Mona Ebadi Jalal | Computer Science | Best Researcher Award

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Ms. Mona Ebadi Jalal | Computer Science | Best Researcher Award

University of Louisville | United States

Author Profile

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Early Academic Pursuits 🎓

Ms. Mona Ebadi Jalal's academic journey is marked by excellence and dedication. She is currently pursuing a PhD in Computer Science at the University of Louisville, where she maintains a perfect GPA of 4.00. Her research focuses on the cutting-edge fields of Machine Learning and Deep Learning, under the guidance of Professor Adel Elmaghraby. Prior to this, she earned a Master’s Degree in Information Technology Engineering from K. N. Toosi University of Technology (KNTU) in Tehran, Iran, where she graduated with an impressive GPA of 17.75/20. Her master’s thesis involved developing a novel deep learning model using recurrent neural networks to forecast incoming call volumes in call centers, a project that earned a perfect grade of 20/20. She also holds a Bachelor’s Degree in Computer Engineering - Software from Payame Noor University in Hamedan, Iran, where she developed a patient information management system for a hospital as part of her thesis.

Professional Endeavors 💼

Ms. Ebadi Jalal’s professional career is equally distinguished. She is currently a PhD Fellow and Research Assistant at the University of Louisville, where she conducts in-depth research in customer behavior analysis, medical image analysis, and diagnostics prediction, utilizing advanced Machine Learning and Deep Learning methods. Before pursuing her PhD, she worked as an IT Consultant specializing in SAP ABAP and Business Data Analysis at Naghshe Aval Keyfiat (NAK) and Faraz Andishan Hesab Companies in Tehran, Iran. During this period, she designed and implemented custom solutions within the SAP framework, conducted thorough analyses of business processes, and managed end-to-end project lifecycles. She has also served as a Software Developer, developing and maintaining web applications and managing relational databases.

Contributions and Research Focus 🔬

Ms. Ebadi Jalal’s contributions to the field of computer science are significant and diverse. Her research primarily focuses on the application of Machine Learning and Deep Learning to customer behavior analysis and medical diagnostics. She has developed predictive models for call center operations and contributed to the advancement of personalized marketing through counterfactual analysis. Her recent work includes a deep learning framework for abnormality detection in nailfold capillary images, which has the potential to revolutionize diagnostics in medical imaging.

Accolades and Recognition 🏅

Ms. Ebadi Jalal’s academic and professional achievements have been recognized with numerous awards and honors. She was awarded a prestigious fellowship for her PhD studies at the University of Louisville in 2022. During her time at K. N. Toosi University of Technology, she was nominated for the Superior Student Researcher honor in 2014. Additionally, she ranked in the top 1% in Iran’s nationwide graduate-level entrance exam in Information Technology Engineering in 2012 and received a national graduate-level full scholarship.

Impact and Influence 🌍

Ms. Ebadi Jalal’s work has had a profound impact on both academia and industry. Her research has led to new insights in customer behavior analysis and medical image diagnostics, influencing the development of more effective marketing strategies and diagnostic tools. As a peer reviewer for several prestigious journals, including IEEE Access and Scientific Reports, she contributes to the advancement of knowledge in her field by ensuring the quality and rigor of published research.

Legacy and Future Contributions 🌟

Ms. Ebadi Jalal is poised to leave a lasting legacy in the field of computer science. Her ongoing research in machine learning and deep learning holds the potential to drive significant advancements in both customer behavior analysis and medical diagnostics. With her strong academic background, extensive professional experience, and numerous accolades, she is well-positioned to continue making groundbreaking contributions to the field in the years to come. Her future work will likely influence the next generation of researchers and practitioners, further solidifying her impact on the world of technology.

Publications

📝 Artificial Intelligence Algorithms in Nailfold Capillaroscopy Image Analysis: A Systematic Review

Journal: MedRxiv
Year: 2024
Authors: Emam, Omar S.; Jalal, Mona Ebadi; Garcia-Zapirain, Begonya; Elmaghraby, Adel S.

