Ad-tech

Online ads don’t just appear — they’re chosen through rapid-fire auctions, behavioral tracking, and complex optimization algorithms. These episodes reveal the machinery behind digital advertising, from attribution modeling to audience segmentation, while also confronting the ethical dilemmas posed by pervasive surveillance and data misuse. It’s a look at a high-stakes ecosystem where every click is measured, modeled, and monetized.

Episodes

Crowdfunded Board Games — It may be intuitive to think crowdfunding a project drives its innovation and novelty, but there are no empirical studies that prove this. On the show, Johannes Wachs shares his research that sought t
Russian Election Interference Effectiveness — There were reports of Russia’s interference in the 2016 US elections. In today’s episode, Koustuv Saha, a researcher at Microsoft Research walks us through the effect of targeted ads for political cam
Placement Laundering Fraud — There is an unsung kind of ad fraud brewing in the ad tech space — placement laundering fraud. On the show, Jeff Kline discusses what placement laundering fraud is, how it can be identified, and possi
Data Clean Rooms — Bosko Milekic, the Co-founder of Optable, a data collaboration platform for the media and advertising industry, joins us today. Bosko talked about the clean rooms, the technology driving data privacy
Dark Patterns in Site Design — Kerstin Bongard-Blanchy is a Research Associate at the University of Luxembourg. She joins us to discuss her study that investigated dark patterns in web designs. She discussed the results, the effect
Internet Advertising Bureau Media Lab — We are joined by Anthony Katsur, the CEO of IAB Tech Lab. Anthony discusses standards within the ad tech industry. He explained how IAB Tech Lab set and propagates global standards, actions to ensure
Your Mouse Reveals Your Gender and Age — When we navigate a webpage, it is fairly easy for our mouse movement to be tracked and collected. Today, Luis Leiva, a Professor of Computer Science discusses how these mouse tracking data can be used
StrategyQA and Big Bench — Did Aristotle Use a Laptop? That's a question from the StrategyQA benchmark which highlights the stretch goals for current artificial intelligence systems. Answering a question like that requires seve
Ad Blockers Effect on News Consumption — While at first glance, the use of ad blockers drops the revenue of news publishers, this may not be completely true. On the show today, Shunyao Yan, an Assistant Professor in Marketing at Leavey Schoo
Your Consent is Worth 75 Euros a Year — People who do not want their data tracked and shared online can pay a token for a cookie paywall. But are the websites keeping to their side of the bargain? Victor Morel, a Postdoc candidate at the Ch
Automated Email Generation for Targeted Attacks — The advancement of generative language models has been a force for good, but also for evil. On the show, Avisha Das, a post-doctoral scholar at the University of Texas Health Center, joins us to discu
Tribal Marketing — Peter Gloor, a Research Scientist at the MIT Center for Collective Intelligence, takes us on a new world of tribe classification. He extensively discussed the need for such classification on the inter
Debiasing GPT-3 Job Ads — We hear about the impeccable achievements of GPT-3 models, but such large generative models come with their bias. On the show today, Conrad Borchers, a Ph.D. student in Human-Computer Interaction, joi
ML Ops in Production — Moses Guttman from Clear ML joins us to share insights about how organizations leveraging machine learning keep their programs on track. While many parallels exist between the software development lif
Ad Network Tomography — Data sharing in the ad tech space has largely been a black box system. While it is obvious the data is being collected, the data sharing process is obscure to users. On the show today, Maaz Bin Musa a
First Party Tracking Cookies — When you accept cookies on a website, you cannot tell whether the cookies are used for tracking your personal data or not. Shaoor Munir’s machine learning model does that. On the show today, the Ph.D
The Harms of Targeted Weight Loss Ads — Liza Gak, a Ph.D. student at UC Berkeley, joins us to discuss her research on harmful weight loss advertising. She discussed how weight loss ads are not fact-checked, and how they typically target the
Podcast Advertising — Growing your podcast to the point of monetization is not a walk in the park. Today, Rob Walch, the VP of Podcast Relations at Libsyn talks about podcast advertising. He discussed how advertising works
Fairness in e-Commerce Search — When we search for products in e-commerce stores, we do not care what goes on under the hood to generate the results. However, there may be an intentional algorithmic effort to gravitate us toward a p
Fraudulent Amazon Reviewers — Chances are that you have bought a product online majorly because of the reviews you saw. Unfortunately, not all reviews are genuine. Today, Rajvardhan Oak shares some insight from his research on fra
Ad Targeting in Amazon Smart Speakers — While we give attention to textual data on the web, many do not know the unique power of echo interactions with smart devices for ad targeting. Today, our guest, Umar Iqbal joins us to discuss his stu
Adwords with Unknown Budgets — Rajan Udwani, an Assistant Professor at the University of California Berkeley joins us to discuss his work on AdWords with unknown budgets. He discussed the previous approaches to ad allocation, as we
Affiliate Marketing Rabbithole — Affiliate marketing creates an opportunity for marketers to gain a commission by promoting a product or service. Cookies are typically used for tracking and the advertiser whose product or service is
Monetization of Youtube Conspiracy Theorists — Cameron Ballard joins us today to discuss his work around YouTube conspiracy theories. He revealed interesting observations about conspiracy theories on YouTube including how predatory ads are most co
User Perceptions of Problematic Ads — Eric Zeng joins us to discuss his study around understanding bad ads and efforts that can be taken to limit bad ads online. He discussed how he and his co authors scrapped a large amount of ad data, a
Political Digital Advertising Analysis — NaLette Brodnax, a political scientist and an Assistant Professor in the McCourt School of Public Policy at Georgetown University joins us to discuss her work on analyzing digital advertisements for p
Privacy Preference Signals — Have you ever wondered what goes on under the hood when you accept a website’s cookies? Today, Maximilian Hils, a PhD student in Computer Science, at the University of Innsbruck, Austria, dissects the
Neural Architecture Search for CTR Prediction — Ravi Krishna joins us today to talk about his recent work on a differentiable NAS framework for ads CTR prediction. He discussed what CTR prediction is about and why his NAS framework helps in buildin
Algorithmic PPC Management — Effectively managing a large budget of pay per click advertising demands software solutions. When spending multi-million dollar budgets on hundreds of thousands of keywords, an effective algorithmic s
Data Skeptic: Ad Tech — Increasingly, people get most if not all of the information they consume online. Alongside the web sites, videos, apps, and other destinations, we’re consistently served advertisements alongside the o
ML Ops — Kyle met up with Damian Brady at MS Ignite 2019 to discuss machine learning operations.

Ad-tech