2024 Computer Science Colloquium and The UNM Computer Science Cleve Moler & MathWorks Chair in Mathematical and Engineering Software Distinguished Lecture Series
The UNM Computer Science Cleve Moler & MathWorks Chair in Mathematical and Engineering Software Distinguished Lecture Series
The Future is not What it Used to be: Thoughts on Some new Futures for Technical Human-Computer Interaction
Scott Hudson, Professor of Human-Computer Interaction at Carnegie Mellon
Monday, November 6, 2024, 2:00 PM
Location: Larrañaga Engineering Auditorium (Centennial 1041)
Abstract:
In this talk I will consider how the future of technical Human-Computer Interaction is different than it used to be - what has changed, what has stayed the same, and mostly what should we do about it. Although it seems mundane, when we consider change in any sort of computing technology, we must consider "the elephant in the room" of Moore's law. I will present two quick thought experiments in this talk to try to convince you that you really don't understand the implications of Moore's law, that this really does matter, and that you should perhaps be thinking a little differently about your work as a result. (Spoiler alert: you are dramatically underestimating how much change in computing power is ahead of you, and probably under-utilizing it's potential for HCI advances.) Based on this, the core of my talk will consider what we might be missing in terms of how we go about our work, and talk about several exemplars of where a different view of a "new future" might lead in terms of specific research directions. With these exemplars as motivation, I will consider some more general thoughts about the methodologies we use in our work, and suggest a few ways we might consider thinking differently about how we go about our work.
Bio:
Scott Hudson is a Professor of Human-Computer Interaction at Carnegie Mellon and previously held positions at the University of Arizona and Georgia Tech. He has published extensively in technical HCI. He recently received the ACM SIGCHI Lifetime Research Award. Previously he received the ACM SIGCHI Lifetime Service Award, was elected to the CHI Academy, and received the Allen Newell Award for Research Excellence at CMU. His research interests within HCI are wide ranging, but tend to focus on technical aspects of HCI. Much of his recent work has been considering advanced fabrication technologies such as new machines, processes, and materials for 3D printing, as well as computational knitting and weaving, and applications of mechanical meta-materials.
The UNM Computer Science Cleve Moler & MathWorks Chair in Mathematical and Engineering Software Distinguished Lecture Series
From Technology to Policy
Ellen Zagura, Professor of Computer Science at Georgia Tech and NSF CISE/CNS Division Director
Monday, November 4, 2024, 2:00 PM
Special Location: In the CS Innovation Space, G-300 in the basement of Farris
Abstract:
In this talk I will describe two journeys that started traditionally for an academic computer scientist and have led unexpectedly to science and technical policy. The first is a research journey in network measurement; the second is a professional career journey from faculty member to Division Director for Computer and Network Systems at the National Science Foundation. Along the way, I will highlight some lessons and key pivot points that shaped my path. Las Vegas and swimming pools will feature in the story.
Bio:
Dr. Ellen Zegura is Regents and Fleming Chair Professor in the School of Computer Science at Georgia Tech. Starting in August 2023, she is on loan from Georgia Tech to the National Science Foundation serving as Division Director for Computer and Network Systems (CNS) within the Computer and Information Science and Engineering (CISE) Directorate. Her research interests lie in computer networking, with an emphasis on mobile and wireless networks, and on ethics education in undergraduate computer science. She is a Fellow of the IEEE and a Fellow of the ACM.
The UNM Computer Science Cleve Moler & MathWorks Chair in Mathematical and Engineering Software Distinguished Lecture Series
Byzantine agreement on external data
Valerie King, University of Victoria
Wednesday, October 30, 2024, 2:00 PM
Location: Larrañaga Engineering Auditorium (Centennial 1041)
Abstract:
Byzantine agreement is a fundamental problem in distributed computing which was formulated over 50 years ago to model the coordination of machines in a network which experience arbitrary faults. More recent applications like blockchain require consideration of a wider range of models and problems. In this talk we’ll explore a novel model introduced by Augustine et al. in DISC 2024 in which the goal is for a set of possibly corrupt machines to cooperate in order to efficiently share the cost of learning external data. Unlike the standard Byzantine agreement model, in this context there is a surprisingly efficient algorithm which works in a permissionless system provided there is a known lower bound on the number of non-corrupted machines at each step and this number is any constant fraction of the total number of machines.
