Class Description

In this class researchers from the industry and academia present topics in Computer Science Related to their work or research. If you are taking this class for credit you will be required to write an abstract for each seminar due by Wednesday at 5PM PT of the same week as the presentation. Abstracts will be in pdf format and submitted through the submission page below. Content of the abstracts will be discussed in the first class meeting and in the class schedule below. Number and quality of abstracts relative to the abstract required for each talk will determine the grade. DO NOT MISS MORE THAN TWO TALKS if you want to pass this course. The course will be run on a 10 point system for each abstract as if they were homeworks. Quality counts. You can flunk by turning in nothing but poor reports. If you come to the class, listen, take a few notes, then this is an easy and fun course.

Note because this class is on Monday, when school is not held on Monday there is no class that week.

Time: M 3:30-4:30
Final: None
Location: EP 204
Text: None


This syllabus is an active document describing speakers and topics plus reference material for the seminar talks.


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1 Aug 21 NO CLASS!
2 Aug 28
Speaker: Kevin Shoemaker
Founder Basicsoft Inc. and Blue Chip Engineering.
Topic: The Secret Sauce
What has to come together for the establishment of a successful startup business. What are the watch outs? How do you recognize the "aha moments"? Why are networking and relationships important? Managing details while you recognize the big picture and create your own niche in a fast moving, heavily funded, instant gratification business environment. Is your goal a lifestyle, a short term or long term business plan.
Supporting Documents:
Shoemaker on LinkedIn,
the Basic Safe tool set ,
Slides for talk


4 Sep 11

Speaker:Predrag T. Tošić
Assistant Professor, Department of Computer Science, University of Idaho
Topic: Modeling Open and Closed Cyber-Physical Systems with Graph Automata and Boolean Networks
We study formal dynamical system foundations for modeling, analysis and behavior prediction of a variety of decentralized cyber-physical infrastructures. We are particularly interested in asymptotic dynamics of several classes of Boolean Networks (BNs) and Graph Automata (GA) models such as Discrete Hopfield Networks, Sequential & Synchronous Dynamical Systems, and variants of classical Cellular Automata (CA). Our recent research is centered on identifying key differences in dynamical behavior between open vs. closed cyber-physical systems, abstracted as BNs and GA.

A closed system can be modeled as a BN or GA in which each node is an "agent" with known local interactions; the challenge is, to predict the emerging behavior and collective dynamics of the entire agent ensemble. In an open cyber-physical system (or other types of open networks of interacting agents), external agents whose behavior is unknown may also be present and/or other aspects of the environment may exercise influence on our agents in potentially complex and unpredictable ways. Importantly, those who design, analyze or monitor the underlying (open) system usually have little or no control over the behavior of external agents or the "environment". To make the open vs. closed system dynamics differentiation as sharp as possible, we severely restrict the allowable kinds of impact of the “external environment" on the agents. We analyze configuration spaces of appropriately restricted types of BNs, GA and CA, mostly focusing on those properties capturing the underlying system's long-term collective behavior. We will summarize several recent results that establish provable "complexity gaps" in the dynamics of closed vs. open systems.
Supporting Documents:
Speaker's web page,
Speaker's publications,
Predrag Tosic is an early mid-career researcher with a unique mix of academic research, industrial and DOE lab R&D experiences. His research interests include AI, Data Science, Machine Learning, Intelligent Agents, and Multi-Agent Systems on the one hand, and Cyber-Physical/Cyber-Secure Systems, Distributed Coordination & Control, Large-scale Complex Networks, Internet-of-Things/Agents, and mathematical & computational models and algorithms for "smart" transportation, energy and other grids, on the other. He is particularly interested in applying data analytics, machine learning, intelligent agent and AI techniques to emerging problems related to large-scale decentralized cyber-physical systems, critical infrastructures and “smart grids”, autonomous vehicles, as well as energy, health care and other domains of major economic and societal impact.