📝 Analyzing the Dynamics of Customer Behavior: A New Perspective on Personalized Marketing through Counterfactual Analysis

Journal: Journal of Theoretical and Applied Electronic Commerce Research
Year: June 2024
Authors: Mona Ebadi Jalal; Adel Elmaghraby

📝 Forecasting Incoming Call Volumes in Call Centers with Recurrent Neural Networks

Journal: Journal of Business Research
Year: November 2016
Authors: Mona Ebadi Jalal; Monireh Hosseini; Stefan Karlsson

📝 Analysis of Customer Behavior in Purchasing and Sending Online Group SMS Using Data Mining Based on the RFM Model

Journal: Sharif Journal of Industrial Engineering & Management
Year: February 20, 2016
Authors: Mona Ebadi Jalal; Somayeh Alizadeh




Saeid Mehdizadeh | Environmental Science | Best Researcher Award

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Dr. Saeid Mehdizadeh | Environmental Science | Best Researcher Award

Urmia University | Iran

Author Profile

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🎓 Early Academic Pursuits

Dr. Saeid Mehdizadeh began his academic journey at Urmia University in Iran, where he earned a Bachelor of Science in Water Engineering Sciences in 2008, followed by a Master's degree in the same field in 2010. His academic performance was consistently outstanding, with GPAs reflecting his dedication and deep understanding of water engineering sciences. He continued his education at Urmia University, where he obtained his PhD in Water Engineering Sciences in 2017, with a remarkable GPA of 19.18/20. His early academic endeavors laid a strong foundation for his future research and professional success.

🛠️ Professional Endeavors

Dr. Mehdizadeh's professional journey is marked by his contributions to the field of water engineering, with a focus on machine learning, artificial intelligence, and optimization algorithms. His work is centered on hydrology, hydrological modeling, drought and flood prediction, river streamflow, rainfall, evaporation, and evapotranspiration. His expertise in these areas has led him to publish numerous influential papers in high-impact journals. Additionally, he has played a significant role in peer review, serving as an outstanding reviewer for prestigious journals like the Journal of Cleaner Production, and as a guest editor for a special issue of the Water Journal.

🧠 Contributions and Research Focus

Dr. Mehdizadeh's research contributions are extensive and impactful, particularly in the application of advanced machine learning models and hybrid techniques to solve complex hydrological problems. His work on the development of wavelet-based hybrid models and the integration of artificial intelligence with time series analysis has provided significant advancements in the modeling of environmental phenomena such as soil temperature, streamflow, and drought. His research is not only theoretical but also practical, offering solutions to real-world problems related to water resources management.

🏆 Accolades and Recognition

Dr. Mehdizadeh has received numerous accolades for his contributions to the field. In June 2018, he was recognized as an outstanding reviewer by the Journal of Cleaner Production, a testament to his expertise and dedication to maintaining high standards in scientific research. His role as a guest editor for the Water Journal further highlights his leadership in the academic community, where he has curated and overseen research on drought monitoring and modeling using advanced machine learning models.

🌍 Impact and Influence

Dr. Mehdizadeh's work has had a profound impact on the field of water engineering and beyond. His research has influenced the way hydrological models are developed and applied, particularly in the context of environmental management and climate change adaptation. His contributions to the understanding and prediction of hydrological phenomena have been widely recognized and cited by peers, underscoring his influence in both academic and practical domains.

🌟 Legacy and Future Contributions

As Dr. Mehdizadeh continues to advance his research, his legacy in the field of water engineering is firmly established. His work on machine learning and artificial intelligence in hydrology sets the stage for future innovations and applications that will further enhance our ability to manage and protect water resources. His ongoing contributions are expected to continue shaping the future of water engineering, with a lasting impact on both the scientific community and society at large.

 

Publications 📚

  • 📄Deep Learning Hybrid Models with Multivariate Variational Mode Decomposition for Estimating Daily Solar Radiation
    Authors: Shahab S. Band, Sultan Noman Qasem, Rasoul Ameri, Hao-Ting Pai, Brij B. Gupta, Saeid Mehdizadeh, Amir Mosavi
    Journal: Alexandria Engineering Journal
    Year: 2024
  • 📄Development of Wavelet-Based Hybrid Models to Enhance Daily Soil Temperature Modeling: Application of Entropy and τ-Kendall Pre-Processing Techniques
    Authors: Saeid Mehdizadeh, Farshad Ahmadi, Ali Kouzehkalani Sales
    Journal: Stochastic Environmental Research and Risk Assessment
    Year: 2023
  • 📄Improving the Performance of Random Forest for Estimating Monthly Reservoir Inflow via Complete Ensemble Empirical Mode Decomposition and Wavelet Analysis
    Authors: Farshad Ahmadi, Saeid Mehdizadeh, Vahid Nourani
    Journal: Stochastic Environmental Research and Risk Assessment
    Year: 2022
  • 📄Establishing Coupled Models for Estimating Daily Dew Point Temperature Using Nature-Inspired Optimization Algorithms
    Authors: Saeid Mehdizadeh, Babak Mohammadi, Farshad Ahmadi
    Journal: Hydrology
    Year: 2022
  • 📄A Novel Hybrid Dragonfly Optimization Algorithm for Agricultural Drought Prediction
    Authors: Pouya Aghelpour, Babak Mohammadi, Saeid Mehdizadeh, Hadigheh Bahrami-Pichaghchi, Zheng Duan
    Journal: Stochastic Environmental Research and Risk Assessment
    Year: 2021

