Nagesh Dewangan – Interpretation Analysis of Deep Learning Models-Best Researcher Award

Posted on by Network Science

Nagesh Dewangan – Interpretation Analysis of Deep Learning Models-Best Researcher Award

Mr. Nagesh Dewangan distinguished academic and researcher in the field Interpretation Analysis of Deep Learning Models. As a dedicated researcher in the field of machinery condition monitoring, his work has focused on advancing knowledge in activity monitoring and fault diagnosis for heavy machinery using deep learning models. His research has led to several key advancements, particularly in the areas of machinery activity recognition and motor fault diagnosis. He has worked on projects focusing on the cycle time of dumper activities and real-time fault diagnosis of motors using acceleration signals. The studies were conducted in both laboratory and real environments, providing comprehensive data for robust analyses. His work has resulted in the development of innovative methodologies and technologies. He has contributed to the creation of new algorithms for activity recognition using convolutional neural networks (CNNs) and developed approaches to enhance the generalizability of models across different environments. Collaborations with institutions like CSIR-Central Institute of Mining and Fuel Research Dhanbad, India, and industry partners like Coal India Limited, India, have enriched his research.

 

🌐 Professional Profile

Educations📚📚📚

He is currently a Ph.D. research scholar in the Acoustics and Condition Monitoring Laboratory, Mechanical Engineering Department, Indian Institute of Technology Kharagpur, India. He received his B.E. degree in Mechanical Engineering from the Bhilai Institute of Technology Durg, India, in 2016, and his M.Tech. degree in Maintenance Engineering & Tribology from the Indian Institute of Technology Dhanbad, India, in 2019. His research interests are in the areas of Mining Machinery, Condition Monitoring, Signal Processing, Fault Diagnosis, Real-time Application, Internet of Things, Machine Learning, and Deep Learning for industry-oriented Product Design and Development. Throughout his academic career, he has been involved in numerous research projects focused on improving machinery efficiency and safety, particularly in the mining industry. His recent work includes analyzing the cycle time of dump truck activities, fuel consumption, and implementing Convolutional Neural Networks for activity recognition.

Experience

He has published a paper in the reputed journal Automation in Construction, where he critically evaluates existing methods and proposes innovative solutions. Additionally, he has co-authored two papers in reputed journals, such as Engineering Transactions and the International Journal of Chemical Engineering. He has also presented his work at various prestigious conferences, such as the International Conference on Mechanical Power Transmission 2019 (IIT Madras), 17th International Conference on Vibration Engineering and Technology of Machinery 2022 (Institute of Engineering, Nepal), National Conference on Condition Monitoring 2023 (NSTL, Visakhapatnam), and World Congress on Engineering Asset Management (RMIT University, Vietnam), sharing his findings and insights with the academic and professional community. For his research work, he predominantly uses MATLAB, Python, LabVIEW, and NI Multisim.

 

📝🔬Publications📝🔬

Hedieh Sajedi – Machine learning – Best Researcher Award

Posted on by Network Science

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📝🔬

S. Pourmohammad Azizi – Time series analysis – Best Researcher Award

Posted on by Network Science

Pourmohammad Azizi – Time series analysis – Best Researcher Award

Mr. Pourmohammad Azizi distinguished academic and researcher in the field Time series analysis.

.

🌐 Professional Profile

Educations📚📚📚

He is currently a Ph.D. candidate in Artificial Intelligence at the Department of Electrical Engineering and Computer Sciences at National Taiwan Ocean University in Taiwan, where he works on smart telecommunication. He earned his Master’s degree in Mathematics from Allameh Tabataba’i University in Tehran, graduating with a GPA of 17.69 out of 20 in 2018. Prior to that, he completed his Bachelor’s degree in Mathematics and Applications at the University of Mazandaran, achieving a GPA of 16.64 out of 20 in 2015. During his academic journey, he also participated in academic visits, including a visit to Lisbon University ISEG- Lisbon School of Economics and Management in 2017, and Guangzhou University in 2015.

Work Experience

He has accumulated significant work experience as an algorithm designer at a Fin-tech company in 2020 and 2021. Additionally, he has been actively involved in Forex trading since 2018. His teaching experience is extensive, having served as a teaching assistant at Allameh Tabataba’i University from 2016 to 2018, where he assisted in courses such as Calculus 1 and 2, Financial Engineering, Numerical Methods in Financial Mathematics, and Numerical Solutions of Stochastic Differential Equations. During the same period, he also taught MATLAB and PYTHON software at Allameh Tabataba’i University and The Petroleum University of Technology. Earlier, from 2012 to 2015, he was a teaching assistant at the University of Mazandaran, contributing to courses like Calculus 1 and 2, Graph Theory, Operations Research, and Programming. His teamwork experience includes serving as the chair of the Financial Mathematics Student Society at Allameh Tabataba’i University from 2016 to 2017, vice chair of the same society from 2015 to 2016, and chair of the Mathematics Student Society at the University of Mazandaran from 2013 to 2015.

 

Research 

He has also gained valuable research experience as a research assistant at Allameh Tabataba’i University from 2017 to 2018, working with Prof. Abdolsadeh Neisy. Additionally, he has participated in several workshops to further his knowledge and skills, including a workshop on inverse problems and big data in 2019, a workshop on machine learning in 2018, and a workshop on decision making in 2015.

 Awards & Honors

He has received several honors throughout his academic career. In 2022, he was awarded the Excellent Researcher Taiwan Government Scholarship (MOST). In 2017, he was recognized as the best master’s researcher at the Faculty of Mathematics. His academic excellence is further demonstrated by his achievement of earning the 37th rank in the mathematics master’s entrance exam and the 28th rank in the science engineering master’s entrance exam in 2015. Additionally, he earned the 2nd rank in the student competitions on Operations Research Olympiad at Semnan University in 2014.

📝🔬Publications📝🔬