*** TA Applicants: Please read this link before you contact me.
** Dear Students, I am always looking for motivated and hardworking undergraduate and graduate students who want to work on a research project and gain experience. Doing research with a faculty member during your undergrduate or graduate studies greatly enriches your skills. IMPORTANT: Please read this link before you contact me for doing research with me.
News:
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- Summer 2023: Away as visiting researcher at Pacific Northwest National Laboratory.
- Summer 2022: Away as visiting researcher at Pacific Northwest National Laboratory.
- Spring/Summer 2022: Presented our research titled "Classification of Gulf War Illness Patients vs Control Veterans Using fMRI Dynamic Functional Connectivity" at the 30th Annual Meeting of International Society of Magnetic Resonance in Medicine (ISMRM), May 2022, in London, UK: https://submissions.mirasmart.com/ISMRM2022/Itinerary/EventDetail.aspx?evt=347 .
- Fall 2021: Our paper titled "An Algebraic Nonuniformity Correction Algorithm for Hexagonally-Sampled Infrared Images: A Simulation Study" was presented at the IEEE Annual International Conference on Image Processing (ICIP), it can be accessed here: https://doi.org/10.1109/ICIP42928.2021.9506284 .
- Summer 2021: Our paper titled "Methane gas leak quantification employing infrared sensing at suspected leak sites" was presented at the Society for Optical Engineering's (SPIE) Annual Infrared Sensors, Devices and Applications Conference as part of the SPIE Annual International Optics+Photonics Meeting, it can be accessed here: https://doi.org/10.1117/12.2595775 .
- Summer 2021: Our paper titled "Algebraic nonuniformity correction for infrared imagery using a hexagonal coordinate scheme" was presented at the Society for Optical Engineering's (SPIE) Annual Infrared Sensors, Devices and Applications Conference as part of the SPIE Annual International Optics+Photonics Meeting, it can be accessed here: https://doi.org/10.1117/12.2596384 .
- Summer 2021: Our paper titled "EEG-based emotion recognition using tunable Q wavelet transform and rotation forest ensemble classifier" co-authored with researchers in Europe got accepted by the Biomedical Signal Processing and Control Journal, it can be accessed here: https://doi.org/10.1016/j.bspc.2021.102648 .
- Spring 2021: Our abstract paper titled "Adaptive space-filling curve for improved feature selection from fMRI brain activation maps: application to schizophrenia classification," was presented at the 29th Annual Meeting of International Society of Magnetic Resonance in Medicine (ISMRM), May 2021, it can be accessed here: https://index.mirasmart.com/ISMRM2021/PDFfiles/1522.html .
- Spring 2021: Extreme Science and Engineering Discovery Environment (XSEDE), Expert Mentoring Producing Opportunities for Work, Education, and Research (XSEDE EMPOWER) funding by National Computational Science Institute (NCSI) was awarded to Dr. Sakoglu in order to support an undergraduate student to dcontinue to do research with him in Spring 2021. On this project, a UHCL Computer Engineering undergraduate student is going to help Dr. Sakoglu with the project which involves Dynamic Functional Connectivity of fMRI neuroimaging data. More info on the NCSI XSEDE EMPOWER program can be found here: http://computationalscience.org/xsede-empower . Undergraduate students, if you are interested in doing research with Dr. Sakoglu and get support in the future, contact Dr. Sakoglu to discuss (first, please read this link ).
- Fall 2020: Dr. Sakoglu is honored to be the University of Houston-Clear Lake’s Finalist/Nominee for the 2020-2021 Minnie Stevens Piper Professor Award . Each year the University of Houston-Clear Lake Piper Award Committee, composed of an equal number of students and faculty, selects one professor to honor for excellence in teaching. This professor then represents the university in competition for the Minnie Stevens Piper Award, which recognizes college and university instructors across the state of Texas. Dr. Sakoglu was also a UHCL Piper Award finalist in 2019-2020.
- Fall 2020: Extreme Science and Engineering Discovery Environment (XSEDE), Expert Mentoring Producing Opportunities for Work, Education, and Research (XSEDE EMPOWER) funding by National Computational Science Institute (NCSI) was awarded to Dr. Sakoglu in order to support an undergraduate student to do research with him in Fall 2020. On this project, UHCL Computer Engineering undergraduate student Andrew Hughes is going to help Dr. Sakoglu with the project, Dynamic Functional Connectivity of fMRI Neuroimaging Data, and he will get trained on how to process and analyze neuroimaging data. More info on the NCSI XSEDE EMPOWER program can be found here: http://computationalscience.org/xsede-empower . Undergraduate students, if you are interested in doing research with Dr. Sakoglu and get support in the future, contact Dr. Sakoglu to discuss (first, please read this link ).
- Summer 2020: Check out our presentations titled "Development of an algebraic nonuniformity correction algorithm for hexagonally-sampled infrared imagery" (authors U. Sakoglu and M. Minton), and, "Infrared sensing technologies assisting environmental monitoring" (P. LeVan and U. Sakoglu)at the SPIE Optics and Photonics: Infrared Sensors, Devices, and Applications X (August 2020) here and here (the links include full-text papers, and presentations).
