Bushra Abro | Artificial Intelligence | Research Excellence Award

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Ms. Bushra Abro | Artificial Intelligence | Research Excellence Award

National Centre Of Robotics And Automation | Pakistan

Ms. Bushra Abro is a Computer and Information Engineer with a strong foundation in Electronic Engineering. She holds a Master’s degree in Computer and Information Engineering and a Bachelor’s in Electronic Engineering from Mehran University of Engineering & Technology, Pakistan, graduating top of her class. With professional experience as a Research Associate and Assistant at the National Centre of Robotics and Automation, she has contributed to projects in deep learning, computer vision, federated learning, and real-time condition monitoring. Her work has earned multiple publications and awards, including a gold medal at the All Pakistan IEEEP Student Seminar. She is passionate about advancing AI-driven technological innovation.

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Featured Publications


Towards Smarter Road Maintenance: YOLOv7-Seg for Real-Time Detection of Surface Defects

– Book Chapter, 2025Contributors: Bushra Abro; Sahil Jatoi; Muhammad Zakir Shaikh; Enrique Nava Baro; Bhawani Shankar Chowdhry; Mariofanna Milanova


Federated Learning-Based Road Defect Detection with Transformer Models for Real-Time Monitoring

– Computers, 2025Contributors: Bushra Abro; Sahil Jatoi; Muhammad Zakir Shaikh; Enrique Nava Baro; Mariofanna Milanova; Bhawani Shankar Chowdhry


Harnessing Machine Learning for Accurate Smog Level Prediction: A Study of Air Quality in India

– VAWKUM Transactions on Computer Sciences, 2025Contributors: Sahil Jatoi; Bushra Abro; Sanam Narejo; Yaqoob Ali Baloch; Kehkashan Asma


Learning Through Vision: Image Recognition in Early Education

– ICETECC Conference, 2025Contributors: Sahil Jatoi; Bushra Abro; Shafi Jiskani; Yaqoob Ali Baloch; Sanam Narejo; Kehkashan Asma


From Detection to Diagnosis: Elevating Track Fault Identification with Transfer Learning

– ICRAI Conference, 2024Contributors: Sahil Jatoi; Bushra Abro; Noorulain Mushtaq; Ali Akbar Shah Syed; Sanam Narejo; Mahaveer Rathi; Nida Maryam

Razi Al-Azawi | Image Processing | Research Excellence Award

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Prof. Dr. Razi Al-Azawi | Image Processing | Research Excellence Award

University of Technology | Iraq

Prof. Dr. Razi Al-Azawi is a distinguished academic and researcher specializing in informatics, artificial intelligence, and advanced computational systems. He holds dual B.Sc. degrees in Laser and Optoelectronics Engineering from the University of Technology and Mathematical Sciences from Mustansiriah University, an M.Sc. in Modeling and Simulation from the University of Technology, and a PhD in Informatics from Kharkov National University of Radio Electronics. Over a career spanning more than two decades, he has taught a wide range of postgraduate and undergraduate courses, including image processing, deep learning, AI, modeling and simulation, information theory, optimization, probability, web design, and advanced programming. His research interests encompass machine learning, data mining, medical image analysis, laser engineering, cybersecurity, and advanced computational modeling. He has supervised over 50 undergraduate theses and numerous postgraduate dissertations at the Higher Diploma, M.Sc., and PhD levels. His scholarly output includes 16 documents, 264 citations by 257 documents, and an h-index of 6. He has served as a reviewer for several international journals and conferences and holds multiple patents under processing. Through his academic leadership and scientific contributions, he continues to advance innovation in computer science, AI, and engineering domains.

