- Supported course instructors with lab demonstration, tests and assignments grading, and student communication.- Run help desk physically and virtually to help various students from Year 1 to Year 4.- Proctoring tests and exams, solving certain issues during exams.- Related courses: Computer Architecture, Computer Network, Advanced Data Structure, etc.

Computer Science research fellowship- Designed and developed a Distributed System in Linux which manages communications and handles network protocols between vehicles and smart devices.- Integrated Veins, OMNET++, SUMO and Simu5G open-source APIs and focused on established object-oriented design patterns for vehicular network.- Developed real-world urban scenarios using C++ and extracted vehicular mobility data based on SUMO.- Built internet of vehicle Event Based System utilizing OMNET++ with Socket Programming (TCP/IP, DNS) techniques to implement communication between vehicle to vehicle and vehicle to infrastructures which deal with over One Million Events.- Architected 5G base station model into the urban system utilizing Simu5G under @Intel to form a novel heterogeneous vehicular network including 5G, WAVE, and DSRC signals.- Bridged the above software by using Veins to conduct the software work together simultaneously.- Developed vehicular network management model based on K-Means algorithm and utilized Markov Decision Process Model to decrease network latency by 67% and Package loss rate by 24% as demonstrated by peer-reviewed research.- Extracted data from road environment to generated image by Python and Matlab, and contributed to the field of the Smart City, Internet of Things, Artificial Intelligence, Cloud Computing, and Fog Computing.

- Performed a thorough evaluation of the cloud solutions’ deficiency, including security assessment, performance evaluation, and cost analysis.- Passed @Microsoft Azure Administrator Associate Certificate and designed Microsoft-like cloud solutions.- Visited clients to gather data and optimize compliant cloud services through Internal Lab analysis.- Defined Standard Operating Procedure (SOP): Slashed administration costs by 20% for training new employees by identifying cloud platform design flaws, implementing SOP documents, and ensuring the continuation and enhancement of services.

Job Search Engine- Created Search, Favorite, Recommendation Java Servlets with RESTful APIs to handle HTTP requests and responses. - Designed and built relational database schema using MySQL on AWS RDS to persist, manage and process jobs data fetched from GitHub API. Used MonkeyLearn API to extract keywords from position descriptions. - Designed content-based recommendation, session-based authentication, keyword extraction algorithms to implement Job Recommendation engine. - Setup and deployed to an AWS EC2 virtual machine instance and installed Redis to cache Search and user Favorite results Reduced the latency 90%. - Constructed UI components in the frontend using JavaScript, HTML, CSS, AJAX enabling users to search/apply for positions, add jobs to favorite as main factors on recommendation engine design. - Set up Redis cache on EC2 machine enabling users to read favorite items and search results from it to decrease the response latency.