Ahmad Hassanat | Machine Learning | Best Researcher Award

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Prof. Ahmad Hassanat | Machine Learning | Best Researcher Award

Professor at Mutah University, Jordan

Professional Profile

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Summary

Prof. Ahmad B. A. Hassanat is a Full Professor of Computer Science at Mutah University, Jordan, and a senior IEEE member. He is globally recognized for his extensive contributions to artificial intelligence, machine learning, biometrics, and image processing. With over two decades of academic and research experience, he has authored numerous impactful papers and books and is widely known for pioneering innovative techniques like the "Hassanat Distance" metric and deep learning-based biometric systems. He is also active in international collaborations, editorial work, and AI-driven healthcare research.

Educational Details

Prof. Hassanat earned his Ph.D. in Computer Science from the University of Buckingham, UK,, with a focus on automatic lip-reading. He holds an M.Sc. in Computer Science from Al al-Bayt University, Jordan, where he specialized in fast string matching algorithms. He completed his B.Sc. in Computer Science at Mutah University, Jordan. His academic foundation reflects a strong blend of theoretical depth and applied research skills in computing and AI.

Professional Experience

Prof. Hassanat has served in multiple academic roles across Jordan and Saudi Arabia, including as a Full Professor at Mutah University and the University of Tabuk. He was Head of the IT Department at Mutah University and a visiting researcher at the Sarajevo School of Science and Technology. Earlier in his career, he worked for the Jordanian Armed Forces as a programmer and systems analyst, where he developed over a dozen mission-critical ICT systems. He is also a founder or co-founder of academic programs, conferences, and novel biometric solutions.

Research Interests

His research spans machine learning, artificial intelligence, image processing, biometrics, pattern recognition, and evolutionary algorithms. He is known for practical innovations such as deep learning for veiled-face recognition, genetic algorithm optimization, voice-based Parkinson’s detection, and machine learning models for epidemiology, security, and finance. He also created the widely referenced Hassanat Distance, improving classifier performance in imbalanced data scenarios.

Author Metrics

Prof. Hassanat has published over 100 journal articles and conference papers, with an H-index of 33, i10-index of 56, and more than 4,000 citations. His work is featured in top journals such as IEEE Access, PLOS ONE, Sustainability, Applied Sciences, and Computers. His algorithmic contributions and models are highly cited in the fields of AI, healthcare informatics, and big data analytics.

Awards and Honors

Prof. Hassanat has been named among the world’s top 2% scientists by Stanford–Elsevier in 2021, 2022, and 2023. He has received the Best Scientist award at Mutah University for 2023 and 2024, and multiple competitive research grants from Jordan and Saudi Arabia. He was the recipient of Mutah University’s Distinguished Researcher Award (2018, 2019), and granted IEEE Senior Membership for his research excellence. His innovations, including terrorist identification from hand gestures and COVID-19 forecasting tools, have received global media attention.

Publication Top Notes

1. Deep learning computer vision system for estimating sheep age using teeth images

  • Authors: AB Hassanat, MA Al-Sarayreh, AS Tarawneh, MA Abbadi, et al.

  • Journal: Connection Science

  • Volume/Issue: 37 (1)

  • Article ID: 2506456

  • Year: 2025

  • Summary:
    This study presents a deep learning-based computer vision system designed to estimate the age of sheep by analyzing images of their teeth. The model likely leverages convolutional neural networks (CNNs) or similar architectures to accurately assess age-related dental features, offering a non-invasive and automated method for livestock age estimation that can assist farmers and veterinarians.

  • Citations: Not provided

  • Access: Details not provided

2. ICT: Iterative Clustering with Training: Preliminary Results

  • Authors: AB Hassanat, AS Tarawneh, AS Alhasanat, M Alghamdi, K Almohammadi, et al.

  • Conference: 2025 International Conference on New Trends in Computing Sciences (ICTCS)

  • Year: 2025

  • Summary:
    This paper introduces a novel method named Iterative Clustering with Training (ICT), presumably a machine learning or data clustering approach. Preliminary results demonstrate its effectiveness in improving clustering accuracy or training efficiency for datasets common in computing science. The approach likely combines clustering with supervised training iterations for better performance.

3. Decision tree-based learning and laboratory data mining: an efficient approach to amebiasis testing

  • Authors: E Al-Khlifeh, AS Tarawneh, K Almohammadi, M Alrashidi, R Hassanat, et al.

  • Journal: Parasites & Vectors

  • Volume/Issue: 18 (1)

  • Article Number: 33

  • Year: 2025

  • Summary:
    This research applies decision tree-based machine learning techniques to mine laboratory data for efficient and accurate diagnosis of amebiasis. The study demonstrates how data mining on clinical data combined with decision trees can improve testing accuracy and streamline diagnostic procedures in parasitology.

4. Non-Invasive Cancer Detection Using Blood Test and Predictive Modeling Approach

  • Authors: AS Tarawneh, AK Al Omari, EM Al-Khlifeh, FS Tarawneh, M Alghamdi, et al.

