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The Department of Computer Science
of Colorado State University, in cooperation with ISTeC
(Information Science and Technology Center), offers the CS
Colloquium series as a service to all who are interested
in computer science. When in-person meetings are possible, most seminars are scheduled for
Monday 11:00AM -- 11:50AM in CSB 130 or Morgan Library
Event Hall. For help finding the locations of our seminar
meetings, consult the on-line CSU campus map. |
Upcoming Events
CS Colloquium Schedule, Spring 2023
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Computer Science Department Colloquium Operational Safety of AI-Enabled Cyber-Physical Systems Speaker: Sandeep Kumar S. Gupta, Associate Dean for Research and Innovation in Fulton School of Engineering. Professor and Director of the School of Computing and Augmented Intelligence in the Ira A. Fulton Schools of Engineering. Arizona State University. When: 10:00AM ~ 10:50AM, Friday January 27, 2023  Abstract: Although Artificial Intelligence (AI)-enabled Cyber-Physical Systems (CPS) such as autonomous cars and artificial pancreas systems are now in regular use, the tools and techniques for ensuring that they continue to operate safely in context-rich and complex interactive environments with humans are still in their infancy. This talk focuses on the techniques for ensuring that safety-certified AI-enabled CPS systems continue to remain safe in the field of operation despite any type of failure, may it be hardware, software, human induced, or environmentally cause. The talk will introduce a holistic and iterative operational safety paradigm which aims at ensuring operational safety of the system based on the field operational data. This paradigm also enables communication between all the stake holders including safety engineers, policy makers, regulators, as well as standardization and law enforcement (compliance) agencies. Novel recent advances from the Arizona State University’s IMPACT lab at the intersection of control theory, model mining, conformal testing, and safety engineering of the human-in-the loop systems will be presented. Bio: Sandeep Kumar S. Gupta is Associate Dean for Research and Innovation in Fulton school of engineering. He was the Founding Director and a Professor Computer Science and Engineering with the School of Computing and Augmented Intelligence (SCAI), Arizona State University, Tempe, AZ and was the Founding Chair of the Computer Engineering Graduate Program. He was the School Director of School of Computing, Informatics, and Decision Systems Engineering (SCIDSE) which was renamed as SCAI. During his tenure as the school director, CIDSE ⁄ SCAI’s research exprenditure funding has tripled, new Online Master’s of Computer Science was launched on Coursera, the faculty size has increased by about 25% (including hire of a NAE member), over 13 junior faculty have received NSF Career awards, and program rankings in the school have steadily gone up. He is member of several Graduate Faculties at ASU including Computer Science, Computer Engineering, Electrical Engineering, and Mechanical Engineering. He received the B.Tech degree in Computer Science and Engineering (CSE) from Institute of Technology, Banaras Hindu University, Varanasi, India, M.Tech. degree in CSE from Indian Institute of Technology, Kanpur, and M.S. and Ph.D. degree in Computer and Information Science from Ohio State University, Columbus, OH. He has served at Duke University, Durham, NC as a post-doctoral researcher; at Ohio University, Athens, OH as a Visiting Assistant Professor; and at Colorado State University, Ft. Collins, CO as an Assistant Professor. His current research is focused on safe, secure and sustainable cyber-physical systems with focus on data centers, pervasive healthcare, body sensor networking, and autonomous vehicles. His research has been funded by the US National Science Foundation (NSF), The National Institute of Health (NIH), Science Foundation of Arizona (SFAz), the Consortium for Embedded Systems (CES), the Intel Corp., Raytheon, Northrop Grumman, and Mediserve Information Systems. Gupta has published over 150 peer reviewed conference and journal articles (Google Scholar h-index 59) has been co-awarded over 15 US patents and has graduated over 15 PHDs and over 25 MS students. He has co-authored two books : Fundamentals of Mobile and Pervasive Computing, McGraw Hill, and Body Sensor Networks : Safety, Security and Sustainability, Cambridge University Press. Gupta currently is or has served on the editorial board of Elsevier Sustainable Computing, IEEE Transactions on Parallel & Distributed System, IEEE Communications Letters and Wireless Networks. Gupta is a Senior Sustainability Scientist, in the Global Institute of Sustainability, ASU. His awards include a Best 2009 SCIDSE Senior Researcher, a Best Paper Award for Security for Pervasive Health Monitoring Application, and two best paper award nominations. Gupta’s research has been highlighted on various research news sites and blogs from various sources including NSF, ACM, ASU and Discovery channel. He was TPC Chair of BodyNets 2008 conference and TPC co-chair for Greencom 2013 conference and SI co-editor for IEEE Pervasive, IEEE Transactions on Computers, IEEE Transactions Knowledge and Data Engineering, and IEEE Proceedings. He is a member of the ACM and a senior member of the IEEE. Gupta heads the IMPACT (Intelligent Mobile and Pervasive Applications and Computing Technologies) Lab (http: ⁄ ⁄ impact.lab.asu.edu) at Arizona State University. |
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Computer Science Department Colloquium Machine Learning for Indoor Navigation with IoT Devices Speaker: Sudeep Pasricha, Walter Scott Jr. College of Engineering Professor, Department of Electrical and Computer Engineering. Colorado State University When: 11:00AM ~ 11:50AM, Monday January 30, 2023 Abstract: The advent of the Global Positioning System (GPS) transformed the global transportation industry and allowed vehicles to not only localize themselves but also to navigate reliably and in a secure manner across the world at high speeds. Today, indoor localization is poised to reinvent the way we navigate within buildings, dense urban areas, and underground mines, with many benefits, e.g., directing emergency response services after a 911 call to a precise location (with sub-meter accuracy) inside a building, accurate tracking of robots, equipment, and inventory in hospitals, factories, and warehouses, etc. As GPS signals are severely attenuated or totally blocked in indoor environments, very different solutions are needed to support localization and navigation. The most effective approaches rely on wireless signals and exploit principles of proximity, trilateration, triangulation, and fingerprinting. In this talk I will present an overview of the most promising approaches for indoor navigation with Internet of Things (IoT) devices. I will discuss the many challenges related to short-term and long-term accuracy, device heterogeneity, battery lifetime, security, and noise resilience that are crucial to address in any indoor navigation solution. Next, I will describe machine learning driven frameworks that address many of the key challenges towards realizing a viable indoor navigation solution with smart IoT devices. Lastly, I will discuss open challenges and new directions of importance as we move towards a future with seamless indoor navigation that promises to significantly enhance our quality of life. Bio: Sudeep Pasricha received the B.E. degree in Electronics and Communication Engineering from Delhi Institute of Technology, India, in 2000, after which he spent several years working for STMicroelectronics, India ⁄ France, and Conexant, USA. He received his Ph.D. degree in Computer Science from the University of California, Irvine in 2008. He joined Colorado State University in 2008 where he is currently a Walter Scott Jr. College of Engineering Professor in the Department of