Recent advances in natural language processing, along with the increased availability of data and computing resources, have dramatically improved our ability to process language data with computers. Yet for many researchers in other fields, it isn’t always straightforward how to apply these tools in practice. I enjoy helping people apply NLP tools to answer questions they care about.
Through D-Lab, I offer free consulting on natural language processing and Python to UC Berkeley’s community. Broadly, if you’re working on a project involving natural language data (text or speech), I’m happy to help. Concretely, I can help with:
- Text classification
- Preprocessing text data
- Sentiment analysis
- Neural networks for NLP
- Using word embeddings
- Information extraction
- Named entity recognition
- Syntactic parsing
- Consuming web APIs
- Web scraping
- Topic modeling
- Python and the Python data science ecosystem
To get help for your project
If you’d like consultation for a project, please submit a consulting request through the D-Lab here.
When you do so, you’ll be asked to write some background information about your project. It’s helpful for me if you can include the information below. It’s ok to leave some of them blank if you’re unsure.
Goal of the project: This could be a research question or a problem you’re trying to solve.
Data: A brief description of any data you currently have or would like to have for your project.
Specific hurdles you’re facing: What’s stopping you from completing your project? How can I help you?
When we meet, it’ll take me some time to make sure I understand your project and its goals. After that, we’ll jointly design some solutions to your problems. Often, this can take more than one meeting.
I want to empower researchers with the knowledge and skills required for the projects they work on. To that end, I rarely write code during consultations other than to illustrate ideas that we talk about. If you’d like to collaborate more heavily on a project, including me writing code, I’m happy to talk about this during our meeting.
If you find my guidance useful and publish work on your project, it’d be great to be mentioned in the acknowledgement section.