Asmaa Seyam | Data Science | Best Researcher Award

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Mrs. Asmaa Seyam | Data Science | Best Researcher Award

Ph.D student, University of Wollongong, Australia

Asmaa Seyam is a seasoned computer engineering professional and educator with over a decade of academic and research experience. Her career spans institutions such as Zayed University and the Islamic University of Gaza, where she has significantly contributed to the fields of programming, networking, and system development. Asmaa is known for her dedication to excellence in teaching and her active involvement in curriculum development and academic leadership.

Profile

Scopus

πŸŽ“ Education

Asmaa earned her Master’s degree in Computer Engineering from Jordan University of Science and Technology (2009–2011), graduating with an excellent GPA of 89.4%. Her thesis focused on optimizing node placement for energy-efficient clustering in wireless sensor networks. She completed her Bachelor’s in Computer Engineering at the Islamic University of Gaza (2003–2008) with an outstanding GPA of 90.67%, showcasing her strong foundation with a SCADA project for power distribution.

πŸ’Ό Professional Experience

Asmaa Seyam served as an Instructor at Zayed University in Abu Dhabi from 2012 to 2022, where she taught a range of IT and engineering courses such as Web Development, Programming, HCI, and Networking. She also worked as a Teaching Assistant at the Islamic University of Gaza and was a Network Trainer at the Ministry of Interiors, demonstrating hands-on expertise in server management, routing protocols, and system maintenance. Her roles were marked by leadership in academic planning, assessment design, student mentorship, and institutional service.

πŸ”¬ Research Interest

Her research interests lie in Internet of Things (IoT), Machine Learning, Artificial Intelligence, and Wireless Sensor Networks. She has published and presented in esteemed journals and international conferences, contributing to the evolution of smart and efficient network systems.

πŸ† Awards and Honors

Asmaa’s achievements include the Zuhair Hijjawi Award for Scientific Research (2008), a DAAD Scholarship for her Master’s studies, and several institutional service recognitions including the IBM Artificial Intelligence Analyst Mastery Award (2019) and the Advance HE Fellowship (2022). She also earned two separate 5-Year Service Awards from Zayed University and CISCO Networking Academy.

πŸ“š Publications

  1. Energy-Efficient Clustering Algorithm for Wireless Sensor Networks Using the Virtual Field Force
    Published in: 5th International Conference on New Technologies, Mobility and Security (NTMS), Istanbul, 2012.
    Cited by: 60+ articles
    πŸ“Œ IEEE Xplore

  2. Energy-Efficient and Coverage-Aware Clustering in Wireless Sensor Networks
    Published in: Wireless Engineering and Technology, Vol. 3, No. 3, 2012, pp. 142–151.
    Cited by: 90+ articles
    πŸ“Œ Scientific Research Publishing

  3. Characterizing Realistic Signature-based Intrusion Detection Benchmarks
    Published in: Proceedings of the 6th International Conference on Info Technology: IoT and Smart City, ACM, Hong Kong, 2018.
    Cited by: 20+ articles
    πŸ“Œ ACM Digital Library

🏁 Conclusion

Asmaa Seyam is a highly qualified and accomplished educator and researcher whose background reflects a strong commitment to both teaching and scholarly work. Her technical breadth, early recognition in research, and academic contributions position her as a strong candidate for the Best Researcher Award. Strengthening her recent research portfolio and expanding her research leadership roles would further elevate her profile.

Dr. Elif YΔ±ldΔ±rΔ±m Lecturer | Data Science and Analytics | Best Researcher Award

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Dr. Elif YΔ±ldΔ±rΔ±m Lecturer | Data Science and Analytics | Best Researcher Award

Dr. Elif YΔ±ldΔ±rΔ±m, Lecturer, Konya Technical University, Turkey

Dr. Elif YΔ±ldΔ±rΔ±m, a dedicated Lecturer at Konya Technical University in Turkey, specializes in Data Science and Analytics. Her commitment to advancing research in this field has earned her recognition as a contender for the Best Researcher Award. Dr. YΔ±ldΔ±rΔ±m’s work focuses on leveraging data-driven insights to solve complex challenges, contributing significantly to the academic community. With a passion for innovation and education, she inspires students and peers alike, shaping the future of data science through her teaching and research endeavors. πŸŒπŸ“Š

Profile 🌟

Orcid

Education πŸ“š

Dr. Elif YΔ±ldΔ±rΔ±m is an accomplished academic, completing her doctoral studies at Hacettepe University’s Graduate School of Science and Engineering in 2019 πŸŽ“. Prior to this, she earned master’s degrees from Hacettepe University in 2017 and Sinop University in 2015 πŸ“š. Her academic journey began with a bachelor’s degree from Sinop University in 2015 πŸŽ“. Dr. YΔ±ldΔ±rΔ±m’s educational background underscores her commitment to advancing in statistical sciences and biomedicine. Her qualifications reflect a strong foundation in research and academic excellence, positioning her as a notable figure in her field.

