Aleksandra Mojsilovic
Also known as Saška Mojsilović
Aleksandra Mojsilovic is a researcher whose work connects machine learning with trustworthy AI. She earned an image-processing PhD in Belgrade in 1997, joined IBM Research in 2000 and became an IBM Fellow in 2014. At IBM, she contributed to AI Fairness 360, AI Explainability 360 and FactSheets. IEEE named her a Fellow in 2017. In 2024, she coauthored Alignment Studio, an architecture for tuning language models to specific values and rules; as of October 2026, she is a Senior Director at Google.
Timeline
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1997
A PhD in image processing
She earns a PhD in image processing at the University of Belgrade in 1997.
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2000
Joining IBM Research
She joins IBM Research in 2000 and begins work on data science for enterprise clients.
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2014
An IBM Fellowship
She becomes an IBM Fellow in 2014, a distinction for sustained technical achievements and leadership.
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2017
An IEEE Fellowship
She becomes an IEEE Fellow in 2017 for contributions to image analysis, data mining and business analytics.
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2018–2019
AI Fairness 360
She is part of the team that releases AI Fairness 360 in 2018, an open-source toolkit with metrics to detect unwanted bias and algorithms to mitigate it. In 2019, she coauthors an article that introduces the toolkit for algorithmic fairness.
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By 2023
Explainability and FactSheets
By 2023, her IBM group's trust work includes AI Explainability 360 and FactSheets for AI services. FactSheets give users label-like information about an AI system's training data, algorithms and bias checks.
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2024
Alignment Studio
She coauthors Alignment Studio in 2024, an architecture that lets application developers tune language models to specific values, social norms, laws and regulations.
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As of October 2026
Senior Director at Google
She is a Senior Director at Google in October 2026.
Career
- Since 2024GoogleSenior Director
- 2001–2024IBM
- From 2000IBM Research
- 1998–2000Nokia
Education
- 1997University of BelgradePhD in image processing
Most-cited works
- AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias
- AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias
- FactSheets: Increasing trust in AI services through supplier's declarations of conformity
- One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability TechniquesWith Pin-Yu Chen
- Adaptive perceptual color-texture image segmentation
Colleagues
Sources and credits
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- IBM’s Saška Mojsilović on her life in AI and recipes - IBM Research
- IBM Impact: Fellows
- 47 SPS Members Elevated to Fellow | IEEE Signal Processing Society
- Introducing AI Fairness 360
- AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias
- Alignment Studio: Aligning Large Language Models to Particular Contextual Regulations for IEEE Internet Computing - IBM Research
- Find Aleksandra Mojsilovic's email & phone number - Senior Director at Google, New York | SignalHire