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surabaya, indonesia
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Kevin P.

@echelon2718

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surabaya, indonesia
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AI Researcher and Engineer

I am an AI Engineer with 4 years of experience in Deep Learning, NLP, and Image Processing. Currently, I am working as a researcher of artificial intelligence at Sepuluh Nopember Institute of Technology and Avalon AI ([login to view URL]). My research is in image generation and image-to-image translation tasks. There are several of my achievements listed below as an Avalon AI member: 1. Built a Fashion Virtual Try-on using Generative Adversarial Networks, leverages image generation technology (2024). 2. Fine-tuned LLaMA-7b model for Personalized Chatbot Systems. We deploy our application on a website using Javascript and Python frameworks (2024). 3. Built workout monitoring system using EfficientNet model implemented on edge devices (2023). 4. Indonesian Speech Recognition System Using Wav2Vec-LM gives 25%-word error rate performance (lower better) (2023). 5. TinyML for Gender and Age Classification Through Voice on Arduino BLE33 Sense Kit Using Deep Neural Network. This system gives significant performance with 85% accuracy on predicting age and 95% accuracy on predicting gender (2023). The key value of this project is to build a tiny machine learning model in an embedded system with the highest performance possible. 6. Sign Language to Speech System Using YOLOv8 and Google Text-to-speech API (2023). 7. Smart Plate Number Recognition Using YOLOv8 Architecture. The provided dataset is plate number images with various characteristics. Our model gives 95.23% accuracy on the test dataset (2023). 8. Built an application for fish disease diagnosis in order to help fishermen to increase productivity of the fish industry. This application leverages deep learning and performs high performance (95% accuracy) (2023). 9. Key contributor to the Indonesian speech-to-text system project by Sepuluh Nopember Institute of Technology. I proposed a novel approach on Transformer for automatic speech recognition tasks whereas this model gives robust performance (2023). 10. Involved in proposal development for OpenAI and OWASP Maryam projects under the Laboratory of Smart City and Cyber Security ITS, focusing on generative AI implementation for intrusion detection (2023). 11. Involved on Self-driving Car with Smart Navigation System Using Reinforcement Learning Algorithm and Convolutional Neural Network Project as an AI engineer, showing knowledge in robotics (2022). My work motto is simple; to give the best quality of every work and satisfy client needs. As a part of Avalon AI team, we assure you to give the best of your projects you gave to us.

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Portfolio

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Erfahrung

Founder and CEO

Avalon Laboratory of AI and Embedded Systems
Apr. 2023 - Aktuell
With a vision and motivation for the future of AI and its benefits to humanity, I firmly commit myself to starting my own R&D company, Avalon. Avalon is dedicated to research in artificial intelligence, particularly in generative AI, NLP, and Computer Vision. Our vision is a world where AI will greatly assist humanity and its progress. To achieve this vision, we are embarking on our mission and contributing to AI research starting from now on.

Ausbildung

Bachelor of Information Technology

Institut Teknologi Sepuluh November, Indonesia 2021 - 2024
(3 Jahre)

Qualifikationen

Satria Data Big Data Competition 2022 Semifinalist

Ministry of Education and Culture of Indonesia
2022
This is a national data science and analytics competition that is issued by The Ministry of Education and Culture of Indonesia. I was working with my team and achieved the 3rd highest position as a semifinalist regarding on health condition analysis by using machine learning approach.

The 3rd Highest GPA in the Department of Information Technology ITS batch 2021

Department of Information Technology ITS
2023
I achieved the third position as a student with the highest GPA in the Department of Information Technology ITS with GPA 3.82/4.00. I am actively assisting my lecturers on various courses, research, and projects related with artificial intelligence.

Veröffentlichungen

EDA and Augmentation of NSL-KDD Data Using DeepGAN to Improve the XGBoost Classification Performance

Arxiv
This study proposes the implementation of Deep Generative Adversarial Networks (GANs) for augmenting the NSL-KDD dataset. The primary objective is to enhance the efficacy of eXtreme Gradient Boosting (XGBoost) in the classification of cyber-attacks on the NSL-KDD dataset. As a result, the method proposed in this research achieved an accuracy of 99.53% using the XGBoost model without data augmentation with GAN, and 99.78% with data augmentation using GAN. https://arxiv.org/abs/2312.10669

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