Marko Panic | Inverse Imaging Problems | Best Researcher Award

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Dr. Marko Panic | Inverse Imaging Problems | Best Researcher Award

Senior Research Associate at BioSense Institute, Serbia📖

Dr. Marko Panić is a Senior Research Associate at the BioSense Institute, University of Novi Sad, Serbia. He specializes in statistical analysis of multi-sensor images with applications in biology, agriculture, environmental sciences, and healthcare. His work focuses on probabilistic graphical models and inverse imaging problems, with significant contributions to international and domestic research projects.

Profile

Scopus Profile

Orcid Profile

Google Scholar Profile

Education Background🎓

Dr. Panić obtained his Bachelor’s and Master’s degrees in Electrical and Computer Engineering from the University of Novi Sad in 2009 and 2010, respectively. He earned his Ph.D. in Computer Science Engineering in 2020 under a joint program between the University of Novi Sad and Ghent University.

Professional Experience🌱

Dr. Panić has actively participated in numerous international projects, including HORIZON2020 initiatives such as ANTARES, agROBOfood, FLEXIGROBOTS, CYBELE, and DRAGON. He has also led and contributed to multiple domestic projects funded by the Serbian government and innovation agencies. As the leader of the Computer Vision research group at BioSense Institute, he supervises five Ph.D. students and has successfully collaborated on industry-focused AI-driven solutions. His team has achieved recognition in competitions like the Syngenta Crop Challenge and OpenCV challenges.

Research Interests🔬

Dr. Panić’s research focuses on computer vision, machine learning, hyperspectral imaging, medical imaging, and AI applications in agriculture, biology, and environmental science. His expertise includes Markov random field modeling, MRI reconstruction, and probabilistic graphical models.

Author Metrics
  • Scopus: 420 citations, h-index: 12
  • Google Scholar: 606 citations, h-index: 13

Awards & Honors

  • Awarded as a Distinguished Scientist (Top 10% in the category of scientific associates) in Technical and Technological Sciences.
  • Led the AITool4WYP project funded by the Innovation Fund.
  • Task leader on the BREATH project funded by the Science Fund.
  • Recognized for achievements in Syngenta Crop Challenge and OpenCV Challenges, securing finalist positions and top awards.
Publications Top Notes 📄

1. Automatic pollen recognition with the Rapid-E particle counter: The first-level procedure, experience, and next steps

Authors: I. Šaulienė, L. Šukienė, G. Daunys, G. Valiulis, L. Vaitkevičius, P. Matavulj, M. Panić, et al.
Journal: Atmospheric Measurement Techniques
Volume/Issue: 12(6)
Pages: 3435-3452
Year: 2019
Citations: 113
DOI: Link

2. A new low-cost portable multispectral optical device for precise plant status assessment

Authors: G. Kitić, A. Tagarakis, N. Cselyuszka, M. Panić, S. Birgermajer, D. Sakulski, et al.
Journal: Computers and Electronics in Agriculture
Volume: 162
Pages: 300-308
Year: 2019
Citations: 58
DOI: Link

3. Soybean varieties portfolio optimization based on yield prediction

Authors: O. Marko, S. Brdar, M. Panić, P. Lugonja, V. Crnojević
Journal: Computers and Electronics in Agriculture
Volume: 127
Pages: 467-474
Year: 2016
Citations: 47
DOI: Link

4. RealForAll: Real-time system for automatic detection of airborne pollen

Authors: D. Tešendić, D. Boberić Krstićev, P. Matavulj, S. Brdar, M. Panić, V. Minić, et al.
Journal: Enterprise Information Systems
Volume/Issue: 16(5)
Article ID: 1793391
Year: 2022
Citations: 38
DOI: Link

5. High temporal resolution of airborne Ambrosia pollen measurements above the source reveals emission characteristics

Authors: B. Šikoparija, G. Mimić, M. Panić, O. Marko, P. Radišić, T. Pejak-Šikoparija, et al.
Journal: Atmospheric Environment
Volume: 192
Pages: 13-23
Year: 2018
Citations: 37
DOI: Link

Conclusion

Dr. Marko Panić is a highly accomplished researcher with a strong background in Inverse Imaging Problems, computational vision, and AI applications in environmental science and agriculture. His leadership, publication impact, and project contributions make him an excellent candidate for the Best Researcher Award. Expanding his research into commercial AI applications and interdisciplinary collaborations could further solidify his standing as a global leader in computational imaging.

