Chun-Jung Huang [email protected] Chiao-Tung University, Ph.D. - Photonics,2015 ~ 2020 Member of The Phi Tau Phi Scholastic Honor Society of the Republic of China. Work Experience TSMC, OPC Chief Engineer (MarPresent) ◆Introduced image anomaly detection techniques to identify and address defects in photomask manufacturing, significantly improving product quality and reducing turnaround time. ◆Managed large-scale data processing tasks, demonstrating expertise in analyzing and handling datasets of hundreds of millions, to bolster model development and optimization. ◆Excelled in distributed computing, optimizing code execution across thousands of systems to
蕭舜誠-Shawn New Taipei City, [email protected] Hi, I’m Shawn. experienced firmware engineer with nearly five years of experties. and a Bachelor’s degree in Electronic Engineering from the NKFUST. Proficient in firmware development using C, with hands-on experience in Embedded Linux System, MCU and Linux System, such as the OOB solution(on NUC980), Platform software Package, and FreeRTOS(on STM32) . comprehended to Python, TensorFlow, and machine learning concepts during university studies. Furthermore, I have proven track record of independently tackling challenging technical projects and embracing new technologies
Nelson Chen Senior engineer Dedicated Software Engineer with 6+ Years of Experience Senior software engineer specializing in web page development and deep learning. Proficient with machine learning technologies, such as TensorFlow, Numpy, etc. Experience Senior engineer • Chicony Electronics Co, Ltd. .Build an Auto-Encoder AI model for defective detection. .Build an object detection model for detecting car types. .Developed a Front-End and Back-End website for data analysis. .Manage the production process and make it automated production. NovPresent Software engineer • Teco image systems co. ltd .Developed and maintained MFP driver
Zikri Alghifahri - Date of Birth 15th JanuaryStarting Carrier as Programmer in 2013 Indonesia Work Experience MarchPresent Software Developer PERBASI Working within Basketball Athletes to gather Data & statistics. Now sports and technology cannot be separated from each other. Therefore, I designed a system that can record all athlete activities and display them into a data set that can be read and studied in the future. Machine learning is the tool I use to achieve this. Currently, Tensorflow is one of the frameworks that I use to support my needs. NovemberPresent Software Developer Dinas Perpustakaan & Arsip Pesawaran
I am a Graduate Student at Penn State, where I attend the laboratory led by Liu Peng, the director of the Cyber Security Lab.My research focuses on Network and System Security, and Deep Learning.
Research Experience
Research Assistant
Pennsylvania State University• 08.2023 - Present
Reinforcement Learning for Advanced Persistent Threat
Analyzing real-world enterprise login data and network data to reconstruct the actual network environment.
Simulating the attack behavior of APT groups such as APT28 or APT41.
Academia Sinica• 09.2021 - 06.2023
Graph-based Neural Attack Behavior Detection and Alignment with Kernel Audit Logs for Advanced Persistent Threats
Simulated APT attack on Linux and Windows
Developed a theory for efficiently reducing kernel audit logs to ensure the high quality of behavior detection
Developed models leveraging graph embedding to correlate and mine suspicious behavior in audit logs
Modeling Threat Representation through Building Cyber Threat Knowledge Base for Advanced Persistent Threats
Developed models to extract semantic context from cyber threat intelligence platforms for generating provenance graphs
Using Honeypot Logs and Packets for Identifying Network Attack Patterns and their Signature
Utilizing BERT-based models to analyze packets and logs from honeypots provided by Soft Bank
P.-Y. Tseng, P.-C. Lin, Edy Kristianto, Vehicle Theft Detection by Generative Adversarial Networks on Driving Behavior. Engineering Applications of Artificial Intelligence (published) [Paper]
Project
Reinforcement Learning for Advanced Persistent Threat
A novel approach to defend against APT attacks, specifically targeting lateral movement.
To formulate APT attack into Observable Markov Decision Process (POMDP) problems
APT Discovery using OSINT and Network & System Logs
Integrated Open-source intelligence, Cyber threat intelligence, and MITRE ATT&CK framework into a cyber threat knowledge base, and developed neural network architectures to analyze and detect APT attacks in a multi-host environment.
Aligned the observed evidence to adversary lifecycle and correlated the relation between the detected
I am a Graduate Student at Penn State, where I attend the laboratory led by Liu Peng, the director of the Cyber Security Lab.My research focuses on Network and System Security, and Deep Learning.
Research Experience
Research Assistant
Pennsylvania State University• 08.2023 - Present
Reinforcement Learning for Advanced Persistent Threat
Analyzing real-world enterprise login data and network data to reconstruct the actual network environment.
Simulating the attack behavior of APT groups such as APT28 or APT41.
Academia Sinica• 09.2021 - 06.2023
Graph-based Neural Attack Behavior Detection and Alignment with Kernel Audit Logs for Advanced Persistent Threats
Simulated APT attack on Linux and Windows
Developed a theory for efficiently reducing kernel audit logs to ensure the high quality of behavior detection
Developed models leveraging graph embedding to correlate and mine suspicious behavior in audit logs
Modeling Threat Representation through Building Cyber Threat Knowledge Base for Advanced Persistent Threats
Developed models to extract semantic context from cyber threat intelligence platforms for generating provenance graphs
Using Honeypot Logs and Packets for Identifying Network Attack Patterns and their Signature
Utilizing BERT-based models to analyze packets and logs from honeypots provided by Soft Bank
P.-Y. Tseng, P.-C. Lin, Edy Kristianto, Vehicle Theft Detection by Generative Adversarial Networks on Driving Behavior. Engineering Applications of Artificial Intelligence (published) [Paper]
Project
Reinforcement Learning for Advanced Persistent Threat
A novel approach to defend against APT attacks, specifically targeting lateral movement.
To formulate APT attack into Observable Markov Decision Process (POMDP) problems
APT Discovery using OSINT and Network & System Logs
Integrated Open-source intelligence, Cyber threat intelligence, and MITRE ATT&CK framework into a cyber threat knowledge base, and developed neural network architectures to analyze and detect APT attacks in a multi-host environment.
Aligned the observed evidence to adversary lifecycle and correlated the relation between the detected