  • Book/Series: Advances and Applications in Bioinformatics and Chemistry

  • Pages: 159-178

  • Year: 2024

  • Summary:
    This paper proposes a non-invasive method for cancer detection by combining blood test results with predictive modeling approaches, likely using machine learning algorithms. The approach aims to provide an early, cost-effective screening tool for cancer by analyzing biomarkers and patterns in blood test data.

5. Extended spectrum beta-lactamase bacteria and multidrug resistance in Jordan are predicted using a new machine-learning system

  • Authors: EM Al-Khlifeh, IS Alkhazi, MA Alrowaily, M Alghamdi, M Alrashidi, et al.

  • Journal: Infection and Drug Resistance

  • Pages: 3225-3240

  • Year: 2024

  • Summary:
    This study develops and applies a machine learning system to predict the occurrence of extended spectrum beta-lactamase (ESBL) producing bacteria and multidrug resistance patterns in Jordan. The predictive model aids in understanding and managing antibiotic resistance, supporting healthcare decision-making and antimicrobial stewardship.

Conclusion

Prof. Ahmad Hassanat embodies the qualities of a world-class researcher—his work is innovative, deeply applied, and globally relevant. From introducing original metrics and models in AI to developing life-saving diagnostic systems and biometric security applications, his impact is both academic and practical.

His dedication to research excellence, mentorship, and cross-disciplinary innovation makes him highly deserving of the Best Researcher Award in Machine Learning.

Shakila Rahman | Machine Learning | Best Researcher Award

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Ms. Shakila Rahman | Machine Learning | Best Researcher Award

Lecturer at American International University, Bangladesh

Author Profile

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Summary

Shakila Rahman is a dedicated academician currently serving as a Lecturer in the Department of Computer Science at the Faculty of Science and Technology, American International University-Bangladesh (AIUB). She holds a strong academic background in Artificial Intelligence and Computer Engineering, with her research focusing on emerging areas such as UAV networking, wireless sensor networks, optimization algorithms, and machine learning. Shakila is actively involved in mentoring students, guiding projects, and publishing impactful research in reputed platforms.

Educational Details

Shakila Rahman earned her M.Sc. in AI & Computer Engineering from the University of Ulsan, South Korea, in 2023 with an impressive CGPA of 4.00 out of 4.50. She completed her B.Sc. in Computer Science and Engineering from International Islamic University Chittagong (IIUC), Bangladesh, in 2019, securing a CGPA of 3.743 out of 4.00. Prior to her university education, she completed her Higher Secondary Certificate (HSC) from Cox’s Bazar Govt. College and Secondary School Certificate (SSC) from Cox’s Bazar Govt. Girls’ High School.

Professional Experience

Shakila is currently employed as a Lecturer in the Department of Computer Science and Engineering at AIUB, Dhaka, Bangladesh, where she has been working since January 2023. She previously served as a Graduate Research Assistant at the University of Ulsan, South Korea, from September 2020 to December 2022 under Professor Seokhoon Yoon. Additionally, she worked as an Undergraduate Teaching Assistant at IIUC in 2019. She has participated in technical boot camps and workshops and actively contributes to academic supervision, having guided several student projects and a machine learning-based thesis group.

Research Interests

Her research interests span a wide range of cutting-edge topics including UAV Networking, Wireless Sensor Networks, Network Systems, Optimization Algorithms, Machine Learning, Deep Learning, Image Processing, and AR/VR Applications in Artificial Intelligence. These multidisciplinary areas reflect her focus on building intelligent and adaptive systems for real-world applications.

Author Metrics

Shakila Rahman actively maintains a presence on prominent academic platforms. Her ResearchGate profile can be found at https://www.researchgate.net/profile/Shakila-Rahman-3, and her ORCID ID is 0000-0001-6375-4174. She is also available on LinkedIn at Shakila Rahman. Her published works and citation records are regularly updated on these platforms.

Awards and Honors

During her master's studies, Shakila was awarded the prestigious Brain Korea 21 (BK21) Scholarship and a fully funded AF1 scholarship at the University of Ulsan, valued at approximately USD 21,000. She also received funding from Korean Government-supported National Research Foundation (NRF) projects to support her graduate research publications. These accolades recognize her academic excellence and research contributions in the field of computer science and engineering.

Publication Top Noted

1. Bilingual Sign Language Recognition: A YOLOv11-Based Model for Bangla and English Alphabets

Authors: N. Navin, F.A. Farid, R.Z. Rakin, S.S. Tanzim, M. Rahman, S. Rahman, J. Uddin, ...
Journal: Journal of Imaging, Vol. 11, Issue 5, Article 134
Year: 2025
Citation: 1 (as of now)
Summary:
This study introduces a YOLOv11-based deep learning model designed to recognize both Bangla and English sign language alphabets in real-time. The model was trained on a custom bilingual sign dataset and achieved high accuracy and low latency. The contribution is notable in promoting inclusivity for hearing-impaired communities in multilingual regions like Bangladesh.