Academic Title πŸŽ“

Dr. Elif YΔ±ldΔ±rΔ±m, currently serving as a Lecturer at Konya Technical University πŸŽ“, brings extensive academic expertise to her role. With a background encompassing doctoral and master’s degrees from prestigious institutions like Hacettepe University and Sinop University πŸ“š, she has solidified her foundation in statistical sciences and biomedicine. Her research contributions, including leading roles in TUBITAK-funded projects 🌟, reflect her commitment to advancing parameter estimation methods in longitudinal and survival data modeling. Dr. YΔ±ldΔ±rΔ±m’s dedication extends beyond research; she actively engages in editorial duties and academic conferences, fostering collaboration and innovation in statistical research 🌐.

Positions and Projects 🌟

Dr. Elif YΔ±ldΔ±rΔ±m has been actively engaged in research at TED University and plays a pivotal role in the TUBITAK Project (1002). Her research focuses on advancing parameter estimation methods in longitudinal and survival data modeling πŸ“Š. This project, funded by TUBITAK, underscores her commitment to pushing the boundaries of statistical sciences 🌟. Through her work, Dr. YΔ±ldΔ±rΔ±m contributes significantly to enhancing our understanding of complex data relationships and their implications for real-world applications πŸ“ˆ. Her dedication to research excellence reflects in her ongoing efforts to innovate and refine statistical methodologies, ensuring robust and reliable outcomes in scientific investigations πŸ†.

Awards and Recognition πŸ†

Dr. Elif YΔ±ldΔ±rΔ±m has been recognized with several prestigious TUBITAK Publication Incentive Awards spanning from 2019 to 2024 πŸ†, underscoring her significant impact on statistical research. Her contributions to the field are marked by a series of groundbreaking publications in esteemed international journals πŸ“„, showcasing her expertise in statistical sciences and biomedicine. These awards highlight her dedication and leadership in advancing methodologies for longitudinal and survival data modeling, affirming her as a trailblazer in academic research. Dr. YΔ±ldΔ±rΔ±m’s achievements not only bolster her academic standing but also exemplify her commitment to pushing the boundaries of statistical analysis and application.

Administrative and Editorial Contributions 🌐

Dr. Elif YΔ±ldΔ±rΔ±m exhibits exemplary leadership in her academic domain, serving as a board member and editor for esteemed academic journals. πŸ“ Her role underscores her commitment to advancing scholarly discourse and ensuring the quality of research publications. 🌐 Through her editorial contributions, she shapes the direction of scientific inquiry and promotes rigorous standards in academic publishing. πŸŽ“ Dr. YΔ±ldΔ±rΔ±m’s editorial insights and board membership reflect her standing as a respected authority in statistical sciences and biomedicine, enriching the academic community with her expertise and dedication. πŸ†

Workshops and Academic Engagement πŸŽ“

Dr. Elif YΔ±ldΔ±rΔ±m is actively engaged in workshops and conferences, playing a pivotal role in fostering academic dialogue and community engagement in statistical research. 🌐 Her participation enhances collaborative efforts, contributing to advancements in statistical sciences and biomedicine. πŸ“Š Through her involvement, she enriches academic discourse and promotes knowledge sharing among peers and scholars worldwide. πŸŽ“ Dr. YΔ±ldΔ±rΔ±m’s dedication to these events underscores her commitment to professional development and innovation in statistical modeling and analysis. 🌟 Her proactive approach inspires others and strengthens the academic community’s collective pursuit of excellence in research and education. πŸ“ˆ

Publications Top Notes πŸ“š

Power analysis of approximation methods for parameter estimation in Cox regression model with longitudinal covariate and tied survival times

Power unit Burr-XII distribution: Statistical inference with applications

Black hole algorithm as a heuristic approach for rare event classification problem

The relationship between PM10 and SO2 exposure and Covid-19 infection rates in Turkey using nomenclature of territorial units for statistics level 1 regions

gsem: A Stata command for parametric joint modelling of longitudinal and accelerated failure time models

Joint Modeling of a Longitudinal Measurement and Parametric Survival Data with Application to Primary Biliary Cirrhosis Study

Testing adiabatic expansion of polytropic universe model with SNe Ia Data

Dr. Mousa Moradi | Data Science and Analytics | Best Researcher Award

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Dr. Mousa Moradi | Data Science and Analytics | Best Researcher Award

Dr. Mousa Moradi, Post Doctoral Research Fellow, Harvard University, United StatesΒ 

πŸŽ“πŸ”¬ Dr. Mousa Moradi, a Postdoctoral Research Fellow at Harvard University, is renowned for his exceptional contributions to data science and analytics. His groundbreaking research, funded by the University Grants Commission (UGC), New Delhi, India, has garnered significant recognition. πŸ†πŸ“Š With a focus on innovative analytical methodologies, Dr. Moradi’s work is pivotal in advancing the field. His dedication and expertise have earned him the prestigious Best Researcher Award, celebrating his impactful achievements. πŸŒŸπŸ“š Dr. Moradi’s commitment to excellence continues to inspire the academic community, driving forward the boundaries of data science and analytics. πŸŒπŸ”