Electrical and Computer Engineering. He is a former University Distinguished Monfort Professor and Rockwell-Anderson Professor. He is currently also Chair of Computer Engineering and Director of the Embedded, High Performance, and Intelligent Computing (EPIC) Laboratory at Colorado State University. His research broadly focuses on software algorithms, hardware architectures, and hardware-software co-design for energy-efficient, fault-tolerant, real-time, and secure computing, for embedded, IoT, and cyber-physical systems. Prof. Pasricha has published more than 250 papers in peer-reviewed journals and conferences that have received 16 Best Paper Awards and Nominations. He has filed for multiple patents and co-authored several books. His contributions have been recognized with many awards, including the ACM Distinguished Speaker Award, George T. Abell Outstanding Research Faculty Award, IEEE Computer Society TCVLSI Mid-Career Research Achievement Award, IEEE Computer Society TCSC Award for Excellence for a Mid-Career Researcher, AFOSR Young Investigator Award, ACM Technical Leadership Award, and ACM SIGDA Distinguished Service Award. He is currently the Vice Chair of ACM SIGDA and the Steering Committee Chair for the IEEE Transactions on Sustainable Computing. He is also a Senior Associate Editor for the ACM Journal of Emerging Technologies in Computing, and an Associate Editor with multiple ACM and IEEE journals. He has served as General Chair and Technical Program Chair of 12 conferences, Steering and Organizing Committee Member of 40+ conferences, and Technical Program Committee Member of 100+ conferences. He is an IEEE Senior Member and an ACM Distinguished Member. |
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Computer Science Department Colloquium Towards a Pervasive and Always-On Augmented Reality Future Speaker: Feiyu Lu, Ph.D. candidate. Virginia Tech When: 11:00AM ~ 11:50AM, Thursday February 2, 2023 Abstract: With the advancements in augmented ⁄ mixed reality (AR ⁄ MR) display technologies, future users will be empowered to wear AR ⁄ MR devices everyday, accessing digital services and information anytime, anywhere without being constrained by location and availability of physical screens. However, it remains unclear how augmented virtual information blends in people’s everyday lives and what are the best inputs ⁄ interactions without being invasive or disruptive to the user's physical reality. In this talk, I will present my Ph.D. research covering three topics: (1) how to obtain information efficiently and unobtrusively with AR displays; (2) how to deliver adaptive and relevant AR content to users on-the-go; and (3) how do general users perceive using our proposed approaches in authentic everyday scenarios. I will cover the motivations, designs, and evaluations of our proposed solutions under each topic, as well as the future directions that I believe are critical to the daily adoptions of AR ⁄ MR technologies. My research contributes to the developments of appropriate information displays and interactions, which are unobtrusive, non-distracting, relevant and safe to use in everyday contexts. Bio: Feiyu Lu is a Ph.D. candidate at Virginia Tech and a member of the 3D Interaction Group directed by Dr. Doug A. Bowman. His research interests lie broadly in the intersections of Augmented ⁄ Mixed ⁄ Virtual Reality (AR ⁄ MR ⁄ VR), 3D User Interfaces (3DUI), and Human-Computer Interaction (HCI). He is especially passionate about the future of AR ⁄ MR and how they may fundamentally change the way people interface with digital information anywhere and anytime. His Ph.D. dissertation seeks to support relevant and unobtrusive information acquisitions in a world where augmented virtual information pervasively exists. He worked as a research intern at Meta Reality Labs Research in the summer of 2021 and 2022, collaborating with industrial researchers to explore the usability of intelligent AR ⁄ MR interfaces. His work has been published at premiere venues of AR ⁄ VR ⁄ HCI, including IEEE VR, ISMAR, TVCG, and ACM CHI, SUI, and has been recognized with an ACM SUI honorable mention award and multiple 3DUI demo awards at the IEEE VR conferences |
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Computer Science Department Colloquium Packing List Colorings Speaker: Ewan Davies. Assistant Professor of Computer Science. Colorado State University. When: 11:00AM ~ 11:50AM, Monday February 13, 2023 Abstract: List coloring of graphs is a fundamental topic introduced and studied systematically by Vizing and Erdős, Rubin, and Taylor in the 1970s. The 3-list coloring problem is complete for the second level of the polynomial hierarchy, and a sustained interest in algorithms that construct list colorings has driven a number of powerful developments in stochastic local search. A structured type of list coloring called list packing was suggested by Alon, Fellows and Hare in 1996, and recently we began the systematic study of the concept. This talk focuses on recent work establishing the basic properties of list packing from a mathematical and algorithmic perspective. Most importantly, our work gives evidence that list packing could be algorithmically easier than the infamous “happy Dean problem” that plagues departments, colleges, and universities to this day. Bio: Ewan Davies is an assistant professor in the Department of Computer Science at the Colorado State University. His primary interests include algorithms and the complexity of problems arising in graph theory, particularly those that cross disciplines such as statistical physics and the foundations of data science. Prior to working at CSU he studied at the University of Cambridge, and received a PhD in graph theory from the London School of Economics. He has worked as a postdoc with Lex Schrijver at the University of Amsterdam and came to study algorithms via research positions at the Simons Institute for the Theory of Computing and the University of Colorado Boulder. Ewan has a background in extremal graph theory and has applied this knowledge to theoretical computer science research which has been published in leading conferences such as STOC, FOCS, ICALP and CCC. |
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Computer Science Department Colloquium Analysis and Evolution of Large, Complex, and Long-lived Data-Intensive Software Speaker: Raffi Khatchadourian. Department of Computer Science at Hunter College. When: 11:00AM ~ 11:50AM, Monday February 20, 2023 Abstract: The Big Data era has brought new challenges to today's engineering of large and complex software systems. Increasingly, software is tasked with handling significant amounts of data and, at the same time, being highly transactional with good throughput. This challenge has brought about the incorporation of functional programming language features, known for their ease of use in distributed programming due to immutability and lack of explicit state, into mainstream, Object-Oriented (OO), statically typed programming languages, and Machine Learning (ML) components being incorporated into large, traditional software systems. However, how to effectively engineer such systems with maximum throughput, modularity, understandability, and maintainability is an open problem as oftentimes such goals compete. In this talk, I will discuss my lab's efforts to devise tools, methodologies, and theories to ease the burden of analyzing and evolving large, complex, and long-lived data-intensive software systems. I will discuss techniques for automated refactoring (semantics-preserving program transformation) to enable mainstream OO programs to incorporate more functional programming language features, handle large amounts of data efficiently using parallel stream processing, and effectively integrate and maintain ML components into traditional systems over time. I will also discuss our ongoing efforts in analyzing and transforming imperative Deep Learning (DL) programs to enhance their nonfunctional features and plans in these areas. Bio: