Elisa Omodei, Predictive Analytics Lead, mobile Vulnerability Analysis and Monitoring at the UN World Food Programme, Vice-President Secretary, The Complex Systems Society


Talk Title:
Who, where, why: non-traditional data and predictive analytics to map socio-economic vulnerabilities


Talk Abstract:
In a rapidly changing world, severely affected by extreme weather events, epidemic outbreaks, economic shocks and conflicts, it is of fundamental importance to understand where the most vulnerable people are, how many they are, and to identify what it is that makes them more vulnerable than others to these threats. During the last decade, research has shown that data such as digital traces, phone metadata and satellite imagery carry relevant information beyond their original purpose and can be used as a proxy to measure socio-economic characteristics and detect vulnerabilities when traditional data is not available. Following an overview of these studies, the talk will deep dive into the UN World Food Programme’s original work on predicting food security. We will then conclude by discussing challenges and limitations, but also opportunities, that come with these approaches.

Speaker Bio:
Elisa Omodei is the Predictive Analytics Lead of the Hunger Monitoring Unit at the World Food Programme’s Research, Assessment and Monitoring division. She also serves as Vice-President Secretary of the Complex Systems Society. She holds a BSc and a MSc in Physics and a PhD in Applied Mathematics for the Social Sciences. After her PhD, she spent a few years in academia before joining the United Nations in 2017, first at UNICEF's Office of Innovation and now at the World Food Programme.

Title: Informing fishery sustainability with network ecology

Abstract:
The world is facing a fisheries crisis, with fish stocks and marine ecosystems collapsing due to human over-exploitation. Understanding the interconnectedness among species in harvested ecosystems and the dynamic responses of ecosystems to fishing is critical for informing managing practices to attain fisheries’ sustainability. Two of our recent publications evaluate such interconnectedness among dozens of species in harvested ecosystems using network analysis, mathematical models and computational tools. First, we investigate the combined effects of artisanal fisheries and climate change on an intertidal food web of the Central Coast of Chile. We show that climate change has a stronger effect on the food web than artisanal fisheries. Second, we incorporate economic rules governing fish extraction based on fish price and yield to evaluate how economic dynamics affect food webs and cause species extinctions. Our work exemplifies the importance of studying the effects of fisheries on the entire food web, instead of only focusing on the target species, and of introducing humans as dynamic components into food web models to answer questions of fisheries sustainability.

Short Bio
Fernanda Valdovinos is a theoretical ecologist and network scientist. She recently joined (July 2020) UC Davis as Assistant Professor in the Department of Environmental Science and Policy, and before then she was Assistant Professor in the University of Michigan’s Department of Ecology and Evolutionary Biology and the Center for the Study of Complex Systems since January 2018. Her group uses network analysis and mathematical modeling to understand and quantify the structure, dynamics, and function of biological communities, including their responses to environmental change such as species extinctions, invasions, climate change, and fisheries. Valdovinos got her PhD in 2014 on Ecology and Evolutionary Biology at the University of Chile, and then conducted her postdoc studies at the University of Arizona and spent part of her postdoc time at UC Berkeley.

Talk Title:
Guiding the Self-Organization of Cyber-Physical Systems

Talk abstract:
Self-organization offers a promising approach for designing adaptive systems. Given the inherent complexity of most cyber-physical systems, adaptivity is desired, as predictability is limited. Here I summarize different concepts and approaches that can facilitate self-organization in cyber-physical systems, and thus be exploited for design. Then I mention real-world examples of systems where self-organization has managed to provide solutions that outperform classical approaches, in particular related to urban mobility. Finally, I identify when a centralized, distributed, or self-organizing control is more appropriate.

Bio: Carlos Gershenson, Research Professor, UNAM

Carlos Gershenson is a tenured, full time research professor at the Universidad Nacional Autónoma de México (UNAM), where he leads the Self-organizing Systems Lab. He was a Visiting Professor at MIT and at Northeastern University (2015-2016). He was a postdoctoral fellow at the New England Complex Systems Institute (2007-2008). He holds a PhD summa cum laude from the Vrije Universiteit Brussel, Belgium (2002-2007). He holds an MSc degree in Evolutionary and Adaptive Systems, from the University of Sussex (2001-2002), and a BEng degree in Computer Engineering from the Fundación Arturo Rosenblueth, México. (1996-2001).

He is Editor-in-Chief of Complexity Digest and member of the Board of Advisors for Scientific American. He has received numerous awards, including a Google Research Award in Latin America and the Audi Urban Future Award.

