Nik Bear Brown - Educational AI
Associate Teaching Professor at Northeastern University with expertise in AI, machine learning, and computational biology, dedicated to developing ethical AI solutions and preparing the next generation of AI engineers.
Who am I? Professor Bear
I am an Associate Teaching Professor at Northeastern University's College of Engineering with expertise in AI, machine learning, and computational biology. With a PhD in Computer Science from UCLA and additional degrees in Finance, MBA, Information Design and Visualization, and Biochemistry, I bring multidisciplinary perspectives to education and research.
I've taught at prestigious institutions including Northeastern University, UCLA, Santa Monica College, Arts Institutes, and LA Film School, specializing in AI engineering, machine learning, game development, algorithms, and data science. As founder of Humanitarians AI and a mentor at AI Skunkworks, I'm dedicated to developing ethical AI solutions and preparing the next generation of AI engineers.
OpenAI Academy: Professors Teaching with AI
As a contributor to the OpenAI Academy series, I focus on practical applications of AI in higher education. Below is an overview of my approach to integrating AI tools that enhance both teaching and learning experiences.
What We Teach
My courses focus on experiential learning where students actively build AI systems while learning the theoretical foundations. This "Learn AI by Doing AI" approach ensures students develop practical skills alongside conceptual understanding. We cover prompt engineering, custom GPT development, ethical AI implementation, and responsible AI integration across various domains.
What We Built
We've developed a comprehensive suite of educational tools including custom GPTs for specific disciplines, interactive assignments that leverage AI capabilities, assessment tools that provide personalized feedback, and workflows that blend AI assistance with traditional learning methods. These resources are designed to be adaptable across different educational contexts.
How We Built It
This page links to Github repositories and YouTube videos on the Humanitarians AI and Nik Bear Brown channels that cover the technical details of implementation. For each project, we provide step-by-step guides, code examples, and best practices. If you need help building anything covered here, reach out to info@humanitarians.ai for assistance and collaboration opportunities.
What The Impact Was
In the video series, I'll cover the measurable impacts of these AI teaching methods, including effects on student engagement, learning outcomes, time efficiency, and professional skill development. I'll share real-world examples from my courses at Northeastern University and provide insights into how these approaches can be adapted for different educational contexts.
Teaching Philosophy: Learning by Doing
Philosophy Overview
Experiential AI, Learning by Doing, Collaborate with companies and researchers.
For the details on how to implement any particular project go to:
or Nik Bear Brown's 501c3 Non-Profit:
Core Principles
Active Engagement Over Passive Consumption
Do it.
AI-Enhanced Personalized Learning
We have an AI Fluency framework called "Botspeak" that teaches people to effectively and ethically leverage AI.
Real-World Problem Solving
Abstract concepts become concrete when applied to meaningful problems. My courses, and non-profit incorporate industry-relevant challenges, social impact projects, and research.
Collaborative Innovation
The most significant technological advancements rarely come from individuals working in isolation. Teach those who are coming after you.
Ethical AI Development
Technical skills must be paired with ethical judgment.
Educational AI Projects
I'll be covering some of the many projects I lead and contribute to at Northeastern University's College of Engineering, Humanitarians AI, and AI Skunkworks. While I'll provide brief overviews here, detailed information, implementation guides, and source code can be found on our websites, YouTube channels, and GitHub repositories linked below.
Agentic AI
Bellman: Reinforcement Learning for Agentic AI
A project applying reinforcement learning theory to agentic AI systems, exploring how these techniques can enhance autonomous decision-making and adaptive behaviors in educational and other AI applications.
GitHub Repository →Project Page →Dayhoff: AI for Computational Biology & Public Health
A modular, agent-based framework that applies AI to biological and health sciences. Named after Margaret Belle Dayhoff, this system helps researchers unlock patterns in bioinformatics, epidemiology, and public health. Includes The RAMAN Effect project, which combines AI with Surface-Enhanced Raman Spectroscopy to detect pathogens and pollutants in wastewater with high precision.
GitHub Repository →Project Page →Madison: AI for Branding & Marketing
Where creativity meets computation. Madison explores how nonprofits and creatives can use AI to develop compelling brands, campaigns, and stories with impact.
