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Burcin Bozkaya
Burcin Bozkaya

Burcin Bozkaya

Sr. Developer Relations Manager
NVIDIA Corporation
Bio

Dr. Burcin Bozkaya is a Sr. Developer Relations Manager at NIVIDA, enabling the AI ecosystem with GPU accelerated software stack, including NVIDIA cuOpt for open-source accelerated decision intelligence, NVIDIA inference microservices for GenAI and RAG, NVIDIA blueprints and more. Dr. Bozkaya holds a doctoral degree in Management Science from University of Alberta, Canada, specializing in combinatorial optimization problems and heuristic optimization. As the Developer Relations lead for decision intelligence, Dr. Bozkaya engages with the developer ecosystem to evangelize and support the open-source community, major optimization ISV partners and key business planners for developing and deploying accelerated optimization solvers.
Prior to joining NVIDIA, Dr. Bozkaya was a Professor and Director of Data Science at New College of Florida, Visiting Professor at MIT Media Lab, Professor of Business Analytics and Operations Management at Sabanci Business School in Istanbul, Türkiye, and co-founder and co-director of Behavioral Analytics of Visualization Lab at Sabanci University, co-founded with MIT Media Lab, and also took on administrative roles as Associate Dean at Sabanci Business School, Director of Sabanci MBA Program and Co-Director of Sabanci ITM Program. Dr. Bozkaya is an author of 50+ peer-reviewed academic articles in reputable journals such as Nature Communications, Nature Scientific Reports, Expert Systems with Applications and Computers & OR.


The Next Era in Decision Intelligence: GenAI-Enabled Accelerated Decision Optimization

The recent rise of generative AI and the widespread use of GPUs for many compute-heavy tasks have opened new opportunities for the decision intelligence community. Decision optimization solver developers can now take advantage of emerging techniques for accelerated optimization on GPUs, solving harder and larger math optimization problems with unmatched speed. Generative AI, in turn, can help decision makers interact with solvers, build and run optimization models using natural language, understand and interpret optimization results, and conduct scenario analysis again in natural language. In this talk, we will cover these two phenomena, giving rise to a new era in decision intelligence with examples from research and industrial communities.

Examples will include large language models that can reason to translate a modeler’s natural language prompts into executable optimization models in various languages, GPU-accelerated solver algorithms that can provide near-real time responses, allowing agile what-if and scenario analyses, and more. The talk will conclude with insights and takeaways for early-career researchers and professionals, as well as seasoned practitioners, to hop on this journey and take part in this new era in decision intelligence.

Essential / Professional / Leadership