Faisal Mehmood | Computer Vision | Best Researcher Award

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Dr. Faisal Mehmood | Computer Vision | Best Researcher Award

Post Doctorate at Shenzhen University, China📖

Faisal Mehmood is a passionate PhD researcher at Zhengzhou University, specializing in Electrical and Information Engineering. With a strong academic background, including degrees in Computer Science, he has a diverse range of expertise in deep learning, computer vision, and human action recognition (HAR). Faisal has authored numerous research papers in prominent journals and conferences and has practical experience as a software developer, database developer, and lecturer. His contributions are recognized in academia, where he also actively reviews for esteemed journals. Faisal continues to focus on advancing technologies in machine learning and artificial intelligence.

Profile

Scopus Profile

Google Scholar Profile

Education Background🎓

  • Ph.D. in Electrical and Information Engineering (2019–2024), Zhengzhou University, Henan, China (1st Division).
  • MS in Computer Science (2015–2017), University of Agriculture Faisalabad (UAF), Punjab, Pakistan (1st Division).
  • MSc in Computer Science (2013–2015), University of Agriculture Faisalabad (UAF), Punjab, Pakistan (1st Division).
  • BSc (2011–2013), Islamia University Bahawalpur, Punjab, Pakistan (1st Division).
  • Intermediate (2008–2010), BISE Bahawalpur, Punjab, Pakistan (1st Division).
  • Matriculation (2006–2008), BISE Bahawalpur, Punjab, Pakistan (1st Division).

Professional Experience🌱

Faisal Mehmood has accumulated a wealth of teaching and industry experience over the years. He has served as a lecturer at institutions such as the University of Agriculture Faisalabad, University of Education Faisalabad, and GC University Faisalabad. Faisal has also gained industry experience as a Software Developer and Database Developer, working on various projects involving database management, web development, and system software design. He has supervised several undergraduate projects and contributed to academic workshops and seminars, fostering an environment of interactive learning and development.

Research Interests🔬

Faisal’s research interests include:

  • Deep Learning: Exploring advanced neural network architectures.
  • Computer Vision: Enhancing image and video processing for real-world applications.
  • Human Action Recognition (HAR): Developing systems for detecting and recognizing human actions through innovative algorithms.
  • Natural Language Processing: Applying machine learning techniques for language understanding and processing.

Author Metrics

Faisal Mehmood has published several research papers in reputed journals, such as IEEE Transactions on Consumer Electronics, Soft Computing, and Computers in Human Behavior, with numerous articles under review. His work has contributed significantly to advancements in the fields of human action recognition, machine learning, and data science. He has received merit scholarships throughout his academic career and has been recognized with awards such as the Chief Minister’s Laptop Scheme and various programming competition wins. Faisal actively contributes to the academic community as a reviewer for top journals and conferences, further enriching his research endeavors.

Publications Top Notes 📄

1. Human action recognition of spatiotemporal parameters for skeleton sequences using MTLN feature learning framework

  • Authors: F Mehmood, E Chen, MA Akbar, AA Alsanad
  • Journal: Electronics
  • Volume: 10
  • Issue: 21
  • Article: 2708
  • Year: 2021
  • Citations: 21

2. Three-dimensional agricultural land modeling using unmanned aerial system (UAS)

  • Authors: F Mahmood, K Abbas, A Raza, MA Khan, PW Khan
  • Journal: International Journal of Advanced Computer Science and Applications
  • Volume: 10
  • Issue: 1
  • Year: 2019
  • Citations: 18

3. Intelligent Transmission Control for Efficient Operations in SDN

  • Authors: R Alkanhel, A Ali, F Jamil, M Nawaz, F Mehmood, A Muthanna
  • Journal: Computers, Materials & Continua
  • Volume: 71
  • Issue: 2
  • Year: 2022
  • Citations: 11

4. Effect of human-related factors on requirements change management in offshore software development outsourcing: A theoretical framework

  • Author: FM Sukana Z
  • Journal: Soft Computing and Machine Intelligence
  • Volume: 1
  • Issue: 1
  • Pages: 36-52
  • Year: 2021
  • Citations: 11

5. Towards successful global software development

  • Authors: M Shafiq, Q Zhang, MA Akbar, T Kamal, F Mehmood, MT Riaz
  • Conference: Proceedings of the 24th International Conference on Evaluation and …
  • Year: 2020
  • Citations: 11

Conclusion

Dr. Faisal Mehmood is undoubtedly a highly deserving candidate for the Best Researcher Award due to his exceptional contributions to deep learning, computer vision, and human action recognition. His innovative frameworks, high-quality publications, and academic success distinguish him as a leader in his field. While there are areas for further improvement, particularly in expanding his research reach and increasing industrial collaborations, his continued growth and success make him a strong candidate for the award. His work, particularly in applying AI and deep learning for practical applications, has great potential to shape the future of technology.

Dr. Mehmood’s combination of academic rigor, technical expertise, and research impact make him a promising figure in the academic community and an excellent candidate for this prestigious recognition.