Abstract: The physical division of labor barriers formed in the agricultural era are gradually being dissolved with the iteration from the industrial revolution to AI technology. As scientific research is a field that highly depends on cognitive abilities, female scholars still need to face the unique social barriers brought by the hidden shackles left by historical divisions in their pursuit of academic dreams. This report will explore how female scholars can grow resiliently and pursue their dreams in work and life during the AI era, in the process of developing institutional affirmative action measures.

Speaker Bio: Guihua Shan, Researcher and doctoral supervisor at the Computer Network Information Center, Chinese Academy of Sciences, Director of the Advanced Interactive Technology and Application Development Department. Her research focuses on visualization and visual analytics, and intelligent interaction. In the past five years, she has led projects including National Key R&D Program subjects, key basic research project subjects, national major science and technology infrastructure projects, CAS knowledge innovation major project subjects, and CAS key deployment project subjects. She has published over 60 papers in important academic journals at home and abroad, applied for 16 national invention patents, and won the first prize of scientific and technological progress from the Command and Control Society. She has led the development of GPVis visualization framework software, supporting major national/local engineering construction, such as the National Major Science and Technology Infrastructure - Earth System Numerical Simulation Facility, Shanghai Astronomy Museum (the world's largest astronomy museum) - Astronomical Digital Laboratory, and CAS Pilot A Earth Big Data Science Engineering.

Abstract: In this report, I will share some of my experiences and insights on the path of scientific research. From the perspectives of "internal" self and "external" environment, I will discuss my understanding and insights on self-cultivation and team building in scientific research, and explore some common pitfalls that female researchers may fall into between these two aspects.

Speaker Bio: Min Lu, Associate Professor and doctoral supervisor at the Department of Urban Spatial Information Engineering, Shenzhen University, head of the Spatial Creative Intelligence and Interaction Research Group at Shenzhen University. Her research focuses on intelligent generation and interaction of spatial creativity such as stylized maps. In recent years, she has published multiple papers in international conferences such as SIGGRAPH, CVPR, VIS, and ACM CHI in the fields of graphics, computer vision, visualization, and human-computer interaction. She has led two National Natural Science Foundation projects and multiple projects from Guangdong Province and Shenzhen City. She has received awards including Best Paper Nomination at IEEE PacificVis 2024, Best Paper Nomination at Computational Visual Media 2020, Best Poster Award at IEEE PacificVis 2018, Best Paper Award at ICUI 2017, and Best Poster Award at ChinaVis 2016. She serves as a program committee member for conferences such as ACM SIGGRAPH Asia, IEEE PacificVis, and ChinaVis, and has long served as a reviewer for IEEE VIS, IEEE TVCG, and ACM TIST. For more information, please visit her personal homepage: https://deardeer.github.io/.

Abstract: This report will start from the research practice of color computing and scientific data visualization, extend to the collaborative interdisciplinary and PBL teaching methods built upon it, and share my growth experience in seeking balance between research and teaching - how to continue exploring under dual pressures, and how to gain reverse healing from students' trust and growth. From the "female perspective", those "glass hearts" that were once questioned have gradually settled into glimmers that illuminate others and oneself.

Speaker Bio: Qiong Zeng, Associate Professor and doctoral supervisor at the School of Computer Science and Technology, Shandong University, Deputy Director of the Computer Science Department, and member of the professor group for the computer-oriented top talent class at Taishan College. Her main research areas are color computing and scientific data visual analysis. She has led 5 projects including National Natural Science Foundation, National Key R&D Program sub-projects, and Provincial Natural Science Foundation. She has published over 20 papers in high-level domestic and international conferences and journals such as ACM CHI, IEEE TVCG, and CVMJ. She won the championship of IEEE VIS 2024 Scientific Visualization Challenge and the Best Paper Award at the Chinese Intelligent Robot Academic Conference; she also received the third prize in the National University Teachers' Teaching Innovation Competition (Shandong Division), the special prize for Teaching Achievement Award from Shandong Artificial Intelligence Society, and the first prize for Teaching Achievement Award from Shandong University.

Abstract: As an art and design worker, I will share my perceptual journey regarding the role and identity of "women" - from self-gender bias and avoidance of being defined, to objectively confronting gender differences and characteristics, to attempting to transcend gender attributes.

Speaker Bio: Jingjing Wei, Associate Professor at the School of Design, Nanjing University of the Arts, master's supervisor, PhD from Central Academy of Fine Arts, and committee member of the Visualization and Visual Analytics Committee of the Chinese Society for Image and Graphics. Her main research areas are data visualization design, visual communication design, and media art design. In the field of data visualization design, she has led and participated in multiple national, provincial, and municipal projects, published over ten papers, won multiple national awards for her works, and received over twenty national, provincial, and municipal competition awards for course achievements. She has participated in data visualization design projects at universities such as the Central Academy of Fine Arts.