Shows / Data Skeptic
Data Skeptic
The Data Skeptic Podcast features interviews and discussion of topics related to data science, statistics, machine learning, artificial intelligence and the like, all from the perspective of applying critical thinking and the scientific method to evaluate the veracity of claims and efficacy of approaches.
Episodes
Data SkepticTastePrint
What if we could 3D print food with customized flavors and textures? Yamato Miyatake joins us to explore how digital food fabrication, human-computer…
Data SkepticGestures Around the Ear
The next evolution of wearable technology may not require new screens or controllers, but new ways to interact with the devices we already wear. Shimon…
Data SkepticImplicit Interactions
How do we design robots and autonomous vehicles that understand the unwritten rules of human behavior? Kyle speaks with Cornell Tech professor Wendy Ju about…
Data SkepticThe Lived Informatics Model
The data we collect about ourselves can tell us a lot—but only if the technology collecting it actually fits into our lives. Daniel Epstein explores personal…
Data SkepticRecommender Systems Today and Tomorrow
In the final episode of our Recommender Systems season, we explore the growing questions of trust, manipulation, privacy, fairness, sustainability, and user…
Data SkepticRecommender Systems Optimization Goals
In part two of the Data Skeptic Recommender Systems season finale, Kyle asks a deceptively difficult question: what should recommender systems actually…
Data SkepticRecommender Systems Origin Story
Where did recommender systems come from, and how do we know when they're actually working? In part one of Data Skeptic's three-part Recommender Systems finale…
Data SkepticSocial Choice for Fair Recommendations
Recommender systems influence nearly every aspect of our digital lives—but what does it mean for those systems to be fair? Robin Burke joins Data Skeptic to…
Data SkepticNews Recommendations
News recommendation algorithms influence far more than what stories we click—they can shape our understanding of the world. In this episode, Kyle Polich speaks…
Data SkepticGive Users the Wheel
What if you could simply tell a recommendation system what you want instead of relying on likes, dislikes, and watch history? Kyle Polich talks with Fuyuan Lyu…
Data SkepticAutoLike
How can researchers audit recommendation systems when the algorithms are hidden from view? Hieu Le joins Kyle Polich to discuss Auto-Like, a reinforcement…
Data SkepticStudent Spotlight: Aaron Payne, Data Analyst
Aaron Payne, an MBA student at Georgia Tech studying business analytics and a Senior Insights Analyst at Chick-fil-A, joins Kyle Polich to talk about turning…
Data SkepticThe Future is Agentic in Recommender Systems
Kyle Polich sits down with Yashar Deldjoo, research scientist and Associate Professor at the Polytechnic University of Bari, to explore how recommender systems…
Data SkepticBook Ratings and Recommendations
Goodreads star ratings can be misleading as measures of "book quality," and research from Hannes Rosenbusch suggests that for many professionally published…
Data SkepticDisentanglement and Interpretability in Recommender Systems
Ervin Dervishaj, a PhD student at the University of Copenhagen, discusses his research on disentangled representation learning in recommender systems, finding…
Data SkepticCollective Altruism in Recommender Systems
Ekaterina (Kat) Fedorova from MIT EECS joins us to discuss strategic learning in recommender systems—what happens when users collectively coordinate to game…
Data SkepticNiche vs Mainstream
Anas Buhayh discusses multi-stakeholder fairness in recommender systems and the S'mores framework—a simulation allowing users to choose between mainstream and…
Data SkepticHealthy Friction in Job Recommender Systems
In this episode, host Kyle Polich speaks with Roan Schellingerhout, a fourth-year PhD student at Maastricht University, about explainable multi-stakeholder…
Data SkepticFairness in PCA-Based Recommenders
In this episode, we explore the fascinating world of recommender systems and algorithmic fairness with David Liu, Assistant Research Professor at Cornell…
Data SkepticVideo Recommendations in Industry
In this episode, Kyle Polich sits down with Cory Zechmann, a content curator working in streaming television with 16 years of experience running the music blog…
Data SkepticEye Tracking in Recommender Systems
In this episode, Santiago de Leon takes us deep into the world of eye tracking and its revolutionary applications in recommender systems. As a researcher at…
Data SkepticCracking the Cold Start Problem
In this episode of Data Skeptic, we dive deep into the technical foundations of building modern recommender systems. Unlike traditional machine learning…
Data SkepticDesigning Recommender Systems for Digital Humanities
In this episode of Data Skeptic, we explore the fascinating intersection of recommender systems and digital humanities with guest Florian…
Data SkepticDataRec Library for Reproducible in Recommend Systems
In this episode of Data Skeptic's Recommender Systems series, host Kyle Polich explores DataRec, a new Python library designed to bring reproducibility and…
Data SkepticShilling Attacks on Recommender Systems
In this episode of Data Skeptic's Recommender Systems series, Kyle sits down with Aditya Chichani, a senior machine learning engineer at Walmart, to explore…
Data SkepticMusic Playlist Recommendations
In this episode, Rebecca Salganik, a PhD student at the University of Rochester with a background in vocal performance and composition, discusses her research…
Data SkepticSustainable Recommender Systems for Tourism
In this episode, we speak with Ashmi Banerjee, a doctoral candidate at the Technical University of Munich, about her pioneering research on AI-powered…
Data SkepticInterpretable Real Estate Recommendations
In this episode of Data Skeptic's Recommender Systems series, host Kyle Polich interviews Dr. Kunal Mukherjee, a postdoctoral research associate at Virginia…
Data SkepticWhy Am I Seeing This?
