Nemertes [Next] Live Virtual Conference Fall 2025

Quantifying the Shifting Dynamics of Complex Causal Interactions

Real-world systems—from the economy to the climate to our brains—are constantly shifting, with cause-and-effect relationships that wax and wane over time. Uncovering the nature of these interactions, however, has proven difficult, as most traditional methods either assume that these relationships are static or require so much data that the problem becomes intractable. This session will consider how new developments in AI, combined with the mathematics of chaotic systems, can help detect and quantify dynamic causal interactions in complex data. In particular, it will highlight approaches that capture how influences between variables change moment to moment, revealing the underlying hidden structure of their behavior and conclude with an exploration of how these approaches open new possibilities to understand how to coordinate, control, and predict the future dynamics of these complex, interdependent systems.

Bio

Gordon Berman, Ph.D. is an Associate Professor Biology at Emory University. Trained as a physicist, his research integrates machine learning, dynamical systems, and data-driven modeling to uncover fundamental principles of animal and human behavior and the neural dynamics underlying it. A key focus of his work is developing novel computational tools to quantify and analyze complex, time-varying interactions in biological systems. Dr. Berman has led interdisciplinary collaborations spanning theoretical physics, neuroscience, biomechanics, and computational biology, with applications ranging from aging to stroke recovery to autism. He has been recognized as a Cottrell Scholar, a Simons Foundation SFARI Investigator, and a recipient of multiple NIH awards.

Governmental Innovation for Cost Avoidance

Bio

Justin Fanelli is technologist and practitioner contributing to both the public and private sectors. His Defense and Intelligence Community career has spanned six agencies and three military services with a majority at the Department of Navy where he currently serves as the acting Chief Technology Officer and the Technical Director of Program Executive Office Digital and Enterprise Services (PEO Digital). He has taught graduate courses for a decade including guest lectures at Stanford University, Massachusetts Institute of Technology, University of Pennsylvania, Harvard, Carnegie Mellon, and others, but Georgetown is his home. Board and Advisory work includes dual-use technology, angel and venture capital investing, and emerging technology, largely focused on artificial intelligence and cybersecurity across different sectors. He is a Fellow at the Open Forum for Artificial Intelligence, the Rodel Institute, and is a member of the Cosmos Club. Recent awards have included the Civilian Exemplary Achievement, the Department of Navy's Engineer and Scientist of the Year, Secretary of the Navy’s Innovation Award, National Intelligence Meritorious Unit Citation, Project Management Institute's Project of the Year, and named to the Federal 100, Health100 and Defense50 twice. Justin received his Bachelor’s and Master’s from Penn State University and the University of Pennsylvania, respectively, both in electrical engineering.

Avoiding Failure as a Pathway to Success

Transforming large organizations through technology is a high-stakes, evolutionary journey, demanding continuous success. Leaders often face deep-seated conflicts between operational discipline and the urgent need for change. This discussion identifies major de-railers such as deeply embedded and risk-laden operating models that guarantee failure, skills mismatched to radical change, and pervasive misinformation flows. We’ll explore how to bridge the builder–operator divide and establish a self-reinforcing cycle of trust and accountability for sustainable organizational agility.

Bio

Larry Fitzpatrick is Executive Vice President and Chief Technology Officer (CTO) for OneMain Financial. As CTO, Larry sets technology strategy, is accountable for the delivery of innovative digital capabilities to meet customer needs and ensures the reliability and security of core systems and infrastructure. He oversees the work of a skilled team of technology professionals dedicated to designing, engineering and delivering the systems and services necessary to support OneMain’s continued growth.

Before joining OneMain in 2020, Larry worked for Amazon Web Services designing new technical services for the financial industry. He has more than 30 years of experience building and leading technology organizations across industries. Always looking for the intersection of growth and innovation, he has been the CTO of software product companies, President of a system integrator, Senior Vice President in corporate IT and led R&D at leading research institutions.

Larry earned a Master of Science in biomedical engineering from the University of Virginia and received his undergraduate degree in biology from Georgetown University. He currently serves on the board of American University’s Kogod School of Business Information Technology Executive Committee.

