New York University Junior Academy Competition

The Junior Academy is a project-based learning program where students form international teams and work with STEM experts through an online community platform. Students participate in innovation challenges where they collaborate under the guidance of STEM mentors to design solutions to real-world problems. Students and mentors can participate from anywhere in the world.

Challenges are sponsored by industry-leading companies and are preceded by a kick-off week, which provides preparation for the challenges and builds relevant skills in areas such as research methods, design thinking and data analysis. Once a challenge begins, students self-select into teams and gain access to STEM experts, who serve as mentors, guiding teams throughout the challenge process. Additional STEM professionals serve as judges who score each solution and choose a winning team. 

My Experience

Participating in the New York Academy of Sciences' Junior Academy was a transformative experience for me during my 11th grade, not only because of the program's prestigious nature but also due to the incredible learning journey it offered. With an acceptance rate of just 10%, being selected for this global STEM community was an honour in itself. The Junior Academy provides students with the opportunity to collaborate with peers from across the world and work alongside STEM experts on solving real-world problems. It’s a platform designed to challenge, nurture, and grow young innovators through project-based learning and team-driven problem-solving.

I was the team lead of Mineral Mavericks, leading our efforts in the Fall 2023 Innovation Challenge: Minerals of Technology. Our mission was to tackle the critical issue of securing mineral supplies in the transition towards a fossil-free society. The challenge was centred on finding innovative ways to use, recycle, and conserve critical minerals necessary for green technologies like electric vehicles and solar panels. Given the increased demand for these minerals and their non-renewable nature, the task demanded not only creativity but also a deep understanding of sustainability and resource management.

Our proposed solution focused on leveraging AI to help manufacturers optimise their use of critical minerals. As outlined in our milestone submission, we brainstormed the idea of an AI-driven model that could analyse the specifications of a product and suggest alternative materials such as graphene where applicable. This AI would not only identify areas where critical minerals could be replaced with more sustainable alternatives but also guide firms through the legal and logistical hurdles involved in sourcing these alternatives. By integrating AI, science, and economics, we aimed to help industries minimise their dependence on these minerals, making strides toward a more sustainable future.

The Junior Academy experience helped me grow in ways I didn’t expect. Being the team lead honed my leadership skills as I coordinated efforts across an international team. Working on a complex problem with tangible, global implications pushed me to think critically, collaborate effectively, and develop solutions that go beyond the classroom. I’m particularly proud of the sense of accomplishment that came from creating something that addresses such a significant issue, and I firmly believe that this challenge strengthened both my problem-solving skills and my passion for innovation. This achievement stands out as a milestone in my personal and academic growth, and I look forward to applying the lessons I’ve learned to future endeavours.

My Team - Mineral Mavericks

As mentioned before, our solution would mainly target figuring out how to create new technologies in a more innovative way where the same minerals aren't needed to the same extent as they are currently.

Our hypothesis is that the implementation of AI based technologies to select effective alternative materials to replace components of existing technologies, would enable a sustainable and fruitful transition into a world that grows more dependent on critical minerals.

We would test this by developing a strongly structured flow chart and model designs of the AI model that would solve the problem as stated in the previous part of our answer.

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