- Summer 2020: Our paper with collaborators in Europe, titled "Multiple sclerosis lesion detection in multimodal MRI using simple clustering-based segmentation and classification," O Cetin, V. Seymen, U Sakoglu, was published in the journal Informatics in Medicine Unlocked, Elsevier (2020). Full-text here .
- Summer 2020: Dr. Sakoglu is teaching summer graduate-level Machine Learning and Applications course. The students will apply ML techniques by doing hands-on team projects and will have chance to join an ML competition. The course includes an introductory chapter on Deep Learning as well at the end.
- Summer 2020: Our paper, titled "An Adaptive Space-Filling Curve Trajectory for Ordering 3D Datasets to 1D: Application to Brain Magnetic Resonance Imaging Data for Classification," U Sakoglu, L Bhupati, N Beheshti, N Tsekos, J Johnsson, was accepted for publication in Lecture Notes in Computational Science (LNCS), Springer, Vol. 12139, pp. 635-646 (2020). Full-text here, or pdf here.
- Summer 2020: Extreme Science and Engineering Discovery Environment (XSEDE), Expert Mentoring Producing Opportunities for Work, Education, and Research (XSEDE EMPOWER) funding by National Computational Science Institute (NCSI) was awarded to Dr. Sakoglu in order to support an undergraduate student to do research with him in Summer 2020. On this project, UHCL Computer Engineering undergraduate student Sasha Petrenko is going to help Dr. Sakoglu with the project, Medical Imaging Data Compression Using Adaptive Space Filling Curves, and she will get trained on how to process and analyze neuroimaging data. More info on the NCSI XSEDE EMPOWER program can be found here: http://computationalscience.org/xsede-empower . Undergraduate students, if you are interested in doing research with Dr. Sakoglu and get support, contact Dr. Sakoglu to discuss.
- Summer 2020: Dr. Sakoglu is a speaker & panelist on the panel topic "Facilitating AI/Machine Learning/Deep Learning", at the Virtual Residency Intermediate/Advanced Conference 2020, organized & hosted by the University of Oklahoma Supercomputing Center for Education & Research, and funded by the NSF & OU. More details here: http://www.oscer.ou.edu/virtualresidency2020.php
- Summer 2020: Dr. Sakoglu is a speaker & panelist on the panel topic "Mapping Research Requirements to Software Tools", at the Virtual Residency Intermediate/Advanced Conference 2020, organized & hosted by the University of Oklahoma Supercomputing Center for Education & Research, and funded by the NSF & OU. More details here: http://www.oscer.ou.edu/virtualresidency2020.php
- Summer 2020: Dr. Sakoglu is a speaker/presenter with topic "Adaptive space-filling curves for fMRI brain activation map classification," at the International Conference on Computational Science (ICCS), organized by Universiteit van Amsterdam (host), Nanyang Technological University - Singapore, and University of Tennessee - Knoxville. More details here: https://www.iccs-meeting.org/iccs2020/
- Spring 2020: As the university transitioned into online education for the rest of the semester, stay safe and well, exercise precaution. Check this page for resources: https://www.uhcl.edu/health-alert/
- Spring 2020: Dr. Sakoglu is on the organizing committee of Imaging Technologies Workshop which will be held at Schlumberger, Houston, TX (now postponed from April to a later date, due to rising COVID-19 concerns). Click here for more info and to register .
- Spring 2020: Dr. Sakoglu is on the organizing committee of "Infrared Sensors, Devices, and Applications X" Conference at SPIE's Annual Optics+Photonics Optical Engineering and Applications Conference, 23-27 August, 2020, San Diego, CA. Click here for more info and to submit an abstract (abstract submissions due
February 12, 2020, extended to February 29, 2020).
- Spring 2020: Expert Mentoring Producing Opportunities for Work, Education, and Research (XSEDE EMPOWER) funding by National Computational Science Institute (NCSI) was awarded to Dr. Sakoglu in order to support an undergraduate student to do research with him in Spring 2020. On this project, UHCL Computer Engineering undergraduate student Mark Minton is going to help develop non-uniformity algorithms for 2-D hexagonal infrared imagers. More info on the NCSI XSEDE program can be found here: http://www.xsede.org . Undergraduate students, if you are interested in doing research with Dr. Sakoglu and get support, contact Dr. Sakoglu to discuss.
- Fall 2019: Congratulations to Lohit Bhupati for defending his master's thesis on finding approximations of optimal space-filling curves for 3D brain MRI volumes and using them in classification of different brain conditions from fMRI brain activation maps!
- Fall 2019: Dr. Sakoglu was selected as a finalist (one of the five faculty) from UHCL for the 2019-2020 Minnie Stevens Piper Award for excellence in teaching. More details here: https://www.uhcl.edu/faculty-research/faculty-recognition
- Fall 2019: Participated in the 1st Translational Imaging Symposium of the Gulf Coast Consortia at Rice University.
- Summer 2019: Our paper, with our UHCL student Francisco Reveriano as the primary author, got accepted at ACM Practice and Experience in Advanced Research Computing (PEARC). Click here to access the full paper.
