Maya always straddled two worlds—equally at home in math class and psych lab. She’s now in year 2 of her PhD, building segmentation models and explaining PCA to undergrads. She loves when code makes neurons “pop” into clarity. She's not always sure her work counts when she’s not slicing brains or running gels—but she's finding her place.
Background
Majored in psychology and mathematics
First in her family to pursue a PhD
Volunteered at mental health clinics
Passionate about machine learning since undergrad
Enjoys mentoring fellow students
Current Situation
Second-year PhD in computational neuroscience
Developing segmentation models for EM data
Mentors an undergraduate student
Attends cross-lab reading groups
Exploring career paths in academia and industry
🎯 Maya's Goals
Maya is eager to shape her research path and support others along the way:
🔬 Short-term (This Year)
Submit a first-author paper on segmentation methods
Improve deep learning skills and experiment tracking
Publish a toolbox for EM analysis
Balance coursework with research deadlines
Expand professional network
🎓 Medium-term (Next 2–3 Years)
Finish PhD with a strong publication record
Speak at major conferences
Take on additional mentoring roles
Collaborate with neurotech companies
Clarify long-term career direction
🚀 Long-term (5+ Years)
Lead a research group bridging ML and neuroscience
Develop open-source tools for connectomics
Promote diversity and mentorship in the field
Advance multi-modal neural analysis
Create accessible training opportunities
💪 Strengths & Challenges
Maya excels at building bridges across disciplines but still faces obstacles:
✨ Strengths
🧠 Cross-disciplinary Knowledge
Combines psychology, math, and computer science to tackle complex problems from multiple angles.
🤝 Collaborative Spirit
Enjoys working with researchers from different backgrounds and helps newcomers feel welcome.
🗣 Clear Communicator
Breaks down technical concepts so that both biologists and computer scientists can follow.
⚡ Challenges
🎯 Balancing Directions
Juggling multiple research interests sometimes scatters her focus.
🔎 Career Uncertainty
Unsure whether to pursue academia or industry and how to prepare for both paths.
Key Insights
Inner Conflict
Wants to help others but worries she’s still too new herself
Torn between staying in academia or joining a neurotech startup
Feels pressure to always be “the explainer” in cross-disciplinary settings
Journey Markers
Published reusable Jupyter template for EM visualization
Presented on model error modes at a neuroML workshop
Started mentoring Julian—and learned as much as she taught
Growth Path
Learns to embrace partial knowledge
Gains feedback literacy through peer review
Realizes her impact comes from enabling others as much as producing code
