Bachelor’s thesis introducing PyConversations, an open-source library that normalizes over 308 million posts from Twitter, Reddit, Facebook, and 4chan into a unified data model for cross-platform social media research.

Key dimensions that have helped me understand multi-arm bandit problems: action space, problem structure, external information, reward mechanism, and learner feedback.

We introduce NewsTweet, a dataset and pipeline for studying embedded tweets in digital journalism, revealing that 13% of Google News articles incorporate tweets and providing insights into how social media becomes newsworthy.

We developed high-frequency monitoring tools to detect coordinated manipulation on Twitter, documenting anomalous follower patterns including sub-second spikes, sawtooth waves, circulating accounts, and weaponized ancient dormant accounts targeting political figures.

We present an unsupervised algorithm for inducing semantic networks from Wiktionary’s crowd-sourced data, creating a WordNet-like resource an order of magnitude larger than Princeton WordNet with over 344,000 linked example sentences.

Discover how NEAT and HyperNEAT changed neuroevolution by automatically designing neural network architectures and scaling them through geometric patterns.

Understand the pattern recognition behind Netflix recommendations, email spam filters, and game-playing AI through three core machine learning approaches.

Explore the building blocks of classic AI reasoning, from knowledge bases and logic to how systems draw new conclusions from existing knowledge.

A sophomore year exploration of evolutionary algorithms applied to Atari games, implementing NEAT-inspired speciation mechanisms for Cartesian Genetic Programming to protect topological innovation while introducing custom crossover operators (subgraph, aligned-node) for evolving neural network policies.

QuAC introduces a conversational QA dataset that models student-teacher interactions, creating context-dependent questions that test systems’ ability to understand dialogue and resolve references.

CoQA extends question answering beyond isolated questions to conversations that require context and reference understanding.

An in-depth guide to GANs: how two neural networks compete to generate realistic data, the math behind it, and the evolution of objective functions that stabilize training.