I am looking for Ph.D. students with strong quantitative background and programming skills with interests around:
- Studying and predicting scientific innovation with AI-based methods.
- Quantifying how humans extend their capabilities with technology in ecologically-plausible sequential decisions.
- Applying AI-based methods to automatically summarize scientific results from large-scale scientific corpora
The methods and techniques used in my research include:
- Big data Machine Learning with Apache Spark including bagging and boosting
- Deep learning with Tensorflow
- Bayesian statistics
- Python, R, Hadoop, and SQL.