MasalaMetrics
AppsAI-powered food analyzer app taken from concept to a shipped product with 10,000+ App Store downloads and seed funding from four investors.
Computer VisionGenerative AIiOSProduct
Causal AI · Robotics · Autonomous Systems
Neel Kariat
AI Researcher • Builder • Entrepreneur • Musician
Building AI that understands why.
I’m interested in the intersection of Causal AI, robotics, and autonomous systems — developing intelligent systems that move beyond detecting problems to understanding and correcting their underlying causes.
About
Curious about more than what happened. Interested in why it happened.
I’m a student working across artificial intelligence, causal reasoning, robotics, software development, and entrepreneurship. What connects those interests is a single question: not just what a system did, but why it did it.
My work spans both sides of that question — theoretical AI research into how cause-and-effect can be modeled computationally, and building real products that people actually use. I like moving between the two, because research without a product stays abstract, and a product without research stays shallow.
Longer term, I want to combine Causal AI with physical robotics and autonomous systems — machines that can reason about the origin of their own failures instead of just reacting to them.
- 01Founded and built an AI-powered consumer application
- 02Published research involving causal inference
- 03Developed patent-pending technology involving autonomous decision-making
- 04Three summers interning at an AI company
- 05Built and experimented with numerous AI projects
- 06Years of violin and orchestra performance
0+
App Downloads
0
Seed Investors
0
Published Research Paper
0
Patent Pending
0 Summers
AI Industry Experience
0×
MSBOA First Division
Featured Project
MasalaMetrics
AI-Powered Food Analysis
MasalaMetrics is an AI-powered food analyzer application I helped create and develop as a startup. It uses AI to interpret what someone is eating and turn that into useful nutritional insight — shipped to the App Store and used by thousands of people.
- 10,000+ downloads on the Apple App Store
- Seed funding from four investors
- A real-world consumer AI application
- End-to-end product development experience
- Startup and entrepreneurship experience
- Idea → product → thousands of real users
From idea → product → users → investors
App screenshots · demo space
Publication
Research
“Beyond Correlation: A Python-Based Causal Inference Framework for Analyzing Type 1 Diabetes Risk Factors”
This research explores how computational causal inference techniques can be used to investigate potential relationships between risk factors and Type 1 Diabetes. Rather than relying only on statistical correlations, the work applies Python-based analytical methods to examine whether specific factors may actually contribute to the outcome.
Correlation
“X and Y occur together.”
Causality
“Does X actually contribute to Y occurring?”
Causal structure
Invention
Inventing Intelligent Decision Systems
Patent Pending
“Advanced Decision-Making Engine for Autonomous System Optimization and Dynamic Problem Solving”
Described here at a high level only. The invention concerns a decision-making engine for autonomous systems: software that assesses the state of a system, reasons about the problem it is facing, and chooses how to act as conditions change — rather than following a fixed, pre-scripted response.
Status: patent pending. No claim is made that a patent has been granted, and confidential details are not disclosed.
- 01Evaluating changing conditions
- 02Reasoning about complex problems
- 03Selecting actions dynamically
- 04Optimizing autonomous system behavior
- 05Adapting decisions as conditions change
Industry
Three Summers Building AI
Three summers of internship experience at an AI company gave me exposure to how AI is actually built and shipped — beyond classroom and side projects. These are the areas the work spanned.
01
Machine Learning
Developing and experimenting with AI/ML models and data-driven applications.
02
Computer Vision
Exploring systems that allow machines to interpret visual information.
03
Generative AI
Building and experimenting with modern AI-powered applications.
04
Causal AI
Investigating models that reason about cause-and-effect relationships.
05
Autonomous Systems
Exploring how intelligent systems can make decisions and respond to changing conditions.
06
AI Application Development
Turning AI concepts into usable software applications.
The Big Idea
What if robots could understand why they fail?
