Artificial Intelligence Research and Engineering Consulting
Welcome to R. Calix AI Labs
R. Calix AI Labs conducts research and provides consulting services in
artificial intelligence, machine learning, deep learning,
industrial AI, computer vision, cybersecurity,
scientific computing, and engineering applications of AI.
The laboratory works at the intersection of academic research and
real-world engineering, developing practical AI solutions for science,
manufacturing, cybersecurity, and industrial systems.
Industrial Artificial Intelligence
Recent work has included collaborations involving CIVS, the
U.S. Department of Energy (DOE)
and
U.S. Steel,
where advanced machine learning methods have been developed
for industrial process optimization and engineering decision support.
This work includes the development of
Neural Input Optimization (NIO),
a machine learning methodology for identifying operating conditions
that satisfy engineering objectives while respecting process
constraints.
These technologies are currently being implemented
within an operating manufacturing environment.
Areas of interest include:
- Industrial Artificial Intelligence
- Machine Vision
- Process Optimization
- Engineering Data Analytics
- Forecasting
- Scientific Computing
- Neural Input Optimization (NIO)
Books and Educational Resources
Over the past decade I have taught and conducted research in
artificial intelligence,
machine learning,
deep learning,
and cybersecurity.
These efforts have resulted in books,
open educational resources,
software,
and numerous peer-reviewed publications.
Current research interests include:
- Machine Learning
- Dynamic Systems and Machine Learning
- Natural Language Processing
- Deep Learning
- Cybersecurity
- Computer Vision
- Industrial AI
- Scientific Machine Learning
- Engineering Applications of AI
Consulting & Collaboration
R. Calix AI Labs welcomes opportunities involving:
- Artificial Intelligence Consulting
- Industrial Technical Services
- Academic Research Collaborations
- Grant Proposal Participation (Consultant or Co-PI)
- Machine Learning Research
- Industrial Process Optimization
- Speaking Engagements and Workshops
Whether your organization is interested in applying artificial
intelligence,
developing industrial AI solutions,
conducting collaborative research,
or exploring new engineering applications,
we would be pleased to discuss potential opportunities.
Email:
rcalix@rcalix.com
Phone:
219-315-9612
Spring 2024
This is a course in Deep Learning
Spring 2024
This course provides a basic introduction to the machine learning pipeline and related concepts. Topics covered include: Machine learning uses and applications; data set requirements; data pre-processing; data annotation, and validation; data representation formats; features and feature representation and extraction; the vector space model; traditional machine learning algorithms; machine learning algorithms and programming; ML evaluation methods; introduction to deep learning algorithms; big data; reinforcement learning; Unsupervised learning; statistical significance analysis; and other special topics.
Spring 2024
Topics include: workstations, servers, services, data centers, security policy, network administration, helpdesks, debugging, upgrades, namespaces, system maintenance management, email and printing services, system backup, remote access, IT support, scripting with Python for system management.
Spring 2022
This is a course in machine learning for cyber security. Topics include: the basic ML approach, features and feature extraction, data set formats, supervised and unsupervised machine learning, applications of machine learning to cyber security: IOT, Malware, IDS, etc.
Fall 2023
This is a course in applied machine learning with PyTorch.
Fall 2023
This is an introductory course to Cryptography. This course covers the implementation of systems assurance with computing systems. Topics include confidentiality, integrity, authentication, non-repudiation, intrusion detection, physical security, and encryption. Encryption algorithms: secret key, DES, PKI, RSA, SSL/TLS, and more. Extensive laboratory exercises are assigned.
Fall 2022
This course covers defensive programming techniques, bounds analysis, error handling, advanced testing techniques, detailed code auditing, software specification in a trusted assured environment. Extensive laboratory exercises are assigned. Topics: buffer overflows, format string vulnerabilities, web SOP, XSS, CSRF, web worms, race conditions, e-commerce security, and more.
Spring 2022
This course covers the design and implementation of assured systems in an enterprise environment. Topics include: Systems design and implementation, network security threats and controls, and special topics.
Fall 2020
This course covers introductory topics in programming using the Python language.
Spring 2021
This course is a project oriented course in multi-tier application development, interface design and implementation, component based application development, and configuration of multi-tier applications. Extensive laboratory exercises are assigned.
Fall 2020
This is a course in Machine Learning
rcalix@rcalix.com
