She was the recipient of the Best Paper Award IFIP Networking Conference in 2013. She has been serving as TPC members and technical reviewer for dozens of journals and international conferences as well.

Robots: “You’ll never walk alone”

Date/Time: Monday, April 9th from 4:10 p.m. - 5:00 p.m.
Location: Barnard Hall 108
Dr. Jeffrey Skidmore

Abstract: Robotics is a fascinating and expanding interdisciplinary field with many potential applications. Robots have already been integrated into many areas of our everyday life and will likely become more prevalent in the coming years. In this seminar I will first provide an overview of robotics and introduce a variety of existing robotic systems. I will then highlight a recent project in which I developed a robotic treadmill system to implement a unique approach to gait rehabilitation after stroke or other neurological injury. I will present the design and operation of the system followed by experimental results and the implications for gait rehabilitation. My goal is to have attendees leave the seminar with a better understanding of the field of robotics and the potential to utilize robots to provide economical and effective solutions to interdisciplinary challenges.

Biosketch: Jeffrey Skidmore graduated with degrees in mechanical engineering from Brigham Young University (B.S.) and Arizona State University (Ph.D.) in 2013 and 2017, respectively. He is currently a postdoctoral researcher in the Department of Biomedical Engineering at The Ohio State University. His research interests include bio-inspired robotics, humanitarian robotics, and robot-assisted neurorehabilitation. He has authored several peer-reviewed publications and has presented his research in China, Sweden, and various locations throughout the United States. Jeffrey has received various awards and honors including being named the Outstanding Graduate for the ASU College of Engineering and twice receiving the Achievement Rewards for College Scientists (ARCS) fellowship.

Computational Pan-Genomics: Algorithms and Applications

Date/Time: Monday, March 26, 2018 from 12:00 p.m. - 2:00 p.m.
Barnard Hall 347
Alan Cleary

Abstract: As the cost of sequencing DNA continues to drop the number of sequenced whole genomes rapidly grows. In the recent past, the cost dropped so low that it is no longer prohibitively expensive to sequence multiple whole genomes for the same species. This has led to a shift from the single reference genome per species paradigm to the more comprehensive pan-genomics approach, where populations of genomes from one or more species are analyzed together.

The total genomic content of a population is vast, requiring algorithms for analysis that are more sophisticated and scalable than existing methods. Furthermore, existing algorithms are generally not intended for analyzing populations, let alone without a reference, and so they are inappropriate for pan-genome analysis. The focus of this defense is the exploration of new algorithms and their applications to pan-genome analysis, both at the nucleotide and genic resolutions.

Computing Reaction Fluxes from Real World Metabolomics Data

Date/Time: Tuesday, March 27, 2018 from 3:00 p.m. - 5:00 p.m.
Barnard Hall 347
Daniel Salinas 

Abstract: Time series metabolomics data can be used to infer rates for the chemical reactions in metabolism. Real world data presents challenges to the application of the stoichiometric models required. In this work, we explore techniques to infer reaction rates from high performance liquid chromatography-mass spectrometry data that is low-coverage, is derived from multiple patients, or has not been matched to metabolites. These techniques are applied to data derived from experiments on osteoarthritic chondrocytes. The techniques used involve modification of the stoichiometric matrix, decomposition of the variation into components according to an analysis of variance model, and selecting a minimal set of pathways that cover the set of mass-to-charge ratios and retention times in the data.

 The results show that the reaction rates inferred from the incomplete data arebiologicallyrelevant, and that the minimal pathways captured ancillary processes that alternative approaches ignored. We conclude that, although the resulting rates and pathways are not conclusive, they provide useful guidance on experiments to pursue. On the experimental side, ourfindingshave lead us to believe that osteoarthritic chondrocytes respond to compression by initiating protein synthesis, opening the possibility of physical therapy as a stimulus for cartilage regeneration.