- Spring 2019: Our paper, "Classification of Cocaine Dependent Participants with Dynamic Functional Connectivity from Functional Magnetic Resonance Imaging Data," Sakoglu U, Mete M, Esquivel J, Rubia K, Briggs RW, Adinoff B, got accepted for publication by Journal of Neuroscience Research (2019) .
- Spring 2019: Our paper, "Exploring brain mechanisms underlying Gulf War Illness with group ICA based analysis of fMRI resting state networks," Gopinath K, Sakoglu U, Crosson B, Haley H, got accepted for publication by Neuroscience Letters, Vol. 710, pp. 136-141 (2019). Click here or here to access.
- Spring 2019: Our abstract titled "Connectomics signatures of Gulf War Illness reveal brain mechanisms underlying the disorder" with co-authors K. Gopinath, B. Crusson, R. Haley, got accepted for presentation at OHBM 2019 .
- Spring 2019: Our abstract titled "Brain mechanisms underlying Gulf War Illness revealed by connectomics signatures of the disease" with co-authors K. Gopinath, B. Crusson, R. Haley, got accepted for presentation at ISMRM 2019 .
- Fall 2018: Congrats to graduate students Sasank Bhamidipati and Jessica De Leon, who defended their MS theses! Click here for photos. .
- Fall 2018: CENG 5331 Machine Learning course students Russell Pannell, Michael Sanchez and Omer Ozdemir got the 1st award with the results of their course research project "Identification of Lung Opacities on Chest Radiographs Using Supervised
Deep Learning Techniques" at the IEEE DUAL Conference 2018, Houston, TX.
- Fall 2018: UHCL Computer Engineering Program passed another ABET comprehensive review / evaluation. ABET.org is the primary organization that accredits college and university programs in applied and natural science, computing, engineering and engineering technology. CENG has been ABET-accredited since 10/1999, now for almost two decades! Proud to be part of the UHCL Computer Engineering Program!
- Summer 2018: Presented AFRL research work at University of Florida Research and Engineering Facility, FL.
- Summer 2018: Awarded by the US Air Force Research Lab (AFRL) a summer faculty research grant to work on optimal sampling for imagers during the Summer of 2018.
- Summer 2018: Presented at tutorial on dynamic functional connectivity at PRNI 2018 and research results on classification of Gulf War Illness using functional connectivity at OHBM 2018 in Singapore. UHCL graduate students Mounika Galla, Sasanka Bhamidipadi were also co-authors of the accepted OHBM abstract and presentation.
- Summer 2018: Our neuroimaging analysis research results on Gulf War Illness fMRI data were presented by collaborator Dr. Gopinath at ISMRM 2018 Annual Meeting in Paris, FR.
- Spring 2018: Presented research results titled "Classification of Gulf War Illness Using Machine Learning in fMRI" and "Classification of Cocaine Addiction Using Hilbert-Curve Ordering of fMRI Activations" at the ISMRM Machine Learning Workshop in Pacific Grove, CA in March 2018. UHCL graduate students Mounika Galla, Sasanka Bhamidipadi, Jessica De Leon and Christian Huerta were co-authors of the accepted abstracts.
- Fall 2017: Presented a talk on fMRI analysis at the IEEE DUAL Automation/Innovation Conference, Gilruth Center, NASA JSC, Houston, TX. My CENG 5931 students Christian Huerta and Jessica De Leon got the 3rd best student award at with their poster "Brain Mapping Based Classification of Functional MRI Data". Congrats! My other students, Mounika Galla and Sasanka Bhamidipadi also presented posters there.
- Fall 2017: New graduate level course: CENG 5931.05 Medical Imaging Data Analysis (Special Topic). Click Syllabus.
- Summer 2017: Our work on Gulf War Neuroimaging project was presented by our collaborator Dr. Gopinath at the 2017 Human Brain Mapping Annual Meeting in Vancouver, BC. Abstract link here.
- Summer 2017: Presented AFRL research work at University of Florida Research and Engineering Facility, FL.
- Spring & Summer 2017: Awarded by the US Air Force Research Lab (AFRL) a summer faculty research grant to work at an AFRL facility on optimal sampling for imagers during the Summer of 2017.
- Apr. 2017: Presented Gulf War Neuroimaging project research at the 25th Annual Conference of the
International Society for Magnetic Resonance in Medicine (ISMRM), Honolulu, HI
- Apr. 2017: Presented research to students as part of the Tech Talks of IEEE UHCL Student Branch.
- Feb. 2017: Presented fMRI data-based classification as part of the IEEE Galveston Bay Section talk series at Gilruth Center, NASA JSC, Houston.
- Jan. 2017: Presented neuroimaging research at the 14th Theoretical and Computational Neuroscience Conference of the Gulf Coast Consortia at Rice University.
- Jan. 2017: Away at Emory University for collaborative work on the DOD project which started in October 2016.
- Oct. 2016: Our paper titled "Successful classification of cocaine dependence using brain imaging: a generalizable machine learning approach" got accepted by the BMC Bioinformatics journal.
