WEBINAR / EVENT
Where Data Meets Decisions: Part 2
See several of our newest (and free) educational examples that students and instructors can use to learn and teach real-world applications of combined data science and optimization problem solving.
March 28 2023
WEBINAR / EVENT
Where Data Meets Decisions: Part 2
See several of our newest (and free) educational examples that students and instructors can use to learn and teach real-world applications of combined data science and optimization problem solving.
March 28 2023
WEBINAR / EVENT
Where Data Meets Decisions: Part 2
See several of our newest (and free) educational examples that students and instructors can use to learn and teach real-world applications of combined data science and optimization problem solving.
March 28 2023
Event Recap
More New Python Notebook Examples that Combine Data Science and Mathematical Optimization
How can you use different prediction models for price optimization and to keep avocado toast on your breakfast menu? How can you identify plagiarism with text similarity? How can you effectively plan for airline disruption in a time of continual flight delays and cancelations?
By combining data science tools and mathematical optimization.
In this session, Gurobi introduces several of our newest (and free) educational examples that students and instructors can use to learn and teach real-world applications of combined data science and optimization problem solving. We review our new data science library of Python Notebook Examples that combine data science tools and prescriptive analytics and offer new data science learners an entry point into problem-solving with optimization.
Presented Materials:
Download the presentation, here.
The Colab Notebooks that we reviewed in the session can be found by visiting:
Airline Planning After Flight Disruption
Event Recap
More New Python Notebook Examples that Combine Data Science and Mathematical Optimization
How can you use different prediction models for price optimization and to keep avocado toast on your breakfast menu? How can you identify plagiarism with text similarity? How can you effectively plan for airline disruption in a time of continual flight delays and cancelations?
By combining data science tools and mathematical optimization.
In this session, Gurobi introduces several of our newest (and free) educational examples that students and instructors can use to learn and teach real-world applications of combined data science and optimization problem solving. We review our new data science library of Python Notebook Examples that combine data science tools and prescriptive analytics and offer new data science learners an entry point into problem-solving with optimization.
Presented Materials:
Download the presentation, here.
The Colab Notebooks that we reviewed in the session can be found by visiting:
Airline Planning After Flight Disruption
Event Recap
More New Python Notebook Examples that Combine Data Science and Mathematical Optimization
How can you use different prediction models for price optimization and to keep avocado toast on your breakfast menu? How can you identify plagiarism with text similarity? How can you effectively plan for airline disruption in a time of continual flight delays and cancelations?
By combining data science tools and mathematical optimization.
In this session, Gurobi introduces several of our newest (and free) educational examples that students and instructors can use to learn and teach real-world applications of combined data science and optimization problem solving. We review our new data science library of Python Notebook Examples that combine data science tools and prescriptive analytics and offer new data science learners an entry point into problem-solving with optimization.
Presented Materials:
Download the presentation, here.
The Colab Notebooks that we reviewed in the session can be found by visiting:
Airline Planning After Flight Disruption
Speakers
Meet Your Expert Speaker
Learn from the best in the industry, bringing years of experience and groundbreaking insights to the forefront of AI personalization.
Jerry Yurchisin
Senior Data Science Strategist
Mr. Yurchisin has over ten years’ experience applying operations research, machine learning, statistics, and data visualization to improve decision making. Before joining Gurobi, Jerry (who also goes by Jerome) was a Senior Consultant at OnLocation, Inc. where he customized several linear programming models within the National Energy Modeling System (NEMS) to analyze implementing specific energy policies and utilizing new technologies.
Prior to OnLocation, Jerry was an Operations Research Analyst & Data Scientist at Booz Allen Hamilton for over seven years. There he formulated scheduling and staffing integer programming models for the US Coast Guard, as well as led a project to quantify the maritime risks of offshore energy installations with the Research & Development Center. Further, Jerry was the technical lead on several Coast Guard studies including Living Marine Resources and Maritime Domain Awareness, providing statistical analysis and building supervised and unsupervised machine learning models. He also performed statistical analyses, machine learning modeling, and data visualization for cyberspace directorates at DoD and DHS.
Jerry has several years of experience teaching a wide variety of college-level mathematics and statistics courses and has a passion for education. He also enjoys golfing, biking, and writing about sports from an analytics point of view. He lives in Alexandria, Virginia with his wife, son, and two dogs.
Jerry holds B.S., Ed. and M.S., Mathematics degrees from Ohio University and an M.S. in Operations Research and Statistics from The University of North Carolina at Chapel Hill.
