Hsien-De Huang (also known as TonTon), is a seasoned professional with over a decade of expertise in Cyber-Security and Artificial Intelligence. His extensive skill set encompasses image recognition, natural language processing, speech processing, and cyber-security, with a focus on x86/Android malware analysis. His career includes the presentation of numerous research papers and patent applications at international cybersecurity conferences, including Defcon AI Village, OWASP AppSec USA, RuxCon, and HITCON. While managing a full-time career, he pursued and completed his Ph.D. in Computer Science and Information Engineering at National Cheng Kung University. His doctoral thesis, titled "Deep Learning-based Anomaly Analysis in Cyber Threats," explores novel approaches in the field. He is also the founder of Taiwan's pioneering artificial intelligence meetup, Deep Learning 101, dedicated to fostering innovation, knowledge-sharing and problem-solving in these dynamic 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、語音處理等在金融壽險、電信客服應用中推動人工智慧/深度學習技術落地,以及在x86/Android惡意程式分析等網路安全領域的應用整合;並曾先後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及政府單位演講,及接受相關雜誌報導 (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」;攻讀博士期間,參與台法聯合團隊交流計畫,赴法國國家信息與自動化研究所進行研究,並參與台英合作研究計畫,前往英國艾賽克斯大學進行訪問研究。他還是台灣最早的人工智慧社群Deep Learning 101和台灣人工智慧社團的發起人,促進人工智慧及資安領域的行業交流。