GitHub Repository →Project Page →Mycroft: AI for Finance
AI tools and innovations that promote economic access, financial literacy, and data-driven decision-making. Part of Humanitarians AI's mission to make financial systems more inclusive.
GitHub Repository →Project Page →Popper: AI for Epistemology & Scientific Method
A project focused on using AI to improve scientific reasoning, hypothesis testing, and evidence evaluation. Named after philosopher of science Karl Popper.
GitHub Repository →Project Page →AI Fluency
BotSpeak: AI Literacy & Fluency
A comprehensive framework designed for everyone, from beginners to builders, that transforms you from an AI tourist into a fluent native. BotSpeak breaks down what AI is, how it works, and how to use it effectively through nine essential pillars.
The Nine Pillars of BotSpeak
1. Strategic Delegation
Thoughtfully distributing tasks between human and AI based on comparative strengths.
2. Effective Communication
Crafting precise prompts with clear intent and context for optimal AI response.
3. Critical Evaluation
Systematically assessing AI outputs for accuracy and bias through multiple sources.
4. Technical Understanding
Applying appropriate prompt patterns and understanding model behavior.
5. Ethical Reasoning
Maintaining accountability and managing privacy boundaries in AI collaboration.
6. Stochastic Reasoning
Understanding the probabilistic nature of AI outputs and embracing variability.
7. Learning by Doing
Building intuition through deliberate practice and systematic analysis.
8. Rapid Prototyping
Accelerating ideation through quick cycles of AI-assisted generation and refinement.
9. Theoretical Foundations
Understanding the science behind AI systems and their fundamental epistemological boundaries.
Three Modes of Interaction
Automation
AI performs specific tasks based on explicit human instructions.
Augmentation
Humans and AI collaborate as thinking partners, each contributing unique strengths.
Agency
AI works independently within parameters established by humans.
While AI technology evolves rapidly, the core challenges of human-AI collaboration remain consistent. BotSpeak provides lasting cognitive tools rather than temporary techniques, helping you develop skills for a future where human-AI collaboration becomes the new literacy.
BotSpeak Series →AI for Education
Dewey: AI for Education
An open-source educational framework built to revolutionize how we learn and teach. Dewey uses specialized AI agents to create interactive, personalized learning across disciplines—rooted in the philosophy of John Dewey. Includes several key projects:
- Medhavi: Intelligent AI books that adapt content to individual learners
- "AI Teaching Revolution" series: Professor Nik Brown's collaboration with OpenAI sharing strategies and tools for AI in classrooms
- Educational video production focused on AI literacy and learning
Educational AI Chatbots
Custom-built educational assistants designed to enhance learning in specific disciplines:
Ada: Calculus Bot
Step-by-step guidance for calculus using scaffolding techniques and Socratic questioning.
Try Ada →Newton: Physics Bot
Interactive physics tutor with dynamic graphs and simulations for visualization.
Try Newton →Grace: Algorithms Bot
Algorithm visualizations and simulations to help understand complex concepts.
Try Grace →Lyrical Literacy: Learning Through Song
A groundbreaking project using generative AI and music to teach kids to read and help people learn new languages. Sing along with AI to unlock literacy for all ages.
Professional Tools
AI assistants designed to enhance professional skills and academic work:
Synthetic Personas
Data-driven personas for survey research, UX testing, and behavioral modeling.
Try Synthetic Personas →One-Minute Pitch
Create concise, impactful business pitches structured for your audience.
Try One-Minute Pitch →Sagan | GSE Writing Bot
Advanced research paper editor for academic structure and methodology feedback.
Try Sagan →AI for Good
Code for a Cause
A collaborative initiative where Humanitarians AI partners with organizations and volunteers to build AI applications with social impact across education, research, and community development.
Learn More →Northeastern x Humanitarians AI
A collaborative lab where Northeastern University students and Humanitarians AI build real-world applications with social impact. Learn AI by doing AI—across education, research, and community development.