2. Towards Safer Cities: AI-Powered Infrastructure Fault Detection Based on YOLOv11

Authors: R.Z. Rakin, M. Rahman, K.F. Borsa, F.A. Farid, S. Rahman, J. Uddin, H.A. Karim
Journal: Future Internet, Vol. 17, Issue 5, Article 187
Year: 2025
Summary:
This paper proposes an AI model using YOLOv11 to identify infrastructure faults (e.g., road cracks, bridge damage) through image data. Designed with smart city integration in mind, the model is tested in urban environments and demonstrates high efficiency.

3. A Hybrid CNN Framework DLI-Net for Acne Detection with XAI

Authors: S. Sharmin, F.A. Farid, M. Jihad, S. Rahman, J. Uddin, R.K. Rafi, R. Hossan, ...
Journal: Journal of Imaging, Vol. 11, Issue 4, Article 115
Year: 2025
Summary:
This paper presents DLI-Net, a hybrid CNN framework for classifying and explaining acne severity. It incorporates Explainable AI (XAI) techniques to enhance trust and transparency in medical AI systems.

4. A Deep Q-Learning Based UAV Detouring Algorithm in a Constrained Wireless Sensor Network Environment

Authors: S. Rahman, S. Akter, S. Yoon
Journal: Electronics, Vol. 14, Issue 1, Article 1
Year: 2024
Citation: 2 (as of now)
Summary:
This study explores a reinforcement learning-based approach using Deep Q-Learning for UAV navigation in constrained wireless sensor networks. The algorithm optimizes path planning in real-time, even in environments with signal interference or node failures.

5. A Deep Learning Model for YOLOv9-based Human Abnormal Activity Detection: Violence and Non-Violence Classification

Authors: S. Salehin, S. Rahman, M. Nur, A. Asif, M. Bin Harun, J. Uddin
Journal: Iranian Journal of Electrical & Electronic Engineering, Vol. 20, Issue 4
Year: 2024
Citation: 2 (as of now)
Summary:
This paper proposes a YOLOv9-based model to detect abnormal human activity, particularly violent behavior, in real-time video surveillance. The system is trained on public datasets and achieves high detection accuracy.

Conclusion

Ms. Shakila Rahman is a promising and emerging researcher, with an impressive blend of academic excellence, funded research, and contributions to cutting-edge domains like machine learning and UAV networks. Her commitment to mentoring students and publishing research makes her a very strong candidate for the Best Researcher Award, particularly among early-career researchers or those in developing countries.

Om Prakash – Computer Vision – Best Researcher Award

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Om Prakash – Computer Vision – Best Researcher Award

Dr. Om Prakash  distinguished academic and researcher in the field Computer Vision.

🌐 Professional Profile

Educations📚📚📚

He earned his Doctor of Philosophy from the University of Allahabad, Allahabad, U.P., India, in November 2014. He has extensive experience in academia and industry. Since March 2020, he has been an Assistant Professor at Academic Pay Level-10 in the Department of Computer Science and Engineering, School of Engineering and Technology, HNB Garhwal University, Srinagar Garhwal, Uttarakhand, India. From May 2019 to February 2020, he worked as a Computer Vision Scientist at Inferigence Quotient LLP, Bengaluru, Karnataka, India. Prior to this, he served as an Assistant Professor in the Department of Computer Science and Engineering at NIRMA University, Ahmedabad, Gujarat, India, from May 2018 to April 2019. Between March 2016 and April 2018, he was a faculty member at the Centre of Computer Education, University of Allahabad, U.P., India. He also completed a Postdoctoral Fellowship at the Gwangju Institute of Science and Technology, South Korea, from March 2015 to February 2016. His earlier experience includes serving as a faculty member at the Centre of Computer Education, University of Allahabad, U.P., India, from August 2007 to February 2

Research Interests

• Computer Vision
• Image and Video Processing
• Wavelet transforms
• Multisensory data fusion
• Video surveillance
• Machine Learning/Deep Learning
• Thermography
• Medical Imaging

Book Edited as Guest Editor

AKS Kushwaha, Om Pakash, M. Khare, J. Gwak, N.T. Binh, “Visual and Sensory Data Processing
for Real Time Intelligent Surveillance System”, Multimed Tools Appl, vol.81, pp. 42097–42098
(2022). https://doi.org/10.1007/s11042-022-14263-3, Springer

 

