Mariam Ben Hassen | Computer Science | Editorial Board Member

Published on by Award and Honors

Assist. Prof. Dr. Mariam Ben Hassen | Computer Science | Editorial Board Member

Assist. Prof. Dr. Mariam Ben Hassen | University of Sfax | Tunisia

Dr. Mariam Ben Hassen is a computer science scholar recognized for her contributions to knowledge management, business process modeling, ontology engineering, and decision support. Her work bridges theoretical innovation with practical frameworks for designing and specifying complex enterprise information systems, emphasizing multi-dimensional modeling, intelligent systems, and extending BPMN through ontological structures. Her research develops conceptual and ontological frameworks to model sensitive business processes, enhance enterprise information systems, and support knowledge-driven decision-making. She has extensive experience in academic teaching, research supervision, and project leadership, producing impactful publications in high-ranking journals and international conferences. Her scholarship integrates knowledge representation with organizational processes, advancing modern perspectives in information systems engineering and providing valuable tools for intelligent, data-informed enterprise management.

Profile : Google Scholar 

Featured Publications 

Conceptual Analysis of Sensitive Business Processes. (2023). Business Process Management Journal. Cited by: N/A.

 

Licheng Liu | Computer Science | Best Researcher Award

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Assoc. Prof. Dr. Licheng Liu | Computer Science | Best Researcher Award 

Associated professor, at Hunan University, China.

Dr. Licheng Liu (刘立成) is an Associate Professor at the School of Electrical and Information Engineering, Hunan University, China. He earned his Ph.D. from the University of Macau under the mentorship of Prof. C.L. Philip Chen, a Fellow of the IEEE and a Member of the European Academy of Sciences. Dr. Liu is recognized as a Yue Lu Scholar and serves as a Ph.D. advisor. He is a Senior Member of IEEE and has received the Hunan Provincial Outstanding Young Scientist Fund. His research interests encompass deep learning, broad learning systems, and sparse manifold learning. He has authored nearly 50 papers in top-tier journals and conferences, including IEEE Transactions on Cybernetics, Neural Networks and Learning Systems, and Circuits and Systems for Video Technology. His work has garnered over 1,265 citations and an h-index of 17.

Professional Profile

Scopus

🎓 Education 

Dr. Liu’s academic journey began with a Bachelor’s degree in Mathematics and Physics from China University of Geosciences (Wuhan) in 2010. He then pursued a Master’s degree in Mathematics at Hunan University, graduating in 2012. His doctoral studies were completed at the University of Macau in 2016, where he worked under the supervision of Prof. C.L. Philip Chen. Throughout his education, Dr. Liu focused on areas such as sparse representation, image processing, and machine learning, laying a strong foundation for his subsequent research endeavors.

💼 Experience

Dr. Liu commenced his professional career as an Assistant Professor at Hunan University’s School of Electrical and Information Engineering in 2016. By 2019, he was promoted to Associate Professor and was honored as a Yue Lu Scholar. In his academic role, Dr. Liu has supervised numerous graduate students and has been actively involved in various research projects, particularly those funded by the National Natural Science Foundation of China. His research contributions have significantly advanced the fields of image restoration, face hallucination, and noise reduction in visual data.

🔬 Research Interests 

Dr. Liu’s research interests are centered on deep learning, broad learning systems, and sparse manifold learning. He is particularly focused on developing novel algorithms and models to enhance image restoration, low-light object detection, and low-quality image recognition. His work aims to address challenges in visual data processing, such as noise reduction and image enhancement, by leveraging advanced machine learning techniques. Dr. Liu’s innovative approaches have led to the development of robust models capable of improving the quality and accuracy of visual data interpretation in various applications.

