Tina Eliassi-Rad's guest appearances

Tina Eliassi-Rad

The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

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COMPLEXITY

Too Lazy to Read the Paper

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It's a new season! And LazyPod is back with a strong line-up of guests. Today on the pod, for the inaugural episode of season 2, is Tina Eliassi-Rad. Tina is an incredibly accomplished scientist. She is a Professor of Computer Science at Northeastern University. She is also a core faculty member at Northeastern's Network Science Institute and the Institute for Experiential AI. In addition, she is an external faculty member at the Santa Fe Institute and the Vermont Complex Systems Center. Her research is at the intersection of data mining, machine learning, and network science. She has over 100 peer-reviewed publications (including a few best paper and best paper runner-up awards); and has given over 200 invited talks and 14 tutorials. Tina's work has been applied to personalized search on the World-Wide Web, statistical indices of large-scale scientific simulation data, fraud detection, mobile ad targeting, cyber situational awareness, drug discovery, democracy and online discourse, and ethics in machine learning.Tina received an Outstanding Mentor Award from the U.S. Department of Energy's Office of Science in 2010, became an ISI Foundation Fellow in 2019, was named one of the 100 Brilliant Women in AI Ethics in 2021, and received Northeastern University's Excellence in Research and Creative Activity Award in 2022.In this wide-ranging conversation, we talk about Tina's life, career and her paper "The Why, How, and When of Representations for Complex Systems" (1).---References:(1) Leo Torres, Ann Sizemore Blevins, Danielle S. Bassett, Tina Eliassi-Rad. The Why, How, and When of Representations for Complex Systems. SIAM Review (SIREV), 63(3): 435-485, 2021.

It's a new season! And LazyPod is back with a strong line-up of guests. Today on the pod, for the inaugural episode of season 2, is Tina Eliassi-Rad. Tina is an incredibly accomplished scientist. She is a Professor of Computer Science at Northeastern University. She is also a core faculty member at Northeastern's Network Science Institute and the Institute for Experiential AI. In addition, she is an external faculty member at the Santa Fe Institute and the Vermont Complex Systems Center. Her research is at the intersection of data mining, machine learning, and network science. She has over 100 peer-reviewed publications (including a few best paper and best paper runner-up awards); and has given over 200 invited talks and 14 tutorials. Tina's work has been applied to personalized search on the World-Wide Web, statistical indices of large-scale scientific simulation data, fraud detection, mobile ad targeting, cyber situational awareness, drug discovery, democracy and online discourse, and ethics in machine learning. Tina received an Outstanding Mentor Award from the U.S. Department of Energy's Office of Science in 2010, became an ISI Foundation Fellow in 2019, was named one of the 100 Brilliant Women in AI Ethics in 2021, and received Northeastern University's Excellence in Research and Creative Activity Award in 2022. In this wide-ranging conversation, we talk about Tina's life, career and her paper "The Why, How, and When of Representations for Complex Systems" (1). --- References: (1) Leo Torres, Ann Sizemore Blevins, Danielle S. Bassett, Tina Eliassi-Rad. <a href="https://epubs.siam.org/doi/pdf/10.1137/20M1355896" rel="nofollow" target="_blank">The Why, How, and When of Representations for Complex Systems</a>. SIAM Review (SIREV), 63(3): 435-485, 2021.

Tina Eliassi-Rad - Dark Side of the Moon

Today we continue our NeurIPS coverage joined by Tina Eliassi-Rad, a professor at Northeastern University, and an invited speaker at the I Still Can't Believe It's Not Better! Workshop. In our conversation with Tina, we explore her research at the intersection of network science, complex networks, and machine learning, how graphs are used in her work and how it differs from typical graph machine learning use cases. We also discuss her talk from the workshop, “The Why, How, and When of Representations for Complex Systems”, in which Tina argues that one of the reasons practitioners have struggled to model complex systems is because of the lack of connection to the data sourcing and generation process. This is definitely a NERD ALERT approved interview!The complete show notes for this episode can be found at twimlai.com/go/547