Raffi Khatchadourian (https: ⁄ ⁄ khatchad.commons.gc.cuny.edu ⁄ ) is an Assistant Professor in the Department of Computer Science at Hunter College and a member of the Doctoral Faculty of The Graduate School and University Center’s Ph.D. Program in Computer Science at the City University of New York (CUNY), where he leads the CUNY PONDER (PrOgramming laNguages anD software Engineering Research) lab. His research interests lie at the intersection of software engineering, programming languages, and reliable (Machine Learning ) systems. He investigates how program analysis, automated refactoring, and type theory can ease the burden of correctly, efficiently, and securely evolving large and complex software. Raffi also studies how software developers use particular programming language constructs (empirical software engineering) and how software engineering methodology can improve statistical programs and artificial intelligence. His work has been externally supported by the National Science Foundation (NSF), the Japan Society for the Promotion of Science (JSPS), Amazon Web Services (AWS), and the Verizon Foundation. Raffi has served as a program committee (PC) member for ECOOP, GPCE ('21, '22), ‹Programming›, IEEE SCAM, and OOPSLA's Onward! and has co-organized SPLASH ('21, '22), ESEC ⁄ FSE, and ECOOP. Originally from Edison, New Jersey. Raffi received his MS and Ph.D. degrees in Computer Science from Ohio State University and his BS degree in Computer Science from Monmouth University in New Jersey. Before joining CUNY, he was a Software Engineer at Apple, Inc. in Cupertino, California. He worked on Digital Rights Management (DRM) for iTunes, iBooks, and the App Store and distributed software that tested various features of iPhones, iPads, and iPods. |
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Computer Science Department Colloquium Perceptual Focus Issues in Extended Reality Speaker: Mohammed Safayet Arefin. Oak Ridge Associated Universities (ORAU) Postdoctoral Fellow at the DEVCOM US Army Research Laboratory (ARL West) When: 11:00AM ~ 11:50AM, Thursday February 23, 2023 Abstract: The extended reality space can be divided into three environmental realities–real world, augmented reality (AR), and virtual reality (VR). In all three realities, information can be presented at different distances from the user. Sometimes users may need to integrate information from different depths by continuously switching visual attention and eye focus. For example, consider a scenario where a soldier is using an optical see-through (OST) AR head-mounted display (HMD) on a battlefield and looking at a real object that is far away (e.g., a tank) while also viewing virtual information (e.g., technical information about the tank) that is optically close to the soldier. In this case, the soldier must change the depth and visual focus to integrate information. This could potentially cause the soldier to miss important information that could cause unexpected errors. This case is true for the VR environment when the soldier performs training. Nevertheless, this situation is also valid for other applications such as surgery, maintenance, industry, and many others. Therefore, this talk will discuss research on perceptual focus issues in extended reality with two empirical studies and one perceptual image processing algorithm. The first experiment investigates three OST AR interface design issues: (1) context switching, where users must switch visual and cognitive attention between information sources, (2) focal distance switching, where users must accommodate (change the shape of the eye's lens) to see, in sharp focus, information at a new distance, and (3) transient focal blur, the focal blur user perceives while switching the focal distance. This talk will discuss a perceptual image processing algorithm that develops a novel font for the AR system. We termed this "SharpView font," a font that looks sharper than standard fonts when seen out-of-focus. This SharpView font promises to mitigate the effect of OST AR interface design issues. The second experiment investigates the behavior of the human visual system with perceptual depth changes in the real world, AR, and VR with eye tracking. This part of the research could be used as a novel tool to adaptively render information based on depth and improve the AR and VR user experience. Bio: Dr. Mohammed Safayet Arefin is an Oak Ridge Associated Universities (ORAU) Postdoctoral Fellow at the DEVCOM US Army Research Laboratory (ARL West). Dr. Arefin has a Ph.D. and MS in Computer Science from Mississippi State University. He also worked twice as a research intern at the DEVCOM US Army Research Laboratory (ARL WEST). His research has been broad-based, centering on the topics of augmented reality, applied perception, virtual reality, eye tracking, and human-computer interaction. He won the 'Certificate of Commendation' from the SES Executive Deputy to the Commanding General of the US Army Futures Command and the ‘Director's Commendation Award’ in recognition of outstanding research achievement during the 2021 DEVCOM-ARL summer student symposium. Dr. Arefin has been active in the premier augmented reality and virtual reality conferences. For six consecutive terms, he has served as a Publication Co-chair in the IEEE Virtual reality (VR) and IEEE International Symposium on Mixed and Augmented Reality (ISMAR) conference committees. In addition, Dr. Arefin is co- founder and co-organizer of the Workshop on Replication in Extended Reality (WoRXR). |
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Computer Science Department Colloquium Human-Centered Cyber-Physical System: with Applications in Gig Delivery Speaker: Yi Ding. Postdoctoral associate at the Institute for Data, Systems, and Society (IDSS) at MIT. When: 11:00AM ~ 11:50AM, Monday February 27, 2023 Abstract: Cyber-Physical Systems (CPS) have been studied for years and provide us with a unified view to model and study complex systems. The deep involvement of human in some CPS applications (e.g., location-based social networks, gig delivery, smart cities) leads to a new research problem: how to build better systems for human in the future? Interestingly, human behavior (e.g., mobility, activity) is a key factor in studying this problem. To understand human behavior, state-of-the-art solutions use sensing technologies with advanced machine learning algorithms to infer human behavior. However, for some real-world large-scale CPS applications, existing solutions cannot work due to the challenges like human behavior uncertainty and practical constraints, e.g., compatibility and scalability. My works address these challenges from a system perspective based on a deep understanding of human mobility and sensing and machine learning techniques. Specifically, I design systems under real-world constraints to collect data from smartphone sensors and other sources on human behavior and analyze the data in different dimensions (e.g., spatial, temporal, and contextual). In this talk, I will use gig delivery (e.g., DoorDash, Uber Eats) as an example to show (1) Why do we need to study human behavior in CPS. (2) How to build systems under real-world constraints to sense and infer human behavior (i.e., couriers’ location information) in the wild to serve millions of merchants and couriers. Finally, I will discuss the future works that I am interested in. Bio: Yi Ding is a postdoctoral associate at the Institute for Data, Systems, and Society (IDSS) at MIT. He received his Ph.D. in Computer Science and Engineering from the University of Minnesota. His research interests lie at the intersection of mobile computing, cyber-physical systems, and spatial-temporal data mining. He is interested in studying human behavior through smartphone sensing and machine learning in cyber-physical systems (CPS) and cyber-human systems (CHS) like gig delivery, location-based services, and smart cities. Yi’s technical contributions have led to 16 papers in premium venues and journals, including SIGKDD, SIGCOMM, NSDI, MobiCom, UbiComp, and RTSS. Yi was the recipient of the 2022 CPS Rising Star and 2021 RTSS Outstanding Paper Award. Working as a research intern at Alibaba Group, Yi led a team to design, build, deploy, and operate a nationwide Bluetooth-based sensing system, serving 1 million couriers, 3 million merchants, and 150 million customers. More information can be found on his webpage https: ⁄ ⁄ yi-ding.me ⁄ . |