PROFILE

Googlescholar

EDUCATION

πŸŽ“ Dr. Mousa Moradi obtained his Ph.D. in Biomedical Engineering from the University of Massachusetts Amherst 🏫 (2020-2024). Prior to this, he earned an M.S. in Biomedical Engineering from Wichita State University πŸ“š (2019-2020). Dr. Moradi also holds an M.S. in Radiology from the National University of Iran πŸ₯ (Shahid Beheshti University) (2012-2014). He began his academic journey with a B.S. in Electrical Engineering from Kermanshah University of Technology ⚑ (2008-2012). Dr. Moradi’s diverse educational background has equipped him with a comprehensive understanding of biomedical engineering and radiology, fostering his innovative contributions to the field. 🧬✨

RESEARCH EXPERIENCE AND ACCOMPLISHMENTS

🌟 Dr. Mousa Moradi is a distinguished Post Doctoral Research Fellow in the Department of Ophthalmology at Harvard Medical School (2024–Present) under the guidance of Dr. Nazlee Zebardast. 🌱 Previously, as a Graduate Research Assistant at UMASS Amherst (2020-2024), Dr. Moradi developed AI algorithms for Optical Coherence Tomography (OCT) and advanced deep learning models for kidney transplant and Age-related Macular Degeneration (AMD). πŸ’‘ He also contributed to the development of robotic-assisted OCT for pre-transplant kidney monitoring. πŸ’» With a rich background in computational modeling, deep learning, and bioinstrumentation, Dr. Moradi is proficient in Python, OpenCV, MATLAB, and more. πŸŽ“ He holds a Master’s from Tehran University of Medical Sciences, specializing in advanced medical technologies.

AWARD AND HONORS

🌟 Dr. Mousa Moradi, a dedicated BME PhD student, has garnered numerous accolades for his outstanding research and academic excellence. He was honored with the SPIE Photonic West Travel Award in 2024 and was a finalist for the Three Minute Thesis at UMASS Amherst in 2023. Previously, he received honorable mention for the SPIE Photonic West Best Student Paper Award in 2022. His academic journey includes prestigious awards such as the Excellence in Research Award and the UMass Dean Fellowship. Dr. Moradi’s achievements also include the Merit-based James Southerland Garvey International Scholarship and the BME MS Scholarship Award at Wichita State University. πŸŽ“

TEACHING EXPERIENCE

Dr. Mousa Moradi has been actively engaged in biomedical education and research, serving as the Lead Instructor at Wellesley College from July to August 2023. His extensive teaching experience includes roles as a Teaching Assistant and Group Discussion Leader for Systems Biology 497B from 2021 to 2023, Bioinstrumentation 480 from 2019 to 2024, and Application of Computers in Biology 335 from 2019 to 2020. Dr. Moradi’s academic contributions also span as an Academic Lecturer for undergraduate courses such as Medical Physics, Health Physics, and Biophysics from 2015 to 2019. πŸŽ“πŸ”¬βœ¨

PRESENTATIONS

Dr. Mousa Moradi has presented groundbreaking research across various conferences and seminars. His contributions include studies on light-tissue interactions in pulse oximetry (SPIE West Photonic Conference 🌐), AMD detection using ensemble learning (UMASS Medical School seminar πŸ‘οΈ), and robotic-assisted optical coherence tomography for kidney monitoring (SPIE West Photonic Conference πŸ€–). He also showcased innovations like high temporal resolution neuroimaging with near-infrared spectroscopy (BMES Annual Meeting 🧠) and designed programmable high voltage power supplies for nuclear medicine (International Conference in Applied Research on Electrical, Mechanical and Mechatronic Engineering ⚑). Dr. Moradi’s work extends to assessing radiation doses from medical devices (IUPESM World Congress πŸ“‘), emphasizing his significant impact on medical physics and engineering.

Β  Publication Top Notes Β 

Effect of ultra high frequency mobile phone radiation on human health

Deep ensemble learning for automated non-advanced AMD classification using optimized retinal layer segmentation and SD-OCT scans

Feasibility of the soft attention-based models for automatic segmentation of OCT kidney images

Feasibility of robotic-assisted optical coherence tomography with extended scanning area for pre-transplant kidney monitoring

Monte Carlo simulation of diffuse optical spectroscopy for 3D modeling of dental tissues

Ensemble learning for AMD prediction using retina OCT scans

Soft attention-based U-NET for automatic segmentation of OCT kidney images

Large Area Kidney Imaging for Pre-transplant Evaluation using Real-Time Robotic Optical Coherence Tomography

Integrating Human Hand Gestures with Vision Based Feedback Controller to Navigate a Virtual Robotic Arm

Design and evaluation of a GUI for signal and data analysis of mobile functional near-infrared spectroscopy systems