Kun Zhang
Acting Department Chair, Director of Center for Integrative Artificial Intelligence (CIAI), and Visiting Professor of Machine Learning
Research Interests
Professor Zhang’s research interests lie in machine learning and artificial intelligence, especially in causal discovery and inference, causal representation learning, and machine learning under data heterogeneity. He aims to make causal learning and reasoning transparent in science, AI systems, and human society.
On the application side, he is interested in biology, neuroscience, computer vision, computational finance, and climate analysis. His research has been motivated by real problems in healthcare, biology, neuroscience, computer vision, computational finance, and climate analysis.
Email
Before joining MBZUAI, Professor Zhang became associate professorship at Carnegie Mellon University (CMU) in the USA to explore machine learning and AI, especially causal learning, and reasoning. Professor Zhang formulates principles and develops methods for automated causal discovery or causal representation learning from various kinds of data; investigates learning problems including transfer learning, representation learning, and deep learning from a causal view; and studies the philosophical foundations of causation and various machine learning tasks.
Professor Zhang is a general and program chair of the 1st Conference on Causal Learning and Reasoning (CleaR 2022) and a program chair of the 38th Conference on Uncertainty in Artificial Intelligence (UAI 2022).
- Senior research scientist at the Max-Planck Institute for Intelligent Systems, Germany.
- Postdoctoral fellow at the University of Helsinki, Finland.
- Ph.D. in computer science from the Chinese University of Hong Kong.
- Bachelor of Science in automation from the University of Science and Technology of China, China.
- Co-authored a best paper finalist paper at CVPR 2019.
- Co-authored best student paper at UAI 2010.
- Best benchmark award of the causality challenge 2008.
- Test of Time Award Honorable Mention at ICML 2022
- Best Paper Award of the workshop on New Frontiers in Adversarial Machine Learning (AdvML 2022) at ICML 2022
- General and program chair of the 1st Conference on Causal Learning and Reasoning (CleaR 2022)
- Program chair of the 38th Conference on Uncertainty in Artificial Intelligence (UAI 2022)
Zhang co-authored a best student paper at UAI 2010, received the best benchmark award of the causality challenge 2008, and co-authored a best paper finalist paper at CVPR 2019.
أخبار ذات صلة
إمارة أبوظبي على خريطة أهم المدن المستضيفة لمؤتمرات الذكاء الاصطناعي الدولية
حضور ملفت لأعضاء الهيئة التدريسية المنتسبة لجامعة محمد بن زايد للذكاء الاصطناعي ضمن اللجنة التنظيمية لفعاليات مؤتمر…
اقرأ المزيد
سبر الأغوار: تحديد المتغيرات السببية الخفية عبر التعلم بالتمثيل السببي
على مر القرون، غالباً ما كان فهمنا للعالم الطبيعي يتطور عبر اكتشاف ظواهر طبيعية كانت فيما سبق…
اقرأ المزيد
باحثون يطورون خوارزمية لتحديد العلاقات السببية بين المتغيرات القابلة للقياس وغير القابلة للقياس المباشر
باحثون من جامعة محمد بن زايد للذكاء الاصطناعي يطورون خوارزمية جديدة قادرة على تحليل حزم بيانات ضخمة…
اقرأ المزيدتواصل مع شئون الكلية
مهتم بالعمل مع أعضاء هيئة التدريس لديناقم بتعبئة النموذج أدناه وسنقوم بالرد عليك.