Computational neuroscience × applied AI

A computational neuroscientist, building AI for brain prediction.

I help research, clinical, and pharma teams design how AI and foundation models work on neural data — and I'm building the platform that does it at scale.

Who I work with

A few kinds of teams sitting on neural data with something real to build.

Device & Platform Companies

Series A–C · FDA-track or CE-marked

  • You have hardware and neural signal data but no AI strategy
  • You need AI features that survive regulatory scrutiny
  • Your investors are asking about the AI roadmap
  • You want a cleared or clearable AI layer, not a prototype

Best fit

Fractional Chief AI Officer, with strategy up front

Primary focus

Clinical Researchers & Scientists

Academic labs · CROs · pharma R&D · hospital networks

  • Running trials with EEG, MEG, LFP, or implant data
  • Need biomarker models that hold up to peer review
  • Want predictive endpoints, not just descriptive stats
  • Building toward commercialization of research findings

Best fit

Research partnership, plus strategy on methodology

Entrepreneurs & Founders

Pre-seed–Series A · neurotechnology

  • Building a neurotech product for the first time
  • Need someone who knows both the neuroscience and the AI
  • Want to avoid costly bets before you've found PMF
  • Looking for a technical co-pilot, not a consulting deck

Best fit

Fractional Chief AI Officer, with strategy to de-risk

Services

How I work with teams

Three ways to bring me in — from a single strategic question to embedded leadership.

01

AI & brain-data strategy

Research leaders · clinical teams · pharma R&D

Before anyone writes a line of code, I help you figure out what's worth building — and how.

  • Where foundation models create real value in your data
  • A prioritized roadmap scoped to your goals
  • Methodology and study design you can trust
  • An honest read on what's feasible now vs. what isn't
02 Most common

Fractional Chief NeuroAI Officer

Teams building a brain-data capability without a full-time hire

I design the approach and direct the build. You get an architect, not just an advisor.

  • Technical direction and model architecture decisions
  • Hands-on analysis scoped to the right people
  • Translation between the science and the product
  • From first prototype to a result you can stand behind
03

Research partnership

Universities · hospitals · labs

I partner on the science — turning your data into peer-reviewed work and real capability.

  • Study design and analysis methodology
  • Co-authorship on resulting publications
  • Support on grants and joint proposals
  • Bridge between clinical questions and machine learning

What the engagement covers

From raw signal to production AI.

Everything neurotech research and clinical teams need — from first data audit to a system your engineers can own and operate.

01

Neural data & signal audit

I read your raw data, processing pipeline, and signal quality end-to-end — before any model is chosen or built.

02

Foundation model selection

Evaluate which models genuinely fit your biomarker task — separating real capability from benchmark performance.

03

Closed-loop AI systems

Build BCI and neuromodulation pipelines your team can own, iterate on, and take to the next regulatory milestone.

04

FDA & CE documentation

Prepare your AI documentation for regulatory submission — written by someone who understands both the algorithm and the pathway.

05

Roadmap & bet prioritization

Rank the right AI bets for your signal type, clinical context, and timeline — and name the wrong ones before they cost you.

06

Stakeholder translation

Turn neurotech AI into clear language your board, investors, and clinical leadership can act on — without losing the science.

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How an engagement runs

From inside,
not from a deck.

A four-phase engagement designed to make me redundant on purpose — your team owns it when we're done.

01 Week 1–2

Signal audit

I read your raw data, processing pipeline, and existing AI stack — before any model is chosen.

02 Week 3–4

Strategy memo

A ranked set of AI bets scoped to your signal type, regulatory path, and timeline — with the wrong ones named.

03 Month 2+

Embedded build

Two days a week alongside your team — building the system, not advising from the sidelines.

04 Ongoing

Handoff & ownership

Your team owns the system. I make myself redundant — that's the point.

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Marzieh Zare
30+
publications
430
citations · h9
12+
yrs experience

The practitioner

A decade at the intersection of neuroscience and applied AI.

I've spent my career at the intersection of neuroscience and applied AI — modeling brain dynamics and neural criticality, applying machine learning to real EEG data, and building production AI systems in industry, from multi-agent LLM systems to computer vision.

I know which approaches survive contact with real neural data, and which collapse the moment they meet your biology. I make the call from the signal, not from a vendor's benchmark sheet.

Ph.D. — Theoretical Physics (complex systems), University of North Texas
Research Associate, Dept. of Psychology — Université Laval
Research across UC San Diego · IPM · Université de Montréal · Shahid Beheshti
Finalist — AI Innovator of the Year, Women in AI Awards North America (2023)
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Engagements

Three ways to work together.

No discovery theatre, no "contact sales." Where I can put a number on it, I do.

Research partners

clinical researchers & academic labs
  • Study design and analysis methodology you can publish
  • Predictive and biomarker modeling on your data
  • Co-authorship on the resulting papers
  • Joint grant applications and proposal support

Scoped around the science and the funding — through co-authorship or a grant line, not a monthly fee.

Start a collaboration

Pharma & enterprise R&D

custom programs
  • Senior AI and scientific advisory across your program
  • Embedded technical leadership for a defined initiative
  • Predictive modeling and methodology for trial and neural data
  • Scope and terms set to the program

Larger programs are scoped custom — let's size it to what you're trying to do.

Talk through a program

Build partners

device companies & founders
Strategy Sprint

The memo + roadmap

4 weeks · fixed fee

$15K–$25K
  • Full audit of your neural data pipeline and signal quality
  • A no-jargon NeuroAI strategy memo: ranked bets that fit your signal, regulatory path, and timeline
  • A prioritized build roadmap — what to build, in what order, and the effort it takes
  • 90-minute leadership walkthrough
Start the sprint
Embedded Fractional

Two days a week, in-house

Monthly retainer · ongoing

~$15K / mo
  • Embedded two days a week, shipping alongside your team
  • BCI, neuromodulation, or biomarker pipeline development
  • Hiring and mentoring your first neural AI engineers
  • Scales down as your team takes over
Talk it through

Start with the 4-week sprint. If the roadmap isn't worth it, we don't continue — no retainer lock-in.

Platforms built

I don't just advise on NeuroAI.
I build it.

Across clinical, research, and consumer neurotech — production platforms that close the gap between neural data and real-world decisions.

Clinical Practice Management

Patient management, progress tracking, and integrated EEG + questionnaire data for neurologists and neurotech clinicians

EEG + questionnaire fusion · longitudinal tracking · multi-agent AI · HIPAA-compliant

Consumer Neurotech

Brain data upload & analysis platform for biohackers & quantified-self users

Multi-agent AI · EEG parsing · plain-language insights

Clinical Trials

Foundation-model predictions for trial endpoints & responder stratification

Foundation models · biomarker signals · Phase I–III · in development

Device Intervention Tracking

A Strava for brain health — tracking device-based and lifestyle brain interventions over time

Covers neurostimulation, meditation, sleep, and wearable-based interventions · longitudinal brain health scoring · personalized response tracking

More coming

New platforms in active development across clinical, research, and consumer neurotech

Have a use case in mind? I'm always interested in where neural data meets unmet clinical or research need.

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