- Oct. 2016: Gave a talk on fMRI based classification at MICCAI 2016 Conference, Athens, Greece.
- Fall 2016: I left TAMUC Computer Science Dept and I am now with Computer Engineering Dept at University of Houston - Clear Lake.
- Summer 2016: Presented infrared imaging related research with AFRL colleagues at the SPIE 2016 Optics+Photonics Conference in San Diego, CA.
- Summer 2016: Away at Air Force Research Lab for summer research.
- Spring 2016: Dr. Sakoglu and collaborators at Emory University and UT-Southwestern Medical Center were awarded a two-year $554,000 research grant by the US Department of Defense (DOD) in order to perform advanced analysis of fMRI data from Gulf War Veterans. The project is for two years, starting in September 2016.
- Spring 2016: Awarded by the US Air Force Research Lab a summer faculty research grant to work at an AFRL facility on IR Imagers during the Summer of 2016.
- Spring 2016: Awarded by ProQuest, LLC an R&D grant to optimize enterprise data & information systems and to support a graduate student work on the project.
- Fall 2015: Our paper, in collaboration with visiting student Sezgin Kacar, got published at the journal "Computer Methods and Programs in Biomedicine"
The paper can be accessed here or in the Publications link above.
- Fall 2015: Our paper, in collaboration with the TAMUC Ontological Semantics Lab at TAMUC, got published at the journal "Expert Systems with Applications" one of the top journals in Artificial Intelligence MS research link here , and Google Scholar link here . The paper can be accessed here or in the Publications link above. Also, in the news: Pride Online .
- Summer 2015: Our paper, in collaboration with the collaborators at the US AFRL and in industry, got published at the Proceedings of the SPIE: Infrared Sensors, Devices, and Applications V, 2015. Find link here or in the Publications link above.
- Summer 2015: My GRA Seetaramaraju (Raju) Jampana successfully defended his master's thesis in Computational Science and graduated! Congratulations Raju!
- Summer 2015: I am away during the summer since I was awarded a summer research grant by the Air Force Research Lab Summer Faculty Research Program to do research at the Kirtland AFRL .
- Summer 2015: (Hired) A paid GAR position, to work on an externally-funded data project, is available. Refer to this flyer for details and instructions how to apply.
- Spring/Summer 2015: Looking for research participants, who will be compensated, for a 1-hour EEG experiment. Refer to this flyer for details.
- Spring 2015: Our new journal paper on GPU-based dynamic functional connectivity analysis of fMRI data , got accepted by the Computerized Medical Imaging and Graphics Journal, Elsevier. It can be accessed here or downloaded here .
- Spring 2015: Advanced Data Analysis Laboratory (ADALab), under the directorship of Dr. Sakoglu, is established at the department at Room Jour203. More details coming soon.
- Fall 2014: My new course CSCI597/502 Statistics for Scientific Computation and Analysis is available in Fall 2014. It is now one of two prerequisite courses for the Computational Science MS program starting this Fall. See the the 2014/15 course catalog for details.
- Fall 2014: (Hired) A graduate research assistant (GRA) position is available starting Fall. See this flyer for details.
- Summer 2014: GARs Kushal Bohra and Johnny Esquivel successfully defended their theses and graduated! Congratulations Kushal and Johnny!
- Summer 2014: Received the competitive TX A&M - Commerce Faculty Research Enhancement Project Award for collecting new EEG data, and developing and testing novel classification algorithms on EEG data.
- Summer 2014: Our paper on GPU implementation of dynamic functional connectivity analysis for fMRI data is accepted for presentation at IEEE International Conference on Electro/Information Technology.
- Spring 2014: Gave a seminar talk on utilizing space-filling curves for suboptimal and optimal 3-D to 1-D mapping and their application to map 3-D MRI data; on 4/16 as part of CSE Colloquium Series at SMU Lyle School of Engineering.
- Spring 2014: Graduate students Kushal Bohra, Johnny Esquivel, undergraduate student Heriberto Flores and visiting scholar Devrim Akgun presented projects supervised by Dr. Sakoglu at the MCBIOS 2014 11th Annual Conference . Kushal got 2nd student presentation award with his work on toolbox development for multivariate classification of fMRI data. Congrats Kushal! Click here for the TAMUC news release on the achievement.
- Spring 2014: Our accepted paper on optimal 3-D to 1-D brain mapping was presented at the ISCA's 2014 Bioinformatics and Computational Biology Conference (BICoB) . You can view the proceeding paper here .
- Fall 2013: Gave a week-long seminar on fMRI analysis methodologies with colleagues at Sakarya University in November 2013, supported by a grant from TUBITAK.
- Fall 2013: Our work on software development for multivariate classification and dynamic functional connectivity analysis for fMRI data got accepted for presentation at the IEEE EMBS 2013 Annual Medical Device Symposium in Dallas. Graduate students Kushal Bohra and Johnny Esquivel (co-advised by Dr. Mutlu Mete) presented the work. Also, another related project presented by graduate student Harish Ankam, also co-authored by Dr. Sakoglu and Dr. Mete, got the 3rd best presentation award. Click here for the TAMUC news release on the achievement.
