Title: TBD

Date/Time: Monday, March 25 4:10 p.m - 5:00 p.m.
Location: TBD
Speaker: Jeff Carver

Abstract: TBD

Biosketch: TBD


Title: TBD

Date/Time: Monday, March  4:10 p.m - 5:00 p.m.
Location: TBD
Speaker: Roby Roberts

Abstract: TBD

Biosketch: TBD


Title: TBD

Date/Time: Monday, March 4 4:10 p.m - 5:00 p.m.
Location: TBD
Speaker: Diane Bimbzock

Abstract: TBD

Biosketch: TBD


Title: TBD

Date/Time: Monday, February 25 4:10 p.m - 5:00 p.m.
Location: TBD
Speaker: Kendra Cook and Griffin Rowell

Abstract: TBD

Biosketch: TBD


Title: TBD

Date/Time: Monday, February 11 4:10 p.m - 5:00 p.m.
Location: TBD
Speaker: Richard Stallman

Abstract: TBD

Biosketch: TBD


Title: TBD

Date/Time: Friday, February 8 4:10 p.m - 5:00 p.m.
Location: TBD
Speaker: Laura Stanley

Abstract: TBD

Biosketch: TBD


Title: TBD

Date/Time: Friday, February 1 4:10 p.m - 5:00 p.m.
Location: TBD
Speaker: Travis Peters

Abstract: TBD

Biosketch: TBD


Title: Data-oriented and Trustworthy IoT Services for a Cyber-Physical World

Date/Time: Friday, January 25 4:10 p.m - 5:00 p.m.
Location: Barnard Hall 108
Speaker: Ruozhou Yu

Abstract: The Internet-of-Things (IoT) has the potential to revolutionize our daily lives. Yet, we are facing major challenges in deploying IoT to solve real-world problems. On one hand, the huge volume of data generated by IoT devices must be transmissible and comprehensible by our existing infrastructures. On the other hand, the complexity, heterogeneity and scale of IoT-based systems have led to new security risks in our digital or even physical lives. Resolving these challenges require sophisticated computing and analytical mechanisms in data science, machine learning, cybersecurity, and/or social sciences, but the applicability of these mechanisms in IoT is largely restricted by the limited computing, networking and energy resources in many real-world IoT scenarios.

In this talk, I will focus on my efforts in addressing the above challenges in resource-constrained IoT. To solve the big data challenge, I design algorithmic solutions for cross-layer networking and computing design, providing guaranteed performance for IoT services and applications, while increasing resource utilization, reducing congestion, and improving system robustness. To solve the security challenge, I propose using the blockchain as a basic building block for establishing a secure IoT platform, and introduce how it can be extended to enable a global scale on-demand IoT marketplace. While the proposed solutions can largely address the above challenges in IoT, many of them also have applications and extensions beyond this specific context.

Biosketch: Ruozhou is a PhD candidate in the School of Computing, Informatics, and Decision System Engineering at Arizona State University. His research expertise lies at the intersection of cybersecurity, networking, and distributed systems. His current research interests include blockchain-based IoT, blockchain payment channels, IoT security, big data computing and analytics, etc. His work has been published on top-tier conferences and journals such as IEEE INFOCOM, IEEE JSAC and IEEE/ACM ToN. He has served as reviewers for top journals such as IEEE JSAC, TMC, TPDS, TWC, etc.


Title: Phylofactorization: evolution + a graph-partitioning algorithm = machine learning + human understanding of biological data

Date/Time: Monday, January 14 4:10 p.m - 5:00 p.m.
Location: Barnard Hall 108
Speaker: Alex Washburne

Abstract:  Biologists are obtaining massive datasets of hundreds of thousands of species and their abundances, traits, and other features. From microbes living in our gut to birds found in tropical rainforests, there is a universal need to make sense of which organisms are sensitive to climate change, which are associated with disease, and more. The theory of evolution defines a history of organisms in the form of a tree going back to common ancestors over 3.6 billion years ago. In this talk, I will discuss how that tree - an acyclic graph - can be used to define a graph-partitioning algorithm for interpretable dimensionality reduction of biological data. So far, this algorithm has yielded insights on the evolution of mammals over the past 65 million years, the microbes who thrive in the intestines of patients with Crohn's Disease or Inflammatory Bowel Disease, the microbes differentiating our intestinal communities over America, how mammalian viruses are more or less likely to jump from animals to people, how mammalian reservoirs are more or less likely to have pathogens capable of infecting people, and more. This algorithm connecting the theory of evolution to reduced rank regression, artificial neural networks, and virtually every tool used for data analysis is accelerating the machine learning and human understanding of biological systems.

Biosketch: Dr. Alex Washburne received undergraduate degrees in Biology and Applied Mathematics from the University of New Mexico. He received his Ph.D. from Princeton University in Quantitative and Computational Biology, where he discovered a mathematical commonality between the dynamics of microbes in humans, trees in tropical rainforests, stocks in the stock market and other entities in competitive systems. The underlying symmetry of competition was used to create statistical tests of competitive intensity which landed Dr. Washburne a job in a hedge fund. While working at a hedge fund, he did a post-doc at Duke University with Diana Nemergut who passed away within 3 months of the start date but secured funding for Alex to continue his research for two years. In this time, he conceived phylofactorization and began work on statistical models of pathogen spillover. He is now a research scientist at MSU working with Raina Plowright on Defense Advanced Research Projects Agency (DARPA) funded projects predicting and preempting the spillover of pathogens like Ebola from wildlife to people. He is the founder and head of Selva Analytics LLC, a consulting firm developing statistical tools to facilitate the accumulation of domain expertise for clients in sectors ranging from biotech and energy to finance and resource management.


 Seminars from 2018.