Full S.T.E.A.M. Ahead is led by a team of three siblings, each with their own unique skill set that together empower their world. Together they have championed in many STEAM-based competitions, developed innovative solutions to real world problems and shared their passion of STEAM with others through team development and workshops they have run. 

Amelia Munday

Co-Founder of Full S.T.E.A.M. Ahead
eSafety Commissioner Youth Advisory Council Member
Little Butterflies Founding Member
Tech Girl Ambassador
FLL Team Apollo Founding Member

Amelia is the team leader and the brains behind all things tech for the team’s innovations. Amelia developed a love of coding and all things science at an early age and this passion has driven her to achieve international success with the teams’ innovations as well as be a top 10 finalist in the 2021 NSW Women of the Year – One to Watch category and a 2022 Young Australian of the Year Finalist. Her abilities have also provided opportunity for early entry into university at the age of 13. She is currently studying a Bachelor of Medical Science and Bachelor of Cognitive and Brain Sciences at Macquarie University. The knowledge gained through these degrees coupled with her STEAM skills will enable Amelia to fulfill her goal of developing tech that supports an inclusive world for neurodiverse indviduals.  

Addison Munday

Co-Founder of Full S.T.E.A.M. Ahead
eSafety Commissioner Youth Advisory Council Member
Little Butterflies Founding Member
Tech Girl Ambassador
FLL Team Apollo Member

Addison is the team’s business manager and PR extraordinaire. She brings to the team a collection of valuable skills such as the ability to talk to anyone about anything, negotiate any deal, perceive the needs of others and entreprenurial skills that could match the best. Her own neurodiverse profile also allows her to think WAY outside the box and discover solutions to problems so unique. Addison loves the opportunity to share the team’s innovations at any time and is always looking for ways to improve and promote the team’s achievements. She is also invaluable to the team when running the team’s learning programs for other students in that she allows others to see that obscure ideas are usually the best and can break process down into new ways of thinking. 

Jacob Munday

Co-Founder of Full S.T.E.A.M. Ahead
FLL Team Apollo Founding Member

Jacob is the team’s graphic designer and master builder (mechanical engineer). With a love of drawing and design, and an eye for detail, Jacob enjoys creating the visual image of the team’s innovations, considering the UX and the overall final product. He also enjoys the challenge of designing and building the physical products for the team whether that be building robots out of Lego or constructing a circuit on an Arduino. Jacob’s own neurodiversity has not only inspired many of the team’s innovations but also provided a unique insider view of the effectiveness and significant impact the team’s innovations can make for neurodiverse individuals. This also allows an inclusive approach to the learning programs developed by the team to inspire others enthusiasm for STEAM. 

Together, with friends from their local homeschool community, these three have formed international award-winning teams for a variety of STEAM based competitions. These include: 

  • FIRST® LEGO® League – Team Apollo   
  • Search for the Next Tech Girl Superhero  – Little Butterflies 

The team have also had remarkable success in pitching and developing their innovations.  These include: 

  • Talk to Hand – Learn Auslan; an app that teaches individual’s Auslan (Australian Sign Language) through videos, games, songs, and quizzes. 
  • Talk to the Hand – My bucket’s Full – an app for individuals with Sensory Processing dysfunction providing a sensory diet to alleviate sensory overload. 
  • AUS-Glove – an Auslan interpreting glove that allows individuals to communicate through sign, which then converts the sign to text on the user’s phone. 
  • AIIA – an artificial Intelligence Interpreter of Auslan – this device uses TensorFlow object detection models to teach the device through machine learning to recognize Auslan signs, convert that to text, then use a text to speech enabler so the intended message can be played as audio.  

Click here to find out more about the team’s innovations, or check out the awards we’ve won.