Climate Change and Climate Variability: The Physics and the Implications

Climate is changing: We’re affecting it and it’s affecting us. While the physics of climate is not as reputable as that of elementary particles or of black holes, it’s no less complex nor less challenging. This session will attempt to offer a feel for the "global weirding" that accompanies global warming; that is, the natural, intrinsic climate variability that is modified by both external, deterministic, and internal, random forces. A fairly new mathematical framework helps explain the way that both types of forces affect the probability distribution associated with climate dynamics: not just the evolution of its mean but also that of higher moments and of the extremes. This framework cannot remove the uncertainties in the climate’s future evolution but it can help to better understand the obstacles and get over them.

Bio

Michael Ghil is a mathematician and physicist, focusing on the climate sciences and their interdisciplinary aspects. He is a founder of theoretical climate dynamics, as well as of advanced data assimilation methodology. He has systematically applied dynamical systems theory to planetary-scale flows, both atmospheric and oceanic. Ghil has used these methods to proceed from simple flows with high temporal regularity and spatial symmetry to the observed flows, with their complex behavior in space and time. His studies of climate variability on many time scales have used a full hierarchy of models, from the simplest ‘toy’ models all the way to atmospheric, oceanic and coupled general circulation models. Ghil has developed a new mathematical framework, Boolean delay equations, which extends cellular automata into continuous time and facilitates therewith machine learning of nonlinear dynamics. Recently, Ghil has also worked on modeling and data analysis in population dynamics, macroeconomics, and the climate–economy–biosphere system.

He is currently a Distinguished Research Professor at the University of California, Los Angeles; a Distinguished Professor Emeritus at the École Normale Supérieure, Paris; and a long-term Visiting Professor at Imperial College London.

What Limits the Speed of Evolution and Innovation in Brains, Machines, and Organizations?

Life as we know it today was made by countless mutations in DNA, setting up the dynamics that allow animals to succeed in their niches. There are the classical insights, “evolution can make behavior better” and the less classical ones such as “constraints make evolution slow." This session will take the core of this insight and apply it to brains, AI systems, and organizations.

Bio

Konrad Körding's research at the University of Pennsylvania combines experimental methods with the application of computational principles. The main principle of his work is the idea of normative models and, in particular, Bayesian statistics. Some of his most controversial work is work on predicting the future success of scientists, leading to a calculator predicting the h-index 10 years into the future. His experimental work addresses motor learning and motor control, relating these phenomena to Bayesian ideas. Most recently, he has focused on methods of analyzing neural data and methods for obtaining large neural datasets. Körding is a frequent advocate of shifting research paradigms in neuroscience, publishing and co-authoring various letters, papers, and talks on the applications of deep learning in neuroscience. In 2023, Körding was one of several prominent scientists leading calls to reverse engineer an entire nervous system.

Körding obtained both a diploma degree and a PhD in physics at ETH Zurich in 1997 and 2001, respectively. He then worked as a postdoctoral fellow at the Collegium Helveticum in Zurich and at University College London, followed by a Heisenberg Fellow position at MIT. He joined the faculty at Northwestern University and the Rehabilitation Institute of Chicago, where he was a professor of physical medicine and rehabilitation, physiology, and applied mathematics. In 2017, he joined the faculty at the University of Pennsylvania with joint appointments in the Department of Neuroscience and Department of Bioengineering.

Virtual Field Trip Part II: Columbia University's Creative Machines Lab

The Creative Machines Lab looks to the biological concepts of self-organization and evolution when designing and constructing robots that self-replicate, ask questions, self-reflect, mimic the humans around them, and more. Lab director Hod Lipson and his students will provide a benchtop look at variety of research projects, including self-learning foosball-playing robots, a tidying-up robot, a robot that anticipates and mimics human facial expressions, a 3-D food printer, an exploration of robot metabolism, and maybe even the world’s fastest soft robotic fish. Plus, featured doctoral student Judah Goldfeder will share his use of AI to optimize buildings’ HVAC control systems by envisioning the building itself as a robot.

Bio

James and Sally Scapa Professor of Innovation in the Department of Mechanical Engineering; Co-Director, Maker Space Facility; Chair, Department of Mechanical Engineering

Hod Lipson is a roboticist who works in the areas of artificial intelligence and digital manufacturing. He and his students love designing and building robots that do what you’d least expect robots to do: Self replicate, self-reflect, ask questions, and even be creative. Lipson’s research asks questions such as: Can robots ultimately design and make other robots? Can machines be curious and creative? Will robots ever be truly self-aware? Answers to these questions can help illuminate life’s big mysteries. Lipson’s research interests include robotics, artificial intelligence, digital manufacturing, and 3-D printing.