📝🔬Publications📝🔬

1. Pratibha Maurya, Arati Kushwaha, Ashish Khare, Om Prakash, Balancing Accuracy and
Efficiency: A Lightweight Deep Learning Model for Covid-19 Detection” Journal
Engineering Applications of Artificial Intelligence. vol. 136, Part B, July 2024, 108999,
ISSN 0952-1976, https://doi.org/10.1016/j.engappai.2024.108999., Elsevier. (SCI).
2. Arati Kushwaha, Ashish Khare, Om Prakash, Human activity recognition algorithm in video
sequences based on the fusion of multiple features for realistic and multi-view
environment. Multimedia Tools and Applications. vol.83, pp. 22727-22748, August 2024,
Springer (SCI)
(https://doi.org/10.1007/s11042-023-16364-z)
3. Neha Sisodiya, Nitant Dube, Om Prakash, Priyank Thakkar, Scalable Big Earth
Observation Data Mining Algorithms: A Review. Earth Science and Informatics, vol.16,
pp. 1993–2016, June 2023, Springer (SCI). https://doi.org/10.1007/s12145-023-01032-5.
4. Ashish Khare, Arati Kushwaha and Om Prakash, Human Activity Recognition in a Realistic
Unconstrained and Multiview Environment using 2D-CNN. Journal of Artificial
Intelligence and Technology (JAIT). vol.3, pp. 100-107, May 2023, Intelligence Science
and Technology Press. (ISTP) (Scopus). (https://doi.org/10.37965/jait.2023.0163)
5. Arati Kushwaha, Ashish Khare, Om Prakash, “Micro-network-based deep convolutional
neural network for human activity recognition from realistic and multi-view visual
data”, Neural Comput & Applic (2023). vol.35, pp.13321–13341, Springer (SCI).
(https://doi.org/10.1007/s00521-023-08440-0)
6. Arati Kushwaha, Ashish Khare, Om Prakash and Manish Khare, “Dense optical flow
based background subtraction technique for object segmentation in moving camera
environment”, IET Image Processing, vol. 14, no. 14, pp. 3393-3404, December 2020, IET
Publication. (SCI)
(https://doi.org/10.1049/iet-ipr.2019.0960).
7. Mounika B. Reddy, Om Prakash, Ashish Khare, “Keyframe extraction using Pearson correlation
coefficient and color moments,”. Multimedia Systems, vol. 26, pp.267–299 (2020), Springer. (SCI)
(https://doi.org/10.1007/s00530-019-00642-8).

8. Mounika B. Reddy, Om Prakash, Ashish Khare, “Video Superpixels Generation through
Integration of Curvelet transform and Simple Linear Iterative Clustering”, Multimedia Tools and
Applications, vol. 78, pp. 25185–25219, March 2019, Springer. (SCI)
(https://doi.org/10.1007/s11042-019-7554-z).

9. Om Prakash, Chang Min Park, Ashish Khare, Moongu Jeon, Jeonghwan Gwak, “Multiscale
Fusion of Multimodal Medical Images using Lifting Scheme based Biorthogonal Wavelet
Transform,” Optik, vol. 182, pp.995-1014, April 2019, Elsevier (SCI)
(https://doi.org/10.1016/j.ijleo.2018.12.028)
10. Manish Khare, Om Prakash and Rajneesh Kumar Srivastava, “Combining Zernike moment and
Complex wavelet transform for Human object classification,” Int. J. Computational Vision and
Robotics, May 2018, vol.18, no.2, pp.140-167, Inderscience Publishers. (Scopus)
(https://doi.org/10.1504/IJCVR.2018.091983)
11. Om Prakash, Jeonghwan Gwak, Manish Khare, Ashish Khare, Moongu Jeon, “Human detection in
complex real scenes based on combination of biorthogonal wavelet transform and Zernike
moments,” Optik, vol. 157, pp. 1267-1281, March 2018, Elsevier. (SCI)
(https://doi.org/10.1016/j.ijleo.2017.12.061)
12. Richa Srivastava, Om Prakash and Ashish Khare, “Local Energy based Multimodal Medical
Image Fusion in Curvelet Domain,” IET Computer Vision, vol.10, issue 6, pp. 513-527, 2016. IET
digital library.(SCI)
(https://doi.org/10.1049/iet-cvi.2015.0251)
13. Om Prakash and Ashish Khare, “Tracking of moving object using energy of Biorthogonal wavelet
transform,” Chiang Mai Journal of Science, vol.42, no.3, pp. 783-795, July 2015, Chiang Mai
University. (SCI)
(https://thaiscience.info/Journals/Article/CMJS/10972713.pdf)
14. Om Prakash and Ashish Khare, “Medical Image Denoising based on Soft thresholding using
Biorthogonal Multiscale Wavelet Transform,” International Journal of Image and Graphics, vol.
14, no. 1 & 2, pp. 1450002 (30 pages), March 2014, World Scientific. (SCI)
(https://doi.org/10.1142/S0219467814500028)
15. Alok Kumar Singh Kushwaha, Chandra Mani Sharma, Manish Khare, Om Prakash and Ashish
Khare, “Adaptive real-time motion segmentation technique based on statistical background model,”
The Imaging Science Journal, vol. 62, no.5, pp. 285-302, 2014, Royal Photographic Society.(SCI)
(https://doi.org/10.1179/1743131X13Y.0000000056)
16. Rajiv Singh, Richa Srivastava, Om Prakash and Ashish Khare, “Multimodal medical image fusion
in Dual tree complex wavelet domain using maximum and average fusion rules,” Journal of
Medical Imaging and Health Informatics, vol. 2, no. 2, pp. 168-173, June 2012, American
Scientific Publishers. (SCI)
(https://doi.org/10.1166/jmihi.2012.1080)