Traditional automation often responds to the symptom of a problem rather than determining its root cause. A motor slows down, so a conventional control system commands: increase motor speed. But the slowdown may come from friction, bearing degradation, temperature, voltage instability, payload variation, lubrication, alignment, or component wear. Running the motor faster treats the symptom.
Causal chain
- 1Bearing Wear
- 2Increased Friction
- 3Higher Motor Load
- 4Temperature Increase
- 5Motor Speed Reduction
Causal reasoning traces the pathway back: the slowdown is the last node, not the first.
Traditional AI
- Motor slows down↓
- Increase motor speed↓
- Temporary correction
Causal AI
- Motor slows down↓
- Analyze causal relationships↓
- Identify increased friction↓
- Trace friction to bearing degradation↓
- Correct underlying cause
Detect → Understand → Explain → Correct
The goal isn’t just autonomous robots.
It’s robots capable of causal reasoning.
Future
Where I Want to Go Next
I want to keep researching the combination of Causal AI, robotics, and autonomous systems — technology that lets robots and machines understand the root causes of abnormal behavior and make more intelligent corrective decisions.
Causal AI + Robotics + Autonomous Systems
- Robotic Root Cause Analysis
- Autonomous troubleshooting
- Causal digital twins
- Predictive maintenance
- Self-correcting robotic systems
- Manufacturing robotics
- Autonomous decision-making
- Human-robot collaboration
Beyond code
Engineering & Music
I’ve played violin and participated in orchestra since elementary school, and have kept performing through high school.
7×Consecutive MSBOA First Division Ratings
Music taught me that complicated systems are built from relationships. A single note matters, but what makes music work is how every note interacts with everything around it. I see engineering in much the same way.
Journey
Milestones so far
Elementary School
Started violin and orchestra
Middle / High School
Continued orchestra and earned repeated MSBOA First Division ratings
AI Internship — Summer 1
First exposure to professional AI development
AI Internship — Summer 2
Expanded work across AI projects
MasalaMetrics
Built and launched an AI food analyzer
10,000+ Downloads
Reached thousands of real users
Seed Funding
Received funding from four investors
AI Internship — Summer 3
Continued applied AI development
Causal AI Research
Investigated causal inference applied to Type 1 Diabetes risk factors
Research Publication
Published “Beyond Correlation: A Python-Based Causal Inference Framework for Analyzing Type 1 Diabetes Risk Factors”
Patent Pending
Advanced Decision-Making Engine for Autonomous System Optimization and Dynamic Problem Solving
Next
Causal AI + Robotics
What happened?
Traditional analytics can answer this.
What will happen?
Predictive AI can help answer this.
Why did it happen?
This is where causal reasoning becomes powerful.
Prediction tells us what might happen next. Causal reasoning may help us understand what to change.
Portfolio
Projects
Type 1 Diabetes Causal Inference
ResearchA Python-based causal inference framework exploring whether risk factors associated with Type 1 Diabetes may contribute to it, beyond correlation alone.
PythonCausal InferenceData Analysis
Autonomous Decision-Making Engine
Causal AIPatent-pending work on a decision engine for autonomous system optimization and dynamic problem solving. Described at a high level only.
Autonomous SystemsOptimizationDecision Modeling
AI Internship Projects
AI/MLThree summers of applied work spanning machine learning, computer vision, generative AI, and AI application development.
Machine LearningComputer VisionGenerative AI
Toolkit
Technologies & areas I work with
Areas I’ve worked in or am actively exploring — listed as scope, not as claimed mastery.
Artificial Intelligence
- Machine Learning
- Causal AI
- Generative AI
- Computer Vision
Programming
- Python
- + add languages
- + add frameworks
Research
- Causal Inference
- Data Analysis
- Experimental Design
Product
- AI Application Development
- Product Design
- Startup Development
Interested in building AI that understands cause and effect?
I’m always interested in research, engineering, robotics, and conversations about what intelligent systems could become.
NEEL KARIAT · BUILDING AI THAT UNDERSTANDS WHY