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Computer Science Department Colloquium Towards a Hardware ⁄ Software Co-Design Approach for CPS and IoT Security Speaker: Anomadarshi Barua. Ph.D. candidate, Computer Engineering at the University of California Irvine. When: 11:00AM ~ 11:50AM, Thursday March 2, 2023 Abstract: Have you ever wondered how simple music can leak deadly pathogens from a bio-safety lab? Have you ever considered how an industrial robotic arm can be compromised from a cloud infrastructure? Have you ever imagined an attacker could use a magnetic field to shut down a weak microgrid? If the above questions excite you, please attend my research seminar, where my research answers the above questions with a practical demonstration of CPS attacks on industry-used infrastructure. With this seminar, the audience will gain a deep insight into how hardware ⁄ software interaction in CPSs can open a “Pandora’s Box” of unknown threats that can come from very unconventional ways. My research sits at the intersection of hardware and software layers in CPSs and IoTs, exploring how interactions of cyber and physical components can affect the safety and controllability of closed-loop control from sensing to actuation. Most attacks on CPSs and IoTs can be propagated from the physical domain to the cyber domain or vice-versa and hence, can be termed as cross-domain attacks. To understand these cross-domain attacks, a very different set of methodologies and tools is needed. My research talks about how these tools can be made. Moreover, the seminar will show how cross-domain vulnerabilities can be handled using new hardware ⁄ software co-design approaches to detect, contain and isolate threats in CPSs and IoTs. Bio: Anomadarshi Barua is a Ph.D. candidate studying Computer Engineering at the University of California Irvine. He received his M.S. degree in Embedded Computing Systems jointly at the University of Southampton (UoS) and the Norwegian University of Science and Technology (NTNU) in 2016. Now, He is working under the supervision of Professor Al Faruque in the Autonomous and Intelligent Cyber-Physical Systems (AICPS) Lab. His current research focuses on the system-level design of embedded and Cyber-Physical-Systems (CPSs) with a special interest in CPS security, low-power design, and computer microarchitecture. He publishes in the security conferences like ACM CCS, USENIX, ACSAC, RAID, and CHES and system conferences, like ICCPS and ICCAD. He also has worked in several industries in North America and Europe, such as Intel Corporation (USA), Solidigm (USA), Nordic Semiconductor (Norway), and IDEAS (Norway). In his leisure time, he likes to travel to new places and go for hiking. |
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Computer Science Department Colloquium Common Teaching Myths—From Tradition to Evidence-Based Practice Speaker: Matt Rhodes. Professor of Psychology. Colorado State University. When: 11:00AM ~ 11:50AM, Monday March 6, 2023 Abstract: Much of what we do in the classroom reflects established and traditional approaches to instruction. However, accepted or established practice is not always tantamount to evidence-based practice. In this talk, I will discuss several major myths that characterize teaching in the college classroom, ranging from how we conduct classroom sessions to considering how we approach students. For each practice, I will identify the myth and then discuss a better approach that can replace or transform the practice. Indeed, advances towards evidence-based practice will often require that we question and challenge assumptions that have long-guided college teaching. Bio: Matthew Rhodes is a professor of psychology at Colorado State University. His research focuses on memory, metacognition, and evidence-based approaches to learning and training. Dr. Rhodes is the author or co-author of over 80 peer-reviewed publications, chapters, and proceedings and recently co-authored, with Anne Cleary and Edward DeLosh, A Guide to Effective Studying and Learning: Practical Strategies from the Science of Learning (2020; Oxford University Press). He is a past Associate Editor for Memory and Cognition and Perspectives on Psychological Science and currently Associate Editor for the Journal of Experimental Psychology: Learning, Memory and Cognition, along with serving on the editorial boards of several other journals in learning and memory. Dr. Rhodes is a Fellow of the Association for Psychological Science and the American Psychological Association (Division 3) and has received several awards for teaching and student mentoring. |
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Computer Science Department Colloquium Security Through Transparency: Demystifying Trust in Server Authentication Speaker: Zane Ma. Postdoctoral research scientist at the Georgia Institute of Technology. When: 11:00AM ~ 11:50AM, Monday March 20, 2023 Abstract: Secure sharing of resources and data begins with authentication. Nearly all web clients (i.e., websites, email, messaging) today delegate server authentication to trusted third-parties called certificate authorities (CAs). In other words, secure web server authentication starts with judicious trust in CAs. Unfortunately, despite 1) a brittle single-points-of-failure design and 2) a history of trust in failing CAs (e.g., DigiNotar, Turktrust, CNNIC), the server authentication ecosystem remains opaque, with basic questions still unclear: What CAs are trusted? How can CAs be circumvented? In this talk, I will discuss my efforts to demystify trust in server authentication, and in doing so, improve web securitythrough more informed trust in CAs. I will first examine the challenge of accurately ⁄ completely identifying CAs and demonstrate how novel Internet-scale measurement can provide a clearer picture, resulting in browser trust changes. I will then look at surprisingly common deviations from trusted CA authentication and analyze their security implications throughthe global perspective of industry collaborators. Ultimately, by uncovering CAs and exceptions, this talk will explore the security value of transparency for trust-based systems and highlight broader opportunities for authentication based on transparency-informed trust. Bio: Dr. Zane Ma is a postdoctoral research scientist at the Georgia Institute of Technology. His research focuses on the security and performance of networked systems. His publications have appeared at highly competitive conferences for computer security, network measurement, and human-computer interaction, as well as receiving a Best Paper award at the 2019 Web conference (WWW). He holds a Ph.D. in Computer Science from the University of Illinois Urbana-Champaign, where he was the recipient of the Graduate Student Outstanding Service Award, a Mavis Future Faculty Fellowship, and the Yunni & Maxine Pao Memorial Fellowship. |
