I am super excited to have David Lazer (1,2) on the pod today. 

David Lazer needs no introduction. But here at lazypod we’re polite, so he get’s one anyway.

David Lazer is a University Distinguished Professor of Political Science and Computer Sciences, Northeastern University, and Co-Director, NULab for Texts, Maps, and Networks. Prior to coming to Northeastern University, he was on the faculty at the Harvard Kennedy School (1998-2009). In 2019, he was elected a fellow to the National Academy of Public Administration.

His research has been published in such journals as Science, Nature, Proceedings of the National Academy of Science, the American Political Science Review, Organization Science, and the Administrative Science Quarterly, and has received extensive coverage in the media, including the New York Times, NPR, the Washington Post, the Wall Street Journal, and CBS Evening News.

He is among the leading scholars in the world on misinformation and computational social science and has served in multiple leadership and editorial positions, including as a board member for the International Network of Social Network Analysts (INSNA), reviewing editor for Science, associate editor of Social Networks and Network Science, numerous other editorial boards and program committees.

As always we talk about David path through science, with a particular emphasis on Computational Social Science (3) - a field that he has been absolutely instrumental in establishing. But we also cover many other topics in this wide-ranging converstation which ends up covering his paper “Product diffusion through on-demand information-seeking behaviour” (4) which is one of his favorite papers and least cited, and which has a super-interesting backstory.

References
(1) https://lazerlab.net
(2) https://cssh.northeastern.edu/faculty/david-lazer/
(3) https://www.science.org/doi/10.1126/science.1167742
(4) https://royalsocietypublishing.org/doi/full/10.1098/rsif.2017.0751

Holy cow, it was great to chat with Brennan Klein (1). It’s another renaissance person on the Pod.

In his research, Brennan attempts to understand how complex systems are able to represent, predict, and intervene on their surroundings across a number of different scales—all in ways that appear to maintain the statistical boundary between them and their environment.

He uses this approach to study a range of phenomena from decision making, to experimental design, to causation and emergence in networks.

Brennan is currently working with Professors Alessandro Vespignani and Sam Scarpino on a research examining the teleology of networks, or why there appears to be an apparent purpose or goal-directedness to the dynamics and structure of networks.

He received a BA in Cognitive Science and Psychology from Swarthmore College in 2014, studying the relationship between perception, action, and cognition.  I received my PhD in Network Science from Northeastern University in 2020.

Now he’s  a postdoc at the Network Science Institute, Northeastern University, he’s a senior researcher at Verses Inc (2) and he’s a Data for Justice Fellow at Institute for the Study of Policing, Incarceration, and Public Safety; The Hutchins Center for African & African American Research at a small university, Harvard.

With those two postdoc advisors, it should come as no surprise that during COVID, Brennan has a number of important COVID related publications as well.

We talk about his paper “Network comparison and the within-ensemble graph distance” (3) but there’s so much more!!

And finally Brennan makes art under the pseudonym JK Rofling (4). I urge every single one of you to go check out his art. It’s great. And I totally didn’t get to ask him about it. Because we spent so much time covering the many other exciting things Brennan has got going on.

References
(1) https://www.jkbrennan.com
(2) https://www.verses.io
(3) https://royalsocietypublishing.org/doi/10.1098/rspa.2019.0744
(4) https://www.jkrofling.com

Today we’re in for something a little bit different. Our guest is “Erik Hoel”, who’s not only a scientist, but also an exciting writer of books and essays. I read his fantastic first book “The Revelations” (1,2) last winters … and when I visited Boston this summer, I took a chance and sought him out. He graciously agreed to chat.

For this interview I traveled out to Erik’s house that’s placed down along a long gravel road and surrounded by lakes and trees on Cape Cod. And we chatted in his first floor study surrounded by a classy collection of books.

So who is Erik? This audience may know him as a research assistant professor at Tufts University in Boston. But that’s only a small part of his story. Erik grew up in his family's independent bookstore, Jabberwocky Bookshop, and this experience has stayed with him, motivating him to write books, reviews, and essays.

At college he became interested in solving the scientific problem of consciousness and ended up receiving his PhD in neuroscience at the University of Wisconsin-Madison. We spend a good chunk of time in the podcast with me learning about consciousness from Erik.

