Multidimensional signal processing, computer vision, AI for social good, AI ethics
Aleksandra (Saška) Mojsilović (born 1968) is a Serbian-American scientist. Her research interests are
artificial intelligence,
data science, and
signal processing. She is known for innovative applications of
machine learning to diverse societal and business problems. Her current research focuses on issues of fairness, accountability, transparency, and ethics in AI. She is an
IBM Fellow[1] and
IEEE Fellow.[2]
Education and career
Mojsilović was born in
Belgrade,
Serbia. She received her PhD in
Electrical Engineering in 1997 from the
University of Belgrade, Belgrade, Serbia. From 1997 to 1998, she was an assistant professor at the University of Belgrade. From 1998 to 2000, she was a Member of Technical Staff at the
Bell Laboratories, Murray Hill, New Jersey. She was at
IBM Research from 2000 to 2023. She is currently employed at Google as their Senior Director, Responsible AI. [3] Prior to joining Google, she led Trustworthy AI at
IBM Research and served as a co-director of IBM Science for Social Good.[4]
Research
Mojsilović's research interests include artificial intelligence, machine learning, multi-dimensional signal processing, and data science. She has applied her expertise to diverse application areas, including computer vision,[5][6][7] multimedia,[8] recommender systems,[9][10] medical diagnostics,[11][12] healthcare,[13] IT operations,[14] business analytics,[15] workforce analytics,[16] drug discovery,[17] disease ecology,[18] and most recently, COVID-19 response.[19][20] A substantial part of her research is focused on development of ethical, responsible, and beneficial AI systems. In 2015, with Kush Varshney, she created IBM Science for Social Good initiative as a way to promote and direct AI research and development towards applications that benefit humanity.[21][22] She was among the first researchers to call for transparent reporting on the development and deployment of AI models and systems.[23][24]
While at
IBM Research she helped create leading open source[25][26][27] and product capabilities[28][29][30][31] in support of fair, explainable, robust, transparent, and responsible AI. Most notable contributions include: AI Fairness 360,[25][32] a toolkit for mitigating bias in machine learning models, AI Explainability 360,[26][33] a toolkit for supporting explanations in AI models, and AI FactSheets 360,[34] an open research effort to foster trust in AI by increasing transparency and enabling governance.
Mojsilović serves on the Board of Directors of Neighborhood Trust Financial Partners, which provides financial literacy and economic empowerment training to low-income individuals.[47]
She lives in
New York City with her husband and daughter.
^Sindhwani, V.; Bucak, S. S.; Hu, J.; Mojsilovic, A., A Family of Non-negative Matrix Factorizations for One-Class Collaborative Filtering Problems,
CiteSeerX10.1.1.157.1873
^Bellamy, Rachel K. E.; Dey, Kuntal; Hind, Michael; Hoffman, Samuel C.; Houde, Stephanie; Kannan, Kalapriya; Lohia, Pranay; Martino, Jacquelyn; Mehta, Sameep; Mojsilovic, Aleksandra; Nagar, Seema (2018-10-03). "AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias".
arXiv:1810.01943 [
cs.AI].
^Arya, Vijay; Bellamy, Rachel K. E.; Chen, Pin-Yu; Dhurandhar, Amit; Hind, Michael; Hoffman, Samuel C.; Houde, Stephanie; Liao, Q. Vera; Luss, Ronny; Mojsilović, Aleksandra; Mourad, Sami (2019-09-14). "One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques".
arXiv:1909.03012 [
cs.AI].