Parul
Gupta
Production Engineer at Meta
"Early Career Mentorship: My Journey from Mentee to Mentor"
"Early Career Mentorship: My Journey from Mentee to Mentor"
11 - 4:10 PM EDT/New York (See in local time)
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05//2025 4:10 PM
05//2025 04:20 PM
America/New_York
#WTGC2025
"Early Career Mentorship: My Journey from Mentee to Mentor"
#WTGC2025
"Early Career Mentorship: My Journey from Mentee to Mentor"
https://www.womentech.net/ringcentral
https://www.womentech.net/ringcentral
"Early Career Mentorship: My Journey from Mentee to Mentor"
"Early Career Mentorship: My Journey from Mentee to Mentor"
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Session: Early Career Mentorship: My Journey from Mentee to Mentor
As a female in tech, I learnt about mentorship opportunities the hard way -- purely through personal experience. I hoped someone had told me about what to expect and how to approach others sooner to excel and utilize my strong skillsets in most effective manner.Through this talk, I will discuss my personal recollections of the myths and realities of mentoring, its importance in early career and fruitful mentoring experiences in my career journey so far.
Additionally, I want to inspire the young female computer enthusiasts to get involved in mentorship, both as a mentee and a mentor, grow their network and set themselves up for success through strong mentoring relationships.
Key Takeaways
- Help will be given to those who ASK
- Grow your network to build your tomorrow
- Have multiple mentors from different areas to provide different types of support
- Start mentoring and give back to society
Bio
Parul is a Production Engineer at Meta with the focus on interactive computing. She graduated from University of Massachusetts Amherst with a masters degree in computer science.She aspires to help bridge the gaps across the genders in the field of technology. She has also mentored aspiring female students and computer science enthusiasts in various early career programs, including non-profit organizations.
Her tech work outside of Meta also reflects the same vision as she is a proud contributor of Fairlearn, an open-source project to help data scientists improve fairness of AI systems.
Outside of work, she enjoys dancing, painting and traveling.
