Hsien-De Huang (黃獻德,also known as TonTon (痛痛)), is a seasoned professional with over a decade of expertise in the field of Cyber-Security and Artificial Intelligence. His extensive skill set encompasses image recognition, natural language processing, speech processing, and cyber-security, with a focus on specializing in x86/Android malware analysis. His career has been marked by the presentation of numerous research papers and patent applications at international cybersecurity conferences, including Defcon AI Village, OWASP AppSec USA, RuxCon, and HITCON. Apart from work, he received the Ph.D. degree in Computer Science and Information Engineering from the National Cheng Kung University. His doctoral thesis is titled "Deep Learning-based Anomaly Analysis in Cyber Threats,". He is also the founder of Taiwan's pioneering artificial intelligence meetup, Deep Learning 101, dedicated to propelling innovation, knowledge-sharing and problem-solver in these exciting fields.

黃獻德 (TonTon),擁有超過10年的研究與開發經驗,包括:圖像識別、自然語言處理、語音處理等人工智慧/深度學習技術落地整合、金融壽險科技應用和x86/Android惡意程式分析等安全領域;並陸續曾任職於國家高速網路與計算中心、安碁資訊、以色列商Verint台灣、台灣雪豹科技及國泰金控數數發中心等單位。同時,他也陸續在Defcon、OWASP AppSec USA、RuxCon和 HITCON等國際資安會議上發表研究,及多篇學術論文和專利申請,並多次受邀至海內外大學、政府單位演講及相關雜誌報導(ex: bbc.com)。他畢業於國立成功大學資訊工程學系,其博士論文為「基於深度學習的網路威脅異常分析」;在攻讀博士時參與台法聯合團隊交流計畫至法國國家信息與自動化研究所及台灣與英國頂尖大學合作研究計畫至英國艾賽克斯大學訪問研究。他還是台灣最早的人工智慧社群Deep Learning 101台灣人工智慧社團的發起人,促進人工智慧及資安行業交流。