Nagios
DNA Graphic
SDLE SunFarm
Global SunFarm Network
Automated Image Processing

Ahmad Maroof Karimi

 

I am a final year Ph.D. student in Department of Electrical Engineering and Computer Science and a graduate research assistant in Solar Durability Lifetime Extension Research Center.
 
Connect:
     Email: axk962[at]case[dot]edu 
     ORCID
     Google Scholar
     Bitbucket
     LinkedIn
 
 
Address:
     10900 Euclid Ave.
     540 White Building,
     Cleveland,
     OH
 

Awards and Honors:

• Best presentation award,Data Science Symposium, Tohoku University, Sendai,Japan, 2018
• International travel award to attend symposium at Tohoku University, Sendai,Japan, 2018
• Full tuition waiver at the University of Toledo for MS program

• Employee of the month award three times at Tata Consultancy Services

 


Publications:

1. Karimi, A. M., Fada, J. S., Parrilla, N. A., Pierce, B. G., Koyutürk, M., French, R. H., Braid, J. L., “Generalized and Mechanistic PV Module Performance Prediction from Computer Vision and Machine Learning on Electroluminescence Images,” Submitted: IEEE Journal of Photovoltaics, p. 9, 2019

2. Khalilnejad, A., Karimi, A. M., Kamath, S., Haddadian, R., French, R. H., Abramson, A. R., “Automated pipeline framework for distributed processing of large-scale building energy time series data,” Submitted: PLOS one, p. 23, 2019

3. Liu, J., Wang, M., Curran, A. J., Karimi, A. M., Huang, W.-h., Schnabel, E., Kohl, M., Braid, J. L., French, R. H., “Real-world PV Module Degradation across Climate Zones Determined from Suns-Voc, Loss Factors and I-V Steps Analysis of Eight Years of I-V , Pmp Time-series Datastreams,” in 2019 46th IEEE PVSC, Chicago IL, USA, Jun. 2019, p. 7

4. Karimi, A. M., Fada, J. S., Hossain, M. A., Yang, S., Peshek, T. J., Braid, J. L., French, R. H., “Automated Pipeline for Photovoltaic Module Electroluminescence Image Processing and Degradation Feature Classification,” IEEE Journal of Photovoltaics, pp. 1–12, 2019. doi: 10.1109/JPHOTOV.2019.2920732

5. Karimi, A. M., Fada, J. S., Liu, J., Braid, J. L., Koyutürk, M., French, R. H., “Feature Extraction, Supervised and Unsupervised Machine Learning Classification of PV Cell Electroluminescence Images,” in 2018 IEEE 7th World Conference on Photovoltaic Energy Conversion (WCPEC) (A Joint Conference of 45th IEEE PVSC, 28th PVSEC 34th EU PVSEC), Jun. 2018, pp. 0418–0424. doi: 10.1109/PVSC.2018.8547739

6. Karimi, A. M., Niyaz, Q., Sun, W., Javaid, A. Y., Devabhaktuni, V. K., “Distributed network traffic feature extraction for a real-time IDS,” in 2016 IEEE International Conference on Electro Information Technology (EIT), May 2016, pp. 0522–0526. doi: 10.1109/EIT.2016.7535295

 

Presentations:

1. Adachi, M., Pierce, B. G., Karimi, A. M., Wilson, L. G., French, R. H., Carter, J. L. W., Fukuyama, H., “Nucleation and Growth of AlN: A Case Study of the Challenges in Blending Materials Science and Data Science in an International Collaboration,” presented at the Symposium BI01—Materials Data Science—Transformations in Interdisciplinary Education, Materials Research Society, 2019 Fall Meeting (Boston MA), Dec. 2019

2. Adachi, M., Sonoko, S., Kanbara, A., Wilson, L. G., Pierce, B. G., Karimi, A. M., French, R. H., Carter, J. L., Fukuyama, H., “AlN growth behavior on Ni-Al liquid solutions,” Invited, presented at the 4th International Workshop on Ultraviolet Materials and Devices (Saint Petersburg, Russia), Sep. 8–13, 2019

