Hedieh Sajedi – Machine learning – Best Researcher Award

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Hedieh Sajedi – Machine learning – Best Researcher Award

Dr. Hedieh Sajedi  distinguished academic and researcher in the field Machine learning.  Her research interests encompass a wide range of advanced topics, including deep learning and machine learning, where she delves into the development and refinement of algorithms that enable computers to learn from and make decisions based on data. She is also deeply involved in multimedia processing, exploring techniques to enhance and manipulate various forms of media, such as images, videos, and audio. Additionally, her work in data mining and information retrieval focuses on extracting meaningful patterns and insights from large datasets, improving the efficiency and accuracy of information retrieval systems. Furthermore, she investigates bio-inspired algorithms, drawing inspiration from natural processes to create innovative computational methods that solve complex problems.

🌐 Professional Profile

Educations📚📚📚

She completed her Ph.D. in Artificial Intelligence and Robotics at Sharif University of Technology in May 2010, following her M.Sc. in the same field from the same institution, which she earned in August 2005. Prior to her postgraduate studies, she obtained her B.Sc. in Computer Software Engineering from Amir Kabir University of Technology in September 2002.

Work Experience:

She has delivered several invited talks on various topics, including “Computer vision and machine learning for medical image analysis” at the Children’s International Research Center in Washington DC, USA, in July 2022, and “Age Prediction based on brain MRI images” at Pompeu Fabra University in Barcelona, Spain, in June 2022. Additionally, she discussed a “Blind Spot Warning System based on Vehicle Analysis in Stream Images” at the same university and “Brain Age Estimation based on Brain MRI Images” at Sehir University of Istanbul, Turkey, in March 2018. Earlier, in March 2014, she presented on the “Application of Steganography and Steganalysis Methods in Medical and Healthcare Systems” at the University of Pavia, Italy. Her executive activities include serving as the Scientific Chair of the International Conference on Pattern Recognition and Image Analysis (IPRIA) in 2023, head of the Computer Science Department from 2018 to 2022, and Scientific Chair of the 6th International Conference on Pattern Recognition and Image Analysis at the University of Tehran in 2022. She also held the position of Head of Computer Services and Information Technology in the College of Science from 2018 to 2020 and served as Inspector of the Image Processing and Machine Vision Society in Tehran, Iran, in 2015 and 2017. Her funded projects include research on the “Detection and Classification of Circular Objects on the Basis of Convolutional Neural Network (CNN)” funded by the Iran National Science Foundation (INSF) from 2021 to the present, “Investigating Brain Health from Brain MRI Images Using Machine Learning Methods,” partially funded by the Institute for Research in Fundamental Sciences (IPM) from 2018 to 2019, “Brain Age Estimation with Mathematical Modeling” funded by INSF from 2017 to 2018, and the development of “A High-Security and High-Capacity Steganography System” funded by INSF from 2011 to 2014.

Honors & Awards

She was recognized as a member of the University of Tehran Top Researchers Club in 2022 and received the Erasmus Mobility Award from the European Union in the same year. Additionally, she was honored with the Honors Program Graduate Award from Sharif University of Technology for the period from 2006 to 2010. Since 2009, she has been an active member of the Scientific Society for Image Processing and Machine Vision.

She has been an instructor at the University of Tehran since 2013, teaching courses such as “Machine Learning,” “Artificial Intelligence,” “Data Mining,” and “Digital Image Processing” in the Department of Computer Science. She has also instructed “Advanced Topics in Artificial Intelligence” since 2020 and “Advanced Information Retrieval” from 2017 to 2020. Additionally, she taught “Advances in AI” from 2013 to 2020 and “Machine Learning in Physics” from 2018 to 2019. Her teaching portfolio includes courses for Ph.D. students at the Institute of Biochemistry and Biophysics, such as “Advanced Data Structure” in 2018-2019. At AmirKabir University of Technology, she instructed “Machine Learning” from 2010 to 2011 and “Artificial Intelligence” in 2010-2011. She also co-instructed “Machine Vision” at Pompeu Fabra University in Barcelona, Spain, in May 2022. Her experience in bio-inspired computing includes teaching “Evolutionary Computing” at the University of Tehran from 2013 to 2016.