Profiles : Scopus |

Featured Publications

Samaneh Saeedinia | Engineering | Best Researcher Award

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Prof.Dr. Samaneh Saeedinia | Engineering | Best Researcher Award

Iran University of Science and Technology | Iran

Dr. Samaneh Alsadat Saeedinia is an accomplished researcher and engineer specializing in Control Electrical Engineering, Computational Neuroscience, Robotics, and Artificial Intelligence. She earned her Ph.D. from Iran University of Science and Technology (IUST), where her thesis focused on designing and stabilizing intelligent decision-making systems to support the treatment of adult focal epilepsy, receiving an excellent grade. She also holds a Master’s degree in Control Electrical Engineering from IUST and a Bachelor’s degree from Imam Khomeini International University. Dr. Saeedinia has extensive experience in signal processing, machine learning, spiking neural networks, EEG and MRI data analysis, and adaptive control systems. She has contributed to numerous high-impact publications in IEEE Transactions, Scientific Reports, and other international journals. Her research interests include computational modeling, intelligent control, data fusion, robotics path planning, and neuroinformatics. Beyond academia, she has led industrial projects in electrical power systems, automation, and instrumentation. She has received multiple awards, including the Khwarizmi International Award and top ranks in academic performance. Dr. Saeedinia is also an experienced educator and mentor, guiding students in advanced control systems, neural networks, and data analysis. Her work bridges engineering, neuroscience, and artificial intelligence, aiming to develop innovative solutions for healthcare and robotic applications.

Profile : Google Scholar

Featured Publications

Saeedinia, S.A., Jahed-Motlagh, M.R., Tafakhori, A., & Kasabov, N.K. (2024). “Diagnostic biomarker discovery from brain EEG data using LSTM, reservoir-SNN, and NeuCube methods in a pilot study comparing epilepsy and migraine” in Scientific Reports, 14(1), 10667.

Mohaghegh, M., Saeedinia, S.A., & Roozbehi, Z. (2023). “Optimal predictive neuro-navigator design for mobile robot navigation with moving obstacles” in Frontiers in Robotics and AI, 10, 1226028.

Roozbehi, Z., Narayanan, A., Mohaghegh, M., & Saeedinia, S.A. (2024). “Dynamic-structured reservoir spiking neural network in sound localization” in IEEE Access, 12, 24596–24608.

Saeedinia, S.A., & Tale Masouleh, M. (2022). “The synergy of the multi-modal MPC and Q-learning approach for the navigation of a three-wheeled omnidirectional robot based on the dynamic model with obstacle collision” in Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science.

Roozbehi, Z., Narayanan, A., Mohaghegh, M., & Saeedinia, S.A. (2025). “Enhanced Multiple Sound Event Detection and Classification Using Physical Signal Properties in Recurrent Spiking Neural Networks” in IEEE Access.

Piotr Porwik | Machine Learning and AI Applications | Best Researcher Award

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Prof. Dr. Piotr Porwik | Machine Learning and AI Applications | Best Researcher Award

University of Silesia | Poland

Prof. Dr. Piotr Porwik is a full professor in the Institute of Computer Science at the University of Silesia in Katowice, specializing in engineering and technical sciences. He earned his M.Sc. in computer science from the University of Silesia in 1978, his Ph.D. in 1985, and completed his habilitation in 2006 at AGH University of Science and Technology in Krakow. His research spans machine learning, biometrics, image processing, biomedical imaging, and spectral methods for Boolean functions. Across his career, he has authored 81 scientific documents that have attracted 1,003 citations from 783 citing documents, and he holds an h-index of 17. He has published extensively in journals, international conferences, books, and book chapters, while also supervising Master’s and Ph.D. students. Prof. Porwik has served in major academic leadership roles, including Deputy Dean and Director of the Institute, and played a key role in shaping academic publishing as Editor-in-Chief of the Journal of Medical Informatics and Technologies. His achievements have been recognized through numerous distinctions, including the Bronze Cross of Merit and multiple awards from the President of the University of Silesia for scientific accomplishments. His work continues to advance biometric security, classifier development, and biomedical informatics, underscoring his long-standing academic influence and research innovation.

Profiles : Scopus | Orcid

Featured Publications

Wrobel, K., Porwik, P., & Orczyk, T. (2025). “Evaluation of the Effectiveness of Ranking Methods in Detecting Feature Drift in Artificial and Real Data” in (Book) / Lecture Notes in?

