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• Performance and Power Modeling
• Create dynamic learning activities for online interactive textbooks.
• Translate content from pdf to an online website using HTML and LaTeX.
• Implement Challenge Activities.
• Perform quality checks on implemented pages for errors.
• CS 120B: Introduction to Embedded Systems
- Instruction of two discussion sections a week.
- Prepare content for discussions.
- Hold two office hours a week to help students with labs and any questions.
- Give students guidance on any problems they are having with labs.
• CS 10C: Introduction to Data Structures and Algorithms
- Host demo sessions for students to demo labs for a grade.
- Grade students’ assignments and exams.
- Give students guidance on any problems they are having with labs and assignments.
• Hyperloop(Alexa for Apps) Team
• Implemented a front-end interface and middleware infrastructure for an internal tool utilized to update a DynamoDB table to be used for updating Alexa commands.
- Front-end: React, JavaScript
- Middleware: JavaScript, AWS API Gateway, AWS Lambda, AWS CloudFormation
• Reduced manual workflow necessary to update datastore from days to minutes.
• Real-time Network-Based Co-Verification and Data Processing Software for Next Generation Imaging Spectrometers (NGIS) with Embedded Multi-Processor System-on-Chip (MPSoC) Instrument Avionics.
- LiveView is an open-source software application that provides real-time visualization tools for Imaging Spectrometer development.
• Worked on the development of a co-verification software suite (LiveView).
• Implemented multiple new features on LiveView using C++.
- Responsible for implementing a new "Overlay Widget" tab on LiveView which allows for two different graphs to be shown on one tab (previously LiveView only had one graph per tab).
- These graphs also allow for the data stream's image types to be dynamically changed as the imaging spectrometer data is running in LiveView.
• Google AI: Perception Team - MediaPipe
- A cross-platform framework for building multimodal applied machine learning pipelines.
• Implemented new features on MediaPipe’s open-source front-end interface using Angular, Typescript, CSS, and HTML (all features already available in production).
- Responsible for showing graphic analytics to provide a more intuitive and information-rich interface.
• Developed technical design documentation to define implementation strategies.
• Adhered to test-driven development in order to leverage unit tests for efficient and precise implementation.
Relevant Coursework: Data Mining Techniques, Artificial Intelligence, Big-Data Management, Information Retrieval and Web Search, Parallel Algorithms, Advanced Operating Systems, Intro to Deep Learning, Design and Analysis of Algorithms, Advanced Computer Networks.
Relevant Coursework: Applied Linear Algebra, Discrete Structures, Intro to Data Science, Software Construction, Probability and Statistics for Engineers, Embedded Systems, Database Management Systems, Intermediate Data Structures and Algorithms, Intro to Software Engineering, Project in Computer Science (Databases), Intro to Artificial Intelligence, Intro to Machine Learning and Data Mining, Compiler Design, Design of Operating Systems, Intro to Information Retrieval.
• Host or find hosts for workshops to grow WinC’s knowledge.
• Focus efforts on reaching out to companies for guest speakers and connections.
• Post internship and job opportunities for members to apply to.
• Provide resume review/feedback.
• Perform mock interviews with members by request.
• Managed SWE’s professional contacts which include alumni and professional guest speakers.
• Maintained a strong relationship with the Career Center.
• Hosted professional development workshops.
• Planed and hosted Evening with Industry.
• Continuously looked for professional contacts and ways to improve our relationship with them.
For the project, my partner and I analyzed stock price and stock news data using Python to ultimately create a machine learning model to predict stock prices based on current events.
What it does:
Its tracks groceries that people have so that they can know what food they have in their pantry.
How we built it:
This product is an iOS application that was made using Xcode. We programmed it with Swift.
What it does:
It matches people with pets that want someone to play with them (especially useful for shelter animals). It then allows the users to chat with their matches.
How we built it:
This product is a JavaScript application that was built in a JavaScript development environment.
What it does:
It accesses your social media followers from many platforms (e.g. Instagram, Facebook, Linkedin) and assigns a raw score based on how popular you are. This score is calculated based on likes, follows, and general engagement.
How we built it:
This product is an iOS application that uses the iOS-centric APIs of social media companies. We also used various third-party frameworks in order to speed up development.
Scholarship awarded to student(s) within the UCR Bourns College of Engineering with the strongest combination of academic performance and preparation for the engineering profession in and beyond the classroom.
Students are placed on the list for achieving a Grade Point Average (GPA) of at least a 3.5 and for having no grade lower than a "B" for the quarter.
Awarded to students with a cumulative GPA at or above a 3.9.
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