Furthermore, she has taught “Distributed Systems” at Azad University, Qazvin, from 2011 to 2013, and courses such as “Computer Networks,” “Compiler Design and Principles,” and “Introduction to Programming” at the University of Tehran. She also taught “Operating Systems,” “Introduction to Programming,” and other foundational courses at Tarbiat Moallem University from 2006 to 2008. Her early teaching roles include instructing “Introduction to Programming” at Sharif University of Technology in 2006-2007 and several technical and scientific presentation courses at AmirKabir University of Technology from 2009 to 2011.

📝🔬Publications📝🔬

Senol Celik – Statistics – Best Researcher Award

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Dr.  Senol celik  distinguished academic and researcher in the field Statistics. He has held academic positions at Bingöl University, Faculty of Agriculture, Department of Animal Science, Biometry and Genetics. He was appointed as an Associate Professor on January 27, 2014, and later became a Doctoral Lecturer on March 25, 2020. Throughout his tenure, he has supervised several Master’s theses. In 2019, he supervised the thesis of Birsen Gök, titled “Examination of Data on Large and Small Livestock Farming in Turkey Using Alternative Regression Methods,” which was completed under the Zootechnics Department at Bingöl University’s Institute of Natural and Applied Sciences.

In 2018, he oversaw Gamze Azak’s thesis, which focused on the “Multivariate Analysis of Milk Yields of Culture, Hybrid, and Native Cattle Breeds in Turkey,” also completed within the Zootechnics Department at the same institute. Additionally, in 2014, he guided Mehmet Dinler’s thesis, titled “Comparative Analysis of Clustering Methods in Livestock Data,” which was successfully defended at Bingöl University’s Institute of Natural and Applied Sciences.

 

🌐 Professional Profiles

 

Educations📚📚📚

He completed his undergraduate degree in Statistics at Anadolu University, Faculty of Science and Literature, in July 1992. Subsequently, he pursued his first Master’s degree in Statistics at Ankara University, Institute of Science, graduating on June 19, 2003, with a non-thesis program. In 2004, he continued his academic journey at the same institution, completing another Master’s degree in Statistics, this time with a thesis titled “Normal Distribution and Inferences Related to Normal Distribution” under the supervision of Fahrettin Arslan. Moving forward, he embarked on his doctoral studies in Zootechnics (Agricultural Sciences) at Ankara University, Institute of Science, and successfully defended his dissertation titled “Time Series Analysis and its Application to Traffic Accident Data” under the guidance of Zahide Kocabas on July 25, 2013.

Conference

He presented several papers at international scientific conferences and had them published in proceedings. In 2021, Şenol Çelik contributed to various fields such as organic farming, health, economics, and artificial intelligence. For instance, he explored students’ perspectives on their respective departments in organic farming management in a paper published in the Euroasia Journal of Mathematics-Engineering Natural & Medical Sciences. Additionally, he investigated health-related studies using the Multivariate Adaptive Regression Splines (MARS) method, as well as the relationship between inflation and unemployment rates in Turkey using the inverse regression model, both presented at the III. International Congress on Creative and Innovative Approaches. Furthermore, he delved into artificial neural networks for modelling and predicting stock closing values and trends in agriculture, demonstrating applications in animal production and suicide rate prediction in Turkey and three major cities using artificial neural networks, presented at the II. International Applied Statistics Conference and the XXI. International Symposium on Econometric Operations Research and Statistics, respectively. Additionally, he contributed to animal science research by investigating the effects of vitamin E and selenium supplementation on the fertility and hatchability of partridges, presented at the III International and XII National Animal Science Conference.

