
Rubayet Rongon
Engineering / Architecture
About Rubayet Rongon:
I am Rubayet Rahman, a MS student in Computer Science, Florida state University. Currently, looking for internship opportunity in Tallhassee.
Experience
Explorer Lab, CS, Florida State University.
1. Research Assistant (Part-time) (Fall 2021 - Spring 2022)
-High Performance Computing
- Improving performance of one of the most used parallel and distributed message passing library (MPI) for different routines. My primary focus was to improve intra-node communication considering modern multi-core architecture. I had to improve communication algorithm considering different factors.
2. Teaching Assistant, CS, Florida State University
-Teaching Assistant (Part-time), Spring 2021-Spring 2021.
-COP3014 Programming I
- This course covers fundamental concepts and skills of programming in a high-level language. Flow of control: sequence, selection, iteration, subprograms. Data structures: arrays, strings, structs
3. Goava AB, Dhaka, Bangladesh
-Software Engineer (Full-time)(Sep 2018 - Dec 2020)
- Goava uses Big Data and Machine Learning to help you discover your most likely buyers. In AWS micro-service architecture my responsibility was to crawl text data from social media and APIs using EC2. Clean, pre-process data and store those in S3 using AWS lambda. Finally, use NLP to develop recommendations and serve those to Clients.
4.IPvision Canada Inc.(Dhaka, Bangladesh)
-Software Engineer (Full-time), Aug 2015 - Jul 2018.
-Responsibility for developing services for social networking app ‘ringID’. Clean and extract our time-series server metric information to predict virtual server memory and CPU usage. Server anomaly detection. System Metric Measurements Forecasting.
Education
2nd year MS. student in Department of Computer Science(Fall 2020 - Present), Florida State University, Florida, USA.
Courses: Advanced Algorithms, Parallel and Distributed Systems, Concurrent Parallel and Distributed programming, Databases Systems, Computer Architecture, Fundamental of Machine Learning Algorithms
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