Dr. Tosic holds a PhD in Computer Science from the University of Illinois at Urbana-Champaign (UIUC). His doctoral dissertation (2006) was on Distributed AI and large-scale Multi-Agent Systems. Most recently, at Washington State University (2015 - 2017) he worked on dynamics of complex networks, graph pattern mining, Boolean Network models of cyber-physical systems, Internet-of-Agents, as well as AI, data analytics and knowledge engineering applied to problems in health care. While at the University of Houston (2009 – 2012), he did research in machine learning, multi-agent distributed computing & control, data mining and distributed database systems, emerging behavior in complex networks, “smart energy” and computational game theory. During his graduate studies and combined five years of non-tenure-track academic research, he authored about 70 peer-reviewed publications; the rest of his career has been spent in high-tech industry. He holds three USPTO patents (IP of Cisco Systems). In addition to PhD in Computer Science, Dr. Tosic holds three MS degrees, two in mathematical sciences and one in computer science. Dr Tosic has a considerable teaching and student mentoring experience. He has been actively involved with IEEE -- the Palouse Section, and is currently President of the Section's Computer Society.

5 Sep 18

Speaker:Dr. Svitlana Volkova from PNNL
Senior Research Scientist, Data Sciences and Analytics Group, National Security Directorate, Pacific Northwest national Laboratory
Topic: Predicting the Future with Deep Learning and Signals from Social Media
Social media communications are reflections of events in the real world that can be used to build a variety of predictive analytics. In this talk I will present three studies that demonstrate how social media signals in combination with deep learning models can be effectively used to make predictions about the future. First, I will discuss the advantages of linguistically infused deep learning models to predict suspicious news posts on Twitter including satire, hoaxes, clickbait and propaganda. I will highlight significant differences in the use of biased, subjective language and moral foundations behind suspicious and trustworthy news posts. I will then present a large-scale analysis on targeted public sentiments using 1.2 million multilingual connotation frames extracted from Twitter. The analysis relies on connotation frames to build models to forecast country-specific connotation dynamics – perspective change over time towards salient entities and events during Brussels bombing. Finally, I will discuss a study on modeling language dynamics in social media by tracking how meaning of words fluctuates over time in the VKontakte social network. My team developed models to forecast short-term shifts in word’s meaning from previous meaning as well as from word dynamics. Our models and novel findings advance the understanding of journalistic portrayal and biases in news reports, and improve situational awareness during crisis events.
Supporting Documents:
Speaker's web page
Svitlana Volkova is a Senior Research Scientist in the Data Sciences and Analytics Group, National Security Directorate at Pacific Northwest National Laboratory. Dr. Volkova’s research focuses on advancing machine learning and natural language processing techniques to develop novel social media predictive and forecasting analytics. Svitlana’s recent work includes forecasting social media dynamics – opinions and emotions, infectious disease outbreaks, real-word events, entity and event-driven connotations, deception detection and information biases in news and social media. Svitlana interned at Microsoft Research at the Natural Language Processing and Machine Learning and Perception teams. She was awarded the Google Anita Borg Memorial Scholarship in 2010 and the Fulbright Scholarship in 2008. She is the Vice Chair of the ACM Future of Computing Academy. She received her PhD in Computer Science in 2015 from Johns Hopkins University where she was affiliated with the Center for Language and Speech Processing and the Human Language Technology Center of Excellence.

6 Sep 25

Speakers: Karen Stevenson, Jeremy Tamsen, Lokesh Mohan
Topic: Intellectual Property
The Office of Technology Transfer (OTT) invites you to learn about intellectual property in the context of computer science. Jeremy Tamsen, Director of OTT, will present to the group with the help of Licensing Associates Karen Stevenson and Lokesh Mohan; together they will describe the invention disclosure, assessment, and commercialization process in OTT. Jeremy will discuss computer science licensing models, and how they have changed in the past five years based on Intellectual Property (IP) litigation in the federal courts. The discussion will include a quick briefing on the court decisions (e.g. the Alice v. CLS litigation, and related fallout), how those decisions changed software patents, and how those changes in turn affected licensing. The presentation will conclude with a discussion of open-source licensing, and how that relates to university work.
Supporting Documents:
Karen Stevenson joined OTT in early 2007. Karen holds a BS in biochemistry and PhD in nuclear chemistry. For nearly 15 years she was employed as a scientist for various federal agencies, first at the US Geological Survey, then the Department of Energy, followed by the US Department of Defense. In addition to her ongoing research, she would review research proposals and ongoing applied research activities and then work with stakeholders to commercialize technologies that resulted from such funding. After leaving federal service, Karen worked as a private consultant assisting companies with their product marketing strategies within government and in the private sector.

