Experience, education, etc.

Google

Software Engineer

Present - 2013

Full stack software engineer and team lead for intelligent customer relationship management platform. Projects include machine learning, large data pipelines, front end development, scalable APIs, and databases.

Team lead for two teams of up to 15 software engineers. Responsible for iteration planning, code review, design documents, and annual objectives.

Contributed to Google’s culture and community by hosting four intern projects, conducting 67 technical interviews, and doing 10 campus recruitment events.

UC Riverside

Teaching Assistant

2013 - 2008

I taught courses in C++, Java, data structures, algorithms, and a senior software project course.

NASA JPL

Software Engineer Intern

2008

Developed a lightweight rover mission simulator. A virtual rover which accepted actual planning commands (move, rotate, take an infrared photo, etc.) and output realistic images of a 3D virtual Mars terrain along with telemetry information. Think a video game version of the Opportunity rover. This was used to test the rover while it was in flight and allowed the team to catch bugs with their platform before the rover landed on Mars.

Harvey Mudd

Research Student

2007

This research intersected my love of programming and music and gave me my first taste of unsupervised machine learning. We developed a technique which read a MIDI music file and used K-means clustering to extract the song’s characteristic style. The style could then be used to automatically generate new musical accompaniment to a given chord sheet. This allows users of the Impro-visor tool to quickly generate background music over which they can practice and write their lead solos.

Education

PhD Computer Science

UC Riverside, 2013 - 2008

BS Computer Science Cum Laude

California Polytechnic University Pomona, 2004 - 2008

Publications

• Herold J., Stahovich T. F.: SpeedSeg: A technique for segmenting pen strokes using pen speed. Computers & Graphics 35, 2 (2011), 250-264

• Herold J., Stahovich T.F.:ClassySeg: A machine learning approach to stroke segmentation. In Proceedings of the 8th Eurographics workshop on Sketch-based interfaces and modeling (New York, NY, USA, 2011), SBIM '11, ACM

• Herold J., T. F. Stahovich: Using speech to identify gesture pen strokes in collaborative, multimodal device descriptions. Artificial Intelligence for Engineering Design, Analysis and Manufacturing (2011), 25: 237-254

• J. Reaver, T. F. Stahovich, and J. Herold: How to make a Quick$: Using hierarchical clustering to improve efficiency of the dollar recognizer. In Proceedings of the 8th Eurographics workshop on Sketch-based interfaces and modeling (New York, NY, USA, 2011), SBIM '11, ACM

• J. Herold, T. F. Stahovich, H. Lin, R. C. Calfee: The effectiveness of "Pencasts" as an instructional medium. In Proceedings of the 2011 American Society for Engineering Education Annual Conference and Exposition, 2011.

• J. Herold and T. F. Stahovich: Automatically Understanding Student Self-Explanations. In Proceedings of the 2012 American Society for Engineering Education Annual Conference and Exposition, 2012.

• J. Herold and T. F. Stahovich: Characterizing Students' Handwritten Self-Explanations. In Proceedings of the 2012 American Society for Engineering Education Annual Conference and Exposition, 2012.

• H. L. Lin, T. F. Stahovich, and J. Herold: Automatic Handwritten Statics Solution Classification and its Applications in Predicting Student Performance. In Proceedings of the 9th Eurographics workshop on Sketch-based interfaces and modeling (New York, NY, USA, 2012), SBIM '12, ACM

• C. Lee, J. Jordan, T. F. Stahovich, and J. Herold: Newtons Pen II: An Intelligent, Sketch-Based Tutoring System and its Sketch Processing Techniques. In Proceedings of the 9th Eurographics workshop on Sketch-based interfaces and modeling (New York, NY, USA, 2012), SBIM '12, ACM

• J. Herold and T.F. Stahovich: The 1¢ Recognizer: A Fast, Accurate, and Easy-to-Implement Handwritten Gesture Recognition Technique. In Proceedings of the 9th Eurographics workshop on Sketch-based interfaces and modeling (New York, NY, USA, 2012), SBIM '12, ACM

• J. Herold and T.F. Stahovich: Using Educational Data Mining to Identify Correlations Between Homework Effort and Performance. In Proceedings of the 2013 American Society for Engineering Education Annual Conference and Exposition.

• J. Herold, A. Zundel, and T.F. Stahovich: A Data-Driven Approach to Categorizing the Spatial Organization of Homework Solutions. In Proceedings of the 2013 American Society for Engineering Education Pacific Southwest Section Conference.

• J. Herold, A. Zundel, and T.F. Stahovich: Mining Meaningful Patterns from Students' Handwritten Coursework. Proceedings of the Sixth International Conference on Educational Data Mining. 2013.

• N. M. Rhodes, M. A. Ung, A. E. Zundel, J. Herold, and T. F. Stahovich: Using a Lexical Analysis of Students' Self-Explanation to Predict Course Performance. Proceedings of the Sixth International Conference on Educational Data Mining. 2013.

• J. Herold: Data Mining Students’ Ordinary Handwritten Coursework: A Dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Computer Science, UC Riverside. 2013.