Casey Fiesler, Assistant Professor, Founding Faculty, Information Science, University of Colorado Boulder

Title: Data Is People: Ethics and Education for Data Science

Abstract: Big data has opened up new possibilities and transformed the ways we conduct research in nearly every discipline. However, ethical considerations and education for research has long focused on human subjects, governed in the U.S. by institutional review boards. Data science often falls through the cracks of these regulations, so it is even more imperative that we have strong ethical norms and guidelines. This starts with the reminder that though data scientists may not interact directly with people, the data collected and analyzed very often comes from people, which opens up important considerations around privacy, consent, and harm. Moreover, applications of data science research, particularly with respect to prediction, have the potential for large-scale societal impacts. In considering the broad landscape of technology ethics when it comes to uses and applications of big data, I will argue for a fundamental shift in how we teach ethics to future data scientists and researchers.

Bio: Dr. Casey Fiesler is an assistant professor and founding faculty in the Department of Information Science as well as Computer Science, by courtesy, at University of Colorado Boulder, where she researches and teaches in the areas of technology ethics, internet law and policy, and online communities. Also a public scholar, she is a frequent commentator and speaker on topics of technology ethics and policy, as well as women in STEM (including consulting with Mattel on their computing-related Barbies). Her work on research ethics for data science, ethics education in computing, and broadening participation in computing is supported by the National Science Foundation, as well as Mozilla and Omidyar Network as part of the Responsible Computer Science Challenge.

Guillermo García-Pérez - Senior Researcher, Theoretical Physics, University of Turku - Finland

Talk title: Emergent spatial entanglement in many-body quantum systems

Abstract: Are the global properties of complex quantum systems simply a consequence of the properties of their individual components? Or are there features that emerge, as a result of self-organisation, uniquely characterising the complex object as a whole? The answer to these questions might unveil up-to-now unknown properties of molecular complexes, proteins, and living organisms, as well as of engineered complex quantum communication networks.

In this talk, I will show how our holistic approach combining quantum physics and complex network theory brings to light the existence of emergent spatial structures of quantum entanglement in a paradigmatic many-particle quantum system [1]. I will also introduce an efficient algorithm for quantum network tomography, showing exponential improvement with respect to existing approaches [2], and hence allowing for the experimental observation of the new entanglement structures that we have discovered.

References:
[1] “Emergent entanglement structures and self-similarity in quantum spin chains”, Boris Sokolov, Matteo A. C. Rossi, Guillermo García-Pérez, Sabrina Maniscalco, arXiv:2007.06989.
[2] “Pairwise tomography networks for many-body quantum systems”, Guillermo García-Pérez, Matteo A. C. Rossi, Boris Sokolov, Elsi-Mari Borrelli, Sabrina Maniscalco, Phys. Rev. Research 2, 023393 (2020).

Bio: Guillermo is a physicist working at the intersection between complex systems and quantum physics. He earned his BSc in Physics and his MSc in Advanced Physics at the University of Barcelona. He obtained his PhD from the same university in 2018 for his thesis on the geometric structure of complex networks. His research in complex networks has covered very disparate topics, ranging from pure mathematics to international trade. As a postdoc at University of Turku, he has worked on quantum computing and simulation, as well as on complex quantum networks.

Dr. Karissa Y. Sanbonmatsu is a structural biologist at Los Alamos National Laboratory, where she leads the Sanbonmatsu Laboratory established in 2001. Her team uses computational and experimental approaches to understand the mechanism of a diverse array of epigenetic and non-coding RNA systems, including chromatin, ribosomes, riboswitches and long non-coding RNAs.

She has been a leading figure in structural studies of long non-coding RNAs in epigenetics and is currently studying the mechanism of epigenetic effects involving chromatin architecture. Her body of work led her to be elected as a Fellow of the American Physical Society in 2012. Most recently, her group set the record for the world’s largest published biomolecular simulation at one billion atoms, the first simulation of an entire gene.

She described her work with epigenetics and came out as transgender in a 2014 TEDxTalk. She also delivered a TED talk at TEDWomen on The biology of gender, from DNA to the brain, in November 2018. The talk, with over 2 million views, covers epigenetics and how hormones control DNA decisions during embryo development.