An award-winning researcher, teacher, and communicator, Lipson enjoys sharing the beauty of robotics though his books, essays, public lectures, and radio and television appearances. He is a professor of Mechanical Engineering and Data Science at Columbia University, where he directs the Creative Machines Lab, which pioneers new ways to make machines that create, and machines that are creative.

Before joining Columbia University in 2015, Lipson spent 14 years as a professor at Cornell University. He received his PhD in 1999 from the Technion—Israel Institute of Technology, followed by a postdoc at Brandeis University and MIT. His work on self-aware and self-replicating robots challenges conventional views of robotics and has enjoyed widespread media coverage. He has also pioneered open-source 3D printing, as well as electronics 3D printing, bio-printing and food printing. Lipson has co-authored over 300 publications that received over 14,000 citations to date. He has co-founded four companies, and is frequent keynoter at both industry and academic events. His TED Talk on self-aware machines is one of the most viewed presentations on AI and robotics.

Evolving Building Performance Assessment Tools and Methodologies to Meet the Moment

This talk will dive into the characteristics of a high performance building, and why energy performance assessment tools and methodologies—namely EnergyStar and Energy Use Intensity (EUI)—need to evolve to keep pace.

Today, ~10 cities and 3 states have passed Building Performance Standards that require existing buildings to undertake energy efficiency retrofits to meet minimum performance thresholds.  These performance thresholds are based upon EnergyStar or equivalent EUI methodologies that were developed when electricity was predominantly generated from fossil fuels and “electric heating” meant heating with electric resistance.  Today, by comparison, 40% of electricity is generated from non-fossil fuel, carbon free energy sources (a percentage that is growing), and heat pumps, which are powered by electricity, can heat air and hot water at 3 to 4 times the efficiency of a gas furnace or boiler. These evolutions along with other building technology advancements mean today’s high-performance building is all electric and responsive to the cost, carbon-intensity, and demand for grid electricity and how many people are in the building.

Yet, EnergyStar and EUI-based methodologies do not measure these characteristics.

With another ~30 cities and 3 states committed to passing Building Performance Standards, and at least 150 institutional and financial investors and 3000 funds, companies, and asset operators committed to EUI thresholds, it's important that we evolve building performance assessment methodologies to keep pace with the definition of high-performance building.  This session will offer a proposal of what that could look like.

Bio

Charlotte Matthews has 25 years of experience in the design, construction and development of real estate, energy infrastructure and technology.  She has also been a trusted advisor for policy makers. 

Most recently, Charlotte was a Managing Director with RMI, a nonprofit working with industry to advance the clean energy transition.  Prior, she led a software product team at Google developing a home automation system for utility customers with dynamic electricity pricing. Before that she worked in commercial real estate, planning and developing green buildings and sustainable infrastructure.

Today, Charlotte sits on the board of CMC Energy Services, a utility program implementer with special expertise in serving low to moderate income communities, and retains a small advising practice that conducts due diligence on projects and start ups for investors.  

Over her career, Charlotte has served on a number of nonprofit boards and government task forces and taught at Columbia University’s Masters in Real Estate Development program.  She holds a BSc in Environmental Science from Brown University.

The Meaning of Artificial General intelligence

AI is all around us—recognizing our faces in photos, constructing our news feeds, answering our questions, writing our essays, and much more. But rapidly improving AI is poised to play a much bigger role in all of our lives. In this talk I will describe how current-day AI works, how “intelligent” it really is, and what our expectations—and concerns—about its near-term and long-term prospects should be.

Bio

Melanie Mitchell is Professor at the Santa Fe Institute. Her current research focuses on conceptual abstraction and analogy-making in artificial intelligence systems. Melanie is the author or editor of six books and numerous scholarly papers in the fields of artificial intelligence, cognitive science, and complex systems. Her 2009 book Complexity: A Guided Tour (Oxford University Press) won the 2010 Phi Beta Kappa Science Book Award, and her 2019 book Artificial Intelligence: A Guide for Thinking Humans (Farrar, Straus, and Giroux) was shortlisted for the 2023 Cosmos Prize for Scientific Writing.

