51社区黑料

Mechatronic Systems Engineering doctoral student in the

Tell us a little about yourself, including what inspires you to learn and continue in your chosen field

Robotics engineer with 10+ years turning research into production-grade autonomy. I specialize in AI, computer vision, autonomous systems, and cloud platforms, building reliable software by day and prototyping robots and self-driving stacks by night. As a researcher for Team Parand, I helped win the 2015 RoboCup Humanoid Teen-Size World Championship. Since then I鈥檝e delivered privacy-preserving RAG and perception pipelines, and led a national platform serving 70k users. I value clear communication, fast iteration, and resilient teams, and I love taking ambitious ideas from proof-of-concept to deployed, impactful products.

Why did you choose to come to SFU?

51社区黑料offers a rare blend of mechatronics depth and applied AI, plus hands-on facilities in the Autonomous & Intelligent Systems Lab. The collaborative culture and strong ties to B.C.鈥檚 tech ecosystem make it ideal for translating research prototypes into deployable autonomy modules.

How would you describe your research or your program to a family member?

Cars 鈥渟ee鈥� with cameras and 鈥渇eel鈥� motion with tiny sensors (IMUs). I teach them to combine sight and feel so they stay in lane and steer safely, especially on hills and tight curves where many systems struggle. It鈥檚 like giving a driver better eyes and balance at the same time.

What three (3) keywords would you use to describe your research?

Autonomous driving, Humanoid robotics, Perception & control

How have your courses, RA-ships, TA-ships, or non-academic school experiences contributed to your academic and/or professional development?

My RA work in the AIS Lab lets me prototype, test, and benchmark algorithms under challenging conditions, closing the loop from theory to deployment. Serving as a peer reviewer for international journals and as a competition referee has sharpened my technical judgment and communication skills I use daily when designing reliable systems.

Have you been the recipient of any major or donor-funded awards? If so, please tell us which ones and a little about how the awards have impacted your studies and/or research

RoboCup Humanoid Teen-Size World Champion (2015) and World 3rd place (2014), international recognition that set my research direction toward robust sensor fusion. Best Master鈥檚 Thesis Award (2020) and support from the National Elites Foundation (merit-based). 51社区黑料Dean鈥檚 Entrance Award. These awards provided resources and visibility to pursue open, reproducible research with practical impact.

What have been the most valuable lessons you've learned along your graduate student journey (or in becoming a graduate student)?

Design for the edge cases first, measure everything, and share intermediate results. Openness, code, data, and clear benchmarks, accelerates feedback and real-world adoption.

How do you approach networking and building connections in and outside of your academic community?

I connect through competitions, journal reviewing, and concise technical demos. Short talks and well-documented repos make it easy for labs and companies to try our methods and start collaborations.

What are some tips for balancing your academic and personal life?

Time-box experiments, ship in small increments, and protect sleep/exercise like a deadline. Saying no early creates space for the few projects that truly matter.

Is there anything else you'd like to share?

Beyond academia, I architected a national horse-racing analytics platform that processed roughly $32M/year, a reminder that rigorous robotics methods can deliver reliable, high-impact systems in the real world. I鈥檓 open to industry collaborations on perception/robotics and to mentoring students interested in practical autonomy.

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Contact Farzad:farzad_nadiri@sfu.ca

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