In this episode of Data Skeptic, we explore the challenges of studying social media recommender systems when exposure data isn't accessible. Our guests Sabrina…
Data SkepticEco-aware GNN Recommenders
In this episode of Data Skeptic, we dive into eco-friendly AI with Antonio Purificato, a PhD student from Sapienza University of Rome. Antonio discusses his…
Data SkepticNetworks and Recommender Systems
Kyle reveals the next season's topic will be "Recommender Systems". Asaf shares insights on how network science contributes to the recommender system field.
Data SkepticNetwork of Past Guests Collaborations
Kyle and Asaf discuss a project in which we link former guests of the podcast based on their co-authorship of academic papers.
Data SkepticThe Network Diversion Problem
In this episode, Professor Pål Grønås Drange from the University of Bergen, introduces the field of Parameterized Complexity - a powerful framework for…
Data SkepticComplex Dynamic in Networks
In this episode, we learn why simply analyzing the structure of a network is not enough, and how the dynamics - the actual mechanisms of interaction between…
Data SkepticGithub Network Analysis
In this episode we'll discuss how to use Github data as a network to extract insights about teamwork. Our guest, Gabriel Ramirez, manager of the notifications…
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Networks and Complexity
In this episode, Kyle does an overview of the intersection of graph theory and computational complexity theory. In complexity theory, we are about the runtime…
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Graphs for Causal AI
How to build artificial intelligence systems that understand cause and effect, moving beyond simple correlations? As we all know, correlation is not causation…
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Network Manipulation
In this episode we talk with Manita Pote, a PhD student at Indiana University Bloomington, specializing in online trust and safety, with a focus on detecting…
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The Small World Hypothesis
Kyle discusses the history and proof for the small world hypothesis.
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Thinking in Networks
Kyle asks Asaf questions about the new network science course he is now teaching. The conversation delves into topics such as contact tracing, tools for…
Data SkepticFraud Networks
In this episode we talk with Bavo DC Campo, a data scientist and statistician, who shares his expertise on the intersection of actuarial science, fraud…
Data SkepticCriminal Networks
In this episode we talk with Justin Wang Ngai Yeung, a PhD candidate at the Network Science Institute at Northeastern University in London, who explores how…
Data SkepticGraph Bugs
In this episode today's guest is Celine Wüst, a master's student at ETH Zurich specializing in secure and reliable systems, shares her work on automated…
Data SkepticOrganizational Network Analysis
In this episode, Gabriel Petrescu, an organizational network analyst, discusses how network science can provide deep insights into organizational structures…
Data SkepticOrganizational Networks
Is it better to have your work team fully connected or sparsely connected? In this episode we'll try to answer this question and more with our guest Hiroki…
Data SkepticNetworks of the Mind
A man goes into a bar… This is the beginning of a riddle that our guest, Yoed Kennet, an assistant professor at the Technion's Faculty of Data and Decision…
Data SkepticLLMs and Graphs Synergy
In this episode, Garima Agrawal, a senior researcher and AI consultant, brings her years of experience in data science and artificial intelligence. Listeners…
Data SkepticA Network of Networks
In this episode, Bnaya Gross, a Fulbright postdoctoral fellow at the Center for Complex Network Research at Northwestern University, explores the…
Data SkepticAuditing LLMs and Twitter
Our guests, Erwan Le Merrer and Gilles Tredan, are long-time collaborators in graph theory and distributed systems. They share their expertise on applying…
Data SkepticFraud Detection with Graphs
In this episode, Šimon Mandlík, a PhD candidate at the Czech Technical University will talk with us about leveraging machine learning and graph-based…
Data SkepticOptimizing Supply Chains with GNN
Thibaut Vidal, a professor at Polytechnique Montreal, specializes in leveraging advanced algorithms and machine learning to optimize supply chain operations…
Data SkepticThe Mystery Behind Large Graphs
Our guest in this episode is David Tench, a Grace Hopper postdoctoral fellow at Lawrence Berkeley National Labs, who specializes in scalable graph algorithms…
Data SkepticCustomizing a Graph Solution
In this episode, Dave Bechberger, principal Graph Architect at AWS and author of "Graph Databases in Action", brings deep insights into the field of graph…
Data SkepticGraph Transformations
In this episode, Adam Machowczyk, a PhD student at the University of Leicester, specializes in graph rewriting and its intersection with machine learning…
Data SkepticNetworks for AB Testing
In this episode, the data scientist Wentao Su shares his experience in AB testing on social media platforms like LinkedIn and TikTok. We talk about how network…
Data SkepticLessons from eGamer Networks
Alex Bisberg, a PhD candidate at the University of Southern California, specializes in network science and game analytics, with a focus on understanding social…
Data SkepticGithub Collaboration Network
In this episode we discuss the GitHub Collaboration Network with Behnaz Moradi-Jamei, assistant professor at James Madison University. As a network scientist…