3. Karimi, A. M., French, R. H., “Invited: Computer Vision and Machine Learning in a Distributed Computing Environment: Photovoltaic Degradation Quantified Using Electroluminescent Images,” presented at the DCMS Materials 4.0 Summer School (TU-Dresden, Dresden Germany), Sep. 10–15, 2018

4. Karimi, A. M., Fada, J. S., French, R. H., “Supervised and Unsupervised Machine Learning of Electroluminescent Images of Photovoltaic Modules,” presented at the PyCon, Python Software Foundation (Cleveland, OH), May 13, 2018

5. Karimi, A. M., Fada, J. S., Liu, J., Braid, J. L., Koyutürk, M., French, R. H., “Supervised and Unsupervised Machine Learning Methods on Photovoltaic Electroluminescence Images to Characterize Degradation,” presented at the Data Science Symposium (Tohoku University, Sendai Japan), Aug. 1, 2018

6. Curran, A. J., Liu, J., Karimi, A. M., Hwang, S. H., Morrison, S. M., Haddadian, R., Braid, J. L., French, R. H., “Inverter level time series analysis of real-world PV performance data,” Poster, presented at the Kyocera Materials Data Science Symposium (CWRU), Jul. 30, 2018

7. Karimi, A. M., Khalilnejad, A., Curran, A. J., Liu, J., Nash, K. J., Fada, J. S., French, R. H., “Energy-CRADLE: A Scalable Infrastructure For Large Scale Distributed Database & Computational Analytics,” (NSF Midwest Big Data Hub Meeting, Omaha, Nebraska), Jun. 2017

8. Kamath, S., Khalilnejad, A., Haddadian, R., Karimi, A. M., Koehrsen, W. J., Blincoe, D. R., Kennedy, Q. C., French, R. H., Abramson, A. R., “A Data Analytics Approach to Identifying Saving Opportunities and Inefficiencies,” Poster Presentation, presented at the Intersections: SOURCE Symposium and Poster Session (Cleveland, OH), Apr. 20, 2018

9. Curran, A. J., Fada, J. S., Karimi, A. M., Zhang, R., Fridman, L. S., Choi, M., Ligh, J. K., Ji, L., Lavrova, O., Jones, C. B., Yang, S., Fabre, R., Köhl, M., Schnabel, E., Peshek, T. J., Braid, J. L., French, R. H., “Module Level Exposure and Evaluation Test (MLEET) for Real-World & Laboratory-Based PV Modules: Common Data and Analytics for Quantitative Cross-Correlation and Validation,” Poster Presentation, presented at the Department of Energy SunShot Poster Crawl, 2017,June

10. Curran, A. J., Karimi, A. M., Hu, Y., Haddadian, R., Peshek, T. J., French, R. H., “Month-by-Month Analysis of the Power Change Rate of RealWorld, Outdoor, Photovoltaic Systems Across Multiple ClimateZones,” presented at the CWRU Cyberinfrastructure Day, Apr. 2017

11. Curran, A. J., Liu, J., Karimi, A. M., French, R. H., “Rate Of Change Determination Of Real-world Commercial PV Power Plants using Data-driven Modeling,” presented at the CWRU Research Showcase (CWRU, Cleveland OH), May 10, 2017

12. Karimi, A. M., Ligh, J. K., Curran, A. J., Khalilnejad, A., Wang, Y., Fada, J. S., Gordon, D. A., Nash, K. J., French, R. H., “E-CRADLE’s Scalable Computing Infrastructure For Large Scale Advanced Computational Analytics,” presented at the CWRU/Tohoku University Data Science Symposium in Life Sciences and Engineering 2017 (Case Western Reserve University, Cleveland OH), Aug. 2017

Teaching Assistant

1. Introduction to Database Systems (EECS 341): Relational model, ER model, relational algebra and calculus, SQL, OBE, views, query processing, normalization theory, concurrency control, object relational systems, Oracle SQL server, Microsoft SQL server.

2. Data Structure (EECS 233): lists, stacks, queues, trees, graphs, searching and sorting, hashing, recursion and higher order functions, introduction to asymptotic analysis.