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

Published 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

Published 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📝🔬

Asif Hamid- Deep learning – Best Researcher Award

Published on by Network Science

Asif Hamid- Deep learning – Best Researcher Award

Mr. Asif Hamid  distinguished academic and researcher in the field  Deep learning. He has accumulated over four years of experience in writing and publishing research articles for journals and conferences. This experience has provided him with a deep understanding of various writing styles, from scholarly articles to book chapters and industry-focused documentation. His role as a reviewer for many prestigious conferences has also sharpened his critical thinking and editorial abilities.

His expertise is not limited to writing; he is skilled in Python and MATLAB programming, which are crucial for his research projects. He possesses basic skills in HTML and is proficient with MS Office tools—Word, Excel, and PowerPoint—as well as LaTeX software, all vital for creating research papers and presentations. Additionally, his ability to utilize internet applications and implement deep learning techniques demonstrates his aptitude for integrating cutting-edge technology into his research activities.

🌐 Professional Profiles

Educations📚📚📚

He is currently pursuing a Ph.D. at the Islamic University of Science and Technology (IUST) in Awantipora, Jammu & Kashmir, India, a program he began in 2020. Prior to this, he earned his Master of Technology degree in Control and Instrumentation Systems from Jamia Milia Islamia (JMI) in India, where he distinguished himself by securing a CGPA of 9.3 out of 10, placing him in the top 1% of his class. His foundational education was completed at Baba Ghulam Shah Badshah University in Rajouri, Jammu & Kashmir, where he received his Bachelor of Technology degree in Electronics and Communication Engineering, achieving a percentile score of 75.6, which also placed him in the top 1% of his peers.

Conference Papers

• Asif Hamid Bhat, Rafiq, D., Nahvi, S. A., & Bazaz, M. A. (2022, May). Discovering low-rank
representations of large-scale power-grid models using Koopman theory. In 2022 Trends in
Electrical, Electronics, Computer Engineering Conference (TEECCON). IEEE.. [Link]
• Asif Hamid Bhat, Rafiq, D., Nahvi, S. A., & Bazaz, M. A. (2022, July). Power Grid parameter
estimation using Sparse Identification of Nonlinear Dynamics. In 2022 International
Conference on Intelligent Controller and Computing for Smart Power (ICICCSP) (pp. 1-6).
IEEE. [Link]
• Asif Hamid Bhat, Rafiq, D., Nahvi, S. A., & Bazaz, Neural network-based time stepping

Awards and Achievements

He has received numerous accolades and support for his academic pursuits. Since 2020, he has been a recipient of the MHRD (Ministry of Human Resource Development, Government of India) fellowship for his Ph.D. studies in the Department of Electrical Engineering at the Islamic University of Science and Technology in Awantipora, Jammu & Kashmir, India, supported by grant number IUST0119013135. In 2019, he successfully qualified the GATE (Graduate Aptitude Test in Engineering) for Electronics and Communication Engineering, scoring 31.67 out of 100. Furthermore, in 2017, he qualified for the M.Tech. program at Jamia Milia Islamia, Delhi, by passing the entrance examination, demonstrating his consistent excellence and competence in his field.

WORKSHOP / SEMINAR / TRAINING / STC attended

1. Presented Discovering low-rank representations of large scale power-grid models using Koopman
theory paper in Electrical, Electronics, Computer Engineering Conference IEEE held on 26-27
may 2022 at Reva University.
2. Presented Power Grid parameter estimation using Sparse Identification of Nonlinear Dynamics
paper in the INTERNATIONAL CONFERENCE ON INTELLIGENT CONTROLLER AND
COMPUTING FOR SMART POWER, IEEE 2022 organized by the Department of Electrical
and Electronics Engineering, Sreenidhi Institute of Science And Technology, Hyderabad,
India during 21–23 July 2022.
3. Reviewer for IEEE international conference on applied intelligence and sustainable
computing 2023.
4. Attend in faculty development program entitled “Research Methodology + Publication Ethics”
organised by Department of computer science and engineering IUST, Awantipora form 7-11
Feb 2022.