🏆 Awards 

Dr. Liu has received several prestigious awards throughout his career. In 2016, he was honored with the Macao SAR Graduate Student Science and Technology Research Award by the Macao Science and Technology Development Fund. In 2018, he was recognized as a Yue Lu Scholar by Hunan University. His excellence in teaching was acknowledged in 2021 when he received the First-Class Teaching Achievement Award from Hunan University. The following year, he was awarded the Special Prize for Higher Education Teaching Achievement by the Hunan Provincial Department of Education. In 2023, Dr. Liu received the National Teaching Achievement Award (Second Class), and in 2024, he was named an Outstanding Master’s Thesis Advisor in Hunan Province. Additionally, he was honored with the Third Prize in Natural Science by the Chinese Association of Automation in 2024.

📚Top Noted  Publications 

Dr. Liu has authored nearly 50 research papers, with 25 published in IEEE/ACM journals. Notable publications include:

1. Weighted Joint Sparse Representation for Removing Mixed Noise in Image (2017)

  • Journal: IEEE Transactions on Cybernetics, 47(3), 600–611.

  • Summary: This paper introduces a method for removing mixed noise in images using a weighted joint sparse representation. The approach aims to effectively address challenges posed by mixed noise types in image processing.

2. Robust Face Hallucination via Locality-Constrained Bi-Layer Representation (2018)

  • Journal: IEEE Transactions on Cybernetics, 48(4), 1189–1201.

  • Summary: The authors propose a robust face hallucination method that utilizes a locality-constrained bi-layer representation. This technique enhances face image resolution while maintaining robustness against noise and outliers. europepmc.org

3. Mixed Noise Removal via Robust Constrained Sparse Representation (2018)

  • Journal: IEEE Transactions on Circuits and Systems for Video Technology, 28(9), 2177–2189.

  • Summary: This paper presents a robust constrained sparse representation method for removing mixed noise from images. The approach adapts to different noise types and effectively restores image quality. figshare.com

4. Discriminative Face Hallucination via Locality-Constrained and Category Embedding Representation (2021)

  • Journal: IEEE Transactions on Systems, Man, and Cybernetics: Systems, 51, 7314–7325.

  • Summary: The authors introduce a discriminative face hallucination method that combines locality-constrained representation with category embedding. This approach improves the quality of face image super-resolution by considering category-specific information.

5. Modal-Regression-Based Broad Learning System for Robust Regression and Classification (2023)

  • Journal: IEEE Transactions on Neural Networks and Learning Systems, 35(9), 12344–12357.

  • Summary: This paper proposes a modal-regression-based broad learning system to enhance robustness in regression and classification tasks. The method addresses challenges posed by noisy and outlier-prone data, improving model performance. pubmed.ncbi.nlm.nih.gov

Conclusion

Dr. Licheng Liu demonstrates exceptional strength as a mid-career researcher with an outstanding publication record, robust funding history, and recognized academic leadership in AI and image processing. His ability to balance theoretical innovation with practical application is evident in his funded projects and impactful publications.

Ernesto Diaz | Computer Science | Best Researcher Award

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Mr  Ernesto  Diaz |  Computer Science |  Best Researcher Award

Assistant Specialist at University of California, San Francisco – Radiology & Biomedical Imaging, United States

Ernesto Diaz is a highly skilled Data Scientist at the University of California, San Francisco (UCSF), specializing in Hyperpolarized Carbon-13 Metabolic Imaging within the Department of Radiology and Biomedical Imaging. He earned his Bachelor of Science in Computer Science from San Francisco State University in 2022, consistently achieving Dean’s List honors.

Profile:

🎓 Education:

San Francisco State University, San Francisco, CA

  • Bachelor of Science in Computer Science, 2022
  • Dean’s List: 2020-2022

💻 Technical Skills:

Languages & Environments: Python, R-Code, C++, MATLAB, HTML, CSS, Shell Scripting, CUDA, UNIX
Packages: Pandas, Matplotlib, NumPy, PyDicom, TensorFlow, PyTorch, Tkinter, Conda, CMake

🔬 Research Experience:

Data Scientist
University of California San Francisco, Department of Radiology and Biomedical Imaging
June 2022 – Present

  • Developed data processing methods for Hyperpolarized Carbon-13 Metabolic Imaging.
  • Lead developer of a Python application for HP 13C DICOM Images metadata integration.
  • Co-developed a deep learning image segmentation tool achieving 80% accuracy in prostate cancer segmentation.
  • Contributed to UCSF’s open-source MR Spectroscopy tool (SIVIC).