Jeremy Tamsen joined OTT in November 2016. He brings to the University ten years of management, marketing and business development experience in the private sector, expertise in intellectual property and technology transfer, and a passion advising inventors and entrepreneurs. He has worked for Starbucks Coffee Company, Boise State University, and Howard Industries, a domestic technology firm. Dedicated to service, Jeremy serves on the Board of Directors for the Palouse Knowledge Corridor and the Be The Entrepreneur Bootcamp, and volunteers with the Idaho Technology Council, the Small Business Development Centers of Idaho, and the Idaho State Bar Association. Tamsen is a proud alumnus of the University of Idaho College of Law.

Lokesh Mohan joined OTT as Licensing Associate in February 2017. Lokesh focuses on commercializing life sciences, and engineering early stage innovations. He earned his MBA in Marketing from the University of Texas and his Bachelor of Engineering in Electronics and Communication from Anna University, India. He brings in 5 years of professional work experience in information technology, academic technology transfer and market research. He has worked with Fortune 100 clients, as well as mid-size companies and several start-ups in north Texas, providing business development and intellectual property marketing services.

7 Oct 2
Speaker: Min Xian, Ph. D.
Assistant Professor in the Department of Computer Science at the University of Idaho
Topic: Deep Learning Insights and Open-ended Questions
Deep learning has emerged as a new area of machine learning research, which utilizes deep architecture for hierarchical data representation and possesses the ability to model complex relationships among data. It has achieved great success in a wide range of fields including computer vision, bioinformatics, social media analysis, speech recognition, natural language processing, big data analysis, machine translation, etc. In this talk, we will explore the insights behind the success of deep learning, and discuss the major open-ended questions in deep learning research.
Supporting Documents:
Speaker's web page,
Slides for talk
Min Xian is an assistant professor in the Department of Computer Science at the University of Idaho. He received his doctorate in computer science from Utah State University (USU), and his master’s in computer science and bachelor’s in information security from Harbin Institute of Technology (HIT) in 2011 and 2008, respectively. He has broad research interests in biomedical big data analysis, machine learning, computer version, image analysis and data topology modeling. Currently, his research focuses on building the theory and algorithms of robust data analysis for solving challenges in cross-disciplinary applications. Xian received the Excellent Ph.D. Dissertation Award, Best Student Paper Award, Excellent Graduate Student Award, and Best Academic Presentation Award of the CS department at USU. He is also a recipient of the Graduate Research and Collaborative Opportunities (GRCO) Grant.
8 Oct 9
Speaker: Ginger Wright
Program manager for domestic nuclear cyber security at Idaho National Laboratory
Topic: Cyber Informed Engineering
Securing Industrial Control Systems in an ever-changing threat landscape requires more than a dedicated team of cybersecurity professionals. Traditional static defense mechanisms like air gaps and reliance on obscure protocols and access mechanisms are no longer reliable in an always-connected, information-rich cyber environment. Though technical solutions exist to protect availability, integrity and confidentiality of industrial systems, these solutions are typically applied late in the system development process and are not part of the underlying engineering design of systems. Training engineers in cybersecurity or hackers in engineering is expensive and often ineffective in addressing systemic vulnerabilities in large and complex system design.

INL has developed a framework for bridging the gap between engineering design and cybersecurity to understand cyber vulnerabilities at the earliest stages in the development life cycle and apply both engineering solutions and cybersecurity technology to control the system attack surface across the entire system engineering process. This methodology focuses on aiding engineering staff who traditionally envision, plan, design, implement, and operate such systems to understand cyber risk (without becoming cyber experts), and to integrate subject matter expertise of cybersecurity specialists to mitigate cyber risk throughout the engineering lifecycle across all manner of plant systems.

In this presentation, INL will present the 11 principles of the CIE methodology and describe how they can be implemented and integrated. A full technical report on Cyber Informed Engineering, including an application aid and an assessment aid will be made available to all interested in the process.
Supporting Documents:
Slides for the talk
Ms. Wright has expertise in critical infrastructure cyber-security assessment, and in cyber security threat analysis applied to critical infrastructure.

9 Oct 16

Speaker: CAPT Shaun C. McAndrew, USN
Professor of Naval Science/Commanding Officer, NROTC University of Idaho/Washington State University
Topic: Ethics in Cyber Warfare – A Naval Perspective
Supporting Documents:
Cyber and the Navy slide set
CAPT Shaun C. McAndrew, a native of Wilkes-Barre, Pennsylvania, was commissioned from the Naval Academy with a BS in Electrical Engineering.

CAPT McAndrew’s flying tours included HSL-43, San Diego, CA, NSA Bahrain, HSL-37, Kaneohe Bay, HI culminating in her command tour at HSM-41, San Diego, CA flying the Navy’s newest combat helicopter, the MH-60R.