Bio:
Valerie King is an American and Canadian computer scientist who works as a professor at the University of Victoria. Her research concerns the design and analysis of algorithms; her work includes results on Byzantine agreement, maximum flow and dynamic graph algorithms, and has played a role in the expected linear time MST algorithm of Karger et al. She became a Fellow of the Association for Computing Machinery in 2014.
Professor King graduated from Princeton University in 1977. She earned a Juris Doctor degree from the University of California, Berkeley School of Law in 1983, and became a member of the State Bar of California, but returned to Berkeley and earned a Ph.D. in computer science in 1988 under the supervision of Richard Karp with a dissertation concerning the Aanderaa–Karp–Rosenberg conjecture.
The UNM Computer Science Cleve Moler & MathWorks Chair in Mathematical and Engineering Software Distinguished Lecture Series
AI’s Next Frontier: Neuromorphic Computing
Suma George Cardwell, Center for Computing Research at Sandia National Laboratories
Wednesday, October 23, 2024, 2:00 PM
Location: Larrañaga Engineering Auditorium (Centennial 1041)
Abstract:
Neuromorphic computing aims to emulate the brain's computational architecture with low energy consumption, offering a way to enhance the performance of modern, power-hungry AI systems. Achieving brain-like cognition and maximizing neuromorphic benefits requires complex neurons, dense connectivity, heterogeneous compute components, scalability with trillions of learnable parameters, and novel algorithms. This necessitates a codesign approach spanning algorithms, architectures, systems, circuits, and devices, along with heterogeneous integration techniques. There is a significant opportunity to design efficient next-generation AI that leverages underlying hardware, like biological codesign seen in the brain.
Dr. Suma George Cardwell is a Principal Member of Technical Staff in the Center for Computing Research at Sandia National Laboratories. She completed her PhD and MS in Electrical and Computer Engineering at Georgia Tech, Atlanta in 2015 and 2011 respectively. She has over ten years of experience in neuromorphic computing, experience in digital/analog system design, IC design, and developing neural algorithms. She also has industry experience, working as Director of Engineering at Mavric Semiconductor researching low power edge computing systems using AI/ML algorithms and at Blackberry designing new system architectures. Her current research focuses on neuromorphic computing, event-based processing, co-design of hardware and machine learning algorithms, AI-enhanced approach to microelectronics and applications of heterogeneous systems from HPC to the edge.
Bio:
Srideep Musuvathy manages the Cognitive and Emerging Computing Department at Sandia National Laboratories. He obtained his PhD in Electrical Engineering from the University of Southern California. He also has Masters Degrees in Computer Science and Mathematics from USC. After his PhD, he was a Postdoctoral Research Associate in the Biomedical Engineering Department, exploring the questions of how the brain controls the body. After several years working as a machine learning researcher, he joined Sandia National Labs in 2018.
Moore has written over 170 papers at the boundary between mathematics, physics, and computer science, including on quantum computing, social networks, phase transitions in NP-complete problems, Bayesian inference, and risk assessment in criminal justice. He is an elected Fellow of the American Physical Society, the American Mathematical Society, and the American Association for the Advancement of Science. With Stephan Mertens, he is the author of The Nature of Computation from Oxford University Press.
The UNM Computer Science Cleve Moler & MathWorks Chair in Mathematical and Engineering Software Distinguished Lecture Series
Neural Inspired Approaches to Artificial Intelligence
Srideep Musuvathy, Cognitive and Emerging Computing Department at Sandia National Laboratories
Wednesday, October 16, 2024, 2:00 PM
Location: Larrañaga Engineering Auditorium (Centennial 1041)
Abstract:
Given that the roots of artificial intelligence lie in natural intelligence, it is hardly surprising that looking to the brain might provide deep insights! In his talk, Srideep will explore how the brain might provide solutions to AI challenges. Inspiration for algorithms can be drawn from neural form and function. His talk will explore several examples that leverage what biological systems can offer to impact AI.
Bio:
Srideep Musuvathy manages the Cognitive and Emerging Computing Department at Sandia National Laboratories. He obtained his PhD in Electrical Engineering from the University of Southern California. He also has Masters Degrees in Computer Science and Mathematics from USC. After his PhD, he was a Postdoctoral Research Associate in the Biomedical Engineering Department, exploring the questions of how the brain controls the body. After several years working as a machine learning researcher, he joined Sandia National Labs in 2018.
