Dr. Mark Karam
PhD in Electrical and Computer Engineering
Dr. Mark Karam is a member of the ICCC alumni community. Documented research areas include recurrent neural networks and nonlinear modeling.
Selected published work: “Development of a Model-Based Dynamic Recurrent Neural Network for Modeling Nonlinear Systems” (2007). Publication details and links are listed below.
Education
- Ph.D. in Electrical and Computer Engineering
Research statistics
Verified ICCC collection
- Documented research records
- 7
- Publication records
- 7
- Degree research records
- 0
Indexed citation figures
- Indexed research works
- 27
- Citations to indexed works · all years
- 187
- Citations received · 2024–2026
- 30
- 202413
- 202511
- 20266
Annual citations: 2024: 13 · 2025: 11 · 2026: 6. Retrieved 2026-10-24. Source 1Checked 2026-10-24
ICCC counts cover the verified collection. Citation figures cover only the displayed indexed source records, not guaranteed career totals. OpenAlex coverage and author clustering can be incomplete. These figures differ from Google Scholar and include self-citations. Compare available member metrics →
Research & Publications
7 research works · Newest first
Authored and co-authored publications, with authors shown in the source order. This list reflects the records currently verified by ICCC and may not be complete.
Development of a Model-Based Dynamic Recurrent Neural Network for Modeling Nonlinear Systems
View PublicationOpenAlex: 0 citations Source ↗
Start here · New researcher guide
A reading workflow, not an author-verified summary. Confirm all details in the original publication.
- Check the fit. Read the abstract and introduction. Write down the research question and explain how it relates to your idea.
- Understand the method. Identify the approach, assumptions, data and evaluation measures in the paper.
- Check reproducibility. Look for linked code, datasets and supplementary material. Availability has not been verified by ICCC.
- Find your next question. Read limitations and future work. Propose one extension and check newer literature before claiming a research gap.
- Plan a first experiment. Define a baseline, the change you will test and a measurable outcome. Discuss feasibility with your supervisor.
For questions or collaboration, visit the member profile and use a listed contact channel. Authorship and collaboration require agreement.
Developing the Theory of a Model-Based Dynamic Recurrent Neural Network
View PublicationOpenAlex: 0 citations Source ↗
Start here · New researcher guide
A reading workflow, not an author-verified summary. Confirm all details in the original publication.
- Check the fit. Read the abstract and introduction. Write down the research question and explain how it relates to your idea.
- Understand the method. Identify the approach, assumptions, data and evaluation measures in the paper.
- Check reproducibility. Look for linked code, datasets and supplementary material. Availability has not been verified by ICCC.
- Find your next question. Read limitations and future work. Propose one extension and check newer literature before claiming a research gap.
- Plan a first experiment. Define a baseline, the change you will test and a measurable outcome. Discuss feasibility with your supervisor.
For questions or collaboration, visit the member profile and use a listed contact channel. Authorship and collaboration require agreement.
Performance enhancement of a fourier/hopflield neural network for nonlinear periodic systems representation
View PublicationOpenAlex: 0 citations Source ↗
Start here · New researcher guide
A reading workflow, not an author-verified summary. Confirm all details in the original publication.
- Check the fit. Read the abstract and introduction. Write down the research question and explain how it relates to your idea.
- Understand the method. Identify the approach, assumptions, data and evaluation measures in the paper.
- Check reproducibility. Look for linked code, datasets and supplementary material. Availability has not been verified by ICCC.
- Find your next question. Read limitations and future work. Propose one extension and check newer literature before claiming a research gap.
- Plan a first experiment. Define a baseline, the change you will test and a measurable outcome. Discuss feasibility with your supervisor.
For questions or collaboration, visit the member profile and use a listed contact channel. Authorship and collaboration require agreement.
A Fourier/Hopfield neural network for identification of nonlinear periodic systems
View PublicationOpenAlex: 10 citations Source ↗
Start here · New researcher guide
A reading workflow, not an author-verified summary. Confirm all details in the original publication.
- Check the fit. Read the abstract and introduction. Write down the research question and explain how it relates to your idea.
- Understand the method. Identify the approach, assumptions, data and evaluation measures in the paper.
- Check reproducibility. Look for linked code, datasets and supplementary material. Availability has not been verified by ICCC.
- Find your next question. Read limitations and future work. Propose one extension and check newer literature before claiming a research gap.
- Plan a first experiment. Define a baseline, the change you will test and a measurable outcome. Discuss feasibility with your supervisor.
For questions or collaboration, visit the member profile and use a listed contact channel. Authorship and collaboration require agreement.
System identification using a Fourier/Hopfield neural network
View PublicationOpenAlex: 3 citations Source ↗
Start here · New researcher guide
A reading workflow, not an author-verified summary. Confirm all details in the original publication.
- Check the fit. Read the abstract and introduction. Write down the research question and explain how it relates to your idea.
- Understand the method. Identify the approach, assumptions, data and evaluation measures in the paper.
- Check reproducibility. Look for linked code, datasets and supplementary material. Availability has not been verified by ICCC.
- Find your next question. Read limitations and future work. Propose one extension and check newer literature before claiming a research gap.
- Plan a first experiment. Define a baseline, the change you will test and a measurable outcome. Discuss feasibility with your supervisor.
For questions or collaboration, visit the member profile and use a listed contact channel. Authorship and collaboration require agreement.
Computational results on recurrent dynamic neural network for signal analysis
View PublicationOpenAlex: 0 citations Source ↗
Start here · New researcher guide
A reading workflow, not an author-verified summary. Confirm all details in the original publication.
- Check the fit. Read the abstract and introduction. Write down the research question and explain how it relates to your idea.
- Understand the method. Identify the approach, assumptions, data and evaluation measures in the paper.
- Check reproducibility. Look for linked code, datasets and supplementary material. Availability has not been verified by ICCC.
- Find your next question. Read limitations and future work. Propose one extension and check newer literature before claiming a research gap.
- Plan a first experiment. Define a baseline, the change you will test and a measurable outcome. Discuss feasibility with your supervisor.
For questions or collaboration, visit the member profile and use a listed contact channel. Authorship and collaboration require agreement.
A recurrent dynamic neural network for noisy signal representation
View PublicationOpenAlex: 17 citations Source ↗
Start here · New researcher guide
A reading workflow, not an author-verified summary. Confirm all details in the original publication.
- Check the fit. Read the abstract and introduction. Write down the research question and explain how it relates to your idea.
- Understand the method. Identify the approach, assumptions, data and evaluation measures in the paper.
- Check reproducibility. Look for linked code, datasets and supplementary material. Availability has not been verified by ICCC.
- Find your next question. Read limitations and future work. Propose one extension and check newer literature before claiming a research gap.
- Plan a first experiment. Define a baseline, the change you will test and a measurable outcome. Discuss feasibility with your supervisor.
For questions or collaboration, visit the member profile and use a listed contact channel. Authorship and collaboration require agreement.
No publications match your search.