Welcome

Working across ML engineering, research, and startup systems.

I'm Nick Mino, a rising junior studying Artificial Intelligence in CMU's School of Computer Science, Co-founder, CTO, and ML Engineer at Posematic, ML researcher at CMU, and Senior Editor at Synthica.

Open to research collaborations, founder conversations, and meeting new people.

Carnegie Mellon University
Artificial Intelligence
Posematic
Senior Editor, Synthica
PosematicProjectsResearchResume
About

Founder, researcher, engineer, and SCS student.

I'm a rising junior in CMU's School of Computer Science studying Artificial Intelligence with a concentration in Algorithms and Complexity. I work across applied ML, engineering, and research: as Co-founder, CTO, and ML Engineer at Posematic, ML researcher at CMU, and Senior Editor at Synthica.

I'm also interested in long-term research paths, including graduate study in machine learning.

Outside of my technical work, I'm a quad-instrumentalist and trilingual: native English and Spanish, elementary Mandarin.

Timeline

Timeline

Sep. 2025 - Present

Co-founder, CTO, ML Engineer

Posematic

Working across ML engineering, technical architecture, product engineering, prototype development, technical direction, UI design, and business operations.

May 2026 - Present

ML Researcher

Carnegie Mellon University

Researching certified adaptive upper regret bound frontiers for AI-supported decision-making, advised by Professor Shixiang (Woody) Zhu.

May 2026 - Present

Senior Editor

Synthica

Focused on the computer science side of an emerging student-led scientific journal focused on AI and technology.

Aug. 2024

AI Major

Carnegie Mellon School of Computer Science

Rising junior studying Artificial Intelligence with a concentration in Algorithms and Complexity.

Feb. 2026

Best Startup

CMU ScottySpark

Posematic won Best Startup at CMU ScottySpark after a live prototype demo.

Jan. 2026

Most Sustainable Innovation Track Winner

TartanHacks 2026

Team lead for Verdant, a hackathon project focused on estimating and reducing the carbon footprint of LLM usage.

Sep. 2025

Honorable Mention

HackCMU

Team lead for Ensemble, an audio project using signal-processing-inspired degradation with PyTorch/torchaudio.

Jun. 2020 - Dec. 2020

Research Assistant

Stanford Paleobiology (SEYI)

Under Dr. Pedro Monarrez

Worked as a research assistant on paleobiology datasets, including hand annotation of trilobite fossil data and data cleaning, representation, and analysis on mollusk fossil datasets related to California-area records, Indigenous presence, fossil locality patterns, and missing fossil records.

Startup

Posematic

Non-generative creative tools

Posematic builds non-generative creative tools for artists, starting with image/sketch-to-editable 3D pose models.

Demo video

Startup

Posematic

Role

Co-founder, CTO, and ML Engineer

Recognition

Best Startup at CMU ScottySpark; live prototype demo.

What I do

ML / AI Systems

  • Computer vision workflows for image/sketch-to-editable 3D pose models
  • PyTorch-based ML work
  • ViT-H model experimentation and evaluation
  • PyTriton inference serving
  • Synthetic data strategy
  • Out-of-domain data adaptation, without implementation details
  • Inference pipeline design

Technical Architecture / Backend

  • Backend architecture for product-facing ML systems
  • Dockerized services
  • PyTriton service integration
  • API design and integration
  • Authentication flows
  • NestJS / Node.js backend work
  • Data and inference pipeline coordination

Product Engineering / Frontend

  • Artist-facing workflow design
  • React Native / TypeScript app development
  • Three.js and WebGL-based 3D/frontend work
  • UI implementation
  • Prototype development
  • Demo preparation

Product / Business / Leadership

  • Technical direction
  • Product strategy
  • Coordinating technical priorities across ML, frontend, backend, and product
  • UI design decisions
  • Business operations
Visit Posematic
Research

Certified Adaptive Upper Regret Bound Frontiers

ML Researcher, Carnegie Mellon University

Certified Adaptive Upper Regret Bound Frontiers

Advised by Professor Shixiang (Woody) Zhu

At CMU, I work with Professor Shixiang (Woody) Zhu on certified decision reliability for AI-supported decisions. My current project studies certified adaptive upper regret bound frontiers: instead of reporting only expected regret or a few manually chosen confidence levels, the goal is to identify where certified upper regret bounds change sharply as reliability requirements vary.