Moore has written over 170 papers at the boundary between mathematics, physics, and computer science, including on quantum computing, social networks, phase transitions in NP-complete problems, Bayesian inference, and risk assessment in criminal justice. He is an elected Fellow of the American Physical Society, the American Mathematical Society, and the American Association for the Advancement of Science. With Stephan Mertens, he is the author of The Nature of Computation from Oxford University Press.
Enhancing Human-Computer Interaction through Spatial Computing
Zhu Wang, postdoc at NYU
Wednesday, October 2, 2024, 2:00 PM
Location: Larrañaga Engineering Auditorium (Centennial 1041)
Abstract:
With the rise of the metaverse, we are in the midst of a revolutionary transition from traditional computing to spatial computing. Powered by technologies like AR/VR/XR, AI, and robotics, spatial computing represents the next leap toward creating a more capable, intuitive, and natural extension of human faculties. In the future, spatial computing will be as integral to daily life as smartphones are today, transforming the way we interact with digital content and the physical world. However, the interaction paradigms have not yet evolved to fully align with this technological shift. The current emphasis remains largely on immersive experiences through stereo displays, which only represent a fraction of what spatial computing has to offer. To explore its full potential, my research focuses on integrating spatial computing with emerging technologies, while aligning it with how we naturally perceive and engage with our physical and virtual environments. In this talk, I will present two key areas of my work:1. Innovating multisensory simulations for perception investigation, assessment and rehabilitation; 2. Designing novel intelligent assistants that leverage AI, robotics, and multimodal inputs to provide context-aware support. I will discuss how these innovations enable a more seamless integration of the digital and physical worlds, making spatial computing a true extension of our bodies and senses.
This is joint work with Alexander Mercier (Harvard School of Public Health) and Sam Scarpino (Northeastern).
Bio:
Zhu Wang is a post-doctoral researcher at Future Reality Lab, New York University. He received his PhD in Computer Science from New York University, advised by Ken Perlin. His research interests span several areas including XR, HCI, robotics, and AI. More specifically, he has been working on: 1. Human balance assessment and rehabilitation with motion analysis, eye-tracking, and force-sensing technologies; 2. XR-based multi-participant collaboration and communication; 3. Interactions with mobile robots and drones; 4. Data-driven content generation and retrieval.
The UNM Computer Science Cleve Moler & MathWorks Chair in Mathematical and Engineering Software Distinguished Lecture Series
Which links matter most? Sparsifying epidemic models with effective resistance
Cris Moore, Professor at the Santa Fe Institute
Wednesday, September 25, 2024, 2:00 PM
Location: Larrañaga Engineering Auditorium (Centennial 1041)
Abstract:
Network science has increasingly become central to the field of epidemiology. However, many networks derived from modern datasets are not just large, but dense, with a high average degree. One way to reduce the computational cost of simulating epidemics on these networks is sparsification, where a subset of edges is selected and reweighted based on some measure of their importance. Following recent work in computer science, we find that the most accurate approach uses the effective resistances of edges, which can be computed from the graph Laplacian. The resulting sparse network preserves both the local and global behavior of the SIR (susceptible-infected-recovered) model, including the probability each node becomes infected and its distribution of arrival times. This holds even when the sparse network preserves less than 10% of the edges of a mobility network from the United States. Our work helps illuminate which links of a network are most important to disease spread. Defining edge importance using purely topological methods, or by thresholding edge weights, does not perform nearly as well.
This is joint work with Alexander Mercier (Harvard School of Public Health) and Sam Scarpino (Northeastern).
Bio:
Cristopher Moore received his B.A. in Physics, Mathematics, and Integrated Science from Northwestern University, and his Ph.D. in Physics from Cornell. Since 2012, he has been a resident professor at the Santa Fe Institute. He has also held visiting positions at the Niels Bohr Institute, École Normale Superieure, École Polytechnique, Université Paris 7, Northeastern University, the University of Michigan, and Microsoft Research.
