franck.dernoncourt@gmail.com
Skype: franck.dernoncourt
MIT, Cambridge, USA

profile for Franck Dernoncourt on Stack Exchange, a network of free, community-driven Q&A sites

Research statement

I am pursuing a PhD in computer science & artificial intelligence at MIT where I currently work on genetic programming.

My research focuses on artificial intelligence (AI). My former project aimed at building conversational agents for serious games. It will mostly make use of semantics, ontology, natural language processing and knowledge engineering.

My previous work dealt with evolutionary algorithms, artificial neural networks, robotics and neuroscience. I built a computational neuroscience model of the medial reticular formation, a part of the brain which is involved in low-level decision making, using artificial neural networks optimized by evolutionary algorithms. I evaluated this model as a virtual mobile robot controller. The report is available here.

My earlier projects focused on fuzzy logic. First, I analyzed to what extent this non-standard logic could explain many experiments that had undermined traditional models of human reasoning in the 20th century. Then, I conducted my own experiment to investigate whether a fuzzy decision-making system could mimic the decisions made by humans. Eventually, I studied the potential applications for databases and decision support systems.


Although AI refers to a vast field of computer science, I strongly believe that having a good background of every subfield in AI is essential for any AI researcher, so as to be able to communicate more efficiently with other AI researchers as well as to select theoretical tools more acuminously when dealing with a new problem. Expertise in one subfield should not excessively overshadow the others.

My CV is available here.

Here is a list of the competences in AI I have developed during my past and current researches. I have obviously not developed an expertise in each of these fields, but I have at least a good background of them:
  1. Fuzzy logic

  2. Evolutionary computation

  3. Neural networks

  4. Computational neuroscience

  5. Semantics

  6. Ontology

  7. Natural language processing

  8. Knowledge representation