- Summer 2013: Received the competetive TX A&M - Commerce Faculty Research Enhancement Project Award for multivariate classification of fMRI data.
- Summer 2013: The new 32 channel wireless dry EEG system has arrived! Click here to see a photo of it on me.
- Spring 2013: Presented research results on the effects of variance on brain functional connectivity analysis, at the Annual Meeting of the ISMRM . Click here for the presentation.
- Spring 2013: Received TAMUC Faculty Development Grant for traveling to ISMRM .
- Spring 2013: Gave an invited seminar talk at the CSE Dept at Texas A&M - College Station.
- Fall 2012: Started Assistant Professor position at Computer Science Dept, Texas A&M University - Commerce (TAMUC).
Education & Bio:
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- Post-Doctoral Training, Neuroimaging/MRI, BRAIN Imaging Center, University of New Mexico Health Sciences Center , Albuquerque, NM
- Ph.D., Electrical and Computer Engineering , Center for High Technology Materials, University of New Mexico, Albuquerque, NM
- M.S., Electrical and Computer Engineering , University of New Mexico, Albuquerque, NM
- B.S., Electrical-Electronics Engineering, Bilkent University
Dr. Unal "Zak" Sakoglu is currently an Associate Professor at Computer Engineering Dept at University of Houston - Clear Lake (UHCL). Prior to UHCL, he was an Assistant Professor of Computer Science, Texas A&M University at Commerce. He had his B.S. degree in Electrical-Electronics
Engineering from Bilkent University, and M.S. & Ph.D. degrees in Electrical and Computer Engineering from University of New Mexico, Albuquerque.
His graduate research involved developing signal/image processing and nonuniformity correction algorithms for better multi-/hyper-spectral sensing with infrared array sensors developed at UNM Center for High Technology Materials, where worked to characterise the sensors; he worked on projects that were supported by NSF and NRO. He is co-author of a patent on spectrally tunable infrared detector) which has been since licensed. Dr. Sakoglu did his post-doctoral training at UNM Neurology Department BRAIN Imaging Center, and Mind Research Network in Albuquerque, where he developed and applied
data analysis & classification techniques to functional magnetic resonance imaging data on NIH-supported projects.
Subsequently, he worked as Research Scientist at UT Southwestern Medical Center Neuroradiology Department, at Abbott Laboratories Translational Neuroimaging Group, and UT Dallas Center for Vital Longevity, where he analyzed different modalities of medical imaging data such as PET/CT, SPECT/CT, MRI and fMRI, during these positions.
He is currently working on development and application of dynamic multivariate pattern classification, data-mining and machine-learning methods to functional
neuroimaging data in order to advance the understanding of how the human brain is functioning and how it is effected by different brain conditions (different stimuli, disease, etc.). He is also working on developing better brain mapping, fMRI signal simulation and visualization techniques for improved dynamic analysis and classification of multidimensional neuroimaging data. He also continues his research interests in infrared imaging and remote sensing. His research has been supported by the DOE, DOD, AFOSR/AFRL, and private industry.
My Linkedin Profile.
Research:
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Dr. Sakoglu's current research includes development and application of dynamic multivariate pattern recognition, classification, data-mining and machine-learning methods to functional neuroimaging data (functional MRI and EEG) in order to advance the understanding of how the human brain is functioning and how it is effected by different brain conditions, focusing on psychiatric conditions such as addiction, and also on Gulf War Illness. Brain is a highly dynamic organ; he and colleagues developed the seminal dynamic functional connectivity analyses of fMRI neuroimaging data (Sakoglu et al, "A method for evaluating dynamic functional network connectivity and task-modulation: application to schizophrenia," Magn. Res. Mater. Phys. Biol. Med. (MAGMA) 2010 23(5-6) pp. 351-366). He is also working on developing improved data processing, mapping and visualization techniques for dynamic analysis and classification of multidimensional neuroimaging data, as well as signal processing techniques for adaptive compression and processing of multidimensional signals/data. Click on the Publications link below for more details on his research activities.
Publications:
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Here is a link to list of Dr. Sakoglu's journal articles and conference abstracts, presentations and proceedings. Links to full texts are available there for most of the publications. Please contact if you have difficulty in downloading any. You can also access most of them here:
Publications on Google Scholar
Teaching
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At UHCL:
- Fall 2023: CENG 5531 Machine Learning and Applications (also cross-listed as senior undergraduate special topic course)
- Fall 2023: CENG 3313 Linear Circuits,
- Fall 2023: CENG 4331 Analysis and Design of Linear Systems,
- Spring 2023: CENG 3313 Linear Circuits,
- Spring 2023: ENGR 2305 Electrical Circuits,
- Spring 2023: CENG 4331 Analysis and Design of Linear Systems,
- Spring 2023: Instructor-on-record for CENG3113 Lab for Linear Circuits,
- Fall 2022: CENG 5531 Machine Learning and Applications (also cross-listed as senior undergraduate special topic course),
- Fall 2022: CENG 3313 Linear Circuits,
- Fall 2022: CENG 4331 Analysis and Design of Linear Systems,
- Fall 2022: Instructor-on-record for CENG3113 Lab for Linear Circuits,
- Spring 2022: CENG 3313 Linear Circuits,
- Spring 2022: ENGR 2305 Electrical Circuits,
- Spring 2022: CENG 4331 Analysis and Design of Linear Systems,
- Spring 2022: Instructor-on-record for CENG3113 Lab for Linear Circuits,
- Spring 2022: CENG 6939 One CENG Master's thesis student.