Mensah Dadzie, B., & Porwik, P. (2025). “Feature-Based Drift Detection in Non-stationary Data Streams Using Multiple Classifiers: A Comprehensive Analysis” in (Book)

Porwik, P., Orczyk, T., Wrobel, K., & Mensah Dadzie, B. (2025). “A Novel Method for Drift Detection in Streaming Data Based on Measurement of Changes in Feature Ranks” in Journal of Artificial Intelligence and Soft Computing Research, (DOI: 10.2478/jaiscr-2025-0008).

Porwik, P., Orczyk, T., & Japkowicz, N. (2024). “Supervised and Unsupervised Analysis of Feature Drift in a New Type of Detector” in Preprint (Research Square)

Porwik, P., Orczyk, T., & Doroz, R. (2022). “A Stable Method for Detecting Driver Maneuvers Using a Rule Classifier” in Lecture Notes in Computer Science

Hamed Etezadi | Quantitative Research | Best Researcher Award

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Mr. Hamed Etezadi | Quantitative Research | Best Researcher Award

McGill University | Canada

Dr. Hamed Etezadi is a research-focused scholar in Bioresource Engineering with a Ph.D. from McGill University, Canada, where his thesis focused on developing decision support infrastructure for sustainable crop production under the supervision of Prof. Viacheslav Adamchuk. He holds an M.S. in Biosystems and Agricultural Engineering from the University of Tehran, Iran, and a B.E. in Agricultural Engineering from Urmia University, Iran. With over 15 years of academic and professional experience, Dr. Etezadi has contributed significantly to precision agriculture, data-driven modeling, remote sensing, machine learning, and autonomous agricultural systems. He has published 6 peer-reviewed journal articles, including Q1 and Q2 journals, and presented at leading conferences such as ASABE and IEEE/CS Robotics and Mechatronics, His research explores soil variability, aerial pollination systems, and predictive modeling for sustainable agriculture. He has received multiple honors, including the FRQNT Scholarship, Grad Excellence Award, and global recognition on Kaggle Notebooks. Dr. Etezadi combines academic teaching, research leadership, and industry experience, including directing growth and innovation in agri-tech platforms, fostering data-driven decision-making, and advancing sustainable farming technologies globally.

Profile : Orcid 

Featured Publications

Etezadi, H., Adamchuk, V., Bouroubi, Y., Leduc, M., Gasser, M.-O., & Titley-Peloquin, D. (2025). “Quantifying intra-field soil variability using categorical data: A case study of predicting soil organic matter using soil survey maps.”

Etezadi, H., & Eshkabilov, S. (2024). “A comprehensive overview of control algorithms, sensors, actuators, and communication tools of autonomous all-terrain vehicles in agriculture.”

Mazinani, M., Zarafshan, P., Dehghani, M., Vahdati, K., & Etezadi, H. (2023). “Design and analysis of an aerial pollination system for walnut trees.”

Zarafshan, P., Etezadi, H., Javadi, S., Roozbahani, A., Hashemy, S. M., & Zarafshan, P. (2023). “Comparison of machine learning models for predicting groundwater level, case study: Najafabad region.”

Salari, K., Zarafshan, P., Khashehchi, M., Chegini, G., Etezadi, H., Karami, H., Szulżyk-Cieplak, J., & Łagód, G. (2022). “Knowledge and technology used in capacitive deionization of water.”

Nicholas Otumi | Neuroscience Data Analysis | Best Researcher Award

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Mr. Nicholas Otumi | Neuroscience Data Analysis | Best Researcher Award

University of Rochester | United States

Nicholas Otumi is a biomedical imaging researcher with a strong foundation in diagnostic imaging and deep learning. He holds a BSc in Diagnostic Imaging Technology from the University of Cape Coast (Ghana) and an MS in Diagnostic Imaging (Bioengineering & Biomedical Engineering) from the University of Rochester (USA), where his coursework included deep learning, inverse problems in imaging, clinical imaging, and signal processing. He has held research and technical roles at multiple institutions: as a remote Research Assistant at Indiana University working on pharmaceutical pricing and market analytics, and at the University of Rochester contributing to segmentation (with UNet-R) and image analysis in brain CT. Previously, as a Research and Teaching Assistant at UCC, he supported imaging equipment courses, data analysis, and undergraduate research. His research interests center on medical image analysis, especially applying deep learning to brain MRI and CT segmentation, classification of disease from imaging, and imaging in resource-constrained settings. He has several manuscripts under review or published, including a multicentre survey on advanced brain MRI in low-resource settings and case reports in radiology.  He is a recipient of honors such as the Harry W. Fischer Research Funds (2025) and the HSEAS Dean’s Fellowship (2024) at Rochester, as well as campus leadership awards in Ghana. Nicholas is committed to advancing AI-driven neuroimaging and translational imaging research across low- and middle-income settings, aiming to bridge technology gaps and enhance equitable access to advanced diagnostic tools.