Moore has written over 170 papers at the boundary between mathematics, physics, and computer science, including on quantum computing, social networks, phase transitions in NP-complete problems, Bayesian inference, and risk assessment in criminal justice. He is an elected Fellow of the American Physical Society, the American Mathematical Society, and the American Association for the Advancement of Science. With Stephan Mertens, he is the author of The Nature of Computation from Oxford University Press.
The UNM Computer Science Cleve Moler & MathWorks Chair in Mathematical and Engineering Software Distinguished Lecture Series
Innovating Future HPC Systems: Seamless Integration, Evolving Architectures, and Advanced Simulation for Co-Design
Arun Rodrigues, Samsung Electronics Device Solutions
Wednesday, September 18, 2024, 2:00 PM
Location: Larrañaga Engineering Auditorium (Centennial 1041)
Abstract:
High-performance computing (HPC) systems have long been constrained by physical limitations, manufacturing challenges, and software requirements. As future systems evolve, they must address these issues with innovative technologies and architectures. Key advancements will involve seamless integration of heterogeneous processing elements, memory proximity to processors, and more cohesive network design. These improvements will be enabled by breakthroughs in packaging, fabrication, and signaling technologies. Simultaneously, programming and execution models must adapt to fully leverage these new architectures. Designing such systems will demand flexible, integrated simulation and modeling capabilities. Comprehensive frameworks will be essential to inform design choices, optimize trade-offs, and facilitate co-design across hardware, runtimes, operating systems, and application software.
Bio:
At Samsung Electronics Device Solutions, Dr. Arun Rodrigues serves as the Principal Engineer for HPC and AI Application Performance and Modeling. In this role, he leads the team responsible for modeling and simulating future systems. Prior to this, he worked at Sandia National Laboratories where he specialized in high-performance computing (HPC) and advanced computing architectures. His expertise lies in system simulation, co-design, and integrating cutting-edge technologies into next-generation HPC systems. One of his notable contributions is the development of the Structural Simulation Toolkit (SST), a modular tool used to simulate complex interactions between processors, memory, and network subsystems. His current focus is on optimizing architectures for upcoming HPC and AI workloads through hardware and software co-design. He holds a Ph.D. from the University of Notre Dame, where he conducted research under Peter M. Kogge on processing-in-memory architectures.
Traffic Tech Bias and Its Impact on Black and Hispanic Communities
Professor Sonia Gipson Rankin, UNM
Wednesday, September 11, 2024, 2:00 PM
Location: Larrañaga Engineering Auditorium (Centennial 1041)
Abstract:
Sonia Gipson Rankin, a Professor at The University of New Mexico School of Law, blends her computer science background with legal expertise, teaching courses such as Torts, Family Law, and Technology and Law. Her scholarship explores the dynamic intersection of AI, technology, and legal frameworks, with publications in the Washington & Lee Law Review, NYU Law Review Online, Wisconsin Law Review, The Bar Examiner, ABA SciTech Magazine, and Nature Reviews Electrical Engineering. Professor Gipson Rankin is part of the Interdisciplinary Working Group on Algorithmic Justice, advising on AI-related issues, and frequently speaks on topics such as AI, technology, algorithmic justice, and implicit bias. She frequently contributes as a legal analyst to media outlets such as BBC World News, Reuters, NPR, Yahoo! Finance, podcasts, and local and international media outlets. Additionally, she regularly presents on AI issues to judges, state bars, state and federal elected officials, and private industries across the United States.
Expectation vs Reality: Why do industry guidelines and certifications fail to ensure baseline security?
Sazzadur Rahaman, University of Arizona
Wednesday, April 24, 2024, 2:00 PM
Location: Centennial Engineering Center STAMM Room - please note the change of room as the auditorium is out of order.
Abstract:
Industry-wide baseline security directly impacts the associated risks in the business. Apart from that, it also has other significant societal impacts. To ensure such security baselines, various industries (i.e., the payment card industry) maintain security guidelines and specifications. For critical domains, adoptions are generally assured through a systematic compliance checking and certification process. However, such compliance evaluations are significantly hindered by several societal and technical roadblocks.
In this talk, I will discuss the challenges of security guideline adoption and industry-wide compliance checking in light of my experience in the payment card industry and IoT. Our study of e-commerce websites and payment apps revealed that there is a significant gap between the guidelines, their adoption by the practitioners, and compliance evaluation. To assess the baseline security of a less-regulated industry, we studied the IoT ecosystem guidelines and industry perspective towards their adoption. Our findings reveal that even the most comprehensive guidelines fall short, i.e., they do not cover security topics widely or deeply. Our usefulness evaluation shows that most guidelines alone will not succeed in preventing IoT-related security failures. The implication for developers is that a single guideline might not be sufficient for in-depth defense.