Today we continue our NeurIPS coverage joined by Tina Eliassi-Rad, a professor at Northeastern University, and an invited speaker at the <a href="https://i-cant-believe-its-not-better.github.io/neurips2021/" rel="nofollow" target="_blank">I Still Can't Believe It's Not Better! Workshop</a>. In our conversation with Tina, we explore her research at the intersection of network science, complex networks, and machine learning, how graphs are used in her work and how it differs from typical graph machine learning use cases. We also discuss her talk from the workshop, “The Why, How, and When of Representations for Complex Systems”, in which Tina argues that one of the reasons practitioners have struggled to model complex systems is because of the lack of connection to the data sourcing and generation process. This is definitely a NERD ALERT approved interview! The complete show notes for this episode can be found at <a href="twimlai.com/go/547" rel="nofollow" target="_blank">twimlai.com/go/547</a>

Hypergraphs, Simplicial Complexes and Graph Representations of Complex Systems with Tina Eliassi-Rad - #547

Democracy is a quintessential complex system: citizens’ decisions shape each other’s in nonlinear and often unpredictable ways; the emergent institutions exert top-down regulation on the individuals and orgs that live together in a polity; feedback loops and tipping points abound. And so perhaps it comes as no surprise in our times of turbulence and risk that democratic processes are under extraordinary pressure from the unanticipated influences of digital communications media, rapidly evolving economic forces, and the algorithms we’ve let loose into society.In a new special feature at PNAS co-edited by SFI Science Board Member Simon Levin, fifteen international research teams map the jeopardy faced by democracies today — as Levin and the other editors write in their introduction to the issue, “the loss of diversity associated with polarization undermines cooperation and the ability of societies to provide the public goods that make for a healthy society.” And yet humankind has never been more well-equipped to understand the problems that we face. What can complex systems science teach us about this century’s threats to democracy, and how to mitigate or sidestep them? How might democracy itself transform as it adapts to our brave new world of extremist partisanship, exponential change, and epistemic crisis?Welcome to COMPLEXITY, the official podcast of the Santa Fe Institute. I’m your host, Michael Garfield, and every other week we’ll bring you with us for far-ranging conversations with our worldwide network of rigorous researchers developing new frameworks to explain the deepest mysteries of the universe.This week on Complexity, we speak with SFI External Professor Tina Eliassi-Rad, Professor of Computer Science at Northeastern University, about her complex systems research on democracy, what forces stabilize or upset democratic process, and how to rigorously study the relationships between technology and social change.If you value our research and communication efforts, please subscribe to Complexity Podcast wherever you prefer to listen, rate and review us at Apple Podcasts, and/or consider making a donation at santafe.edu/give. Please also be aware of our new SFI Press book, The Complex Alternative, which gathers over 60 complex systems research points of view on COVID-19 (including those from this show) — and that PhD students are now welcome to apply for our tuitionless (!) Summer 2022 SFI GAINS residential program in Vienna. Learn more at SFIPress.org and SantaFe.edu/Gains, respectively. Thank you for listening!Join our Facebook discussion group to meet like minds and talk about each episode.Podcast theme music by Mitch Mignano.Follow us on social media:Twitter • YouTube • Facebook • Instagram • LinkedInRelated Reading &amp; Listening:Tina’s Website &amp; Google Scholar Page“What science can do for democracy: a complexity science approach”Tina Eliassi-Rad, Henry Farrell, David Garcia, Stephan Lewandowsky, Patricia Palacios, Don Ross, Didier Sornette, Karim Thébault &amp; Karoline Wiesner“Stability of democracies: a complex systems perspective”K Wiesner, A Birdi, T Eliassi-Rad, H Farrell, D Garcia, S Lewandowsky, P Palacios, D Ross, D Sornette and K Thébault“Measuring algorithmically infused societies”Claudia Wagner, Markus Strohmaier, Alexandra Olteanu, Emre Kıcıman, Noshir Contractor &amp; Tina Eliassi-Rad1 - David Krakauer on The Landscape of 21st Century Science7 - Rajiv Sethi on Stereotypes, Crime, and The Pursuit of Justice35 - Scaling Laws &amp; Social Networks in The Time of COVID-19 with Geoffrey West38 - Fighing Hate Speech with AI &amp; Social Science (Garland, Galesic, Olsson)43 - Vicky Yang &amp; Henrik Olsson on Political Polling &amp; Polarization: How We Make Decisions &amp; Identities51 - Cris Moore on Algorithmic Justice and The Physics of Inference“Stewardship of global collective behavior” - Joe Bak-Coleman et al.Michelle Girvan - Harnessing Chaos &amp; Predicting The Unpredictable with A.I.Transmission T-015: Anthony Eagan on Federalism in the time of pandemicTransmission T-031: Melanie Moses and Kathy Powers on models that protect the vulnerableAlso Mentioned:Simon DeDeoElizabeth HobsonDanielle AllenAlexander De TocquevilleStewart BrandSafiya NobleFilippo MenczerJessica FlackRajeev GandhiScott AdamsDavid Brin