Empirical Software Engineering and Technical Debt

Date/Time: Friday, March 2, 2018 from 4:10 p.m. - 5:00 p.m.
Barnard Hall 108
Graziela Simone Tonin

Abstract: The main topic of the talk will be empirical software engineering with a focus on technical debt. The studies and results conducted in two Brazilian software companies and an XP Course will be discussed and compared with the literature. As a result, a conceptual model for technical debt management was constructed. Additionally, projects developed at a Software Engineering Laboratory will be shown, including details on one in smart cities and, an extension project to teach technology and entrepreneurship in poor communities which aims to empower people in difficult situations. Furthermore, works at a Computer Science Junior Company and at the University Business Incubator encouraging students to create and develop their own business will be explained.

Bio: Graziela graduated in 2009 in Computer Science from URI-Brazil. She then worked as a Systems Analyst, IT Coordinator, Project Manager, and Researcher. She finished her Master of Science degree at UFPE-Brazil in 2011, where she has also worked as a researcher at a Samsung project. She started her Ph.D. at USP in 2012, where she received a prestigious Ph.D. Fellowship award from IBM-Research. She lived in several places in Brazil and in the United States where she did an internship at UMBC/Baltimore with Professor Seaman. She gave several lectures in Brazil (AgileBrazil, AgileTrends, Women in Technology), in the United States (Agile 2014) and Germany (XP2017). She was invited to attend the important meeting of scientists on Technical Debt in Dagstuhl/Germany. Her talks focus on empirical software engineering, technical debt, and female entrepreneurship. She is currently an assistant professor at the Federal University of Fronteira Sul -Brazil. Her research is focused on the technical debt area, empirical software engineering, smart cities, and entrepreneurship.

Machine Learning-Enhanced Visualization

Date/Time: Monday, February 26, 2018 from 4:10 p.m. - 5:00 p.m.
Barnard Hall 108
Matthew Berger

Abstract: Visualization is indispensable for exploratory data analysis, enabling people to interact with and make sense of data. Interaction is key for effective exploration, and is dependent on two main factors: how data is represented, and how data is visually encoded. For instance, text data may be represented as a 2D spatialization and visually encoded through graphical marks, color, and size. Typically, these factors do not anticipate how a user will interact with the data, however, which limits the set of interactions one may perform in data exploration. In this talk I will focus on how machine learning can be used to improve data representations and visual encodings for user interaction. My research is centered on building machine learning models when visualization, and in particular how a user interacts with data, is the primary objective. I will first discuss how to learn data representations for the purpose of interactive document exploration. I will demonstrate how compositional properties of neural language models, built from large amounts of text data, empowers the user to semantically explore document collections. Secondly, I will show how to learn visual encodings for the purpose of exploring volumetric data. Deep generative models are used to learn the distribution of outputs produced from a volume renderer, providing the user both guidance and intuitive interfaces for volume exploration.

Bio: Matthew Berger is a postdoctoral research associate in the Department of Computer Science at the University of Arizona, advised by Joshua A. Levine. Previously he was a research scientist with the Air Force Research Laboratory. He received his PhD in Computing from the University of Utah in 2013, advised by Claudio T. Silva. His research interests are at the intersection of machine learning and data visualization, focusing on the development of visualization techniques that are driven by machine learning models.

Slaying the White Dragon with Computers

Date/Time: Monday, February 12, 2018 from 4:10 p.m. - 5:00 p.m.
Barnard Hall 108
Marc Rubin

Abstract: In this seminar, Dr. Rubin will summarize how cyber-physical systems can be used to sense, detect, and ultimately predict snow avalanches.  Specifically, Marc will discuss several open applied computer science research projects within avalanche forecasting, including the use of deep learning to detect avalanches within seismic data, machine learning to predict snowpack stability from snow penetrometer data, and computer vision to classify microscopic images of snow crystals.

Bio: Dr. Marc Rubin received his PhD in Computer Science in 2014 from Colorado School of Mines where he was an NSF IGERT Fellow within the interdisciplinary SmartGeo research program.  Dr. Rubin’s research focuses on the application of wireless sensor technologies and machine learning algorithms towards automatic geohazard monitoring.  Dr. Rubin is currently an Instructor and Program Lead of Computer Science at Oregon State University-Cascades and, when not teaching, enjoys learning about new technologies, mountain biking, and skiing.