Later he was a postdoctoral researcher at Columbia University and a visiting scholar at the Institute for Advanced Study in Princeton. Alongside his academic accolades, Erik was named one of Forbes 30 Under 30 and in 2017 he was chosen as a NYC Emerging Writers Fellow for his short stories.

My interview with Erik is different from what I normally do on the Pod. We do cover his past and motivations, but I actually did read his book, and we talk about that. As well as the writing process - and the creative process - in some detail.

I also want to flag up that Erik is a great thinker and essayist. You can find his stuff on his substack “The Intrinsic Perspective” (3). I love all of his writing, but a particular favorite is his recent award-winning book review (4), which among other thing proposes a new theory for why human civilization took a while to get off the ground … and why Twitter might be taking us back to the roots. I highly recommend that you check out his writing.

References
(1) https://www.erikphoel.com
(2) https://www.amazon.com/Revelations-Novel-Erik-Hoel/dp/1419750224
(3) https://erikhoel.substack.com
(4) https://erikhoel.substack.com/p/the-gossip-trap

PS In the beginning of the podcast, we talk about how I first became aware of Erik. In case you’re interested, the whole thing is described here https://sunelehmann.com/2022/01/09/oh-twitter/

Today on the Pod we are lucky to have Laura Alessandretti (1) visiting us.

Laura is an Assistant Professor in Modelling of Human Dynamics at the Technical University of Denmark. She is interested in Computational Social Science, Data Science and Complex Networks. She studies aspects of human behavior combining analysis of large-scale datasets, analytical models and numerical simulations.

Previously, she was a PostDoctoral researcher at the Copenhagen Centre for Social Data Science and at DTU Compute. Before that, Laura got her PhD in Mathematics at City, University of London, and her Master's in Physics of Complex Systems at École normale supérieure de Lyon. She’s also doing many things to serve the scientific community, for example Laura will be the general chair (with Luca Aiello) of the IC2S2 conference in Copenhagen.

Laura is a close collaborator and a good friend of mine, so today’s podcast is a little bit different than many others. We discuss the long and winding road leading to our joint paper “The Scales of Human Mobility” (2).

The sound is a little less perfect than sometimes, but the content is top-notch, so I hope you’ll stick with it in spite of that.

References
(1) https://laura.alessandretti.com
(2) https://www.nature.com/articles/s41586-020-2909-1

Hey Everyone,

Today, we have another amazing guest. It’s Esteban Moro (1)!

Esteban is a researcher, data scientist and professor at Universidad Carlos III (UC3M) in Spain and Visiting Professor at MIT Media Lab and MIT Connection Science at IDSS. Previously, I was researcher at University of Oxford.

He is a native of Salamanca (Spain) … we talk about that … and hold a PhD in Physics.

Esteban’s work lies in the intersection of big data and computational social science, with special attention to human dynamics, collective intelligence, social networks and urban mobility in problems like viral marketing, natural disaster management, or economical segregation in cities.

Esteban is creative and exploring in his work, and has made important contributions in a number of topics, especially recently using massive datasets to understand problems like how humans communicate, how to political opinion spreads in social networks or building alternative wellbeing indexes.

His work has appeared in major journals including PNAS or Science Advances and is regularly covered by media outlets The Atlantic, The Washington Post, The Wall Street Journal, El País (Spain).

In our conversation, we talk about his career, his science, and go deep with his 2011 paper “Dynamical strength of social ties in information spreading” (2), which is not only an interesting paper … but also comes with a very nice story of how we can build communities in science by collaborating even between competing groups.

References
(1) http://estebanmoro.org
(2) https://journals.aps.org/pre/abstract/10.1103/PhysRevE.83.045102

Credits
The podcast has theme music by Waylon Thornton (and a little bit by me as well). WT's songs are "American Heart" and "Seven". Via freemusicarchive.org and licenced under CC BY-NC-SA. The podcast was funded in part by the Villum Foundation.

Today’s guest on the pod is Baruch Barzel (1).

Baruch has a wikipedia page (2), which summarizes his work very nicely. It says that he’s known for his work in the research of complex and stochastic systems, specifically on stochastic moment equations and universality in network dynamics.

Then it says: “Also a public lecturer in Israel, and presents a weekly corner on Jewish thought in Israel National Radio.” And you’ll hear it when we talk! He’s a born communicator, a great interview.

