In 7th grade, my parents set a lock screen on Windows XP because they believed that using a computer would lead me to neglect my studies. To overcome this, I installed Ubuntu on an SD card as a means to access the computer without needing the password. This was the starting point of my journey with computers.
In the 9th grade, I found myself drawn to the world of Android OS upgrading and began developing third-party Android ROMs. It was during this time that I realized the need to expand my knowledge in order to fully satisfy my passion. This realization ultimately motivated me to pursue a master's degree in computer science.
View ResumeDeployed and maintained websites on Kubernetes, ensuring seamless and efficient operation. Integrated ChatGPT into the websites, enhancing user experiences and providing personalized assistance. Leveraged Docker, MariaDB, PostgreSQL, and MongoDB to support website deployment and management.
Conducted research on identifying misinformation about Covid-19 using Python and Spark. Utilized PySpark.ml to pre-process tweet data and employed GloVe 100D and Universal Sentence Encoder to map cleaned tweets to vector space. Trained the model using DNN from Spark NLP, resulting in a 91.89% F1-score. Implemented Spark-Streaming to detect fake news in real-time.
Designed an image search engine, implemented with Python and TensorFlow. Detected and cropped the facial part of images using multiple pre-trained neural networks. Constructed K-nearest neighbors indexes for images in a target dataset based on the extracted features. Searched the top similar images for the target image using KNN, and achieved 85% accuracy on the LFW dataset.
Conducted research on object tracking in a two-dimensional world with multiple objects and obstacles. Developed a Python-based tracker using the Kalman filter algorithm. Automated the assignment of multiple trackers to each object. Achieved accurate tracking even when similar objects crossed over each other.
Detected salient objects without prior knowledge by calculating regional contrast values, implemented the algorithm using C++ and OpenCV. Improved calculation speed by quantizing into 12 colors and computing pixel saliency in the CIELAB color space. Optimized pre-processing tasks for various computer vision applications to enhance efficiency on large industrial datasets.
Developed a file system simulator with inode-block structure using C++. Implemented Linux file system calls including file copy (cp), move (mv), and access control (chmod). Created a custom data-serialization format to enable file encryption, with support for zip and unzip operations.
Led a team of four to design and develope a Smart Calendar system using Java, facilitating efficient communication between faculty members and students by real-time notifications. Applied Agile development methodologies to ensure efficient and top-notch project delivery. Implemented cross-domain cookie persistence for seamless user synchronization with the school's message board. Reduced bandwidth usage and enabled server-initiated data transmission by WebSocket connections built with OkHttp.
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