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Computer Science Department Colloquium Road to the Next Generation of Advanced Systems Engineering Speaker: Istvan David, Postdoctoral Research Fellow at the University of Montreal, Canada. When: 10:00AM ~ 10:50AM, Monday March 27, 2023 Abstract: Nowadays engineered systems have reached a previously unprecedented complexity. Pertinent examples include software-intensive and cyber-physical systems. Systems are becoming faster, more autonomous, and more embedded into the fabric of modern society, severely challenging traditional systems engineering techniques. To cope with these challenges, novel systems engineering paradigms are needed. These paradigms will be characterized by an increased blending of human and machine reasoning, and multi-paradigm collaboration capabilities; and will enable more sustainable and human-centered systems engineering practices. This talk presents the latest results along these lines, and built on these results, proposes a research map for the next 5–7 years. Bio: Istvan David is a Postdoctoral Research Fellow at the University of Montreal, Canada. His research has been focused on advanced engineering paradigms of complex systems, such as digital twinning of cyber-biophysical systems. He maintains a research line on the automated inference of engineering models and simulators, for which he received the highly prestigious IVADO postdoctoral research grant from the Institute for Data Valorization. Previously, Istvan spent time as a Postdoctoral researcher at the Vrije Universiteit Amsterdam in the Software and Sustainability research group, where he was exposed to the state of the art of software-focused research on sustainability, heavily influencing his research program. He received his PhD from the University of Antwerp, Belgium for his work on systems engineering processes in 2019. His collaborations with industry partners led to the development of the PROxIMA process modeling, simulation, and optimization toolset, contributing to more sustainable systems engineering processes at the partner companies. Apart from his academic profile, Istvan possesses significant industry experience in technical and management roles. In 2019-2020, he served as the Head of Innovation for a world-renowned quality engineering company, leading digital innovation efforts during a crucial organizational pivot. Previously, he worked as an R&D Software Engineer for Mentor Graphics (currently Siemens), where he contributed to state-of-the-art modeling tools for the AUTOSAR-based design of automotive systems, especially for VOLVO, BMW, and GM. Previously, during his undergraduate years, he worked in various software developer roles, took initiative on software quality assurance efforts, and initiated and oversaw the introduction of novel project management frameworks at multiple companies. |
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Computer Science Department Colloquium Learning Hybrid Dynamical Systems From Data Speaker: (Cancelled) Sriram Sankaranarayanan, S.J. Archuleta Endowed Professor of Computer Science. University of Colorado Boulder. When: 11:00AM ~ 11:50AM, Monday March 27, 2023 Abstract: We present an algorithm for learning multi-modal (hybrid) linear dynamical systems from time-series data. This problem is identical to checking if we can fit k or fewer (hyper) planes through a given set of data points so that each point is sufficiently close to one of the k hyperplanes. This is known to be NP-hard for k < 2. Existing approaches resort to expensive algorithms that are exponential in the number of data points, rely on spatio-temporal locality properties and ⁄ or use heuristics inspired by k-means clustering. In our work, we present a novel formulation of this problem that introduces a gap between the YES and NO answers for the problem. For problem instances that fall into this gap, our algorithm is permitted to provide either answer. By exploiting this gap in our problem formulation, we obtain a conceptually simple algorithm that has time complexity linear in the number of data points but exponential in the dimensionality of the state-space. This allows us to provide scalable algorithms for problems that involve large amounts of data but in relatively "low dimensions". We will demonstrate the applicability of our approach to interesting learning problems and talk about some recent extensions of our results. All relevant concepts will be explained during the talk. Joint work with Guillaume Berger, Monal Narasimhamurthy, Kandai Watanabe and Morteza Lahijanian. Bio: Sriram Sankaranarayanan is a professor of Computer Science at the University of Colorado, Boulder. His research interests include automatic techniques for reasoning about the behavior of computer and cyber-physical systems. Sriram obtained a PhD in 2005 from Stanford University where he was advised by Zohar Manna and Henny Sipma. Subsequently he worked as a research staff member at NEC research labs in Princeton, NJ. He has been on the faculty at CU Boulder since 2009. Sriram has been the recipient of awards including the CAREER award from NSF (2009), the Provost's faculty achievement award (2014) and the Coursera outstanding innovation award (2022). |
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Computer Science Department Colloquium (ideas for) The Next Five Years Speaker: Bruce Draper, Professor. Computer Science. Colorado State University. When: 11:00AM ~ 11:50AM, Wednesday March 29, 2023 Abstract: Bio: Bruce Draper has been a professor at Colorado State University since 1996, teaching at all levels of the curriculum and leading research projects in computer vision and machine learning. He has spent the last three and half years on an IPA assignment as a program manager for the Defense Advanced Research Projects Agency (DARPA), creating and managing programs in computer ⁄ human symbiosis, adversarial AI, and geometric underpinnings of machine learning. |
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Computer Science Department Colloquium Virtual Reality Nature Immersion for Stress Reduction and Enhanced Wellbeing Speaker: Victoria Interrante. Professor of Computer Science. University of Minnesota When: 11:00AM ~ 11:50AM, Monday April 3, 2023 Abstract: The potential health benefits of contemplative immersion in the natural world are widely appreciated, having been cited in the scientific literature for well over a century. Several theories have been advanced to explain the basis for the observed beneficial outcomes, including Stephen & Rachel Kaplan’s Attention Restoration Theory (ART), which posits that immersion in nature supports the restoration of depleted attentional capacity by evoking effortless ‘soft fascination’ while providing abundant opportunity for reflection, and Edward Wilson’s Biophilia hypothesis, which advances the theory that human beings have an innate affinity for living things, including natural environments that support life in an evolutionary sense. The vast literature on beneficial outcomes from exposure to nature includes a wide range of findings, from reduced recovery time among surgical patients whose hospital rooms offer a view of nature, to increased cognitive abilities and lower physiological measures of stress after brief periods of walking in nature, to reduced risk of psychiatric disorders among people who had continuous access to green space as children. Given all of these benefits, there is increasing interest in multiple research communities to more clearly understand the conditions under which and mechanisms through which time spent in nature translates to increased well-being. In this talk, I will outline a nascent research agenda aimed at exploring the potential of using immersive virtual reality technology to extend the benefits of nature immersion to populations who lack ready access to natural spaces and to help elucidate the features of a nature immersion experience that best support restorative outcomes. Bio: Dr. Victoria Interrante is a Professor in the Department of Computer Science at the University of Minnesota, where her research focuses on improving the human experience in immersive virtual reality environments. She also directs the university-wide Center for Cognitive Sciences and its accompanying interdisciplinary graduate program. In addition to her work with virtual nature, she is pursuing projects on improving spatial understanding and reducing cybersickness in immersive virtual environments, and on enhancing the outcomes of potential bias mitigation interventions through the use of VR technology. She is a former editor-in-chief of the ACM Transactions on Applied Perception and a recipient of the 2020 IEEE VGTC Virtual Reality Career Award for her lifetime contributions to visualization and visual perception for augmented and virtual reality. |