📝🔬Publications📝🔬

  • Hierarchical deep learning-based adaptive time stepping scheme for multiscale simulations

    Engineering Applications of Artificial Intelligence
    2024-07 | Journal article
    DOI: 10.1016/j.engappai.2024.108430
    CONTRIBUTORS: Asif Hamid; Danish Rafiq; Shahkar Ahmad Nahvi; Mohammad Abid Bazaz

  • Neural network-based time stepping scheme for multiscale partial differential equations

    2023 7th International Conference on Computer Applications in Electrical Engineering-Recent Advances (CERA)
    2023-10-27 | Conference paper
    DOI: 10.1109/cera59325.2023.10455439
    CONTRIBUTORS: Asif Hamid; Danish Rafiq; Shahkar Ahmad Nahvi; Mohammad Abid Bazaz

  • Deep learning assisted surrogate modeling of large-scale power grids

    Sustainable Energy, Grids and Networks
    2023-06 | Journal article
    DOI: 10.1016/j.segan.2023.101031
    Part ofISSN: 2352-4677
    CONTRIBUTORS: Asif Hamid; Danish Rafiq; Shahkar Ahmad Nahvi; Mohammad Abid Bazaz

  • Power Grid parameter estimation using Sparse Identification of Nonlinear Dynamics

    2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP)
    2022-07-21 | Conference paper
    DOI: 10.1109/iciccsp53532.2022.9862464
    CONTRIBUTORS: ASIF HAMID BHAT

Sankar Shanmuganathan – Generative adversarial networks

Published on by Network Science

Dr. Sankar Shanmuganathan – Leading Researcher in Generative adversarial networks

Dr.  Sankar Shanmuganathan  a distinguished academic and researcher in the field of Generative adversarial networks. He is currently serving as a Professor in the Department of Computer Science and Engineering at Saveetha School of Engineering, SIMATS, Chennai, Tamil Nadu, India. A dedicated, resourceful, and goal-driven professional educator, he is passionate about programming and has a solid commitment to academic growth. With over 20 years of experience, he is a seasoned researcher and has taught courses for both undergraduate and postgraduate students. He has successfully supervised 20 Bachelor’s theses and 10 Master’s theses, demonstrating his mentorship skills. His contributions extend to publishing articles in peer-reviewed journals and conferences, obtaining three patents, and securing grants from AICTE for organizing technical events.🌟💻🔬

Eduvation

He completed his Ph.D. in Information Technology from Hindustan University in 2018. 🎓 Prior to that, he earned a Master’s degree in Software Engineering from Periyar Maniammai College of Technology, affiliated with Anna University, Chennai, Tamil Nadu, in 2006, achieving a first-class distinction. 🏆 His academic journey began with a Bachelor’s degree in Computer Engineering from Arulmigu Kalasalingam College of Engineering, Srivilliputhur, Tamil Nadu, in 1992, where he also excelled with a first-class distinction. 🏅 This degree was affiliated with Madurai Kamaraj University, Madurai, Tamil Nadu. 🌟

Professional Profiles:

RESEARCH ACTIVITIES

🗣️He has obtained three patents from IP Australia, showcasing his innovative contributions. The first patent, dated October 27, 2021 (Patent No: 2021102955), is titled “A System and Method for Agile Meeting Dashboard.” The second patent, dated May 5, 2021 (Patent No: 2021101703), pertains to “3D Printing of Cost-Effective Human Skull Models and Skull Implants.” The third patent, dated April 7, 2021 (Patent No: 2021100286), is for “Aqua Life: A Compact Device Extracting Drinkable Water from Sea Water.”

In addition to his research achievements, he has undertaken various consultancy projects. Notably, he developed a software product for MEL Systems and Services Ltd, Chennai, involving the creation of advanced reports using Python, Django, and MongoDB. Another significant project involved the development of a software product to detect glaucoma in optical coherence tomography images for M/s Appasamy Associates R & D, Chennai, implemented in Java and Matlab.

