Personal Profile:
College: Stanford University
Hometown: Springfield, VA
Major: Computer Science (4.02 GPA)
Major Influence: Grandmother, Aki
Personal Car: KIA Optima
10-Year Predictions: 1) Self-driving cars 2) Consumers select carbon minimizing routes 3) Dedicated race tracks for fun 4) Decline in road accident casualties
What You May Not Know About Me: On a quest, with friends, to try every boba tea shop in the South Bay Area. 20 down. More to go.
A Conversation with Arisa Chue:
How did you get so interested in cars/the auto industry?
I’ve always been fascinated by cars. I remember my dad would drive me in his 2-seater MR2, with me in the passenger seat, putting my hand on the gear shift as he rowed through the gears from 1-5, watching the tach spin and drop when he put the clutch in. My dad used to work on that car in the driveway and I would watch him explain the different, completely analog systems, from the Yamaha-built engine in the back to the spare wheel in the front.
So, when did it get serious for you?
I grew up thinking of cars as mechanical marvels, but things began to change when the industry evolved away from purely mechanical connections to more computers, drive-by-wire and sensors. When that happened, the automobile became a platform that could be abstracted by software. With today’s EVs, most of the car is controlled by software from a central console. And software happens to be an interest of mine. I’m working this summer at a startup that enables self-driving cars to better understand the intersection of maps and the input it obtains from its sensors, lidars and cameras in real-time.
What automotive aspect interests you most?
Data telemetry, sensor data, and the using AI and Machine Learning to drive the envelope of safety, performance and, perhaps even joy. The McLaren F1 has more than 300 sensors, with over 80,000 telemetry parameters, collecting 1.5 terabytes of data over a typical race weekend. We are not yet tapping the full possibilities of what such a data rich environment can mean for downstream applications: in areas such as efficiency, tuning, driver aids etc. I hope to play a part.
Talk about your enjoyment of motorsports.
Aside from the adrenaline rush of watching wheel-to-wheel racing, I am intrigued by applications for Artificial Intelligence (AI) and Machine Learning in motorsports. Motorsports is an industry that relies heavily on data and analytics to gain a competitive advantage. Milliseconds sometimes are the difference between a podium finish and an also-ran.
In design, AI helps in optimization of the sum of parts where millions of data points are taken into consideration. The design of a competitive model records data points from sensors that increasingly form the bulk of the vehicle. From wind-tunnel testing, to optimum weight-balance, to understanding minute differences in fuel-air mixtures, AI can analyze the data to derive optimum design decisions.
AI can even project, or manufacture data points, based on statistical linear-progression mathematical models. This cuts the development by a significant factor by only performing human and vehicle testing where necessary to train the model. This would shave time and cost from developing models and prototyping competition ideas and concepts.
In addition to vehicle design, AI can also be applied to optimize driver performance. Drivers are athletes: their performance, reaction times, hand-eye coordination effectiveness, driving lines taken, even biometric data input such as heart rates and blood pressure all help to provide insights into areas for improvement. AI algorithms can pinpoint such areas for driver feedback.
There are so many more use cases for the intersection of software and motorsports - it is such a rich data field.
How do you approach the challenges of being a minority engineering student in what has been traditionally a non-minority career path?
As a female studying Computer Science, I see this imbalance every day: 54% of the college cohort identifies as female but only 20% of all CS majors are women. This is reflected in industry as well: women make up 47% of the workforce but are still statistically underrepresented in STEM education and careers. Women make up 33% of Tech but only 3% of Tech companies have women CEOs.
One of the reasons there is gender inequality in STEM workplaces is perhaps because of a constrained pipeline. If we could do more to encourage girls to explore engineering careers early on, we might have better outcomes.
I have used my voice to advocate for change and raise awareness about the importance of gender diversity and inclusion. I have also joined and helped to create various groups that support and encourage women and other underrepresented groups in technology. Others have helped me along the way, I’ve always had strong mentors and role models who encouraged and inspired me. I hope to one day help and inspire other women.
About STEAM Sports Foundation
Recognizing workforce and economic development as integral parts of corporate growth, STEAM Sports Foundation works with companies, educators and sports groups to develop initiatives around science, technology, engineering, arts and math that impact the world of sports and entertainment. The foundation’s focus is on scholarships and career summits in an effort to help create tomorrow’s vibrant workforce. Its “Women of Color” scholarship program in automotive/motorsports engineering provides diversity to a transportation industry that is ever-changing via innovation and technology with individuals who traditionally did not consider these career paths simply because they saw few who looked like them in the industry. The foundation is located in Alpharetta, GA. Bob Dickinson is founder and executive director.
Donations can be made via PayPal. ACH transfers are available. Benevity registered.
FOR MORE INFORMATION: 770-815-0125 bob@steamsportsfoundation.org www.steamsportsfoundation.org
Comments