Undergraduate Researcher
UCSF, Department of Radiation Oncology
August 2021 – June 2022

  • Automated 3D spine metastases radiation planning.
  • Designed a Python/Tkinter GUI for treatment planning, boosting efficiency by 50%.

NIH Funded SF BUILD Scholar
San Francisco State University
June 2021 – June 2022

  • Selected for leadership potential and dedication to underserved communities.
  • Focused on diversity in NIH-funded research.

🏆 Awards & Scholarships:

  • NIH Diversity Supplement Award: 2022-2024
  • NIH-SF BUILD Scholar: 2021-2022
  • Dean’s List: San Francisco State University, 2020-2022

📅 Committees & Leadership:

  • UCSF PROPEL Scholar: Promoting equity in scientific research (2022-2024)
  • Metro Near-Peer Mentoring Program: Mentored first-year college students (2020-2022)
  • Google Developer Student Club: Engaged in peer-to-peer learning and community solutions (2019)

🎯 Certifications:

  • CITI Training Certificate: Social/Behavioral Research, 2022
  • Near-Peer Mentor Training: Metro Student First, 2020

Publication Top Notes:

  • The genomic landscape of hypodiploid acute lymphoblastic leukemia
    L. Holmfeldt, L. Wei, E. Diaz-Flores, M. Walsh, J. Zhang, L. Ding, …
    Nature Genetics, 45(3), 242-252, 2013. (Citations: 841)

  • Single-cell profiling identifies aberrant STAT5 activation in myeloid malignancies with specific clinical and biologic correlates
    N. Kotecha, N.J. Flores, J.M. Irish, E.F. Simonds, D.S. Sakai, S. Archambeault, …
    Cancer Cell, 14(4), 335-343, 2008. (Citations: 290)

  • Ex vivo drug response profiling detects recurrent sensitivity patterns in drug-resistant acute lymphoblastic leukemia
    V. Frismantas, M.P. Dobay, A. Rinaldi, J. Tchinda, S.H. Dunn, J. Kunz, …
    Blood, The Journal of the American Society of Hematology, 129(11), e26-e37, 2017. (Citations: 240)

  • p53 loss promotes acute myeloid leukemia by enabling aberrant self-renewal
    Z. Zhao, J. Zuber, E. Diaz-Flores, L. Lintault, S.C. Kogan, K. Shannon, …
    Genes & Development, 24(13), 1389-1402, 2010. (Citations: 211)

  • Response and resistance to MEK inhibition in leukaemias initiated by hyperactive Ras
    J.O. Lauchle, D. Kim, D.T. Le, K. Akagi, M. Crone, K. Krisman, K. Warner, …
    Nature, 461(7262), 411-414, 2009. (Citations: 156)

  • K-RasG12D expression induces hyperproliferation and aberrant signaling in primary hematopoietic stem/progenitor cells
    M.E.M. Van Meter, E. Díaz-Flores, J.A. Archard, E. Passegué, J.M. Irish, …
    Blood, 109(9), 3945-3952, 2007. (Citations: 138)

  • Phase II study of the oral MEK inhibitor selumetinib in advanced acute myelogenous leukemia: a University of Chicago phase II consortium trial
    N. Jain, E. Curran, N.M. Iyengar, E. Diaz-Flores, R. Kunnavakkam, …
    Clinical Cancer Research, 20(2), 490-498, 2014. (Citations: 133)

