Amir came from the world of edge devices and object tracking. But when he saw a 3D fly brain reconstructed by a global team, he knew: this was the next frontier. He’s fluent in models and metrics, but unsure what a dendrite means. And he’s learning that science doesn’t move like startups do. But the challenge—that's the hook.
Background
PhD in computer vision
Five years in industry building ML systems
Contributor to several open-source projects
Minimal formal neuroscience training
Passionate about interdisciplinary work
Current Situation
Industry researcher exploring neuroscience collaborations
Self-studying neuro literature and attending seminars
Building models for large neural datasets
Balancing corporate objectives with academic curiosity
Expanding network with university labs
🎯 Amir's Goals
Amir wants to apply his industry skills while learning the language of neuroscience:
🔬 Short-term (This Year)
Grasp core neuroscience terminology
Prototype ML models for connectomics datasets
Attend a neuroscience conference
Connect with academic collaborators
Share progress through workshops
🎓 Medium-term (Next 2–3 Years)
Establish a cross-disciplinary research program
Co-author papers with neuroscientists
Develop tools for data integration
Mentor students bridging CS and neuroscience
Blend industry and academic perspectives
🚀 Long-term (5+ Years)
Lead a team applying AI to brain research
Create interpretable neural modeling frameworks
Support open science initiatives
Bridge industry and academia
Contribute to brain-inspired AI breakthroughs
💪 Strengths & Challenges
Amir brings technical expertise but must adapt to a new research culture:
✨ Strengths
💡 Machine Learning Mastery
Expertise in building scalable models and pipelines gives him an edge in analyzing big datasets.
🔧 Systems Thinking
Sees how pieces fit together and optimizes workflows efficiently.
⚡ Challenges
📖 Limited Neuroscience Background
Needs time to understand biology concepts that collaborators take for granted.
⏳ Adjusting Pace
Science often moves slower than industry projects, which can be frustrating.
Key Insights
Inner Conflict
Struggles to read dense neuro papers
Unsure when to push his tech or adapt it
Wants to contribute but not overstep
Journey Markers
Tuned a transformer model for segment consistency
Co-created a dashboard with a neuro postdoc to evaluate proofread merges