Publications in International Conference Proceedings

  • B. Reddy Mounika, Om Prakash, Ashish Khare, “Key Frame Extraction using Uniform Local Binary Pattern,” 2018 Second International Conference on Advances in Computing, Control and Communication Technology (IAC3T), University of Allahabad, Allahabad, 21-23 Sept 2018. IEEE
  • Abhishek Srivastava, Pronaya Bhattacharya, Arunendra Singh, Atul Mathur, Om Prakash, Rajeshkumar Pradhan, “A Distributed Credit Transfer Educational Framework based on Blockchain,” 2018 Second International Conference on Advances in Computing, Control and Communication Technology (IAC3T), University of Allahabad, Allahabad, 21-23 Sept 2018. IEEE
  • Om Prakash, Alok Kumar Singh Kushwaha, Moongu Jeon, “An approach towards Object Tracking based on Rotation Invariant Moments of Complex Wavelet Transform,” in International Conference on Advances in Computing, Control and Communication Technology (IAC3T-2016), University of Allahabad, Allahabad, 25-27 March 2016.
  • Arati Kushwaha, Ashish Khare, Om Prakash, Jong-In Song, Moongu Jeon, “3D Medical Image Fusion using the Dual Tree Complex Wavelet Transform,” in IEEE 4th International Conference on Control, Automation and Information Sciences (ICCAIS-2015), Changshu, China, 29-31 October 2015. IEEE
  • Manish Khare, Om Prakash, Rajneesh Kumar Srivastava, Ashish Khare, “Contourlet Transform based Human Object Tracking,” Proceedings of 27th SPIE Electronic Imaging, Vol. 9410 (Visual Information Processing and Communication VI), 08-12 February 2015, San Francisco, USA. SPIE
  • Om Prakash, Manish Khare, Ashish Khare, “Biorthogonal Wavelet Transform Based Classification of Human Object Using Adaboost Classifier,” Proceedings of IEEE 3rd International Conference on Control, Automation and Information Sciences (ICCAIS-2014), Gwangju Institute of Science and Technology (GIST), South Korea, pp. 194-199, 02-05 December 2014. IEEE
  • Manish Khare, Om Prakash, Rajneesh Kumar Srivastava, Ashish Khare, “Daubechies Complex Wavelet Transform Based Approach for Multiclass Object Classification,” Proceedings of IEEE 3rd International Conference on Control, Automation and Information Sciences (ICCAIS-2014), Gwangju Institute of Science and Technology (GIST), South Korea, 206-211, 02-05 December 2014. IEEE
  • Prashant Srivastava, Om Prakash, Ashish Khare, “Content-Based Image Retrieval Using Moments of Wavelet Transform,” Proceedings of IEEE 3rd International Conference on Control, Automation and Information Sciences (ICCAIS-2014), Gwangju Institute of Science and Technology (GIST), South Korea, pp. 159-164, 02-05 December 2014. IEEE
  • Om Prakash, Arvind Kumar, Ashish Khare, “Pixel-level Image Fusion Scheme based on Steerable Pyramid Wavelet Transform using absolute Maximum fusion rule,” Proceedings of IEEE International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT-2014), Ghaziabad, India, pp. 770-775, 07-08 February 2014. IEEE

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

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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📝🔬

Pavithra sekar – Deep Learning – Best Researcher Award

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Pavithra sekar -Deep Learning – Best Researcher Award

Dr. Pavithra sekar distinguished academic and researcher in the field Deep Learning.

🌐 Professional Profile

Educations📚📚📚

She holds a Bachelor of Engineering (B.E.) in Computer Science Engineering, which she completed in April 2006 with a percentage of 75.6%, earning a first-class with distinction from Vel Tech Engineering College, affiliated with Anna University. She further advanced her education by obtaining a Master of Engineering (M.Tech) in Information Technology in June 2011, achieving a percentage of 8.43 and graduating with first-class honors from Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College, also affiliated with Anna University. She completed her academic journey with a Ph.D. in Information Technology, awarded on January 24, 2020, from St. Peter’s Institute of Higher Education and Research.

PROFESSIONAL EXPERIENCE:

She possesses about 17 years of experience in the field of education, encompassing teaching, administration, and research. Currently, she holds the position of Assistant Professor Sr in the School of Computer Science and Engineering at Vellore Institute of Technology, Chennai. Her career includes roles such as Assistant Professor (Sr) in the Department of Computer Science and Engineering at VIT Chennai since December 15, 2023. Previously, she served as Assistant Professor (SG) and IPR coordinator in the Department of Information Technology from March 31, 2021, to December 7, 2022, at Rajalakshmi Engineering College. Prior to that, she was Assistant Professor & Assistant HOD in the Computer Science & Engineering Department at VelTech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College for 9.6 years, from July 6, 2011, to January 25, 2021. She began her career as a lecturer in the Department of Information Technology at VelTech MultiTech Dr. Rangarajan Dr. Sakunthala Engineering College from August 24, 2006, to September 25, 2009.

