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Seminar

AIcrowd : Crowdsourcing Artificial Intelligence to Solve Real-World problems
AIcrowd : Crowdsourcing Artificial Intelligence to Solve Real-World problems

26/May/2022
26/May/2022

Speaker:

Sharada Mohanty
Sharada Mohanty

Institution:

AIcrowd
AIcrowd

Language :

EN
EN

Type :

Hybrid
Hybrid

Description:

TBA

Initially started as a project at EPFL, Switzerland, AIcrowd is a community of ~60,000 AI researchers all over the world, who come together to solve real world problems to win cash prizes, travel grants, co-authorships in research papers. At AIcrowd, we use competitions and benchmarks to build meaningful research communities which can come together while they collaborate and compete to push the state of art in Artificial Intelligence Research. The long term vision is to evolve into a giant distributed research lab, which celebrates community led research, for the community by the community. 

Sharada Mohanty is the CEO and Founder of AIcrowd, a platform for crowdsourcing Artificial Intelligence for real world problems. His research focuses on using Artificial Intelligence for diagnosing plant diseases, teaching simulated skeletons how to walk, scheduling trains in simulated railway networks, and on AI agents which can perform complex tasks in Minecraft. 

He is extremely passionate about benchmarks and building communities. He has led the design and execution of many large-scale machine learning competitions and benchmarks, such as NeurIPS 2017: Learning to Run Challenge, NeurIPS 2018: AI for Prosthetics Challenge, NeurIPS 2018: Adversarial Vision Challenge, NeurIPS 2019: MineRL Competition, NeurIPS 2019: Disentanglement Challenge, NeurIPS 2020: Flatland Competition, NeurIPS 2020: Procgen Competition, NeurIPS 2021 NetHack Challenge, to name a few.

During his Ph.D. at EPFL, he worked on numerous problems at the intersection of AI and health, with a strong interest in reinforcement learning. In his previous roles, he has worked at the Theoretical Physics department at CERN on crowdsourcing compute for PYTHIA powered Monte-Carlo simulations; he has had a brief stint at UNOSAT building GeoTag-X, a platform for crowdsourcing analysis of media coming out of disasters to assist in disaster relief efforts. In his current role, he focuses on building better engineering tools for AI researchers and making research in AI accessible to a larger community of engineers.

Initially started as a project at EPFL, Switzerland, AIcrowd is a community of ~60,000 AI researchers all over the world, who come together to solve real world problems to win cash prizes, travel grants, co-authorships in research papers. At AIcrowd, we use competitions and benchmarks to build meaningful research communities which can come together while they collaborate and compete to push the state of art in Artificial Intelligence Research. The long term vision is to evolve into a giant distributed research lab, which celebrates community led research, for the community by the community. 

Sharada Mohanty is the CEO and Founder of AIcrowd, a platform for crowdsourcing Artificial Intelligence for real world problems. His research focuses on using Artificial Intelligence for diagnosing plant diseases, teaching simulated skeletons how to walk, scheduling trains in simulated railway networks, and on AI agents which can perform complex tasks in Minecraft. 

He is extremely passionate about benchmarks and building communities. He has led the design and execution of many large-scale machine learning competitions and benchmarks, such as NeurIPS 2017: Learning to Run Challenge, NeurIPS 2018: AI for Prosthetics Challenge, NeurIPS 2018: Adversarial Vision Challenge, NeurIPS 2019: MineRL Competition, NeurIPS 2019: Disentanglement Challenge, NeurIPS 2020: Flatland Competition, NeurIPS 2020: Procgen Competition, NeurIPS 2021 NetHack Challenge, to name a few.

During his Ph.D. at EPFL, he worked on numerous problems at the intersection of AI and health, with a strong interest in reinforcement learning. In his previous roles, he has worked at the Theoretical Physics department at CERN on crowdsourcing compute for PYTHIA powered Monte-Carlo simulations; he has had a brief stint at UNOSAT building GeoTag-X, a platform for crowdsourcing analysis of media coming out of disasters to assist in disaster relief efforts. In his current role, he focuses on building better engineering tools for AI researchers and making research in AI accessible to a larger community of engineers.