reducing parameter training volume to 2% , decreasing memory usage by 70%, and increasing training speed by 25%. Architecture Optimization: Used Direct Preference Optimization (DPO) to optimize Reinforcement Learning, improving model efficiency and decision quality. [ G itHub ] Graduate Research Assistant OctOct 2023 Institute of Information Science, Academia Sinica, Taiwan Natural Language and Knowledge Processing Lab (NLP Lab) Publication: Published in ACM CIKMSequential Text-based Knowledge Update with Self-Supervised Learning for Generative Language Models . [ Paper | GitHub ] Performance has improved by 18.8% compared to traditional methods in the past and surpassed SOTA LLMs by 39.6

趙啟雲 chiyun chao A software engineer with 4 years of experience in AI model training and backend development. In the domain of machine/deep learning, I am familiar with: - focus on NLP(Natural language processing) and DPI(Deep packet inspection) - NLP networks such as Transformer, BERT, T5 - have experience with AI training platform development with mlflow, Label Studio, DVC In terms of backend development, I have the following experience： - backend framework: Spring boot, Flask - familiar with DB syntax for Elasticsearch, PosgresSQL and MSSQL Taiwan E-mail: [email protected] Skill languages Python JAVA backend

incorporating: - A clean architectural approach - Integration with Firebase services - Support for the latest Android features ensuring scalability for future organizational growth - Successfully retained a 4.6-star user rating and boosted job application rates by 10%. • AI Implementation: Created an AI tool to convert UI test cases from natural language into UiAutomator2 scripts, seamlessly integrating them into the CICD process. This resulted in a 90% acceleration UiAutomator2 test case generation. • Technology Introduction: - Flutter: Developed an in-house App Dashboard to consolidate Android/iOS/backend CICD build statuses and test report outcomes. Single-handedly

including Recurrent Neural Network (RNN), word2vec, paragraph vector. Working Experience Intern, JulDec 2014 Phalanx Biotech Develop machine learning solutions for cancer gene detection and TSMC semiconductor quality prediction. Intern, JulAug 2013 Solid State System Assisted in CMOS MEMs microphone product development including proto-type simulation, fabrication/packaging process, defect analysis and market survey. Achievements 1. Qualified of preliminary contest of TSMC Big Data Analytics for Semiconductor Manufacturing. Taiwan,Completion of Broad-DREAM Gene Essentiality Prediction Challenge, 2014 Professional Skills Research Field Machine Learning Deep Learning Computer Vision Natural Language Processing Lang...

expressions, enhancing user interaction experiences. Emotion Recognition Systems: Developing AI systems capable of understanding and responding to user emotions, used to enhance customer service and user interactions. Voice Technology (TTS): Natural Voice Generation: Employing Text-to-Speech (TTS) technology to convert text into natural, fluent voice across multiple languages, suitable for virtual assistants and customer service bots. Voice Interaction Interfaces: Developing voice interaction interfaces that enable digital personas to conduct natural dialogues, offering more humanized interaction methods. Large Language Models and Natural Language Processing: Personalized Response Generation: Leveraging personality-driven large language models to provide customized

and honed my skills in dynamic tech stacks. As a seasoned product manager, I've successfully navigated the intersection of user needs and technical innovation, steering product strategies for optimal growth. From leading software teams at IBM to co-founding a startup that delved into machine learning and natural language processing, I bring a unique blend of technical prowess, product expertise, and entrepreneurial flair. My expertise in growth hacking working with early stage startups around the world involves leveraging lean startup methodologies and data-driven decision-making to drive business success. I'm excited to bring

Jeffrey Lin ( 林奕勳 ) ESUN Bank, Intelligent Finance Technology Department, AI Engineer focusing on Enterprise-Level ML Frameworks and Design Patterns [email protected] TW, Taipei CAREER SUMMARY 6+ years of deep learning research and development experience, with a strong ability in prototyping, evaluation, and deployment of models, in both academical and industrial environment. 2+ years of financial AI development experience, specialized in the design of python API, SDK, and framework for optimizing the deployment flow of data science, ETL, and machine learning pipelines. 1+ year of participation in the technology management