 

DEVELOPMENT ACTIVITIES

She possesses a thorough understanding of her subject area, demonstrating an exceptional ability to effectively communicate complex concepts to her students. Her strong communication and comprehension skills enhance her role in internal administrative tasks within educational institutions. She has a proven track record in coordinating various activities such as symposiums, student projects, and conferences, where she provides guidance and support to ensure successful outcomes. Her extensive experience includes roles as Class Coordinator, Conference Coordinator, Project Coordinator for contests, and organizing events like the MOTOROLA FAER EVENT. Additionally, she has served as ISO coordinator, handled NBA coordination, and participated actively in autonomous file activities. She is involved in setting question papers for autonomous colleges and universities and has excelled in roles such as Class In-Charge, Student Mentor, and AICTE CII-Survey participant. She diligently maintains semester-wise result analysis reports, prepares weekly schedules, and curates course materials for effective teaching. Her commitment to excellence is evident in achieving over 90% results across all subjects and receiving a publication award of 16,000. Notably, she achieved a perfect 100% result in key subjects like Computer Programming, Operating System, Computer Architecture, Advanced Computer Architecture, and Problem Solving And Python Programming.

📝🔬Publications📝🔬

1. S. Pavithra and K. Venkata Vikas, “Detecting Unbalanced Network Traffic Intrusions With Deep
Learning,” in IEEE Access, vol. 12, pp. 74096-74107, 2024, doi: 10.1109/ACCESS.2024.3405187.
2. . Pavithra, T. Veeramani, S. Sree Subha, J.P. Sathish Kumar, S. Shanmugan, Ammar H.
Elsheikh, F.A. Essa, “Revealing prediction of Perched Cum Off-Centered Wick Solar Still
Performance using network based on Optimizer algorithm” Process Safety and
Environmental Protection,Volume 161,2022, Pages 188-200,ISSN 0957-
5820,https://doi.org/10.1016/j.psep.2022.03.0092022, .(SCI, Scopus).)(Impact factor: 7.92).
3. Meena, M., Kavitha, A., Karthick, Pavithra.S “Effect of decorated photoanode of
https://doi.org/10.1007/s12034-022-02828-9 .(SCI, Scopus).)(Impact factor: 1.92).
4. S.Pavithra, P.M Anu “An Efficient Data Aggregation with Optimal Recharging in Wireless
Rechargeable Sensor Networks” (Submission code: IJAIP-221302) for the International
Journal of Advanced Intelligence Paradigms (IJAIP) Inderscience
DOI: 10.1504/IJAIP.2022.10040244,2022 (Scopus). Impact factor ( 0.63)
5. S.Pavithra Assistive Chatbot device to support Visually Impaired Person to access
Transport Mode Status Using Deep Learning Model ARPN Journal of Engineering and
Applied Sciences waiting for Publication 2022. (Scopus).
6. S.Pavithra, R.Karthikeyan P.M Anu “Detection and classification of 2D and 3D Hyper
Spectral Image Using Enhanced Harris Corner Detector” “Scalable Computing: Practice and
Experience, ISSN 1895-1767, Volume 21, Issue 1, pp. 93–100, DOI

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📝🔬

Asif Hamid- Deep learning – Best Researcher Award

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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

Muhammad Nawaz – Geo Artificial Intelligence Award – Best Researcher Award

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Muhammad Nawaz – Geo Artificial Intelligence Award – Best Researcher Award

Dr. Muhammad Nawaz distinguished academic and researcher in the field Geo  Artificial Intelligence. He has held various academic positions spanning nearly four decades. Beginning his career as a secondary science teacher at the Institute of Academic Service in Lahore, Pakistan, from 1986 to 1990, he then transitioned into roles within the field of geography and GIS. His journey in academia led him to serve as a Subject Specialist in Geography for the Ministry of Education, Government of Punjab, Pakistan, from 1990 to 1993. Subsequently, he embarked on a career in higher education, holding positions such as Lecturer in Geography at Punjab University from 1993 to 1999, followed by roles as Assistant Professor and later as Associate Professor in GIS, along with various administrative responsibilities including Associate Head and Coordinator of the M.Sc. GIS Program at Punjab University from 1999 to 2006. He expanded his international experience by serving as a Lecturer in Environmental Science eLearning at the School of Environment, Charles Darwin University (CDU), Australia, from 2007 to 2012, and then as a Lecturer/Coordinator of the Tertiary Enabling Program (Environment & Geoscience) at CDU from 2012 to 2015. Since 2015, he has been contributing his expertise as a Senior Lecturer in the Department of Geography at the National University of Singapore. Throughout his career, he has demonstrated a commitment to education and has made significant contributions to the fields of geography, environmental science, and geoscience education.