Democracy is a quintessential complex system: citizens’ decisions shape each other’s in nonlinear and often unpredictable ways; the emergent institutions exert top-down regulation on the individuals and orgs that live together in a polity; feedback loops and tipping points abound. And so perhaps it comes as no surprise in our times of turbulence and risk that democratic processes are under extraordinary pressure from the unanticipated influences of digital communications media, rapidly evolving economic forces, and the algorithms we’ve let loose into society.In <a href="https://phys.org/news/2021-12-natural-democracy-collapse-polarization-loss.html" rel="nofollow" target="_blank">a new special feature at PNAS co-edited by SFI Science Board Member Simon Levin</a>, fifteen international research teams map the jeopardy faced by democracies today — as Levin and the other editors write in their introduction to the issue, “the loss of diversity associated with polarization undermines cooperation and the ability of societies to provide the public goods that make for a healthy society.” And yet humankind has never been more well-equipped to understand the problems that we face. What can complex systems science teach us about this century’s threats to democracy, and how to mitigate or sidestep them? How might democracy itself transform as it adapts to our brave new world of extremist partisanship, exponential change, and epistemic crisis?Welcome to COMPLEXITY, the official podcast of the Santa Fe Institute. I’m your host, <a href="https://www.santafe.edu/people/profile/michael-garfield" rel="nofollow" target="_blank">Michael Garfield</a>, and every other week we’ll bring you with us for far-ranging conversations with our worldwide network of rigorous researchers developing new frameworks to explain the deepest mysteries of the universe.This week on Complexity, we speak with SFI External Professor Tina Eliassi-Rad, Professor of Computer Science at Northeastern University, about her complex systems research on democracy, what forces stabilize or upset democratic process, and how to rigorously study the relationships between technology and social change.If you value our research and communication efforts, please subscribe to Complexity Podcast wherever you prefer to listen, rate and review us at <a href="https://podcasts.apple.com/us/podcast/complexity/id1482984603" rel="nofollow" target="_blank">Apple Podcasts</a>, and/or consider making a donation at <a href="http://santafe.edu/give" rel="nofollow" target="_blank">santafe.edu/give</a>. Please also be aware of our new SFI Press book, <a href="https://www.sfipress.org/books/the-complex-alternative" rel="nofollow" target="_blank">The Complex Alternative</a>, which gathers over 60 complex systems research points of view on COVID-19 (including those from this show) — and that PhD students are now welcome to apply for our tuitionless (!) Summer 2022 SFI GAINS residential program in Vienna. Learn more at <a href="http://SFIPress.org" rel="nofollow" target="_blank">SFIPress.org</a> and <a href="http://SantaFe.edu/Gains" rel="nofollow" target="_blank">SantaFe.edu/Gains</a>, respectively. Thank you for listening!<a href="https://facebook.com/groups/santafeinstitute" rel="nofollow" target="_blank">Join our Facebook discussion group</a> to meet like minds and talk about each episode.Podcast theme music by <a href="https://deathlessmusic.bandcamp.com/releases" rel="nofollow" target="_blank">Mitch Mignano</a>.Follow us on social media: <a href="http://twitter.com/sfiscience" rel="nofollow" target="_blank">Twitter</a> • <a href="http://youtube.com/c/sfiscience" rel="nofollow" target="_blank">YouTube</a> • <a href="http://facebook.com/santafeinstitute" rel="nofollow" target="_blank">Facebook</a> • <a href="http://instagram.com/sfiscience" rel="nofollow" target="_blank">Instagram</a> • <a