Learn More →PredictaBio: Protein Synthesis with AI
AI-powered platform creating "recipes" for novel proteins with specific properties. This accelerates discovery and enables design of proteins for applications in biotechnology, healthcare, and sustainability.
GitHub Repository →The RAMAN Effect: AI for Wastewater Epidemiology
A platform combining AI and spectroscopy to detect public health threats through wastewater. RAMAN uses spectral analysis to identify pathogens and pollutants with high precision—advancing global epidemiology.
GitHub Repository →Computational Skepticism
Popper: AI Validation & Computational Skepticism
Named after Karl Popper, this project embraces the scientific method by challenging AI systems to prove themselves. It offers tools and methods to evaluate, verify, and stress-test AI models through rigorous evidence-based reasoning.
GitHub Repository →Nerd Life
AI Tutorials & Tools
Hands-on how-tos and walkthroughs for AI tools like ChatGPT, Midjourney, Runway, and more—built for creatives, nonprofits, and curious minds new to the field.
View Tutorials →Animation Tests & Visual Experiments
A peek behind the curtain—explore our generative art tests, motion studies, and creative experiments using AI animation tools. From rough cuts to visual R&D.
View Experiments →Talks, Classes, Workshops & Events
Guest lectures, workshops, student showcases, and community events from Humanitarians AI and its collaborators, including sessions from Northeastern University.
View Talks →Research
Publications
Our students and Fellows write books and research articles on a wide range of topics in AI and machine learning. These publications explore cutting-edge concepts, methodologies, and applications across various domains, contributing to the advancement of AI knowledge and practice.
View Publications →Cognitive Type Project: AI Typography
Revolutionizing typeface design with AI-driven models that create smarter, more accessible fonts. Our "Text to Type" foundational models optimize readability for various needs—boosting ad engagement, enhancing children's reading experiences, supporting dyslexic readers, and analyzing typography's cognitive impact through AI and eye-tracking.
Learn More →Synthetic Personas
A collaboration with Alderman+Ward developing AI tools that create data-driven synthetic personas for survey methodologists. By integrating Big Five personality traits and demographic data, we help improve survey question testing and response quality while reducing research costs and resources needed for effective user testing.
Learn More →Connect With Our Work
Nik Bear Brown
Courses Taught
Northeastern University
INFO 6205: Program Structure Algorithms
CSYE 7270: Building Virtual Environments
INFO 6105: Data Science Engineering Methods
INFO 7390: Advances in Data Sciences and Architecture
CSYE 7370: Deep Reinforcement Learning Game Engineering
DAMG 6210: Data Management and Database Design
INFO 7375: ST: AI Engineering Apps - Prompt Engineering and GenAI
CSYE 7374: Special Topics: Computational Skepticism
INFO 6210: Data Management and Database Design
CSYE 7245: Big Data Systems Integration Analytics
DA 5030: Intro Data Mining/Machine Learning
CS 3540: Game Programming
CS 4300: Computer Graphics
CS 4850: Building Game Engines
CS 5850: Advanced Building Game Engines
DS 6020: Collect/Store/Retrieve Data
DS 6030: Intro Data Mining/Machine Learning
CS 4800: Algorithms Data
ENGR-0201: Organizing Academic Success - AI for Personalized Learning with Claude
INFO 7375: Branding and AI
CSYE 7374/INFO 7374: Research Methods in Artificial Intelligence
University of California, Los Angeles (UCLA)
CS 31: Programming in C++
Santa Monica College
CS 52: Programming in C++
Arts Institutes
Programming in C++
Game Programming
LA Film School
Game Programming
AI Education Initiatives
Humanitarians AI Incorporated
As founder of this nonprofit organization, I lead the development of AI-driven educational resources focused on social impact and ethical application of technology.
AI Skunkworks
As an active mentor in AI Skunkworks, I guide students in developing innovative AI-based projects and fostering industry collaborations.
Recognition for Educational Innovation
Dean's Award, College of Engineering
Northeastern University (2024-25)
RISE Award
Computer and Information Sciences (2022)
Fostering Engineering Innovation in Education Award
Northeastern University (2021-22)
Red Hat Academy Director's Award
2020