  • Bcl-2 is a therapeutic target for hypodiploid B-lineage acute lymphoblastic leukemia
    E. Diaz-Flores, E.Q. Comeaux, K.L. Kim, E. Melnik, K. Beckman, K.L. Davis, …
    Cancer Research, 79(9), 2339-2351, 2019. (Citations: 80)

  • Diacylglycerol kinase inhibition prevents IL-2-induced G1 to S transition through a phosphatidylinositol-3 kinase-independent mechanism
    I. Flores, D.R. Jones, A. Ciprés, E. Díaz-Flores, M.A. Sanjuan, I. Mérida
    The Journal of Immunology, 163(2), 708-714, 1999. (Citations: 71)

  • Regulation of diacylglycerol kinase α by phosphoinositide 3-kinase lipid products
    A. Ciprés, S. Carrasco, E. Merino, E. Díaz, U.M. Krishna, J.R. Falck, …
    Journal of Biological Chemistry, 278(37), 35629-35635, 2003. (Citations: 69)

  • Targeting oncogenic ras
    E. Diaz-Flores, K. Shannon
    Genes & Development, 21(16), 1989-1992, 2007. (Citations: 65)

  • Cooperative loss of RAS feedback regulation drives myeloid leukemogenesis
    Z. Zhao, C.C. Chen, C.D. Rillahan, R. Shen, T. Kitzing, M.E. McNerney, …
    Nature Genetics, 47(5), 539-543, 2015. (Citations: 48)

  • Abnormal hematopoiesis in Gab2 mutant mice
    Y. Zhang, E. Diaz-Flores, G. Li, Z. Wang, Z. Kang, E. Haviernikova, S. Rowe, …
    Blood, 110(1), 116-124, 2007. (Citations: 48)

  • β2-chimaerin provides a diacylglycerol-dependent mechanism for regulation of adhesion and chemotaxis of T cells
    M. Siliceo, D. García-Bernal, S. Carrasco, E. Díaz-Flores, F.C. Leskow, …
    Journal of Cell Science, 119(1), 141-152, 2006. (Citations: 48)

  • Membrane translocation of protein kinase Cθ during T lymphocyte activation requires phospholipase C-γ-generated diacylglycerol
    E. Díaz-Flores, M. Siliceo, C. Martínez-A, I. Mérida
    Journal of Biological Chemistry, 278(31), 29208-29215, 2003. (Citations: 48)

  • Rapid screening of COVID‐19 patients using white blood cell scattergrams, a study on 381 patients
    J. Osman, J. Lambert, M. Templé, F. Devaux, R. Favre, C. Flaujac, D. Bridoux, …
    British Journal of Haematology, 190(5), 718-722, 2020. (Citations: 34)

  • NRAS G12V oncogene facilitates self-renewal in a murine model of acute myelogenous leukemia
    Z. Sachs, R.S. LaRue, H.T. Nguyen, K. Sachs, K.E. Noble, N.A. Mohd Hassan, …
    Blood, 124(22), 3274-3283, 2014. (Citations: 30)

  • PLC-γ and PI3K link cytokines to ERK activation in hematopoietic cells with normal and oncogenic Kras
    E. Diaz-Flores, H. Goldschmidt, P. Depeille, V. Ng, J. Akutagawa, K. Krisman, …
    Science Signaling, 6(304), ra105-ra105, 2013. (Citations: 21)

  • Evolution of artificial intelligence-powered technologies in biomedical research and healthcare
    E. Diaz-Flores, T. Meyer, A. Giorkallos
    Smart Biolabs of the Future, 23-60, 2022. (Citations: 18)

  • Stat5 is critical for the development and maintenance of myeloproliferative neoplasm initiated by Nf1 deficiency
    Z. Sachs, R.A. Been, K.J. DeCoursin, H.T. Nguyen, N.A.M. Hassan, …
    Haematologica, 101(10), 1190, 2016. (Citations: 18)