I would say that Baruch studies how network structure and dynamics impact one another. The he wants to predict how signals spread along network pathways. That he wants to uncover the network components that contribute to the system’s stability and resilience, to detectthe nodes and links that enable information to flow throughout the system. But, of course, his ultimate goal is to systematically use complex network data to understand, predict and control the observed behavior of the system he cares about.

We talk about all that in the paper that I’ve been too lazy to read: “Spatiotemporal signal propagation in complex networks” (3), we might even spill over into  “Reviving a failed network through microscopic interventions” (4).

References
(1) https://www.barzellab.com
(2) https://en.wikipedia.org/wiki/Baruch_Barzel
(3) https://www.nature.com/articles/s41567-018-0409-0
(4) https://www.nature.com/articles/s41567-021-01474-y

Credits
The podcast has theme music by Waylon Thornton (and a little bit by me as well). WT's songs are "American Heart" and "Seven". Via freemusicarchive.org and licenced under CC BY-NC-SA. The podcast was funded in part by the Villum Foundation.

Today’s guest on the pod is Piotr Sapiezynski!

Piotr (1) is an Associate Research Scientist at Northeastern University in Boston, MA.

My interview with Piotr is part two of my three part series on of algorithms & filter bubbles. And today’s is a great conversation, not to be missed. Piotr really explain the logic and strong evidence that he (& a team of collaborators) has discovered around filter bubbles. I already knew a lot of this, but my mind was still blown.

The core of Piotr’s work is auditing platforms and their algorithms for fairness and privacy.

Together with his collaborators, Piotr investigates systems that are optimized for corporate profit yet drive many aspects of our daily lives. All too often we find these systems have (possibly unintended but often predictable) side effects that bring harm to individuals and the society.

Before diving into algorithm audits he worked on analyses of behavioral data collected from smartphones to model human mobility, spread of diseases, development of relationships, and to predict life outcomes. This experience made him closely aware of and alert to the privacy risks associated with accumulation of personal data.

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References
(1) https://sapiezynski.com

Today’s guest is Aniko Hannak. But for reasons I forgot to ask her in the podcast, everyone calls her Ancsa.

Anyway, Ansca is an Assistant Professor at the computer science department of the University of Zürich (1).

Ancsa’s work investigates a variety of content serving websites such as Search Engines, Online Stores, Job Search Sites or Freelance Marketplaces.

In this quickly changing online ecosystem, companies track users' every move and feed the collected data into big data algorithms in order to match them with the most interesting, most relevant content. Since these algorithms learn on human data they are likely to pick up on social biases and unintentionally reinforce them.

In her PhD work, Ancsa created a methodology called Algorithmic Auditing which tries to uncover the potential negative impacts of large online systems.

In our conversation - we talk about her background in math, sociology, and computer science, how she was “too lazy to read” an important book, how a kind gesture from Laszlo Barabasi changed her life, and finally we go deep - exploring both the why and the how of Ancsa’s pioneering work which lead to the idea of algorithmic auditing. We end up talking about her recent paper “Understanding Inequalities in Ride Hailing Services Through Simulations” which in some ways is a reaction to the limitations of algorithmic auditing (2).

PS This is part one of a mini-series exploring the topics of algorithms & filter bubbles. Later installments will feature Piotr Sapiezynski, and Alan Mislove.

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References:
(1) http://ancsahannak.me
(2) https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7162900/

Today's guest is Rosemary Braun, an associate professor at the Department of Molecular Biosciences at Northwestern University.

Rosemary works at the interface between mathematics, statistics, physics, and biology, where she develops and applies powerful computational methods to investigate living systems at multiple scales — from the atomic level, to the gene level, to the systems level, to the tissue/organismal level, and finally to the population level.  

We talk abou her 2018 paper "Universal method for robust detection of circadian state from gene expression" (1).

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References

(1) Rosemary Braun, William L. Kath, Marta Iwanaszko, Elzbieta Kula-Eversole, Sabra M. Abbott, Kathryn J. Reid, Phyllis C. Zee, and Ravi Allada.  Universal method for robust detection of circadian state from gene expression. https://www.pnas.org/doi/10.1073/pnas.1800314115

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).
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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.