- Fall 2021: CENG 3313 Linear Circuits,
- Fall 2021: CENG 4331 Analysis and Design of Linear Systems,
- Fall 2021: CENG 2112.01/03 Lab for Digital Circuits.
- Summer 2021: CENG 5531.01 Machine Learning and Applications,
- Summer 2021: CENG 6939 One CENG Master's thesis student.
- Spring 2021: CENG 3313 Linear Circuits
- Spring 2021: ENGR 2305 Electrical Circuits
- Spring 2021: CENG 4331 Analysis and Design of Linear Systems
- Spring 2021: Instructor-on-record for CENG3113 Lab for Linear Circuits.
- Spring 2021: CENG 6939 One CENG Master's thesis student.
- Fall 2020: CENG 3313 Linear Circuits,
- Fall 2020: CENG 4331 Analysis and Design of Linear Systems,
- Fall 2020: CENG 5631 Digital Image Processing,
- Fall 2020: CENG 6939 One CENG Master's thesis student.
- Fall 2020: Instructor-on-record for CENG3113 Lab for Linear Circuits.
- Summer 2020: CENG 5531.01 Machine Learning and Applications
- Summer 2020: CENG 4389 and 5389 Independent Study/Research with one graduate and two undergraduate student research assistants.
- Spring 2020: CENG 3313 Linear Circuits
- Spring 2020: ENGR 2305 Electrical Circuits
- Spring 2020: CENG 4331 Analysis and Design of Linear Systems
- Spring 2020: Instructor-on-record for CENG3113 Lab for Linear Circuits
- Fall 2019: CENG 3313 Linear Circuits
- Fall 2019: CENG 4331 Analysis and Design of Linear Systems
- Fall 2019: CENG 5431 Digital Signal Processing
- Fall 2019: CSCI 6939 One CSCI Master's thesis student.
- Fall 2019: CENG 4389 One CENG independent study student.
- Summer 2019: CENG 5531.01 Machine Learning and Applications
- Summer 2019: CSCI 6939 One CSCI Master's thesis student.
- Spring 2019: CENG 3313 Linear Circuits
- Spring 2019: ENGR 2305 Electrical Circuits
- Spring 2019: CENG 4331 Analysis and Design of Linear Systems
- Spring 2019: CENG 5631 Digital Image Processing (syllabus here.)
- Fall 2018: CENG 4331.01 Analysis and Design of Linear Systems
Fall 2018: CENG 5431.01 Digital Signal Processing (cancelled)
- Fall 2018: CENG 5531.01 Machine Learning and Applications (syllabus here.)
- Fall 2018: CENG 6939 Two CENG MS thesis students.
- Summer 2018: CENG 6939 Two CENG MS thesis students.
- Spring 2018: CENG 3313 Linear Circuits
- Spring 2018: CENG 3264 Engineering Design and Project Management
- Spring 2018: CENG 5389 Two CENG Graduate Independent Study students
- Fall 2017: CENG 4331.01 Analysis and Design of Linear Systems
- Fall 2017: CENG 5931.05 Medical Imaging Data Analysis (newly created graduate special topic course, syllabus here.)
- Fall 2017: CENG 5389 One CENG graduate independent study student
- Spring 2017: CENG 3314 Advanced Linear Circuits
- Spring 2017: CENG 6431 Digital Signal Processing Implementations
- Fall 2016: CENG 4331 Analysis and Design of Linear Systems
Prior, at TAMUC:
- Spring 2016: CSCI 502 Statistics for Computational Science and Analysis (syllabus here)
- Spring 2016: CSCI 516 Fundamental Concepts of Computing and Machine Organization (Assembly Programming Language) (2 Sections)
- Fall 2015: CSCI 502 Statistics for Computational Science and Analysis (syllabus here)
- Fall 2015: CSCI 516 Fundamental Concepts of Computing and Machine Organization (Assembly Programming Language) (3 Sections)
- Spring 2015: CSCI 502 Statistics for Computational Science and Analysis (syllabus here)
- Spring 2015: CSCI 516 Fundamental Concepts of Computing and Machine Organization (Assembly Programming Language)
- Spring 2015: CSCI 518 MS Thesis (1 thesis student)
- Winter 2014/15: CSCI 530 Operating Systems (Online)
- Fall 2014: CSCI 502 Statistics for Computational Science and Analysis (newly created course, syllabus here)
- Fall 2014: CSCI 516 Fundamental Concepts of Computing and Machine Organization (Assembly Programming Language), one online one face-to-face section.