Furthermore, he contributed to software bug fixing for General Electricals T & D Limited, Chennai, utilizing VB.NET technology. Additionally, he conducted corporate training for General Electricals T & D Limited, Chennai, imparting VB.NET platform skills to GE employees, preparing them to independently develop utility software. The funds received for training amounted to Rs. 2,00,000. Overall, his diverse expertise and accomplishments reflect his commitment to both innovation and practical application in the field.

BOOKS AUTHORED / CHAPTER CONTRIBUTED

AUTHORED BOOK on OBJECT ORIENTED PROGRAMMING Published by Laxmi PublicationsChennai,
2009
CHAPTER CONTRIBUTED LEAN SIX SIGMA: SIX SIGMA PROJECTS AND PERSONAL EXPERIENCEPublished by In-Tech Open Access Publications, Crotia, 2012

RESEARCH PAPERS PUBLISHED

  • Deep generative adversarial networks with marine predators algorithm for classification of Alzheimer’s disease using electroencephalogram
    • Authors: J.C. Sekhar, Ch Rajyalakshmi, S. Nagaraj, S. Sankar, Rajesh Saturi, A. Harshavardhan
    • Published in: Journal of King Saud University – Computer and Information Sciences
    • Volume 35, Issue 10, December 2023
    • DOI: 10.1016/j.jksuci.2023.101848
  • Exploration of Performance of Dynamic Branch Predictors used in Mitigating Cost of Branching
    • Authors: Akash Ambashankar, Ganesh Chandrasekar, AR Charan, S Sankar
    • Published in: 2022 IEEE Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT)
  • AI Enabled Educational Bot to Improve Learning Outcomes using Bag of Words Algorithm
  • Intelligent Organ Transplantation System Using Rank Search Algorithm to Serve Needy Recipients
    • Authors: S Sankar, U Shuruti, B Bhuvaneshwari
    • Published in: 2022 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES)
  • Understanding Query Intention in Search Queries of Learners in Blended Learning Environments
    • Authors: Vivekananthamoorthy Natarajan, Sankar Shanmuganathan
    • Published in: 2022 IEEE 4th International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA)
  • Sign language translator using YOLO algorithm
    • Authors: Bhavadharshini, M., Josephine Racheal, J., Kamali, M., Sankar, S.
    • Published in: Advances in Parallel Computing, 2021, 39, pp. 159-166
  • Detection of Anomalous Behaviour in Online Exam towards Automated Proctoring
    • Authors: Susithra V, Resham A, Bishruti Gope, Sankar
    • Published in: IEEE International Conference on System, Computation, Automation and Networking
    • DOI: 10.1109/ICSCAN53069.2021.9526448
  • Development of Novel Technique to Detect and Validate Pulmo Malignancy during Early Stages
    • Authors: Dhanalakshmi R, Shree Harini R, Pravallika M, S Sankar
    • Published in: International Journal of Current Research and Review, volume: 13 issue: 17, pp. 56-60, 12th September 2021
    • DOI: http://dx.doi.org/10.31782/IJCRR.2021.131711
  • Sentiment Analysis of Twitter Political Data using GRU Neural Network
    • Authors: Seenaiah Pedipina, Sankar S and R Dhanalakshmi
    • Published in: International Journal of Advanced Science and Technology 29(6), pp. 5307-5320, ISSN 2207-6360, SERSC Australia
  • Sentimental Analysis On Twitter Data Of Political Domain
    • Authors: Seenaiah Pedipina, Sankar S and R Dhanalakshmi
    • Published in: Dogo Rangsang Research Journal, UGC Care Group I Journal, Vol-10 Issue-07 No. 16 July 2020, ISSN:2347-7180
  • An Improved Framework for Sentiment Analysis for College Reviews
    • Authors: T. Sri Devi, R. Dhanalakshmi, S. Sankar
    • Published in: International Journal of Advanced Trends in Computer Science and Engineering, 9(2), 1959-1963