OWEN JOW

Here's a list of languages with which I've had some form of exposure. Keep in mind that each label is relative to me and my own degree of experience:

• Lots of exposure: Java, Python, English, C#, C++, HTML/CSS
• 7/10 exposure: JavaScript, C, Japanese, MIPS assembly, SQL, Ruby, Scala
• Some exposure: Swift, Objective-C, Scheme

I have a decent level of experience with each of the following:

• Operating Systems: UNIX, OS X, Linux
• Software: Autodesk Maya, Photoshop, LaTeX
• Frameworks / Runtime Environments: Django, Unity, Rails, ROS

Due to the possibility of plagiarism, I'm unable to post my code for these projects. However, if you would like further information about any of them, I'd be more than happy to answer your questions!

• CS 61A | Python + Scheme: Scheme Interpreter
• For our final 61A project, we built a Scheme interpreter in Python. This interpreter could be run interactively, during which it would cycle repeatedly through the read-eval-print loop.
• CS 61A | Scheme: Recursive Art Contest
• Using Turtle graphics in Scheme, we were challenged to "unleash our inner recursive artist" by creating a visualization of some computational process. This was my entry; it was effectively a fusion of multiple terdragons.
• CS 61B | Java: Gitlet
• Here we designed and implemented (from the ground up!) our own version control system, which was modeled after Git.
• CS 61C | MIPS + Logisim: Processor Design
• A working processor built by wiring together logic gates. We were required to construct all of the CPU logic (including that contained within the ALU and register file components).
• CS 61C | Python: Performance Optimization/Convolutional Neural Networks
• In this project, we added optimizations to a CNN implementation so that it could identify at least 3000 cat images per second. We did this using techniques along the lines of loop unrolling, SIMD instructions, and OpenMP.
• CS 61C | Python: Deep Learning Algorithm + Spark [Part 1][Part 2]
• Here, we again optimized a convolutional neural network – except this time we did it with Apache Spark and MapReduce. After we were finished, we ran our implementations on clusters of AWS EC2 servers in order to test our image-identifying code on a massive number of samples.
• CS 168 | Python: Reliable Transport
• As our second 168 project, we built a simple transport protocol ("BEARS-TP") that was required to provide in-order, reliable delivery of UDP datagrams – even in the presence of arbitrary hindrances like packet loss, duplication, and re-ordering. This was done by imbuing our sender with "go back N," "fast retransmit," and "selective acknowledgement" functionality.

• CS 61A Undergraduate Student Instructor [UC Berkeley EECS Department]
  January 2016 -
  
  During the spring semester of 2016, I rejoined the CS 61A course staff as a UGSI. Accordingly, I was responsible for leading lab/discussion sections, being available online and in office hours, and grading assignments. I also worked with other staff members to develop course content (e.g. exams, quizzes, and supplementary resources).

• Backend Engineer [Project Campanile; ASUC Office of the CTO]
  October 2015 - December 2015
  
  As part of Project Campanile, I worked on the backend for Berkeleytime, a Django application serving as an expansive conduit for Berkeley course and campus data. Among other duties, I helped develop an API, fine-tuned search UX, and contributed to general bug fixes.

• CS 61A Group Tutor/Reader [UC Berkeley EECS Department]
  August - December 2015
  
  As a member of Berkeley's CS 61A course staff (under Professor John DeNero), I tutored students in weekly small-group sessions, hosted extra office hours, and graded programs/exams for composition and correctness. I also got my picture on the website, which means I'm one step closer to being famous.