- Fall 2014: CSCI 518 MS Thesis (1 thesis student)
- Fall 2014: CSCI 490 Independent Honor's Readings
- Summer 2014: CSCI 516 Fundamental Concepts of Computing and Machine Organization (Assembly Programming Language)
- Summer 2014: CSCI 530 Operating Systems (Online)
- Summer 2014: CSCI 518 MS Thesis (1 thesis student)
- Summer 2014: CSCI 507 Computational Science Internship
- Spring 2014: CSCI 516 Fundamental Concepts of Computing and Machine Organization (Assembly Programming Language)
- Spring 2014: CSCI 430 Operating Systems
- Spring 2014: CSCI 518 MS Thesis (1 thesis student)
- Spring 2014: CSCI 491 Independent Honor's Readings
- Fall 2013: CSCI 516 Fundamental Concepts of Computing and Machine Organization (Assembly Language)
- Fall 2013: CSCI 524 Analysis and Design of Software Systems
- Fall 2013: CSCI 430 Operating Systems
- Fall 2013: CSCI 518 MS Thesis (1 thesis student)
- Spring 2013: CSCI 595: Research Literature & Techniques
- Spring 2013: CSCI 430: Operating Systems
- Spring 2013: CSCI 489: Independent Study
- Fall 2012: CSCI 524 Analysis and Design of Software Systems
- Fall 2012: CSCI 430 Operating Systems
Students and Visiting Scholars Supervised:
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- Current:
- Amaresh Mishra, graduate student, dynamic functional connectivity analyses-based classification of fMRI data
- Previous or graduated
- Andrew Hughes, undergraduate student, dynamic time-series analyses of fMRI data.
- Olexandra 'Sasha' Petrenko, undergraduate student, data-adaptive signal/image compression techniques and applications to medical imaging data.
- Michael Sanchez, MS student, image subject identification using deep learning methods.
- Mark Minton, undergraduate student, image processing for infrared imagers.
- Lohit Bhupadi, MS Thesis Student and GRA, Finding Optimal Space Filling Curves for fMRI Brain Activation Mapping and Classification.
- Mitchell Jefferies, undergraduate student, 3D hexagonal sampling of data.
- Francisco Reveriano, undergraduate student, Applications of Deep Learning and Computer Vision Applications.
- Jessica de Leon, MS Thesis Student, Classification Using Hilbert Space Filling Curve Ordering of fMRI Activity Maps.
- Sasanka Bhamidipati, MS Thesis Student & GRA, Machine Learning Applications to Classify Events from EEG Data.
- Mounika Galla, MS Student & GRA, worked on Advanced fMRI Data Analysis Based on Functional Connectivity and ICA.
- In the Past @TAMUC:
- A. Mutalip Dirik, MS Student and Graduate Research Assistant (supported by my ProQuest grant), Enterprise Information Systems, 02/2016 - 08/2016. Project completed.
- Dr. Ozdemir Cetin, visiting scholar, Assoc. Prof at Sakarya University, Turkey, medical image analyses, 08/2015 - 12/2015.
- Heriberto Flores, senior undergraduate honors thesis student, Structural Brain Data Mapping, 08/2013 - 12/2015. Graduated.
- Seetaramaraju Jampana, MS Thesis Student and Graduate Student Worker (supported by my FREP 2015 grant), Novel Time-Series Classification Analysis of EEG Data, 09/2014 - 08/2015. Graduated.
- John Esquivel, MS Thesis Student and Graduate Research Assistant (supported by my FREP 2014 grant), Dynamic Analysis of fMRI Data, 08/2013 - 08/2014. Graduated.
- Kushal Bohra, MS Thesis Student and Graduate Research Assistant (supported by my startup grant), Multivariate Classification of fMRI Data, 08/2012 - 08/2014. Graduated.
- Dr. Devrim Akgun, Visiting Scholar / Assistant Professor, Sakarya University, Turkey, GPU-based and parallel implementation of medical image analysis algorithms. 01/2014 - 06/2014.
- Sezgin Kacar, visiting scholar & PhD student, Sakarya University, Turkey, biomedical signal processing tool development. 10/2013 - 12/2013.
- Brandon Provost, senior undergraduate student, Hirsch-index (h-index)-based Computer Science Department Rankings, 01/2013 - 05/2013. Graduated.
Service/Committees:
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- ABET Engineering Accreditation Commission Program Evaluator (06/2023 - current)
- UHCL College of Science and Engineering Faculty Development and Research Fund Committee (2022 - 2023)
- UHCL M.S. Piper Award Committee (2021)
- Computer Engineering Graduate Program Assessment and Planning for Institutional Effectiveness (2019-current), UHCL
- Computer Engineering Program Website Faculty Liaison (2019-current), UHCL
- Computer Engineering Program ABET Compliance (2017-current), UHCL
- Computer Engineering Program Curriculum Development (2016-current), UHCL
- Computer Engineering Graduate Program Faculty Adviser (2016-current), UHCL
- Engineering Department Representative, CSE Computing, Library and Research Committee (2019-2020), UHCL
- Vice Chair, Education Committee of the IEEE Galveston Bay Section (2018 - 2019).