Her staff tour assignments were at COMUSNAVCENT/FIFTH Fleet, Manama, Bahrain, Multi-National Forces Iraq (MNF-I) as a liaison to Multi-National Security Transition Command Iraq (MNSTC-I) Comptroller, and the OPNAV N51Posture and Policy staff. She most recently served as the First Battalion Officer and Deputy Commandant at the Naval Academy. She is currently the PNS/Commanding Officer at the Uof I/WSU.

She earned her master’s degree at the National War College studying National Strategic Studies.

CAPT McAndrew’s decorations include the Legion of Merit, Bronze Star Medal, Meritorious Service Medal, additional personal awards, various unit commendations and service/campaign awards.

10 Oct 23 Michigan State "Ethics Toolbox Experiment: Scientific virtues". This in class exercise is for enrolled students only. If you are not enrolled please join us Nov 27 for our next invited lecture.
11 Oct 30 Michigan State "Ethics Toolbox Experiment: Scientific virtues". This in class exercise is for enrolled students only. If you are not enrolled please join us Nov 27 for our next invited lecture.
12 Nov 6 Michigan State "Ethics Toolbox Experiment: Scientific virtues". This in class exercise is for enrolled students only. If you are not enrolled please join us Nov 27 for our next invited lecture.
13 Nov 13 Michigan State "Ethics Toolbox Experiment: Scientific virtues". This in class exercise is for enrolled students only. If you are not enrolled please join us Nov 27 for our next invited lecture.
Fall Break
15 Nov 27

Speaker:Dr. Glenn A. Fink
Senior Cyber Security Researcher, Pacific Northwest National Labs
Topic: Security and Privacy Grand Challenges for the Internet of Things
The growth of the Internet of Things (IoT) is driven by market pressures, and while security is being considered, the security and privacy consequences of billions of such devices connecting to the Internet cannot be easily conceived of. The possibilities for unintended surveillance through lifestyle analysis, unauthorized access to information, and new attack vectors will continue to increase by 2020, when up to 50 billion devices may be connected. This talk summarizes our recent papers on the various kinds of vulnerabilities that can be expected to arise, and presents a research agenda for mitigating the worst of the impacts. We hope to explain the potential dangers of IoT and highlight the research opportunities in the areas of security and privacy that IoT presents.
Supporting Documents:
Slides of talk Biography:
Dr. Glenn A. Fink has been working in computer security with an emphasis on agent-based approaches and human-centric requirements since 2006. He is the lead inventor of several technologies including PNNL’s Digital Ants technology, which Scientific American cited as one of ten “world changing ideas” in 2010. His recent work includes research in bio-inspired cyber security. Dr. Fink has chaired three workshops on loT security and privacy, published several papers and book chapters on the topic, and edited a book on security and privacy of cyber-physical systems to be published this Fall.

16 Dec 4

Speaker: Jason Dearien
Senior Application Engineer, Schweitzer Engineering Laboratories
Topic: Requirements and Challenges of Building Software for Critical Infrastructure
The power system and other critical industrial control systems (ICS) require precise control. The control algorithms are often distributed between devices that communicate high speed messages to make decisions. These control messages and the processes that produce and consume them must do their job perfectly every time without fail. When these processes don’t do their job the consequences can be very inconvenient, very expensive or even fatal. There are a lot of challenges in building systems that can meet these requirements especially when you consider the hardware these applications run on. Due to the long life of our products (products older than 15 years are not uncommon) and the extremely tough environmental standards the processor and memory available are always limited. In this talk we will discuss some of the critical power systems applications and discuss some of the challenges in building them and discuss one of the more extreme architectures I developed to help solve these problems. Supporting Documents:
Jason Dearien received his BSCS from the University of Idaho in 1993. After graduation, he was a founding member of a small startup involved in software contracting, running an ISP and doing web development. Later, he was in charge of software development for a fabless semiconductor company working on ASIC development for compression and error correction technologies. In his 16 years at Schweitzer Engineering Laboratories, Inc., he has worked in various R&D product development groups as a Senior Software Engineer, spending most of his time focusing on protocol, local-area network, and security product development. He is now a Senior Application Engineer in the R&D Systems Engineering Department, where he is involved in customer support for system-related questions, system-level product validation, and working with different development groups on common product requirements.



  • Due to a situation beyond my control, the homework submission page will no longer be used. We will be using BBLearn for the rest of the semester.

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