Verified Expert in Engineering
Data Scientist, Software Engineer, and Developer
Amazon Web Services (AWS), Linux, Python, SQL, Jakarta EE
The most amazing...
...project I've built is a combined sentence parser and text compressor; the former finds the parse tree that produces the shortest code length for the latter.
- Developed machine-learning algorithms for sentence parsing and modeling.
- Designed, developed, and performance-tuned back-end SQL databases.
- Worked on DevOps to enable the code to run on Linux instances on the AWS cloud (S3, EC2, RDS, and Spot Market).
- Designed the software architecture in Java to ensure that all the pieces interacted smoothly.
- Developed algorithms in Python to extract truck information (location, truck type, and so on) from email text; the challenge lay mainly in the widely varying text structure.
- Built a suite of evaluation, management, and analysis tools for the system using MySQL, EC2, and CI tool.
- Created an admin web app console in Flask to help developers control, analyze, and debug the core NLP components.
- Helped to develop an NLP system to detect sentiment in user experience narration transcripts; used Python and Keras.
- Took on the main challenge which was the limited amount of available training data; a key insight was how to use information from other datasets to help with our problem.
- Created a visualization tool that used the neural network to highlight key phrases of strong sentiment.
- Worked as the primary developer of a big data audience analysis system.
- Programmed Hadoop, using native Java SDK, to process big data from real-time ad exchanges.
- Developed a system to connect the Hadoop output to a machine learning algorithm.
- Built a visualization/analysis back-end in MySQL to enable clients to understand the audience profile and characteristics.
- Integrated the audience analysis system with other components of the company's stack (the bidder system and the operations console).
- Wrote additional significant ETL code in Java for the company's reporting system.
Rodale Press (Contract)
- Developed SmartCoach and SmartCoachPlus—an automated training program generator for runners.
- Developed a MySQL back-end for a second version.
- Implemented complex training program generation rules.
Mirror Encoding Libraryhttps://github.com/comperical/MirrorEncode
This technique avoids a crucial difficulty in compression, requiring the encoder and decoder to be perfectly in sync. Using this library, developers can easily create new data compression algorithms with just a few lines of code.
The diagram is very useful for documentation purposes; other developers (or the original developer, at a later point in time) can easily understand the way the code works just by looking at the diagram, without needing to dive into the specific details.
Ozora Research Sentence Parserhttp://ozoraresearch.com/crm/public/parseview/UserParseView.jsp
The parser is built in combination with a specialized text compressor which compresses text by using a parse tree. The parser produces the tree that will produce the smallest code length for the given sentence. You can demo the parser at the link provided.
Notes on a New Philosophy of Empirical Sciencehttps://arxiv.org/abs/1104.5466
This philosophy guided my work at Ozora Research. In this case, the relevant data set was English newspaper text. To compress this data, I developed theories of grammar and syntax, and build those theories into a data compressor.
Statistical Modeling as a Search for Randomness Deficiencies | Ph.D. Thesis
According to algorithmic information theory, if a given model is a perfect fit for a data set, then when you encode the data using the model, the resulting encoded data (typically a bit string) is completely random. This implies that if you have a model—and encode the data using the model and find a randomness deficiency in the encoded data—then there is a flaw in your model. Furthermore, an analysis of the randomness deficiency illustrates a way to improve the model.
The thesis developed a suite of machine learning algorithms that work by using this idea.
Natural Language Processing (NLP), GPT, Generative Pre-trained Transformers (GPT), Machine Learning, Algorithms
Object-oriented Design (OOD)
Linux, Amazon EC2, Jakarta EE, Amazon Web Services (AWS), JEE
MySQL, PostgreSQL, Amazon S3 (AWS S3), JSON
Keras, React, TensorFlow
Azure Machine Learning, Amazon Elastic MapReduce (EMR)
Ph.D. in Machine Learning
University of Tokyo - Tokyo, Japan
Master of Science in Artificial Intelligence
McGill University - Montreal, Canada
Master of Science in Physics
University of Connecticut - Storrs, CT, USA
Bachelor of Arts in Applied Math and Computer Science
Harvard University - Cambridge, MA, USA