- Kun Qian: “AI赋能脑健康工程“, in Lecture Series for the 1st Summer Camp of Excellent Undergraduate Students for School of Medical Technology, Beijing Institute of Technology (BIT), invited by BIT, Beijing, China, July 15th, 2022.
- Kun Qian: “Computer Audition: A Novel Venue in Digital Health（计算机听觉：数字健康的新领域）“, in Lecture Series for the 4th Summer School of Human-Computer Interaction and Film Technology, invited by Xiamen University, Xiamen, China, July 15th, 2022.
- Kun Qian: “Computer Audition and AIoT: Towards Intelligent Medicine（计算机听觉和人工智能物联网：迈向智慧医学）“, invited by BIT Zhengzhou Academy of Intelligent Technology, Zhengzhou, China, May 26th, 2022.
- Kun Qian: “爱上脑科学——AI领域的前沿探索”, invited by Sichuan Normal University, Chengdu, China, May 20th, 2022.
- Kun Qian: “Could Computer Audition and AIoT Contribute to Digital Health? Perspectives and Insights（计算机听觉和人工智能物联网可以为数字医学贡献力量吗？前瞻与观点）“, invited by Shenzhen MSU-BIT University (SMBU), Shenzhen, April 2nd, 2022.
- Kun Qian: “Artificial Intelligence for Medicine: Insights and Perspectives from Computer Audition（人工智能医学：计算机听觉的视角与观点）“, invited by Centre for Education and Examination of the Ministry of Industry and Information Technology of the People’s Republic of China, Beijing, China, March 11th, 2022.
- Kun Qian: “Intelligent Medicine: A View of Computer Audition and AIoT（智慧医学：关于计算机听觉和人工智能物联网）“, invited by South China University of Technology, Guangzhou, China, December 14th, 2021.
- Kun Qian: “让机器可以聆听世界——计算机听觉与脑健康” in the Lecture Series of Brain Sciences, invited by XUTELI School at Beijing Institute of Technology (for the most excellent undergraduates at BIT), Beijing, China, December 8th, 2021.
- Kun Qian: “How Machine Intelligence Works for Healthcare: Perspectives from Computer Audition and AIoT（机器智能如何用于医疗健康：来自计算机听觉和人工智能物联网的观点）“, invited by TUM Beijing-TUM Global & Alumni Office, Beijing, China, December 5th, 2021.
- Kun Qian: “Could Audio be a Novel Digital Phenotype? Perspectives and Challenges（音频可以成为一种新的数字表型吗？前景与挑战）“, invited by Gesellschaft Chinesischer Informatiker in Deutschland e.V. (GCI), Magdeburg, Germany, November 20th, 2021.
- Kun Qian: “Aiming for a Better Life via Machine Intelligence: From Computer Audition to AIoT（通过机器智能面向更美好的生活：从计算机听觉到人工智能物联网）“, invited by Xidian University, Xi’an, China, August 26th, 2021.
- Kun Qian: “Human-Centered Computer Audition: Exploring the Frontiers（以人为中心的计算机听觉：探索前沿）“, invited by Shandong University, Jinan, China, October 17th, 2020.
- Kun Qian: “Computer Audition for Healthcare: A Time for Leveraging the Power of AI（基于机器听觉的健康医疗：一个AI赋能的时代）“, invited by Shenzhen University General Hospital, Shenzhen, China, September 10th, 2020.
- Kun Qian: “A.I. Betters Our Life: Applications from General Audio to Wearable Data“, invited by Kyushu University, Fukuoka, Japan, November 7th, 2019.
- Kun Qian: “A.I.4Sound: Healthcare, Ecology, and Security“, invited by Xi’an Jiao Tong University, Xi’an, P. R. China, April 12th, 2019.
- Kun Qian: “A.I.4Healthcare: On the Way from Audio to Spontaneous Physical Activity“, invited by Shanghai University, Shanghai, China, April 10th, 2019.
- Kun Qian: “Teaching Machines on Snoring: AI-based Methods for Localisation of Snore Sound’s Excitation“, invited by Waseda University, Tokyo, Japan, December 8th, 2018.
- Kun Qian: “Machine Listening for Applications in Healthcare and Ecology“, invited by Tsinghua University, Beijing, China, October 22nd, 2018.
- Kun Qian: “Recent Developments in Machine Listening for Localisation of Snoring“, invited by Chongqing University, Chongqing, China, October 10th, 2018.
- Kun Qian, Christoph Janott: “Snore Sound Classification for Diagnosis and Surgical Plan on Obstructive Sleep Apnea“, invited by Shanghai University, Shanghai, China, March 23rd, 2016.
- Kun Qian: “Bird Sound Recognition via Extreme Learning Machines“, invited by Shanghai Jiao Tong University, Shanghai, China, March 21st, 2016.
- Kun Qian: “Cloud-based System for Processing Snore Related Signals“, invited by Shanghai Jiao Tong University, Shanghai, China, July 23rd, 2013.
- Kun Qian: “Preliminary Study About Acoustic Features of Snore Signals“, invited by Hohai University, Nanjing, China, December 17th, 2012.