Rahul Swamy
Data Science Intern, Gurobi Optimization
Rahul Swamy is a researcher passionate about creating innovative tools that combine machine learning and mathematical optimization. During his current Ph.D. in Operations Research at UIUC, his work in mathematical optimization and game theory has led to publications in journals such as Operations Research and the Journal of Combinatorial Optimization. His work on fairness-optimized political redistricting has received honors such as First Place in the 2019 INFORMS Service Science Best Paper Award. In his free time, Rahul enjoys backpacking and performing improv.
Speakers
Meet Your Expert Speaker
Learn from the best in the industry, bringing years of experience and groundbreaking insights to the forefront of AI personalization.
Jerry Yurchisin
Senior Data Science Strategist
Mr. Yurchisin has over ten years’ experience applying operations research, machine learning, statistics, and data visualization to improve decision making. Before joining Gurobi, Jerry (who also goes by Jerome) was a Senior Consultant at OnLocation, Inc. where he customized several linear programming models within the National Energy Modeling System (NEMS) to analyze implementing specific energy policies and utilizing new technologies.
Prior to OnLocation, Jerry was an Operations Research Analyst & Data Scientist at Booz Allen Hamilton for over seven years. There he formulated scheduling and staffing integer programming models for the US Coast Guard, as well as led a project to quantify the maritime risks of offshore energy installations with the Research & Development Center. Further, Jerry was the technical lead on several Coast Guard studies including Living Marine Resources and Maritime Domain Awareness, providing statistical analysis and building supervised and unsupervised machine learning models. He also performed statistical analyses, machine learning modeling, and data visualization for cyberspace directorates at DoD and DHS.
Jerry has several years of experience teaching a wide variety of college-level mathematics and statistics courses and has a passion for education. He also enjoys golfing, biking, and writing about sports from an analytics point of view. He lives in Alexandria, Virginia with his wife, son, and two dogs.
Jerry holds B.S., Ed. and M.S., Mathematics degrees from Ohio University and an M.S. in Operations Research and Statistics from The University of North Carolina at Chapel Hill.
Rahul Swamy
Data Science Intern, Gurobi Optimization
Rahul Swamy is a researcher passionate about creating innovative tools that combine machine learning and mathematical optimization. During his current Ph.D. in Operations Research at UIUC, his work in mathematical optimization and game theory has led to publications in journals such as Operations Research and the Journal of Combinatorial Optimization. His work on fairness-optimized political redistricting has received honors such as First Place in the 2019 INFORMS Service Science Best Paper Award. In his free time, Rahul enjoys backpacking and performing improv.
Speakers
Meet Your Expert Speaker
Learn from the best in the industry, bringing years of experience and groundbreaking insights to the forefront of AI personalization.
Senior Data Science Strategist
Jerry Yurchisin
Mr. Yurchisin has over ten years’ experience applying operations research, machine learning, statistics, and data visualization to improve decision making. Before joining Gurobi, Jerry (who also goes by Jerome) was a Senior Consultant at OnLocation, Inc. where he customized several linear programming models within the National Energy Modeling System (NEMS) to analyze implementing specific energy policies and utilizing new technologies.
Prior to OnLocation, Jerry was an Operations Research Analyst & Data Scientist at Booz Allen Hamilton for over seven years. There he formulated scheduling and staffing integer programming models for the US Coast Guard, as well as led a project to quantify the maritime risks of offshore energy installations with the Research & Development Center. Further, Jerry was the technical lead on several Coast Guard studies including Living Marine Resources and Maritime Domain Awareness, providing statistical analysis and building supervised and unsupervised machine learning models. He also performed statistical analyses, machine learning modeling, and data visualization for cyberspace directorates at DoD and DHS.
Jerry has several years of experience teaching a wide variety of college-level mathematics and statistics courses and has a passion for education. He also enjoys golfing, biking, and writing about sports from an analytics point of view. He lives in Alexandria, Virginia with his wife, son, and two dogs.
Jerry holds B.S., Ed. and M.S., Mathematics degrees from Ohio University and an M.S. in Operations Research and Statistics from The University of North Carolina at Chapel Hill.
Data Science Intern, Gurobi Optimization
Rahul Swamy
Rahul Swamy is a researcher passionate about creating innovative tools that combine machine learning and mathematical optimization. During his current Ph.D. in Operations Research at UIUC, his work in mathematical optimization and game theory has led to publications in journals such as Operations Research and the Journal of Combinatorial Optimization. His work on fairness-optimized political redistricting has received honors such as First Place in the 2019 INFORMS Service Science Best Paper Award. In his free time, Rahul enjoys backpacking and performing improv.