Photo credit: Kate Joyce for the Santa Fe Institute

Challenges and Novel Approaches Toward Controlling the Global H5N1 Outbreak

The current Highly Pathogenic Avian Influenza outbreak in North America (2022–present) represents the largest domestic animal disease outbreaks in the last 10,000 years of animal agriculture with respect to geography (6 of 7 continents affected), species affected (domestic and wild avian and mammals), mortality (over 300 million poultry), and economics (over 20 billion dollars). The primary reservoir of the virus are waterfowl such as wild ducks and geese. Despite our understanding of how the virus ‘spills over’ from wild waterfowl to domestic poultry and livestock, current methods of farm level biosecurity don’t integrate the spatial and temporal aspects of waterfowl bird migration and roosting behavior into a predictive risk model.

This session will present the WaterFowl Alert Network, which leverages a combination of already available tech including radar, satellite, and telemetry to make daily risk models of waterfowl location for the hundreds of thousands of commercial poultry and livestock farms in the United States. Farmers and other stakeholders are provided historic, daily, and forecasted risk assessments that they can utilize to mitigate the risk of viral spillover to their farms, thus protecting the nation’s food animals. Other applications in renewable energy (e.g., habitat assessment for birds near turbines and solar farms) and recreation are also being explored.

To learn more about the WaterFowl Alert Network and how it remotely predicts waterfowl location and avian influenza risk for the nations farmers please go to: waterfowlalertnetwork.com

To view some real-life examples of how the WaterFowl Alert Network works Pitesky invites you to follow him on LinkedIn: www.linkedin.com/in/maurice-pitesky

Bio

Maurice Pitesky is an associate professor of cooperative extension at the UC Davis School of Veterinary Medicine with an appointment in poultry health and food safety epidemiology.  Dr. Pitesky earned his BS in biology from UCLA, and his DVM and MPVM from UC Davis. Pitesky is also boarded in Preventative Veterinary Medicine (DACVPM).

Pitesky’s academic research interests are focused in major areas:

1. Using various epidemiological techniques and cartography to understand how avian diseases move in time and space.  
2. Using remote sensing such as weather radar, telemetry and satellite imagery for waterfowl predictive modeling around the world
3. Disease modeling of avian diseases 
4. Using web-scraping and computational linguistics to understand the role of social media in sentiment associated with animal diseases 
5. Gaining a better understanding of small-scale poultry production with respect to environmental sustainability, poultry heath, and food safety.

Perceiving Something Entirely New: Olo

If humans were given an entirely new sense or new sensory information, would they be able to make sense of them and invent new percepts to attribute to them? We’ve developed a special type of display called Oz Vision that can test those ideas, specifically in the area of color vision. With the Oz display, we bypass the early image-forming processes and directly stimulate vision at the level of individual cones. With this system, we can generate retinal signals that natural light can never produce. For example, because the middle wavelength sensitive M-cone’s spectral sensitivity overlaps with the short (S) and long (L) wavelength sensitive cones, there is no light in nature that can excite them exclusively. But the Oz display can track and deliver light to patches of M-cones only. We discovered that this type of stimulation elicits a deeply saturated sensation of color—which we call olo—that lies outside of the human color gamut. This is the beginning of a series of new projects aiming to explore the limits of perception.

Bio

Throughout his 30-year academic career, Austin Roorda has pioneered the development and use of advanced optical systems for studying human vision in healthy and diseased eyes. He was first to map the human trichromatic cone mosaic while he was a postdoc at the University of Rochester, he invented the adaptive optics scanning laser ophthalmoscope (AOSLO) in his first faculty position at the University of Houston and, over the course of 20 years at the University of California Berkeley, he developed ways to track eye motion and test human vision in healthy and diseased eye on a microscopic scale. His latest work involves the use of his AOSLO technology to track and stimulate human cone photoreceptors in ways that expand the sensory capabilities of human vision. As of July 2025, he returned to Canada to join the faculty at the University of Waterloo, his alma mater. He is a Fellow of Optica and ARVO. Notable awards include the Distinguished Alumni Award from the University of Waterloo, the Glenn Fry Award from the American Academy of Optometry, a Guggenheim Fellowship, an Alcon Research Institute Award, a Leverhulme Visiting Professorship from Oxford University, the Rank Prize in Optoelectronics, and the Boynton Prize from Optica.