href="https://linkedin.com/company/20131/" rel="nofollow" target="_blank">LinkedIn</a>Related Reading &amp; Listening:Tina’s <a href="http://eliassi.org/" rel="nofollow" target="_blank">Website</a> &amp; <a href="https://scholar.google.com/citations?user=TXb5Ym8AAAAJ&amp;hl=en" rel="nofollow" target="_blank">Google Scholar Page</a>“<a href="https://www.nature.com/articles/s41599-020-0518-0.epdf" rel="nofollow" target="_blank">What science can do for democracy: a complexity science approach</a>” Tina Eliassi-Rad, Henry Farrell, David Garcia, Stephan Lewandowsky, Patricia Palacios, Don Ross, Didier Sornette, Karim Thébault &amp; Karoline Wiesner“<a href="https://iopscience.iop.org/article/10.1088/1361-6404/aaeb4d/meta" rel="nofollow" target="_blank">Stability of democracies: a complex systems perspective</a>” K Wiesner, A Birdi, T Eliassi-Rad, H Farrell, D Garcia, S Lewandowsky, P Palacios, D Ross, D Sornette and K Thébault“<a href="http://www.eliassi.org/papers/nature-measuring-algorithmically-infused-societies.pdf" rel="nofollow" target="_blank">Measuring algorithmically infused societies</a>” Claudia Wagner, Markus Strohmaier, Alexandra Olteanu, Emre Kıcıman, Noshir Contractor &amp; Tina Eliassi-Rad<a href="https://complexity.simplecast.com/episodes/1" rel="nofollow" target="_blank">1 - David Krakauer on The Landscape of 21st Century Science</a> <a href="https://complexity.simplecast.com/episodes/7" rel="nofollow" target="_blank">7 - Rajiv Sethi on Stereotypes, Crime, and The Pursuit of Justice</a> <a href="https://complexity.simplecast.com/episodes/35" rel="nofollow" target="_blank">35 - Scaling Laws &amp; Social Networks in The Time of COVID-19 with Geoffrey West</a> <a href="https://complexity.simplecast.com/episodes/38" rel="nofollow" target="_blank">38 - Fighing Hate Speech with AI &amp; Social Science (Garland, Galesic, Olsson)</a> <a href="https://complexity.simplecast.com/episodes/43" rel="nofollow" target="_blank">43 - Vicky Yang &amp; Henrik Olsson on Political Polling &amp; Polarization: How We Make Decisions &amp; Identities</a> <a href="https://complexity.simplecast.com/episodes/51" rel="nofollow" target="_blank">51 - Cris Moore on Algorithmic Justice and The Physics of Inference</a><a href="https://www.pnas.org/content/118/27/e2025764118" rel="nofollow" target="_blank">“Stewardship of global collective behavior” - Joe Bak-Coleman et al.</a><a href="https://www.youtube.com/watch?v=MLNtHK0-DEw" rel="nofollow" target="_blank">Michelle Girvan - Harnessing Chaos &amp; Predicting The Unpredictable with A.I.</a> <a href="https://santafe.edu/news-center/news/transmission-t-015-anthony-eagan-federalism-time-pandemic#Reflection" rel="nofollow" target="_blank">Transmission T-015: Anthony Eagan on Federalism in the time of pandemic</a> <a href="https://santafe.edu/news-center/news/transmission-t-031-melanie-moses-and-kathy-powers-models-protect-vulnerable#Reflection" rel="nofollow" target="_blank">Transmission T-031: Melanie Moses and Kathy Powers on models that protect the vulnerable</a>Also Mentioned:Simon DeDeo Elizabeth Hobson Danielle Allen Alexander De Tocqueville Stewart Brand Safiya Noble Filippo Menczer Jessica Flack Rajeev Gandhi Scott Adams David Brin

Tina Eliassi-Rad on Democracies as Complex Systems

Professor Tina Eliassi-Rad of Northeastern's Network Science Institute talks with Michael and Dave about topics ranging from graph structures and machine learning to AI ethics and the nature of democracy. [Title image courtesy of Tina Eliassi-Rad]

Professor <a href="Tina%20Eliassi-Rad" rel="noopener nofollow" target="_blank">Tina Eliassi-Rad</a> of Northeastern's Network Science Institute talks with Michael and Dave about topics ranging from graph structures and machine learning to AI ethics and the nature of democracy. [Title image courtesy of Tina Eliassi-Rad]