Invited Talks

FTC Open Meeting on Rulemaking against Incentivized Reviews (2022)

I was invited to present my work on underground review services and their operations at the Federal Trade Commissions meeting on proposed rulemaking against fraudulent and incentivized reviews. See my full public comment here: Comment on Fake Reviews

Talk on Fraudulent Reviews at FakeSpot (2022)

Trusted by over a million customers, Fakespot protects consumers while saving them both time and money by using AI to detect fraudulent product reviews and third-party sellers in real-time. I was invited to present my research on fraudulent reviews and their detection with machine learning and statistical analysis.

Workshop on Phishing at the NSF Cyber Security Summit (2020)

I delivered a half-day workshop on phishing tactics and training methodologies at the NSF Cyber Security Summit 2020. The event was attended by students, professors and researchers working towards accessible and affordable solutions for cyber security solutions. In the workshop, I covered phishing goals and tactics. I also presented a tutorial on phishing training with the tool called GoPhish.

Keynote Session on Adversarial ML at TrustedCI Summit (2020)

I delivered a 30 minute talk on adversarial machine learning at the Trusted CI summit 2020 in San Diego. I presented fundamentals of adversarial machine learning, generative adversarial networks, adversarial attacks and their implications on real world systems.

Workshop on Security with Machine Learning at NSF Cyber Security Summit (2022)

I conducted a half-day workshop on machine learning modelling for cyber security. The workshop was attended by Ph.D. students and professors from across the US. Topics covered included deep fake detection, anomaly detection, adversarial machine learning, transformers and GANs.

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