 

Research 

He has contributed extensively to national peer-reviewed journals and presented papers at various national scientific conferences. In his publications, Şenol Çelik has covered a wide range of topics including path analysis of carcass measurements in Japanese quails, analysis of body measurements in Turkish Arabian horses, and investigation of egg quality traits and feather color effects on egg weight in Japanese quails. Additionally, he has presented findings on subjects such as honey production comparisons across regions in Turkey, utilization of spline functions in modelling live weight in organic chickens, and estimation of live weight in chickens by age using Newton interpolation method. Furthermore, his research extends to fields such as dairy production economics, climate effects on crop yields, and the relationship between livestock and forage crop production, among others. He has also authored technical notes and short articles on predictive modelling in goat growth and technologies in smallholder poultry development. Moreover, he has served as an editor for several publications focused on statistical research in various fields including agriculture, engineering, and natural sciences.

International peer-reviewed journals:
  • Azak Gamze, ÇELİK ŞENOL (2019). Investigation of milk yield from culture, cross-bred and native cattle breeds in Turkey by multivariate analysis of variance (MANOVA). APPLIED ECOLOGY AND ENVIRONMENTAL RESEARCH, 17(6), 14945-14959.
  • Can Ağırbaş Nihal, ÇELİK ŞENOL, Sapmaz Kadriye (2019). MODELING FORAGE CROPS PRODUCTION USING THE TIME SERIES METHOD. Fresenius Environmental Bulletin, 28(11), 7763-7776.
  • ÇELİK ŞENOL (2019). Modeling and Estimation of Potato Production in Turkey with Time Series Analysis. International Journal of Trend in Research and Development (IJTRD), 6(5), 111-116.
  • ÇELİK ŞENOL (2019). Prediction of Mandarin Production in Turkey through Artificial Neural Networks and Time-Series Analysis. International Journal of Trend in Research and Development, 6(5), 85-90.
  • ÖZTÜRK YASİN, ÇELİK ŞENOL, ŞAHİN EMRE, AÇIK MEHMET NURİ, ÇETİNKAYA BURHAN (2019). Assessment of Farmers’ Knowledge, Attitudes and Practices on Antibiotics and Antimicrobial Resistance. ANIMALS, 9(9), 653.
  • ÇELİK ŞENOL, ŞENGÜL TURGAY, ŞENGÜL AHMET YUSUF (2019). Relationships between Egg Quality Traits in Quails Examined with Data Mining Methods. Yüzüncü Yıl Üniversitesi Tarım Bilimleri Dergisi, 29(3), 433-439.
  • ÇELİK ŞENOL (2019). ESTIMATION OF THE ORANGE PRODUCTION IN TURKEY BY MEANS OF ARTIFICIAL NEURAL NETWORKS. GLOBAL JOURNAL OF ENGINEERING SCIENCE AND RESEARCHES, 6(9), 10-16.
  • ÇELİK ŞENOL (2019). Logistic Regression Analysis and An Application Regarding Students’ Success. Journal of Multidisciplinary Engineering Science Studies (JMESS, 5(6), 2628-2631.
  • ÇELİK ŞENOL (2019). Comparing Predictive Performances of Tree-Based Data Mining Algorithms and MARS Algorithm in the Prediction of Live Body Weight from Body Traits in Pakistan Goats. Pakistan Journal of Zoology (PJZ), 51(4), 1447-1456.
  • ÇELİK ŞENOL, BOYDAK ERKAN (2019). Determination Of Several Plant Characteristics Affecting Yield Per Decare In Peanut Using Different Regression Models. Journal of Multidisciplinary Engineering Science Studies (JMESS), 5(3), 2540-2544.
  • ÇELİK ŞENOL (2018). Using Lagrange interpolation to determine the milk production amount by the number of milked animals. American Journal of Engineering Research (AJER), 7(8), 264-271.
  • ÇELİK ŞENOL, ŞENGÜL TURGAY, SÖĞÜT BÜNYAMİN, ŞENGÜL ÖMER, İNCİ HAKAN (2018). Çanakkale ilinde sağılan koyun sayısı, süt üretimi, dolar kuru ve altın fiyatı ilişkisi: ARDL Bound testi yaklaşımı. JOURNAL OF AWARENESS, 3, 173-180.
 Publication📚✨📚✨