Profile Evaluation for Stanford and Berkley

[baffledfuturephd]

I have been long fascinated by the research work of a few Professors at Stanford and Berkeley. The areas are ML Systems and AI Fairness. I would love them as my PhD advisors, but as you may know, getting into these two universities for CS PhD is not easy. I plan to apply the next admissions cycle.

I am wondering if I am even remotely close to Stanford/Berkeley PhD applicant profile and if not, I am looking for a practical piece of advice that could help me make further progress. I am determined to improve myself to ultimately conduct research alongside folks I deeply respect.

My profile (briefly):

Research Experience:

• First-authored papers at applied AI/ML conferences and journals: ACM-BCB (~28% acceptance rate), JAMIA (~20%), AMIA Informatics Summit, etc. Around 65 citations so far
• Have unpublished/arXiv manuscripts in PL and type theory, GNNs, algorithmic fairness, and point-set topology (some with citations)
• 4 more AI/NLP papers in progress (3 of them first-authored). Hope to result in publications in AI/NLP conferences/journals

Work Experience:

• 9-month long research internship at the well-known research institution. Researched NLP and GNNs in healthcare applications
• Sequoia Capital-backed startup. Researched and implemented ambient intelligence and edge computing systems. I was a Research Engineer
• Currently, I work as an ML Research Scientist in academia

Teaching Experience:

• Sophomore: TA for Introduction to Computer Science (intro)
• Junior: TA for Object-Oriented Programming with Java (mid-level)
• Senior: TA for Computational Models (upper-level)
• As a part of my job, I have given guest lectures and mentored several students
• Also, co-authored MICS (regional teaching and CS conference) paper on making teaching CS more enjoyable!

Serving AI/CS Community and Other Community Contributions:

• Reviewer or subreviewer at ICLR, LREC, Big Data, etc
• Co-organizer and the Technology Chair of The 1st International Workshop on Ethics and Bias of Artificial Intelligence in Clinical Applications (EBAIC 2023)
• Presented my work at workshops and webinars
• I also have a YouTube channel, where I make videos about AI and Software Engineering

Education:

• Liberal arts college, magna cum laude with near-perfect CS GPA. Math honor society inductee

Other:

• Exceptional ability-based Green Card I-140 approval by the USCIS
• Recipient of 2 Dean's Office summer research awards
• Dean's List recipient for almost all semesters
• Recipient of multiple highly competitive scholarships
• Multiple-time finalist of national math Olympiad in my country of birth (TOP 6/7 was the highest rank)
• IMO and iPhO nominee for the national team in my country of birth
• Gold medal for academic excellence (middle/high school award, awarded to a handful of high school graduates every year)

Edited March 27, 2023 by baffledfuturephd
Specified what is MICS