Talk Title: Science for the next pandemic: from large-scale simulations of genes to 3-D reconstructions of chromosomes

Talk Abstract: While most cells in the body have identical 1-D genomes, cells in different tissues have remarkably different cell shapes, internal structures and functionality. Recent studies suggest that the 3-D structure of the genome differs from cell to cell, and that these differences have profound effects on the function of the underlying DNA, impacting cell structure and functionality. Interestingly, viral infections also affect the 3-D organization of the genome. While the common paradigm suggests that chromosome compaction causes gene silencing, few mechanistic studies on full chromosomes have been performed to support this. Recently, the development of high throughput sequencing technology has produced precise information regarding gene-gene interactions. The Hi-C technique cross links chromosomes with themselves, revealing DNA-DNA interactions. These samples are then fragmented and ligated to produce small loops containing the DNA-to-DNA interaction sequences. Finally, a 2-D contact map is produced. While many suspect that patterns in the 2-D contact map reflect 3-D proximity of genes, this is difficult to discern. We use constrained molecular simulations to produce 3-D reconstructions of full chromosomes highly consistent with Hi-C experimental data for the process of X chromosome silencing, shedding light on the chromosome compaction. Changes in 3-D structure, could, in principle, be used to detect more subtle signatures of viral infections. In addition to full chromosome simulations, results from the first explicit solvent MD simulations of an entire gene locus (using the LANL Trinity supercomputer) will be presented. This pilot study is the first billion-atom simulation published in the biosciences. Simulations such as these have the ability to push HPC resources much more than conventional simulations in the physical sciences.

Talk title:
Computer Vision: Who benefits and who is harmed?

Talk abstract:
Computer vision has ceased to be a purely academic endeavor. From law enforcement, to border control, to employment, healthcare diagnostics, and assigning trust scores, computer vision systems are being rapidly integrated into all aspects of society. In research, there are works that purport to determine a person’s sexuality from their social network profile images, others that claim to classify “violent individuals” from drone footage. These works were published in high impact journals, and some were presented at workshops in top tier computer vision conferences such as CVPR.
A critical public discourse surrounding the use of computer-vision based technologies has also been mounting. For example, the use of facial recognition technologies by policing agencies has been heavily critiqued and, in response, companies such as Microsoft, Amazon, and IBM have pulled or paused their facial recognition software services. Gender Shades showed that commercial gender classification systems have high disparities in error rates by skin-type and gender, and other works discuss the harms caused by the mere existence of automatic gender recognition systems. Recent papers have also exposed shockingly racist and sexist labels in popular computer vision datasets--resulting in the removal of some. In this talk, I will highlight some of these issues and proposed solutions to mitigate bias, as well as how some of the proposed fixes could exacerbate the problem rather than mitigate it.


Bio: Timnit Gebru, Expert Research Scientist and AI Ethicist

Timnit Gebru is an expert research scientist and AI ethicist , working to reduce the potential negative impacts of AI. Timnit earned her doctorate under the supervision of Fei-Fei Li at Stanford University in 2017 and did a postdoc at Microsoft Research NYC in the FATE team. She is also the cofounder of Black in AI, a place for sharing ideas, fostering collaborations and discussing initiatives to increase the presence of Black people in the field of Artificial Intelligence.

Marie-Josée Fortin, University of Toronto, Professor, FRSC, Canada Research Chair in Spatial Ecology

Talk Title:
Ecological Networks in Dynamics Landscapes

Talk Abstract:
Network ecology is an emerging field allowing researchers to conceptualize and model complex and dynamic ecological systems. Here, I highlight the parallel developments in ecological network studies and spatial network applications and their convergence in the use of network theory. Then, I summarize how ecological, spatial, temporal, and spatio-temporal networks can be formalized into the framework of multilayer networks. Specifically, I present how the spatio-temporal network can be analysed focusing either on the dynamics on the network or of the network. Such distinctions provide the foundations for the formulation of an “ecological network dynamics hypothesis” (ENDH) stating key network topologies that constrain the dynamic of ecological systems. Such an ENDH could in turn permit assessing trade-offs in network topologies and functions that affect the persistence of ecological systems. I then propose the integration of ecological networks with spatial networks to improve our understanding of complex ecological systems. This integration combines filtering the ecological interaction network based on motifs with the delineation of patches in the spatial network using an edge detection algorithm scalable to species dispersal abilities. I conclude that network ecology with its analytical methods will improve our understanding on how ecological systems will respond in spatially dynamic landscapes.

Bio:
Marie-Josée Fortin is a University Professor in the Department of Ecology and Evolutionary Biology at the University of Toronto. She is a Fellow of the Royal Society of Canada and holds a Tier 1 Canada Research Chair in Spatial Ecology. Professor Fortin is recognized internationally as a leader in spatial ecology with expertise in network theory to address both fundamental and applied research to conserve biodiversity in fragmented landscapes. She pioneered the field of spatial analysis of ecological data and contributed to the development of numerous analytical methods and models. Her research endeavors focus on conservation biology issues. She investigates how ecological processes and environmental factors affect species persistence, species dispersal, and species range dynamics. Her research is at the interface of several disciplines (spatial ecology, conservation, forest ecology, disturbance ecology, community ecology, landscape genetics, spatial epidemiology, spatial statistics, spatially-explicit modeling, and network theory) where the most important challenging problems lie.