A Dynamically Responsive Built Environment: The Interplay of Design and Science

Bio

Jenny E. Sabin is an architectural designer whose work is at the forefront of a new direction for 21st century architectural practice — one that investigates the intersections of architecture and science and applies insights and theories from biology and mathematics to the design of responsive material structures and ecological spatial interventions for diverse audiences. Sabin is the Arthur L. and Isabel B. Wiesenberger Professor in Architecture and the inaugural Chair for the new multicollege Department of Design Tech at the Cornell College of Architecture, Art, and Planning where she co-established a new advanced research degree in Design Technology. She is principal of Jenny Sabin Studio, an experimental architectural design studio based in Ithaca and Director of the Sabin Lab at Cornell AAP. Her book, LabStudio: Design Research Between Architecture and Biology, co-authored with Peter Lloyd Jones was published in July 2017. In that same year, Sabin won MoMA & MoMA PS1’s Young Architects Program with her submission, Lumen.

Virtual Field Trip Part I: Columbia Fusion Research Center

This session will be a virtual field trip of the newly minted Columbia Fusion Research Center, which has a mandate of working in close collaboration with private fusion industry players to develop and deploy a reliable, sustainable, and scalable energy source. Although just founded this past spring, with Carlos Paz-Soldan as its founding director and doctoral student Dylan Schmeling as field trip guide, this Center already boasts numerous fusion installations and experiments: the High-Beta Tokamak (HBT-EP), the Columbia University Tokamak for Education (CUTE), the Columbia Stellarator eXperiment (CSX), and student-run Pellets At Columbia (PAC). Some of these are under development, such as CSX, which repurposes the Columbia Non-Neutral Torus (CNT) into a superconducting quasi-symmetric stellarator to optimize plasma confinement geometries.

Bio

Dylan Schmeling is a Ph.D. student in Applied Physics at Columbia University, where he conducts experimental research on the Columbia Stellarator eXperiment (CSX), an experiment under development at the Columbia Fusion Research Center. His work centers on the design, diagnostics, and cryogenic testing of high-temperature superconducting (HTS) magnets for advanced stellarator configurations. Prior to Columbia, he contributed to the EPOS stellarator project at the Max Planck Institute for Plasma Physics in Germany, helping to develop cryogenic vacuum systems and diagnostics for HTS magnet testing. Raised in Tanzania with an international background, Dylan brings a global perspective to his research. His interests lie in pushing the frontiers of fusion energy through precision engineering and experimental plasma physics.

AI: A Contrarian’s Viewpoint

Having written books over the past decade critical of Big Tech, Jonathan Taplin is keenly aware that the coming AI revolution will profoundly change society—not always for the better. This session will address two significant concerns: First, the threat to the livelihood of artists, whose life work—music, books, photographs, paintings, video—has been used as fodder to train AI models under the guise of “fair use,” with copyright itself under threat by the five men in control of the AI and social media ecosystems. Second, and even more wide-reaching, predictions are in wide circulation for robots to supplant a majority of routine physical-labor jobs and AI to replace half of knowledge workers within the coming 15 years or sooner. If correct, what President Trump is touting as a “golden age” would turn into a dystopian nightmare with millions of unemployed citizens across all income levels. This session is intended to raise the alarm.

Bio

Jonathan Taplin’s extraordinary journey has put him at the crest of every major cultural wave in the past half century: he was tour manager for Bob Dylan and the Band in the ’60s, producer of The Concert For Bangladesh and major films in the ’70s for Martin Scorsese, Wim Wenders and Gus Van Sant, an executive at Merrill Lynch’s Media Mergers and Acquisition Group in the ’80s, creator of the Internet’s first video-on-demand service in the ’90s, and a cultural critic and author writing about technology in the new millennium. He is the author of Move Fast and Break Things: How Facebook, Google and Amazon Cornered Culture and Undermined Democracy; The Magic Years: Scenes From a Rock and Roll Life; and The End of Reality: How 4 Billionaires Are Selling a Fantasy Future of the Metaverse, Mars and Crypto. His commentary has appeared in The New York Times, Washington Post, Time Magazine, The Huffington Post, The Guardian, Medium, The Washington Monthly, and the Wall Street Journal. He is the Director Emeritus of the Annenberg Innovation Lab at the University of Southern California.