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Computer Science Department Colloquium Building a Great Computer Science Department Speaker: Dr. Yashwant Malaiya. Professor, Computer Science. Colorado State University When: 10:00AM ~ 10:50AM, Monday April 10, 2023 Abstract: The Computer Science department at Colorado State University is a respected well established department engaged in high quality teaching, research and service. It has made great progress in its past 50 years. It is our ambition to see it rising relative to our peers in the US and globally. I will share ideas about what it will take. Among other things, we need to continually observe not only our peers but also the top institutions and the developments in the computing field. Bio: Yashwant Malaiya joined Colorado State university in 1982 as an associate professor in 1982 and was promoted in 1990 to full professor. He has taught a number of undergraduate and graduate courses including Computer Organization, Operating Systems, Computer Architecture, Fault tolerant Computing and Quantitative Security. He has conducted research in fault modeling, software and hardware testing, fault tolerance, and quantitative cybersecurity. He has contributed the concepts of "detectability profile" and "antirandom testing" and has developed the Alhazmi-Malaiya Logistic Vulnerability Discovery Model. He was involved in the development of the International Conference on VLSI Design, IEEE International conference on Software Reliability Engineering and the IEEE International Workshop on IDDQ Testing. He is a recipient of the IEEE Third Millennium Medal and the IEEE CS Golden Core Award. |
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Computer Science Department Colloquium The Coupling of Electric Power and Transportation Infrastructures: Opportunities and Challenges Speaker: Dr. Anna Scaglione. Professor, Electrical & Computer Engineering Cornell Tech. The New York City campus of Cornell University. When: 10:30AM Reception 11:00 ~ 11:50AM Talk, Monday April 10, 2023 Abstract: The electric grid is at the cusp of significant transformation, due to the pressure of increasing the penetration of distributed renewable energy resources that is both economically beneficial (renewable energy has never been cheaper) as well as necessary to curb CO2 emissions and address climate change. On the demand side, the greatest pressure for change comes from ensuring a smooth transition to electrified transportation systems. In fact, large populations of electric vehicles can be either an immense resource of flexibility for the grid, or a foe, depending on how car charging is managed both spatially as well as in time. This talk will explain why, if car charging that is not aligned with peaks of renewables, the costs of power generation and delivery will increase while global CO2 emissions may be minimally affected. More importantly, we will describe possible solutions. Specifically, we will model the coupling for these two networks that allows to define strategies for computing congestion pricing for travel and charging at the retail level. We will discuss how to design digital interfaces, so that individuals can make independent driving and charging decisions, while minimizing energy and transportation costs. Furthermore, we will describe how to capture this flexibility at the level of whole-sale markets of electricity, through aggregate low order models that allow to foresee the behavior of the populations of electric vehicles in clearing the market at the transmission grid level. Bio: Anna Scaglione (M.Sc.'95, Ph.D. '99) is currently a professor in electrical and computer at Cornell Tech, the New York City campus of Cornell University. Prior to rejoining Cornell in 2022, she held faculty positions at Arizona State University, the University of California at Davis, Cornell University (the first time, from 2001 to 2008) and the University of New Mexico. She is IEEE fellow since 2011 and received the 2013, IEEE Donald G. Fink Prize Paper Award, the 2000 IEEE Signal Processing Transactions Best Paper Award the NSF CAREER grant (2002). She is co-recipient with her students of several best student papers awards at conferences and received the 2013 IEEE Signal Processing Society Young Author Best Paper Award with one of the PhD students. She was Distinguished Lecturer of the Signal Processing Society in 2019 and 2020. Dr. Scaglione's expertise and research considers theoretical and applied problems is in statistical signal processing, communications networks and cyber-physical infrastructures for sustainable energy delivery systems, where her work has focused on addressing renewable sources and demand response integration and emerging cyber-security challenges in embedding intelligence in critical infrastructures systems. To arrange a meeting with the speaker, please contact Prof. Anura Jayasumana Anura.Jayasumana@ColoState.edu. |
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Computer Science Department Colloquium Grid Graph Signal Processing: Theoretical Models and Machine Learning Algorithmsf Speaker: Dr. Anna Scaglione. Professor, Electrical & Computer Engineering Cornell Tech. The New York City campus of Cornell University. When: 3:00 ~ 4:00pm, Monday April 10, 2023 Abstract: This presentation proposes that physical laws governing signals from infrastructures, such as the grid, can be viewed as examples of a Graph Signal Processing (GSP) signal. By doing so, statistical and algebraic properties of the signal can be uncovered, and GSP can be applied to develop machine learning algorithms using a parametric Bayesian framework. The talk introduces the algorithmic foundations of GSP modeling for analyzing signals and multivariate-time series on a graph and shows how power systems modeling supports the idea that grid voltage phasors are a low-pass graph signal process. The connection between GSP modeling and Graph Fourier Transforms (GFTs) is established, and the talk explores how to use them to derive various applications, including sampling schemes, denoising, interpolation, classification, system identification, and showcases how graph neural networks can be applied to inference problems and reinforcement learning Bio: Anna Scaglione (M.Sc.'95, Ph.D. '99) is currently a professor in electrical and computer at Cornell Tech, the New York City campus of Cornell University. Prior to rejoining Cornell in 2022, she held faculty positions at Arizona State University, the University of California at Davis, Cornell University (the first time, from 2001 to 2008) and the University of New Mexico. She is IEEE fellow since 2011 and received the 2013, IEEE Donald G. Fink Prize Paper Award, the 2000 IEEE Signal Processing Transactions Best Paper Award the NSF CAREER grant (2002). She is co-recipient with her students of several best student papers awards at conferences and received the 2013 IEEE Signal Processing Society Young Author Best Paper Award with one of the PhD students. She was Distinguished Lecturer of the Signal Processing Society in 2019 and 2020. Dr. Scaglione's expertise and research considers theoretical and applied problems is in statistical signal processing, communications networks and cyber-physical infrastructures for sustainable energy delivery systems, where her work has focused on addressing renewable sources and demand response integration and emerging cyber-security challenges in embedding intelligence in critical infrastructures systems. To arrange a meeting with the speaker, please contact Prof. Anura Jayasumana Anura.Jayasumana@ColoState.edu. |