DJ Patil has held a variety of roles in Academia, Industry, and Government.
He is Head of Technology for Devoted Health, a Senior Fellow at the Belfer Center at the Harvard Kennedy School, and an Advisor to Venrock Partners.

Dr. Patil was appointed by President Obama to be the first U.S. Chief Data Scientist where his efforts led to the establishment of nearly 40 Chief Data Officer roles across the Federal government. He also established new health care programs including the Precision Medicine Initiative and the Cancer Moonshot, new criminal justice reforms including the Data-Driven Justice and Police Data Initiatives that cover more than 94 million Americans, as well as leading the national data efforts. He also has been active in national security and for his efforts was awarded by Secretary Carter the Department of Defense Medal for Distinguished Public Service which the highest honor the department bestows on a civilian.

In industry, he led the product teams at RelateIQ which was acquired by Salesforce, was founding board member for Crisis Text Line which works to use new technologies to provide on demand mental and crisis support, and was a member of the venture firm Greylock Partners. He has also was Chief Scientist, Chief Security Officer and Head of Analytics and Data Product Teams at the LinkedIn Corporation where he co-coined the term Data Scientist. He has also held a number of roles at Skype, PayPal, and eBay.

As a member of the faculty at the University of Maryland, his research focused on nonlinear dynamics and chaos theory and he helped start a major research initiative on numerical weather prediction. As an AAAS Science & Technology Policy Fellow for the Department of Defense, Dr. Patil directed new efforts to leverage social network analysis and the melding of computational and social sciences to anticipate emerging threats to the US. He has also co-chaired a major review of US efforts to prevent bioweapons proliferation in Central Asia and co-founded the Iraqi Virtual Science Library (IVSL). In 2104 he was selected by the World Economic Forum as a Young Global Leader and is also a Member of the Council of Foreign Relations.

More details can be found on his LinkedIn profile: http://www.linkedin.com/in/dpatil and can be followed on twitter @dpatil

Talk title: Spatial Social Network (SSN) Analysis: Social Networks in Geographic Space

Description: Social networks have a geographic component--whether the network represents individuals in a local neighborhood association or virtual gamers across the world. Modeling a social network in geographic space allows for the study of new principles about how spatial situation affects power, formation and communities in networks. This talk will introduce a few case studies that examine spatial social network (SSN) dynamics within a geographic information systems (GIS) environment using GIS operations, geovisualization and spatial analysis methods. The results show how geographical features likely enable or preclude ties.

Clio Andris, Assistant Professor, School of Interactive Computing., School of City & Regional Planning, Georgia Tech

Bio: Clio Andris is an assistant professor with a joint appointment in the School of City & Regional Planning and School of Interactive Computing. She is also the director of the Friendly Cities Lab: Data Driven Love for Community. She was an assistant professor in the Geography Department at Penn State from 2014-2019. Prior to that, Clio was a postdoc at the Santa Fe Institute (2012-2014), MIT Dept. of Urban Studies and Planning (2012), and Singapore-MIT Alliance for Research and Technology (SMART) (2011-2012). She holds a PhD in Urban Information Systems (MIT, 2011), MS in Geography (U. South Carolina, 2008) and BA in American Studies with Geography minor (Boston U., 2006). She was a National Defense Science and Engineering Graduate (NDSEG) Fellow during her PhD and was a member of the Senseable City Lab under Carlo Ratti. She has been advised by Luis Bettencourt (SFI), Joseph Ferreira Jr. (MIT) and David Cowen (USC). she conducts research in urban analytics and geographic information systems (GIS), specifically on inter-place connectivity and social systems. She frequently attends and has had leadership roles at IEEE SIGSPATIAL, GIScience, the AAG (American Association of Geographers) Annual Meeting, and the International Cartographic Conference. Clio was named a TRELIS Fellow in 2019.

Talk Title: Modeling Shield Immunity — From Concept to Implementation

Abstract: Developing intervention strategies that can reduce transmission and alleviate the impacts of social distancing is an essential goal of long-term public health responses to the ongoing COVID-19 pandemic. In this talk I will describe our efforts to develop models of ‘shield immunity’, i.e., leveraging serological testing and the increased interaction rates of recovered individuals to reduce new chains of transmission and foster safer economic re-engagement. I will then discuss initial steps to translate these principles into actions, including connecting serological test analytics and developing feasibility models for implementation in pilot settings.

Affiliation: School of Biological Sciences, Georgia Institute of Technology; School of Physics, Georgia Institute of Technology
Program in Quantitative Biosciences, Georgia Institute of Technology; Associate Editor, Journal of Theoretical Biology
Senior Editor, ISME J