- Organizing Committee Member, SPIE Conference on Infrared Sensors, Devices, and Applications XI(2021), X(2020), IX (2019), VIII (2018), VII (2017), and VI (2016) .
- Reviewer for Journals: IEEE Journal of Biomedical and Health Informatics, Human Brain Mapping, Brain Connectivity, NeuroImage, Journal of Medical Systems, Computational Statistics and Data Analysis, Imaging Science Journal, Optics Communications, Annals of Operations Research
- Professional Memberships and Past-memberships: IEEE, ACM, SPIE, ISMRM, ESMRMB (Assoc. Member), ASEE, ISCA, OHBM, CNS, SfN.
- Faculty Supervisor, TAMUC Local TAMUC ACM Student Chapter (2015 - 2016).
- Coordinator, TAMUC Computational Science Graduate Program (2012 - 2016)
- Member, TAMUC Graduate Curriculum Development Committee (2012 - 2016)
- Member, TAMUC Graduate Admission Committee (2013 - 2016)
- Member, TAMUC Graduate Faculty (2012 - 2016)
- Member, Committee for the TAMUC CS department's ABET accreditation application (2013 - 2016)
Other Links:
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Dear Students:
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**I am always looking for motivated and hard-working undergraduate and graduate students who want to work on a research project as volunteers, as part of independent study, or master's thesis; so I would be happy to train and supervise you. Funding may be available for students as research assistants (RAs), as I always seek funding to support RA students, and, our program, department or school may also have funding available to support. Volunteer students who worked on a project with me, or students who are doing an independent study or master's thesis will be given priority for any possible paid RA positions in the future upon I receive funding. The key is, do establish connection early on with me, earlier than the semester that you intend to help, so we can have enough time to discuss and find ways to support.
There are different ways you can help me with research. If you just simply want to volunteer, I will be happy to meet you weekly and give you a small project to work on. But probably the best way to get started for you is to sign up for an independent study class under my supervision and obtain 1-to-3 credit-hours towards your degree for doing research with me for one semester. An independent study course, either as undergraduate or graduate, counts towards your electives. If you are a graduate student and you really like a research topic and if you want to commit even more time, i.e. for two semesters, you can sign up for master's thesis and do research with me for two semesters, I will be happy to supervise you. For example, I've had graduate students who did independent study and then they continued into master's, spanning 3 or more semesters doing research with me.
If you are interested, please email me with your interest with the following attached: 1) A current resume/CV, 2) copy of your unofficial UHCL transcripts, 3) copy of your previous transcripts if you have other degrees, 4) any other supporting documents, like TOEFL, IELTS, GRE scores, description of any projects you have done, and if you have co-authored any papers, etc. attach them, it would be helpful. Please go over my research interests, list of publications, and email me what part of my research you would be interested in.
In any case, if you are interested in doing research with me, I also encourage you to take any course(s) that I am teaching; I also give priority to students who have taken or who are taking my courses; it gives me a chance to get to know you better also. The graduate courses that I teach include: Machine Learning and Applications, Digital Image Processing, and Digital Signal Processing. When I teach any of these courses, I usually offer (co-list) these graduate courses as an undergraduate special topic course too, so that undergrads can take as an elective.
As always, if you have any questions, feel free to email me.
Dear TA Applicants:
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***Dear TA Applicants: Thanks for your interest in doing TA with me in the next semester.
Please send me the following info fully, if you haven't already; in one single email:
1. a copy of the filled TA appliction form that you sent to the CENG program;
2. your current CV/resume;
3. the courses that you enrolled for in the next semester (the semester that you are applying for), and, your weekly class schedule for that semester;
4. list your experience with courses such as Machine Learning, Electrical Circuits, and, Signals and Systems (i.e. whatver courses I am teaching the next semester), and, whether you have taken any of these courses anywhere and what were your grades, who was/were the instructor(s) if you took them at UHCL, which textbook did you use;
5. if you have taken any of my courses in the past from me, state which course(s) at which semester and what grade you got;
6. your unofficial transcripts from UHCL and from your undergraduate, and, from any other program(s) that you attended or graduated;
7. if you did TA before for another course or instructor at UHCL or anywhere, for which course(s) and when and where, who was the instructor, their contact information; and brief description of your TA duties and experience [if it was some other on-campus work that you did (such as an RA for a faculty, or working at the library, tutoring center, etc.) which was not necessarily TA job, still provide when and where was the job, the nature of the job in a sentence, and do provide the contact information of your supervisor of that job] .
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Thanks for stopping by and please check back soon!
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Unal "Zak" Sakoglu, Ph.D.
Associate Professor, Computer Engineering
University of Houston - Clear Lake
Houston, TX
Phone/voicemail: +1 (281) 283-3813
Email: mylastname AT uhcl DOT edu
UHCL Webpage: http://sce.uhcl.edu/sakoglu
Webpage, Linkedin http://www.linkedin.com/in/unalsakoglu
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Copyright 2016 - 2023 Unal Sakoglu
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