Applied Complexity: Digital Acequias for Collective Perception and Action and Bringing Intelligence to the Light
Stephen Guerin, Simtable
Wednesday, March 27, 2024, 2:00 PM
Location: Larrañaga Engineering Auditorium (Centennial 1041)
Abstract:
As we collectively build omnipresent sensor/actuator networks coupled with omniscient AI, what are the design approaches informed by the science of complexity to realize self-sovereign 'sousveillant" data architectures for self-governance and collective intelligence? I will demonstrate some of my work on Simtable.com, Realtime.Earth, AgentScript.org, and the research of RedfishGroup and the Harvard Visualization Lab that attempts to address this question and my 35-year journey in HCI, agent-based modeling, spatial augmented reality, and decentralized computing networks. I will make the case that New Mexico and research at UNM, LANL, Sandia, and Santa Fe Institute is uniquely suited to bring about a fundamental change in the architecture of the next era of collective computing.
Bio:
Stephen Guerin is the inventor and CEO of Simtable, which produces interactive simulations for firefighters and communities that are projected onto physical 3D sandtables. Simtable was developed in 2009 and named one of Time Magazine's top 5 inventions in 2011, along with Apple's Siri and the Lytro camera. Simtable is the first "app" on RedfishGroup's AnySurface platform for making all surfaces in the room interactive via coupled projector/camera systems. Stephen is a Research Associate in the Visualization Research and Teaching Lab in the Earth and Planetary Sciences at Harvard University. His focus includes geospatial agent-based models, interactive projection for local and remote collaboration, complex systems, and artificial life.
Stephen is also the founder and CEO of RedfishGroup. Redfish developed graphics applications in commercial prepress and interactive media 1991-1993. Redfish operated in Beijing and Shanghai 1994-1997 with the first foreign commercial servers on the Chinese Internet and provided early web services to multinational and Chinese firms. Redfish hosted the US Embassy in China, one of the first embassies to go online. In 1996, Stephen originated the popular phrase "Great Firewall of China". He remains deeply interested in China's development and US-China relations.
Stephen maintains a 25-year research relationship with his mentor, Stuart Kauffman, and has lectured as a faculty member of Santa Fe Institute's Complex System Summer School. Stephen researches universal laws in self-organization, structure formation in non-equilibrium systems, and living systems. He's currently exploring how primal and dual systems interact via "Least Action". He suspects bidirectional path tracing in dual particle/field systems may be a general algorithm more universal than natural selection for system evolution and symmetry breaking.
Stephen lives in Santa Fe with his wife, Alison, and their two sons.
A little light reading: changes in lighting technology and the human and environmental health
Tom Igoe, Arts Professor, NYU
Wednesday, February 28, 2024, 2:00 PM
Location: Larrañaga Engineering Auditorium (Centennial 1041)
Abstract:
The lighting industry has seen some significant changes in the past decade. There are four driving forces behind this:
- LEDs are the primary lighting technology now;
- Digital control of light is becoming increasingly common;
- Recent discoveries in biology have detailed light's impact on human health;
- The lighting industry has a material impact on the environment.
These factors change profoundly how we design, how we teach lighting design, how we make lighting fixtures. The first two affect what we can do with light; the second two affect what we should do with light. In this talk, I'll discuss these factors in context of the lighting industry and its intersection with digital systems and human and environmental health.
Bio:
Tom Igoe is the area head for physical computing courses at NYU’s Interactive Telecommunications Program (ITP) in the Tisch School of the Arts. In these courses, he teaches programming and electronics as tools for art and design, starting with how to sense and respond to human physical expression. His research interests also include networks, lighting design, the environmental and social impacts of technology development, clocks, and monkeys. He is a co-founder of Arduino, and hopes to visit Svalbard and Antarctica someday.