Profiles : Orcid | Google Scholar

Featured Publications

Piersson, A. D., Nunoo, G., Dzefi-Tettey, K., & Otumi, N. (2025). Utility of advanced brain MRI techniques for clinical and research purposes in a low-resource setting: A multicentre survey. Next Research.

Fiagbedzi, E., Arkorful, J., Brobbey, I. F., Appiah, E., Nyarko, S., Otumi, N., Piersson, A. D., Nimo, O., Ofori, I. N., & Gorleku, P. N. (2025). A case of ruptured infrapatellar bursa sac with Baker’s cyst. Radiology Case Reports, 20(1).

Fiagbedzi, E., Arkorful, J., Appiah, E., Otumi, N., Ofori, I., & Gorleku, P. N. (2024). A rare case of intussusception in a 6-month-old baby. Radiology Case Reports, 19(10).

Dinesh Babu Vunnava – Big Data Analytics – Best Researcher Award

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Dr. Dinesh Babu Vunnava - Big Data Analytics - Best Researcher Award

Rv Institute Of Technology,Guntur - India

Author Profile

Early Academic Pursuits

Mr. Dr. Vunnava Dinesh Babu embarked on his academic journey with a Bachelor's degree in Technology from NRI Institute of Technology. This laid the foundation for his passion for computer science and engineering. Following his undergraduate studies, he pursued a Master's degree in Computer Science from St. Mary's Group of Institutions. This period allowed him to delve deeper into the intricacies of his field, fostering his enthusiasm for learning and research.

Professional Endeavors

Armed with a solid educational background, Mr. Dinesh Babu transitioned into the professional realm with an eagerness to make a difference. Joining Chebrolu Engineering College as the Head of Computer Science and Engineering Department marked a significant milestone in his career. With over 11 years of experience in academia, research, teaching, training, and consultancy, he brings a wealth of knowledge and expertise to his role. His dedication to continuous learning is evident in his pursuit of a Ph.D. from Saveetha Institute of Medical and Technical Science in Chennai.

Contributions and Research Focus

Mr. Dinesh Babu's contributions extend beyond the confines of the classroom. He is actively involved in guiding and conducting research on various aspects of technology, with a particular emphasis on cryptography and network security. His research papers and textbooks serve as a testament to his educational inclinations and commitment to advancing knowledge in his field. By exploring new avenues and pushing the boundaries of technological understanding, he inspires both his students and peers alike.

Accolades and Recognition

Throughout his career, Mr. Dinesh Babu has garnered recognition for his exemplary work and dedication to education. His contributions have been acknowledged through accolades and awards, highlighting his impact in the academic community. These accolades serve as a testament to his unwavering commitment to excellence and innovation in education.

Impact and Influence

As the Head of the Computer Science and Engineering Department, Mr. Dinesh Babu plays a pivotal role in shaping the academic experiences of his students. His efforts to foster a positive, encouraging, and effective learning environment are evident in the success of his students. By offering industry internships and value-added courses, he equips students with the skills and knowledge needed to thrive in the ever-evolving field of technology. His influence extends beyond the classroom, inspiring future generations of technologists to pursue their passions and make meaningful contributions to society.

Legacy and Future Contributions

Mr. Dinesh Babu's legacy is one of excellence, dedication, and innovation in education. Through his relentless pursuit of knowledge and commitment to student success, he leaves an indelible mark on the academic community. As he continues his journey, his future contributions are poised to further enrich the field of computer science and engineering. By remaining at the forefront of research and education, he ensures that his impact will be felt for years to come, shaping the minds of future generations and driving progress in technology and beyond.

Notable Publication