Towards a Secure Cyber World: Leveraging Human Factors in Improving Security and Privacy

Date/Time:  Monday, 5 February, 2018 from 4:10 PM - 5:00 PM
Barnard Hall 108
Mahdi Nasrullah Al-Ameen

Abstract:  Users are often considered to be the weakest link in security. For example, while creating an authentication secret, in most cases, users choose a password reflecting common strategies and patterns that ease memorization, but offer weak security. System-assigned passwords provide higher security guarantee, however, suffer from poor memorability.  In the first part of my talk, I discuss how I addressed this usability-security tension in user authentication. In particular, I designed and evaluated a novel cued-recognition authentication scheme, which provides users with memory cues to learn system-assigned keywords. I conducted several studies, including real-life field studies, to quantify the impact of providing different types of memory cues, e.g., graphical, verbal, and spatial cues, where I identified the best combination of memory cues to offer high memorability for a secure authentication scheme. In the second part of my talk, I present the findings from a real-world case study, where I explored the factors facilitating the successful preservation of security goals of Panama Paper Project–a worldwide collaboration among hundreds of investigative journalists. I identified the lessons that can be drawn from this case study to support the development of similarly effective processes for both privacy-preserving collaborations and security systems in general. The findings from my studies reflect the significance of considering human factors in improving Cybersecurity and privacy, and highlight the potentials for future work to develop usable and understandable security tools and strategies.

Bio: Dr. Mahdi Nasrullah Al-Ameen is a Post-doctoral Fellow in the School of Computing at Clemson University. His research interest is broad within the domain of Cyber Security, where he is particularly excited about designing and building systems that address the security and privacy challenges faced by end users of existing and emerging technologies. His research focuses on designing a novel security system to provide resilience against cyberattacks, and evaluating its usability in real-life contexts. He also led multiple projects in improving the security and privacy in peer-to-peer (P2P) networks. The findings from his studies are reported in top-tier venues, like USENIX Security Symposium, CHI, IEEE TPDS Special Issue, and in several prestigious venues, including Journal of Networks, Symposium on Usable Privacy and Security (SOUPS),ACM Symposium on Information, Computer, and Communications Security, and European Symposium on Research in Computer Security(ESORICS).  Dr. Al-Ameen completed his PhD from the University of Texas at Arlington, winning the Outstanding Doctoral Dissertation Award for his research on Cyber Security and Privacy.


S^1 and S^3 and S^2, oh fy! A digital Hopf fibration

Date/Time: Monday, 29 January, 2018 from 4:10 PM - 5:00 PM
Location: Barnard Hall 103 (Note the room change)
Speaker: Nick Scoville

Abstract: Digital images surround us. They are found in our computers, iPhones, televisions, and more. Because they are so integrated into our lives, there is a constant need to manipulate and investigate these images. Anything that one might want to do with a digital image will inevitably involve some kind of mathematics, whether it be linear algebra, geometry, or topology. To that end, we will introduce topology in the digital setting, noting some places where it is similar and different than in the smooth setting. In particular, we will work with digital homotopy between digital images by viewing a digital image as a graph. Although there is a notion of digital fibration in this context, there seem to be very few non-trivial examples of digital fibrations. We will construct a digital analogue of the Hopf fibration, the most important single example in the history of algebraic topology. Because the 3-sphere in this setting consists of only 24 pixels, this example is robust yet small enough to be written down and investigated explicitly. This talk will be accessible to undergraduates.

Bio: Nicholas Scoville is a faculty member at Ursinus College.  At Ursinus, he is the Joseph Beardwood III Chair of Mathematics.  His research is in topology.  He hols a BS and MS from Western Michigan University, and MA and PhD from Dartmouth College.

The role of application layer mechanisms in content distribution for mobile Web and augmented reality

Date/Time: Monday, October 2, 2017 from 4:10 p.m. - 5:00 p.m.
Location: Barnard Hall 108
Speaker: Mike Wittie

Abstract: In this talk I will present several methods for speeding up mobile Web content delivery in cellular networks. The common theme in these approaches is to give the application layer a choice in the use of network resources. Instead of using cross layer approaches, we rely on light weight application-layer measurement implemented and validated in the context of Akamai's CDN infrastructure. I will also discuss the implications of these results for the delivery of augmented reality content - traffic that is both similar and quite different in its characteristics from the mobile Web.

 Seminars from 2017.