2 talks: "Interactive Murals" and "Travel Reduction Algorithm"
Alyshia Bustos, Jaime Gould
Wednesday, March 20, 2024, 2:00 PM
Location: Larrañaga Engineering Auditorium (Centennial 1041)
Abstracts:
Title: Interactive Murals
This work explores Interactive Murals; a mural that blends traditional mural practices and ubiquitous computing, which contains embedded electronics including sensors, actuators, and microcontrollers. I designed three interactive murals in collaboration with a professional muralist, Nanibah Chacon. We developed a suitable workflow for creating interactive murals. This workflow guided us in teaching middle and high school students a series of introductory workshops and interactive mural workshops. Nanibah and I designed and constructed two large outdoor interactive murals with students. After each project, I conducted semi-structured interviews with students, and I determined that students gain agency, learn technical skills, and positively shift their perspectives of computer science by designing and building interactive murals. This talk also each aspect of the workflow for the most recent interactive mural at the National Hispanic Cultural Center.
Title: Travel Reduction Algorithm
Travel Reduction Algorithm (TRAvel) Slicer is a slicing software that minimizes X, Y, and Z travel movements in 3D printing. Conventional slicing software often generates travel movements to print everything within each given layer. These travel movements can negatively impact the quality of prints, especially in models with branching structures. Moreover, for some printers and some materials, travel movements can make printing impossible. TRAvel Slicer combines Zhao et. al.’s method of space-filling Fermat spirals and introduces a method of vertical ordering in order to minimize travel movements in X, Y, and Z. I demonstrate how TRAvel Slicer increases efficiency of print time and makes it feasible to print complex models on Direct Write 3D printers in novel materials.
What is wrong with Artificial intelligence?
Manel Martínez-Ramón, UNM
Wednesday, March 6, 2024, 2:00 PM
Location: Larrañaga Engineering Auditorium (Centennial 1041)
Abstract:
The public opinion about AI bounces between the utopia, with the promise that AI will promote unseen productivity, and the dystopia, where society will collapse and fail. This last one raises fear, controversy, and lack of social acceptance. This makes it necessary to rebrand AI in an unapologetic way, to demonstrate its benefits to society through its incorporation as an engineering tool. There is a quest to construct a corpus of AI fundamentals, AI engineering and industrial and societal applications. In this talk we will review the present context of AI, its outstanding drawbacks from the societal point of view and avenues for a more optimistic future.
Bio:
Dr. Manel Martínez-Ramón is a Professor in the ECE Department. He holds the King Felipe VI Endowed Chair, sponsored by the household of the King of Spain. He received a M.S. in Telecommunications Engineering with a major in Electronics from Universitat Politècnica de Catalunya (Barcelona, Spain) in 1994, and a Ph.D. in Telecommunications Technologies from Universidad Carlos III de Madrid (Madrid, Spain) in 1999. He joined the UNM ECE Department in 2013 as a full professor. His research activities include applications of machine learning to smart antennas, smart grid, photovoltaics, particle accelerators, and others. He is co-author of several books. Among them Digital Signal Processing with Kernels (IEEE Press/Wiley, 2018), Machine Learning Applications in Electromagnetics and Antenna Array Processing (Artech House, 2021) and Deep Learning: a practical approach (Wiley, 2024) are the most recent ones.
A little light reading: changes in lighting technology and the human and environmental health
Tom Igoe, Arts Professor, NYU
Wednesday, February 28, 2024, 2:00 PM
Location: Larrañaga Engineering Auditorium (Centennial 1041)
Abstract:
The lighting industry has seen some significant changes in the past decade. There are four driving forces behind this:
- LEDs are the primary lighting technology now;
- Digital control of light is becoming increasingly common;
- Recent discoveries in biology have detailed light's impact on human health;
- The lighting industry has a material impact on the environment.
These factors change profoundly how we design, how we teach lighting design, how we make lighting fixtures. The first two affect what we can do with light; the second two affect what we should do with light. In this talk, I'll discuss these factors in context of the lighting industry and its intersection with digital systems and human and environmental health.
Bio:
Tom Igoe is the area head for physical computing courses at NYU’s Interactive Telecommunications Program (ITP) in the Tisch School of the Arts. In these courses, he teaches programming and electronics as tools for art and design, starting with how to sense and respond to human physical expression. His research interests also include networks, lighting design, the environmental and social impacts of technology development, clocks, and monkeys. He is a co-founder of Arduino, and hopes to visit Svalbard and Antarctica someday.
