AI Research and Education

Using Technology in Context
About Us

Blue Bell Envirobotics Lab (BBELL) is an AI research institute specializing in the development of Machine Learning (ML) and AI applications in various contexts of science and engineering. We also provide educational services in AI and IoT.

BBELL office wall with world map and entry table
BBELL main lab and meeting room with iMac workstations
Our Focus

BBELL conducts applied machine learning and AI research in environmental and atmospheric science, cheminformatics, bioinformatics, GIS, and quantitative risk assessment, turning complex scientific data into practical models and decision-support tools.

On the education side, we offer hands-on training in AI, data science, robotics, and IoT, helping students and professionals build modern computing and sensing skills grounded in real-world scientific and engineering applications.

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Research

Our research connects machine learning, AI, and domain expertise to solve problems in environmental science, air quality, GIS, bioinformatics, risk assessment, and robotics.

Ozone concentration spatial map
Environmental Engineering

We develop ML- and AI-driven models for air quality forecasting, pollution dispersion, and weather–climate analytics, including regulatory air dispersion modeling for air permitting and compliance. Beyond the atmosphere, our work extends to data-driven modeling of ecosystems, water and soil quality, and climate impacts; groundwater and surface water modeling; and AI-driven environmental transport and fate modeling.

These models are combined with GIS-based geospatial analysis to support environmental decision-making, exposure assessment, and sustainability planning.

Time series of nitrogen dioxide across the U.S.
Geospatial Analysis

We design web-based GIS and spatial database systems for environmental and engineering applications. Our work includes building interactive mapping dashboards, geospatial databases, and visualization systems; integrating model outputs with GIS; and performing advanced geospatial analysis to support decision-making at regional and national scales.

Diagram illustrating PBPK physiological models
Bioinformatics

We apply quantitative structure–activity relationship (QSAR) modeling and physiologically based pharmacokinetic (PBPK) modeling to support drug discovery, toxicology, and health risk assessment. Our work also includes benchmark dose lower confidence limit (BMDL) estimation, Bayesian uncertainty quantification, and multiple-path particle dosimetry (MPPD) modeling, linking molecular and biological data to real-world health outcomes.

Worker spraying field representing exposure assessment
Risk Assessment

BBELL performs consumer, worker, and environmental exposure and risk assessments. We integrate mechanistic models, exposure scenarios, and uncertainty analysis to provide transparent, quantitative support for regulatory reviews, product stewardship, and policy decisions in an AI-informed framework.

Student working with a modular robot next to a laptop
Robotics & IoT for Science & Engineering

Our robotics and IoT work links intelligent sensing and environmental monitoring with embedded systems and electromechanical design. We prototype smart, connected devices and mobile platforms and use these systems as teaching tools for students and professionals learning AI, control, and real-time data acquisition in scientific and engineering contexts.

Our Mission

  • AI & Machine Learning for Science & Engineering

    Develop and apply AI and machine learning methods in scientific and engineering contexts—programming models, simulations, and data pipelines that connect code to real-world measurements and decisions.

  • AI, Electromechanical Design & 3D Printing

    Combine AI with hardware: robotics, IoT, sensors, control systems, and 3D printing to build intelligent devices and experimental platforms for science and engineering.

  • AI Education for All Ages & Professions

    Provide accessible AI education for every generation—from elementary students to seniors—and for professionals such as farmers, high school teachers, clinicians, and industry experts so they can confidently use AI in their own domains.

Want to learn more? Check out Youtube

Lab

BBELL is a hands-on space for research, teaching, and collaboration. Here’s a glimpse inside our lab environment.

Classroom with desks and large display screen
Classroom 1

Bright, flexible classroom space for lectures, workshops, and group projects.

Alternative angle of classroom with desks and windows
Classroom 2

Multiple seating layouts support coding labs, problem-solving sessions, and exams.

Computing lab with iMac workstations along wooden desks
Computing Lab

Networked workstations for coding, data science, and ML projects.

Conference cabinet with posters, iMac and robotics kits
Collaboration Room

Our primary teaching and collaboration area, with displays and robotics tools for demonstrations.

Two student-built mobile robots on a wooden surface
Student-built Robots

Custom robots used in our robotics and coding courses, built by students.

Display case containing small spherical robots
Educational Robots

Small, programmable robots introduce younger learners to algorithms and STEM.

Blue couch and bookshelves in lounge area
Lounge & Reading Area

A comfortable space for mentoring, informal discussions, and quiet study.

Snack table and mini fridge next to wall-mounted TV
Break Corner

Snacks and drinks keep students energized during longer workshops and camps.

World map installation in BBELL hallway
Global Perspective

Our work reflects global environmental, health, and technology challenges.

Education

We foster students from elementary school to seniors as they adapt to a fast-growing, AI-driven environment. Our students have earned awards in state, regional, and national competitions; obtained certifications; been admitted to prestigious universities; secured internships in university labs; and, as undergraduates, been accepted into government and research companies. Most importantly, they learn real knowledge that they can carry forward.

Colorful code editor on a screen

Learn the fundamentals of popular programming languages such as Python, Java, and C++ and earn practical certifications that you can put on your resume and college applications. We recommend Python for beginners.

Build algorithmic thinking and problem-solving skills to prepare for programming contests, hackathons, and technical interviews.

Make websites dynamic with JavaScript. Learn about DOM manipulation, events, and basic logic to build interactive front-end experiences.

Introduction to data analysis, visualization, and basic statistics using Python libraries such as pandas and matplotlib, with examples from environmental and biomedical datasets.

Learn to build and code robots and simple IoT devices using Arduino boards, sensors, and motors. Students connect their creations to the physical world through sensing, control, and data logging.

Start with block-based game creation in Scratch, then progress to Python (PyGame) and C# for more advanced 2D games. Along the way, students learn logic, physics, and storytelling through play.

Explore the fundamentals of machine learning and AI using the Vibe Coding platform and Python-based tools. Students build simple models, interpret predictions, and discuss responsible AI use.

Design and prototype applications that connect user interfaces to ML models and AI services. Students build small web, mobile, or desktop apps that call prediction APIs or local models and present results clearly to end users.

Designed especially for seniors and non-technical learners, this course covers how to use generative AI tools effectively and safely: asking good questions, checking answers, protecting privacy, and recognizing misinformation and bias.

Get in touch with us!

Blue Bell (BBELL) Envirobotics Lab, LLC

768 N Bethlehem Pike,
Lower Gwynedd, PA 19002

Phone: (267) 742-0135

Email: information@bluebellenvirobotics.com