🌐 Professional Profiles

Educations📚📚📚

He holds a diverse range of qualifications reflecting his dedication to academic excellence and professional development. His educational journey began with a Bachelor’s degree in Geography, with majors in Geology and Chemistry, from Bahauddin Zakariya University, Pakistan, in 1986. Building upon this foundation, he pursued a Master’s degree in Geography from Punjab University, Pakistan, in 1990. Continuing his academic pursuits, he obtained a Master of Science in Geoinformatics from the University of Twente – ITC, Netherlands, in 1998, further specializing in the field. In 2010, he achieved a significant milestone by earning his Doctor of Philosophy in Environmental Science from Charles Darwin University (CDU), Australia, showcasing his commitment to advanced research and scholarship. Recognizing the importance of pedagogical skills in higher education, he completed a Graduate Certificate in Teaching and Learning in Higher Education from CDU in 2012. This extensive educational background underscores his expertise and dedication to his field, enabling him to make significant contributions to academia and research throughout his career.

Teaching Experience

With an extensive background in teaching, he has been actively engaged in educating students in various facets of geography and environmental science since 2015 at the Department of Geography, National University of Singapore. His teaching portfolio encompasses a wide array of courses catering to different aspects of spatial data handling, GIS applications, environmental modeling, earth surface processes, energy futures, and terrestrial and coastal environments.

In courses such as Spatial Data Handling (GE6211), GIS Application (GE5226), and Environment Modelling (GE4212), he imparts knowledge on topics ranging from spatial data mining, big data analytics, and spatial uncertainty to ecological models, epidemic dynamics, and environmental modeling with GIS and remote sensing.

Moreover, his expertise extends to courses like Earth Surface Processes, Landform, and Ecosystem (GE3256), Energy Futures, Environment, and Sustainability (GE3254), and Planet Earth (XD3103), where he delves into subjects such as geomorphological processes, climate change, global energy resources, and the geological evolution of Earth.

Additionally, he plays a pivotal role in educating students on water and environmental issues in courses like Water and Environment (GE2229) and Terrestrial and Coastal Environments (GE2220), covering topics such as catchment hydrology, fluvial geomorphology, coastal processes, and landforms.

Furthermore, he contributes to courses like The Biophysical Environment of Singapore (GES1004/GESS1002), providing insights into Singapore’s geology, weather, climate, soil erosion, and coastal processes, tailored to the local context.

Through his teaching endeavors, he enriches students’ understanding of geographical and environmental concepts, equipping them with the knowledge and skills necessary to address contemporary challenges in these fields.

Recent Teaching, Research and Service Awards

He has been consistently recognized for his outstanding contributions in teaching, research, and service within the academic community. In 2023, he received the Annual Digital Education Award (ADEA 2023) from the National University of Singapore, acknowledging his innovative approaches to digital education. Additionally, he was honored with the NUS Safety & Health Commitment Award (NUSSHA 2023) by the Office of Risk and Management Compliance (ORMC) for his dedication to ensuring safety and health standards in academic environments.

In 2022, his commitment to teaching excellence was recognized with the Faculty Teaching Excellence Award (FTEA 2022) from the Faculty of Arts and Social Science at the National University of Singapore. Furthermore, his research efforts were acknowledged with the Encouragement (Research) Award (PUPP 2022) from the Wuhan Municipal Bureau of Natural Resources & Planning, China, highlighting his significant contributions to the field.

Moreover, in 2021, he was honored with the Service Award and Certificate of Accomplishment (COA 2021) from the Office of Human Resources at the National University of Singapore, underscoring his exemplary service to the university community.

These awards reflect his dedication, expertise, and impact across various domains of academia, demonstrating his commitment to excellence in teaching, research, and service roles.

📝🔬Publications📝🔬

Jorge Laureano Moya Rodríguez – Neural Networks – Best Researcher Award

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Jorge Laureano Moya Rodríguez – Neural Networks

 Prof Dr.  Jorge Laureano Moya Rodríguez distinguished academic and researcher in the field Neural Network.  Jorge Laureano Moya Rodríguez is a Professor Emeritus at the Central University “Marta Abreu” de las Villas. Cuba. He received his Ph.D. in Mechanical Engineering at this university in 1994. He published over a three hundred papers in professional journals and he has authored several books in mechanical and electrical engineering. He has several international and national awards, including some from the Academy of Sciences of Cuba. He has lectured in different Universities of Spain, México, Nicaragua and Brazil. He is currently visiting professor at the Federal University of Bahia in Brazil. Dr. Moya’s research interests are Multiobjective Optimization, Logistics, Computer Aided Design, and Computer Aided Engineering.

Ele é também membro da ERASMUS MUNDUS ASSOCIATION (EMA) e da Associação Mexicana de Modelagem Numérica e Engenharia (AMMNI). Reconhecido como bolsista de produtividade em Pesquisa pelo CNPq (nível 2) e consultor ad hoc do CNPq, ele contribui como árbitro para diversas revistas científicas e instituições acadêmicas em países como Venezuela, Colômbia, Peru e Cuba. Com uma ampla lista de mais de 50 projetos de pesquisa concluídos e implementados em Cuba, ele é considerado Professor de Mérito pela Universidade Central Marta Abreu de Las Villas. Sua atuação como professor abrange cursos de pós-graduação e disciplinas de mestrado em várias universidades, incluindo a Universidade Federal do Espírito Santo (Brasil), Universidade Veracruzana (México), Universidade Técnica do Estado de Aragua (Venezuela) e Universidade Nacional de Engenharia (Nicarágua). Ele também coordenou o Mestrado em Engenharia Mecatrônica em várias universidades na Venezuela e trabalhou como professor convidado em diversas instituições no México, Peru e Espanha. Anteriormente, ele foi pesquisador do ITEGAM, professor visitante na Universidade Federal do Espírito Santo e na Universidade Federal da Bahia.