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Computer Science Department Colloquium Campus Visit with NSF CISE AD Dr. Margaret Martonosi Speaker: Margaret Martonosi is the US National Science Foundation’s (NSF) Assistant Director for Computer and information Science and Engineering (CISE) When: 4:00pm Reception 4:30pm ~ 5:30pm Talk , Thursday April 13, 2023 Abstract: The National Science Foundation (NSF) supports a majority of US academic research in the Computer and Information Science and Engineering (CISE) topic areas. Since February, 2020, Dr. Margaret Martonosi serves as NSF CISE AD, stewarding the CISE directorate’s $1B annual budget on behalf of research, education, workforce and infrastructure funding in CISE topic areas and for science as a whole. In her role at CISE, Dr. Martonosi works to advocate for and set the direction of research funding across the important topic areas comprised within the CISE space. Past CISE research funding has planted the seeds that have germinated into major scientific, economic, and societal impacts including advances in artificial intelligence, cloud computing, search, and fundamentals of computational theory and computer hardware and systems design. The directorate has also helped to catalyze transformative work on CISE education and workforce issues, including broad efforts on K-12 and undergraduate computer science education to move towards the goal of ensuring effective and accessible CISE education for all students. In addition, investments through the Office of Advanced Cyberinfrastructure positioned within CISE have supported advanced computing systems and services, which have in turn enabled breakthroughs in all areas of science and engineering. Dr. Martonosi is conducting a series of “virtual campus visits” to engage in conversation about a vision for CISE research going forward, and to field Q&A from the CISE community. Please join us for this highly-interactive session and please bring your input and questions! Bio: Margaret Martonosi is the US National Science Foundation’s (NSF) Assistant Director for Computer and information Science and Engineering (CISE). With an annual budget of more than $1B, the CISE directorate at NSF has the mission to uphold the Nation’s leadership in scientific discovery and engineering innovation through its support of fundamental research and education in computer and information science and engineering as well as transformative advances in research cyberinfrastructure. While at NSF, Dr. Martonosi is on leave from Princeton University where she is the Hugh Trumbull Adams '35 Professor of Computer Science. Dr. Martonosi's research interests are in computer architecture and hardware-software interface issues in both classical and quantum computing systems. Dr. Martonosi is a member of the National Academy of Engineering and the American Academy of Arts and Sciences. She is a Fellow of the Association for Computing Machinery (ACM) and the Institute of Electrical and Electronics Engineers (IEEE). |
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Computer Science Department Colloquium NSF Mini Workshop on Proposal Writing Speaker: Dr. Margaret Martonosi is the US National Science Foundation’s (NSF) Assistant Director for Computer and information Science and Engineering (CISE) When: 9:30am ~ 11:30am , Friday April 14, 2023 Abstract: The National Science Foundation (NSF) supports a majority of US academic research in the Computer and Information Science and Engineering (CISE) topic areas. Since February, 2020, Dr. Margaret Martonosi serves as NSF CISE AD, stewarding the CISE directorate’s $1B annual budget on behalf of research, education, workforce and infrastructure funding in CISE topic areas and for science as a whole. In her role at CISE, Dr. Martonosi works to advocate for and set the direction of research funding across the important topic areas comprised within the CISE space. Past CISE research funding has planted the seeds that have germinated into major scientific, economic, and societal impacts including advances in artificial intelligence, cloud computing, search, and fundamentals of computational theory and computer hardware and systems design. The directorate has also helped to catalyze transformative work on CISE education and workforce issues, including broad efforts on K-12 and undergraduate computer science education to move towards the goal of ensuring effective and accessible CISE education for all students. In addition, investments through the Office of Advanced Cyberinfrastructure positioned within CISE have supported advanced computing systems and services, which have in turn enabled breakthroughs in all areas of science and engineering. Dr. Martonosi is conducting a series of “virtual campus visits” to engage in conversation about a vision for CISE research going forward, and to field Q&A from the CISE community. Please join us for this highly-interactive session and please bring your input and questions! Bio: Margaret Martonosi is the US National Science Foundation’s (NSF) Assistant Director for Computer and information Science and Engineering (CISE). With an annual budget of more than $1B, the CISE directorate at NSF has the mission to uphold the Nation’s leadership in scientific discovery and engineering innovation through its support of fundamental research and education in computer and information science and engineering as well as transformative advances in research cyberinfrastructure. While at NSF, Dr. Martonosi is on leave from Princeton University where she is the Hugh Trumbull Adams '35 Professor of Computer Science. Dr. Martonosi's research interests are in computer architecture and hardware-software interface issues in both classical and quantum computing systems. Dr. Martonosi is a member of the National Academy of Engineering and the American Academy of Arts and Sciences. She is a Fellow of the Association for Computing Machinery (ACM) and the Institute of Electrical and Electronics Engineers (IEEE). |
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Computer Science Department Colloquium Towards Better VR ⁄ AR Training Applications Speaker: Dr. Anil Ufuk Batmaz. Assistant Professor, Computer Science and Software Engineering. Concordia University When: 11:00AM ~ 11:50AM, Monday April 17, 2023 Abstract: Virtual Reality (VR) and Augmented Reality (AR) Head-mounted displays (HMDs) are quickly becoming more affordable and accessible for training applications. Based on this trend, software developers, engineers, and practitioners from various fields are increasingly using HMDs in VR ⁄ AR applications, with target areas including training and continuing professional development for, e.g., health care workers, sports training, and pilot training. However, the current technology and methods used in VR ⁄ AR systems still restrict user performance and user experience, making the resulting applications potentially unattractive to patients, trainees, or professionals. In this talk, I introduce my research that aims to widen the application of VR and AR technologies in training systems. I first present how the user’s experience during mid-air interaction in VR ⁄ AR head-mounted displays can be improved through Human-Computer Interaction methods and then how insights from cognitive science can provide better feedback to users. Finally, I discuss how machine learning and AI can be integrated into VR\AR training systems. Bio: Dr. Anil Ufuk Batmaz received his PhD in 2018 from the University of Strasbourg, France, in Biomedical Engineering. During his PhD studies, he explored the extent to which the human perceptual system adapts to conditions of multisensorial constraints for planning, control, and execution of complex tasks during image-guided surgery. He proposed novel precision based-training methods to improve the motor skills of novice surgeons in image-guided surgical training systems. After his PhD, Dr. Batmaz worked as a postdoctoral fellow at Simon Fraser University. His research was focused on improving the motor performance and user experience of the trainees in remote VR ⁄ AR training systems, specifically for eye-hand coordination training systems. He designed a digital twin of an eye-hand coordination training system which can be used for remote rehabilitation of patients and training of surgeons. In 2021, he started working as an assistant professor at Kadir Has University, where his research is focused on better VR ⁄ AR training systems and simulators for mobile health applications. Since 2022, Dr. Batmaz is affiliated with Concordia University, Computer Science and Software Engineering Department. His current research is focused on the effects of technical limitations of VR ⁄ AR systems on user performance and user experience. |
