Through their research, the entrants to the 2023 MIMO Symposium Poster Competition tackled challenges ranging from anomaly detection in manufacturing processes, to the optimized charing of fleets of electric vehicles, to the reduction of air pollution from manufacturing facilities. Each poster featured an innovative and unique application of advanced analytics, optimization, or AI to a complex operational challenge, with demonstrated impact. Congratulations to the winners of this year’s prizes!
- Zetta Prize: Best Application of AI in Industry
- Schneider Electric AI for Sustainability Prize: Best Application of AI to Accelerate Sustainability
- MIT-Pillar AI Collective Prize: Best Potential for Commercialization of AI Research or Technology
- Fan Favorites
Zetta Prize: Best Application of AI in Industry
The Zetta Prize is designed to grow the community of Al innovators intent on bridging the gap between what’s possible and the practical technologies to make it happen. This award not only honor’s the recipients for their applied use of Al to solve operational issues, but also for their commitment to improving industrial performance through cutting-edge technology. The intent of this recognition is to inspire researchers; open doors to future collaborations, research funding and job opportunities in operations; and create a ripple effect of positive impact for years to come.
First Place
Title: Physics-Based Planning for Automating Contact-Rich Assembly
Author(s): Yunsheng Tian
Runner Up
Title: Ingot AI: A computer vision software for monitoring construction waste
Author(s): Nikita Klimenko, David Linstone, Niklas Hageman and Mikita Shpakau
Schneider Electric AI for Sustainability Prize: Best Application of AI to Accelerate Sustainability
The Schneider Electric Sustainability Prize is designed to grow the community of innovators intent on finding and deploying positive solutions that address current and future challenges in energy and climate and to accelerate the contributions of AI to sustainability as they relate to manufacturing and operations. This award would not only honor the recipients for their novel use of AI to solve climate issues, but also for their commitment to making the world a more sustainable place through cutting-edge technology. The intent of this recognition is to open doors to future collaborations, job opportunities in sustainability, and funding for further research, creating a ripple effect of positive impact for years to come.
First Place
Title: Optimal Electric Vehicle Charging Schedule
Author(s): Paolo Luciano and Peter Jacobson
Runner Up
Title: Multi-Modal Transit Time Prediction for E-Commerce Fulfillment Optimization and Carbon Emissions Reduction
Author(s): Kathryn Angevine
MIT-Pillar AI Collective Prize: Best Potential for Commercialization of AI Research or Technology
The MIT-Pillar AI Collective Prize is a $12,000 Summer Fellowship to be awarded to an outstanding MIT student researching the practical applications of AI and machine learning, and addressing some of the biggest challenges and opportunities associated with the technology. The winner of the prize will get the opportunity to explore the commercialization of their research or technology and develop it further during the Summer of 2023. The award honors both the student’s exceptional skills in AI and the potential to take their research to market. Judges will also be awarding up to $15,000 in AWS Compute Credits, to the projects most deserving and most in need of additional compute funding. Through these recognitions, the MIT-Pillar AI Collective looks to foster entrepreneurship and the commercialization of AI research and technology.
Winner: Summer Fellowship
Title: Enhancing 7 Hospitals’ Operations: AI Decision Support Tool in Action
Author(s): Liangyuan Na
Winners: Compute Credits
Title: Physics-Based Planning for Automating Contact-Rich Assembly
Author(s): Yunsheng Tian
Title: P5: Predicting Polymer Properties and Processing with Physics-informed Reinforcement Learning for Biomanufacturing
Author(s): Paloma Gonzalez-Rojas and Neil Malur
Title: Ingot AI: A computer vision software for monitoring construction waste
Author(s): Nikita Klimenko, David Linstone, Niklas Hageman and Mikita Shpakau
Fan Favorites
Title: Predicting Medical Asset Manufacture Date
Author(s): Evan Marrone, Cameron Cubra, and Austin Ader
Title: Reducing Air Pollution in Industrial Operations with Artificial Intelligence
Author(s): Léonard Boussioux and Cynthia Zeng