 

Sasank V.V.S | Computer Science | Best Researcher Award

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Assist Prof Dr. Sasank V.V.S | Computer Science | Best Researcher Award

K L University | India

Author Profile

Scopus

Early Academic Pursuits

Dr. Sasank V.V.S. exhibited a strong academic foundation from the outset. He completed his secondary education at Jassver English Medium School in 2007 with a First Class distinction, scoring 72.66%. He continued to excel in his Intermediate studies at Mega Junior College, graduating in 2009 with an 84.1% mark, also achieving First Class. His academic journey progressed to higher education at Gitam Institute of Technology, GITAM University, where he obtained his B.Tech in Information Technology in 2013 with a CGPA of 8.15, earning a Distinction. He further advanced his education with an M.Tech in Computer Science and Technology from the same institution, graduating in 2016 with a remarkable 9.11 CGPA, securing the top rank in his department. Dr. Sasank completed his Ph.D. at K.L. University in 2023, marking a significant milestone in his academic career.

Professional Endeavors

Dr. Sasank has a rich professional background in both academia and industry. He began his teaching career as a Teaching Assistant in the CSE Department at Gitam University from October 2015 to April 2016. He then served as an Assistant Professor at the Lendi Institute of Engineering & Technology, VIZIANAGARAM, from June 2016 to April 2017. Following this, he joined Anil Neerukonda Institute of Technology & Sciences (ANITS) as an Assistant Professor and Placement Officer from June 2017 to April 2019. He has been affiliated with K L University since July 2019, initially in the CSE Department and later in the CSIT Department, where he also served as the ERP Registration In-charge. His teaching repertoire includes subjects such as DBMS, Software Engineering, Computer Architecture & Organization, Term Paper, UI/UX Design, and DevOps.

Contributions and Research Focus

Dr. Sasank's research primarily focuses on advanced topics in computer science and engineering. His areas of interest include brain tumor classification, real-time traffic management using IoT and machine learning techniques, and the evolution of modern women in literature. He has published a significant number of papers in reputed journals, including  SCI papers and several Scopus-indexed articles. His notable publications include works on hybrid deep neural networks, automatic tumor growth prediction, and brain tumor classification using modified kernel-based softplus extreme learning machines. Additionally, he has guided numerous B.Tech and M.Tech project batches, contributing to the academic growth of his students.

Accolades and Recognition

Dr. Sasank has received several accolades for his academic and research achievements. He was the top ranker in his M.Tech program at Gitam University in 2016. He has published 18 papers, including SCI, Scopus, and WOS-indexed journals, and has contributed to two book chapters. His innovative research has led to the publication of two patents: one on real-time traffic management using IoT and machine learning techniques, and another on the evolution of modern women in Manju Kapur’s novels. Additionally, he has earned global certifications, including Google Associate Cloud Engineer and AWS Cloud Practitioner, and has presented his research at various international conferences.

Impact and Influence

Dr. Sasank's contributions to the field of computer science and engineering have had a significant impact on both academic and practical applications. His research on brain tumor classification and real-time traffic management has potential real-world implications, advancing the fields of medical imaging and smart city technologies. As an educator, he has influenced many students through his teaching and mentorship, guiding them in their academic and research endeavors.

Legacy and Future Contributions

Dr. Sasank's ongoing research and academic activities are expected to leave a lasting legacy in the field of computer science and engineering. His contributions to brain tumor classification and IoT-based traffic management are poised to influence future research and development in these areas. As he continues to publish and present his work, Dr. Sasank is likely to inspire and mentor the next generation of engineers and researchers, ensuring continued innovation and excellence in his field.

 

Notable Publications

Prostate cancer classification using adaptive swarm Intelligence based deep attention neural network 2024

Effective Segmentation and Brain Tumor Classification Using Sparse Bayesian ELM in MRI Images 2023

Hybrid deep neural network with adaptive rain optimizer algorithm for multi-grade brain tumor classification of MRI images 2022 (14)

An automatic tumour growth prediction based segmentation using full resolution convolutional network for brain tumour 2022 (27)

Hate Speech & Offensive Language Detection Using ML &NLP 2022 (4)