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Computer Science Department Colloquium Attack-Averse Solutions for Emerging Immersive Tech Security Speaker: Dr. Diksha Shukla. Assistant Professor. Dept. of Electrical Engineering and Computer Science University of Wyoming, Laramie When: 11:00AM ~ 11:50AM, Monday April 24, 2023 Abstract: With the increasing use of wearable and immersive technologies, security solutions need to be more stringent. These technologies pose new challenges for security professionals due to their portability, connectivity, and unique interfaces. Additionally, the threats posed by side-channel attacks are often overlooked in security assessments. Attack-averse security solutions are necessary to protect user data, prevent device hijacking, and ensure privacy. This talk will present current user authentication methods for wearable technology and immersive (AR ⁄ VR) devices and examine their limitations and associated risks. The talk will also discuss the serious security threats posed by video-based side channels and explore dynamic behavioral biometric solutions for attack-averse authentication. Furthermore, ideas for forthcoming solutions to ensure secure and seamless interaction will be discussed as these technologies continue to evolve. Bio: Diksha Shukla is an Assistant Professor of Electrical Engineering and Computer Science at the University of Wyoming, Laramie. She received a Ph.D. in Computer & Information Science and Engineering from Syracuse University in 2019. Before that, she received MS in Mathematics from Louisiana Tech University, Ruston, and MS in Computer Applications from Jawaharlal Nehru University, New Delhi, India, in 2014, and 2011 respectively. Her research interests include trustworthy machine learning, cybersecurity, and computer vision. Her research spans applications of these areas to IoT devices, wearables, attack-averse authentication, and side-channel attack formulation. Dr. Shukla’s research has appeared at top ACM and IEEE venues including IEEE TIFS, IEEE Euro S&P, ACM CCS, ACM TOPS, and USENIX Security. |
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Computer Science Department Colloquium Human-Aware AI -- A Foundational Framework for Human-AI Interaction Speaker: Sarath Sreedharan. Assistant Professor of Computer Science. Colorado State University. When: 11:00AM ~ 11:50AM, Monday May 1, 2023 Abstract: We are living through a revolutionary moment in AI history. We are seeing the development of impressive new AI systems at a rate that was unimaginable just a few years ago. However, AI's true potential to transform society remains unrealized, in no small part due to the inability of current systems to work effectively with people. A major hurdle to achieving such coordination is the inherent asymmetry between the AI system and its users. In this talk, we will discuss how the framework of Human-Aware AI (HAAI) provides us with the tools required to bridge this gap and support fluent and intuitive coordination between the AI system and its users. We will see how HAAI acts as a foundational framework for both understanding and developing algorithms to address various central problems in AI, including explainability and value alignment. Bio: Sarath Sreedharan is an Assistant Professor at Colorado State University. His core research interests include designing human-aware decision-making systems that can generate behaviors that align with human expectations. He completed his PhD from Arizona State University, where his doctoral dissertation received one of the 2022 Dean’s Dissertation Award for Ira A. Fulton Schools of Engineering. His research has been published in various premier research conferences, including AAAI, ICAPS, IJCAI, AAMAS, IROS, HRI, ICRA, ICML and ICLR, and journals like AIJ. He has presented tutorials on his research at various forums and is the lead author of a Morgan Claypool monograph on explainable human-AI interactions. He was selected as a DARPA Riser Scholar for 2022 and a Highlighted New Faculty by AAAI. His research has won multiple awards, including the Best System's Demo and Exhibit Award at ICAPS-20 and Best Paper Award at Bridging Planning & RL workshop at ICAPS 2022. He was also recognized as a AAAI-20 Outstanding Program Committee Member, Highlighted Reviewer at ICLR 22, IJCAI 2022 Distinguished Program Committee Member and Top Reviewer at NeurIPS 22. |
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Computer Science Department Colloquium Liveness Analysis, Modeling, and Simulation of Blockchain Consensus Algorithms’ Ability to Tolerate Malicious Miners Speaker: Amani Altarawneh, Computer Scholar, Colorado State University. When: 11:00am ~ 12:00pm, Monday May 8, 2023 Abstract: The blockchain technology revolution and concomitant use of blockchains in various applications have resulted in many organizations and individuals developing and customizing their own fit-for-purpose consensus algorithms. Because security and performance are principally achieved through the chosen consensus algorithm, the reliability and security of these algorithms must be both assured and tested. This talk presents a methodology to assess such algorithms for their security level and performance, and liveness of byzantine consensus algorithms for permissioned blockchain systems. In this methodology, we use a Digital Ledger Technologies (DLTs) consensus algorithm classification to understand the miner-selection process. We compile the “security ingredients” that enable consensus algorithms to achieve liveness, safety, and byzantine fault tolerance (BFT) in blockchain systems. We organize these requirements as a new taxonomy that describes requirements for security. And, Brewer’s theorem is utilized to explain tradeoffs between availability and consistency in consensus algorithm design. This analysis reveals the liveness of the given consensus algorithm and its ability to protect against malicious miner denial of services (DoS) attacks. Digital signatures are employed to prove integrity and non-repudiation of messages passing in the systems. Queueing theory and Markov chains are applied to determine the average waiting time of client transactions when malicious miners work to slow the system. Queuing theory and Markov chains jointly are employed to test a given blockchain’s ability to perform correctly despite the presence of malicious miners or resistant nodes. Overall, the methodology provides a roadmap to guide developers during the design phase of consensus algorithms to render these algorithms more secure and robust. Bio: Amani Altarawneh received her BA from Mu'tah University in Computer Science, Alkarak, Jordan, and MS in CS from Bridgewater State University in MA, USA. She received her Ph.D. in Computer Science ⁄ Cyber Security from the University of Tennessee at Chattanooga (UTC), Tennessee, USA. Amani Altarawneh is a computer science scholar with a specialization in cybersecurity at Colorado State University. Her primary interests are in the areas of blockchain, cybersecurity, IoT, smart cities, and parallel programming. Her research includes security methods and novel analysis techniques on different types of blockchains. Her work addresses availability analysis of consensus algorithms for blockchain systems using formal methods and by combining established techniques. The major achievements of her work thus far are developing a new consensus algorithm classification methodology, as well as designing a security ingredients taxonomy. Her current research is focused on the security of the smart contract using automated tools, and formal verification methods. |