 

🌐 Professional Profiles

Educations: 📚🎓

Jorge Laureano Moya Rodríguez, known in bibliographic citations as J. L. M. Rodríguez, J. L. Moya, Jorge Moya, Jorge Laureano Moya Rodríguez, J. Moya, Jorge Rodríguez, Jorge L. Moya Rodríguez, or variations thereof, is affiliated with the University Federal da Bahia, where he works within the Program of Industrial Engineering Postgraduate Studies.

He completed a postdoctoral position in 2011 at the Universidad de Oviedo, UNIOVI, Spain, funded by the Agencia Española de Colaboración Internacional, AECI, Spain. The research was in the field of Engineering.

In 2008, he undertook a postdoctoral fellowship at the Universidad de Oviedo, UNIOVI, Spain, funded by ERASMUS MUNDUS, EM, Germany. The research focus was in Engineering.

In 2005, he conducted postdoctoral research at the Universidad Católica de Leuven, KLU, Belgium, supported by VLIR, VLIR, Belgium. The research was within the field of Engineering.

Publication

 

Tumlumbe Juliana Chengula – Computer Vision -Best Researcher Award

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Tumlumbe Juliana Chengula  – Computer Vision

Tumlumbe Juliana Chengula  a distinguished academic and researcher in the field of Computer Vision. He possesses proficiency in several programming languages, with a focus on Python. His expertise extends to utilizing various tools such as Tableau, QGIS, PyTorch, and Tensorflow, showcasing a well-rounded skill set in data science and machine learning. Additionally, he has earned certifications in Data Science Tools, SQL for Data Science, and Machine Learning with Python, all from IBM. Furthermore, he has completed the “Using Python for Research” certification from Harvard University, underscoring his commitment to continuous learning and staying at the forefront of relevant technologies in the field. These skills and honors collectively highlight his comprehensive knowledge and dedication to the dynamic and evolving realm of data science.

Eduvation

His master’s studies at Amirkabir University of Technology (AUT) in Tehran, Iran, from September 2018 to October 2021, he specialized in Electrical Engineering with a focus on Control. During this period, he maintained a GPA of 3.5/4, and his final project earned a perfect score of 4/4. Prior to his master’s degree, he completed his Bachelor’s in Power Electrical Engineering at Yazd University, Iran, from September 2014 to August 2018, achieving a GPA of 3.1/4.

Professional Profiles:

Employment Experience
As a Graduate Research Assistant at South Carolina State University since August 2022, she has been actively engaged in the collection, recording, and analysis of transportation data, utilizing proficient tools such as Python, Tableau, PowerBI, and QGIS. Her research focus involves the application of cutting-edge technologies, including Machine Learning, Deep Learning, and Artificial Intelligence, to address challenges within the transportation industry.
Over the course of her tenure, she has showcased her contributions by delivering six impactful presentations on her research in Machine Learning and Artificial Intelligence at seven distinguished transportation conferences. Furthermore, her commitment to scholarly dissemination is evident through the submission and acceptance of two peer-reviewed articles, which are slated for presentation at the prestigious 2024 Annual Transportation Research Board conference. These accomplishments underscore her dedication to advancing knowledge and providing innovative solutions to enhance the efficiency and effectiveness of the transportation sector.
Research Project Highlights
She has made notable contributions to the field of transportation through her research endeavors, addressing critical issues with cutting-edge technologies. One of her significant projects involves enhancing road safety through Ensemble Learning, specifically in detecting driver anomalies using vehicle inbuilt cameras. In another study, she employed Topic Modeling and Categorical Correlations to unveil patterns associated with autonomous vehicle disengagements, shedding light on crucial aspects of autonomous driving systems.
Furthermore, she delved into the realm of quantum computing to improve classification performance in traffic sign recognition, utilizing an optimized hybrid classical-quantum approach. Additionally, her research extends to the realm of sustainable urban mobility, where she has applied Explainable Artificial Intelligence to predict bike-sharing station capacity. These diverse projects showcase her proficiency in utilizing advanced technologies and methodologies to address multifaceted challenges within the transportation sector.
Publication

Improving road safety with ensemble learning: Detecting driver anomalies using vehicle inbuilt cameras

Machine Learning with Applications
2023-12 | Journal article
DOI: 10.1016/j.mlwa.2023.100510
CONTRIBUTORS: Tumlumbe Juliana Chengula; Judith Mwakalonge; Gurcan Comert; Saidi Siuhi