The project connects conformal methods, split-data recalibration, inverse feasible region perspectives, and predict-then-optimize systems. The focus is on building a sharper view of downstream decision reliability than average regret or isolated confidence levels can provide.

Research Area

Decision-Aware ML

Current focus

Studying model-supported decisions where downstream regret and reliability matter more than standalone predictive accuracy.

Research Area

Uncertainty Quantification

Research interest

Using reliability requirements and uncertainty-aware evaluation to reason about decisions under model uncertainty.

Research Area

Model Evaluation

Research interest

Evaluating models by downstream decision behavior and certified regret changes.

Research Area

Learning and Optimization

Research interest

Connecting learning systems to optimization settings, especially predict-then-optimize workflows.

Research Area

Reliable AI Systems

Research interest

Building toward systems where theoretical guarantees remain meaningful under practical constraints.

Coursework

Relevant Coursework

Core CS

  • 15-281 Artificial Intelligence: Representation and Problem Solving
  • 15-213 Introduction to Computer Systems
  • 15-150 Principles of Functional Programming
  • 15-122 Introduction to Imperative Programming
  • 15-112 Fundamentals of Programming

Math / Probability

  • 36-219 Probability Theory and Random Processes
  • 21-241 Linear Algebra
  • 21-259 Calculus in Three Dimensions
  • 15-151 Mathematical Foundations for Computer Science

AI / Robotics

  • Concepts in Artificial Intelligence
  • Concepts in Robotics
Skills

Tools and technologies.

Languages

PythonCSMLRTypeScriptJuliaJava

ML / Data

PyTorchNumPyComputer VisionUncertainty QuantificationtorchaudioFine-TuningModel Evaluation

Systems / Infra

DockerGitPyTritonInference PipelinesData PipelinesTechnical Architecture

Product / Startup

Technical StrategyProduct EngineeringRapid PrototypingUser-Driven Development

Research

Conformal MethodsStatistical ReasoningDecision-Aware ML
Projects

Projects.

Verdant

TartanHacks 2026 sustainability track winner

Most Sustainable InnovationJan. 2026

Role

Team Lead

Tags

LLMsSustainabilityModel RoutingPrompt Complexity AnalysisConversation CompressionHackathon

Verdant estimated and reduced the carbon footprint of LLM usage through prompt complexity analysis, model routing, and context-preserving conversation compression. I led the team and worked on workflow design, product design, prompt-complexity routing, compression, and overall integration.

LLMsSustainabilityModel RoutingPrompt Complexity AnalysisConversation CompressionHackathon

Ensemble

HackCMU honorable mention audio project

HackCMU Honorable MentionSep. 2025

Role

Team Lead

Tags

AudioSignal ProcessingPyTorchtorchaudioHackathon

Ensemble generated vintage audio effects using signal-processing-inspired degradation and PyTorch/torchaudio. The project was recognized with a HackCMU Honorable Mention.

AudioSignal ProcessingPyTorchtorchaudioHackathon

3D Chess Engine

Experimental chess variant and search engine

15-112 Term Project

Role

Solo developer

Tags

PythonSearchGame AIHeuristicsPruningAlgorithms

I built a Python engine for a 3D chess variant as my 15-112 project. The engine used 8-ply search with custom heuristics: it assumed the opponent would avoid obviously terrible moves, evaluated aggressive moves first when the position justified it, and short-circuited once a move crossed a value threshold, reducing the search space across plies.

PythonSearchGame AIHeuristicsPruningAlgorithms
Contact

Let's talk about research, product, or engineering.

Open to research collaborations, founder conversations, editorial questions, and meeting new people.

EmailLinkedInGitHubORCIDResume