Venkataraman Thangadurai | 3D Computer Vision | Best Researcher Award

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Prof. Dr. Venkataraman Thangadurai | 3D Computer Vision | Best Researcher Award

Professor | University of St Andrews | United Kingdom

Prof. Dr. Venkataraman Thangadurai is a globally renowned expert in solid-state chemistry, electrochemical energy storage, and advanced battery technologies. With a research focus on fast ion conductors, solid electrolytes, lithium- and sodium-based batteries, and fuel cell materials, he has made pioneering contributions to both fundamental science and practical energy solutions. Prof. Thangadurai has authored over 278 peer-reviewed journal articles, 6 book chapters, and 21 conference proceedings, and has delivered 180 conference presentations, 83 posters, and 80 invited talks at top universities, institutes, and companies worldwide. His work has resulted in 13 patents/patent applications and has placed him among the top 1% of authors in Royal Society of Chemistry journals by citations in 2020. As of March 2025, his research has received 25,991 citations with an h-index of 69, reflecting the high impact of his work globally.He is the Founder and Advisor of Ions Storage Systems, Maryland, USA (2012–present) and Founder and Director of Superionics, Calgary, Canada (2021–present), translating cutting-edge research into commercial energy storage technologies. His research highlights include optimizing lithium nucleation overpotentials in garnet-based hybrid solid-state batteries, developing doped sodium gadolinium silicate ceramics for fast Na⁺ conduction, and enhancing electrocatalysts for lithium–sulfur batteries.Prof. Thangadurai collaborates extensively with leading international researchers and institutions, including the University of Calgary, University of Maryland, University of St Andrews, University of Kiel, Yale University, and ANSTO, advancing cross-disciplinary solutions in energy materials. Beyond his scientific contributions, he mentors emerging scientists and actively promotes innovation that addresses global energy challenges. His work has significant societal impact, enabling safer, high-performance, and sustainable energy storage solutions critical for electric mobility, grid storage, and renewable energy integration.

Profiles: Google Scholar | ORCID | Scopus

Featured Publications

1. Murugan, R., Thangadurai, V., & Weppner, W. (2007). Fast lithium ion conduction in garnet-type Li₇La₃Zr₂O₁₂. Angewandte Chemie International Edition, 46(41), 7778–7781.
Cited By : 3691

2.Han, X., Gong, Y., Fu, K., He, X., Hitz, G. T., Dai, J., Pearse, A., Liu, B., Wang, H., … Thangadurai, V. (2017). Negating interfacial impedance in garnet-based solid-state Li metal batteries. Nature Materials, 16(5), 572–579. Cited By : 2088

3.Thangadurai, V., Narayanan, S., & Pinzaru, D. (2014). Garnet-type solid-state fast Li ion conductors for Li batteries: Critical review. Chemical Society Reviews, 43(13), 4714–4727. Cited By : 1712

4.Pal, B., Yang, S., Ramesh, S., Thangadurai, V., & Jose, R. (2019). Electrolyte selection for supercapacitive devices: A critical review. Nanoscale Advances, 1(10), 3807–3835.
Cited By : 1229

5.Wang, C., Fu, K., Kammampata, S. P., McOwen, D. W., Samson, A. J., Zhang, L., … Thangadurai, V. (2020). Garnet-type solid-state electrolytes: Materials, interfaces, and batteries. Chemical Reviews, 120(10), 4257–4300. Cited By : 1130

Prof. Dr. Venkataraman Thangadurai  pioneering research in solid-state chemistry and advanced battery technologies drives global innovation in energy storage, enabling safer, high-performance, and sustainable batteries that power electric mobility, renewable energy integration, and next-generation clean technologies.

Fatma Zahra Sayadi | Deep Learning | Best Innovation Award

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Prof. Fatma Zahra Sayadi | Deep Learning | Best Innovation Award

Associate Professor | University of Sousse | Tunisia

Fatma Elzahra Sayadi is a highly accomplished researcher and academic specializing in electronics and microelectronics, with current research focused on video surveillance systems, real-time processing, and signal compression. She earned her PhD in electronics for real-time systems from the University of Bretagne Sud in collaboration with the University of Monastir and has also completed her engineering and master’s studies in electrical and electronic systems. She has extensive professional experience as a maître de conférences and previously as a maître assistante and assistant technologist, teaching courses in microprocessors, multiprocessors, programming, circuit testing, and industrial electronics. Her research interests include signal processing, parallel architectures, microelectronics, real-time systems, and communication networks. She has actively participated in national and international research projects and collaborations with institutions in France, Italy, Germany, and Morocco. Her work has been published in over 37 journal articles, 40 conference papers, and six book chapters, and she has supervised several doctoral and master’s theses. She has been recognized with awards such as the first prize at the Women in Research Forum at the University of Sharjah and contributes to professional communities as a reviewer, evaluator, and organizer of academic events. She is skilled in research methodologies, signal and data analysis, electronic system design, and digital education innovation. Her academic contributions have been cited by 395 documents, with 69 documents contributing to her citations, and she has an h-index of 13.

Profile: Google Scholar | Scopus | ORCID 

Featured Publications

  1. Basly, H., Ouarda, W., Sayadi, F. E., Ouni, B., & Alimi, A. M. (2020). CNN-SVM learning approach based human activity recognition. In International Conference on Image and Signal Processing (pp. 271–281). 77 citations.

  2. Bouaafia, S., Khemiri, R., Sayadi, F. E., & Atri, M. (2020). Fast CU partition-based machine learning approach for reducing HEVC complexity. Journal of Real-Time Image Processing, 17(1), 185–196. 53 citations.

  3. Haggui, O., Tadonki, C., Lacassagne, L., Sayadi, F., & Ouni, B. (2018). Harris corner detection on a NUMA manycore. Future Generation Computer Systems, 88, 442–452. 48 citations.

  4. Basly, H., Ouarda, W., Sayadi, F. E., Ouni, B., & Alimi, A. M. (2022). DTR-HAR: Deep temporal residual representation for human activity recognition. The Visual Computer, 38(3), 993–1013. 40 citations.

  5. Bouaafia, S., Khemiri, R., Messaoud, S., Ben Ahmed, O., & Sayadi, F. E. (2022). Deep learning-based video quality enhancement for the new versatile video coding. Neural Computing and Applications, 34(17), 14135–14149. 35 citations.

Puja Gupta | Computer Vision | Excellence in Research

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Dr. Puja Gupta | Computer Vision | Excellence in Research

Asst Professor at Shri G.S. Institute of Technology & Science | India

Dr. Puja Gupta is a dedicated researcher and academic with expertise in artificial intelligence, machine learning, IoT, and smart computing technologies. She has contributed significantly to the field through her high-quality publications in reputed journals, patents, and innovative product development. Her work has addressed real-world challenges in healthcare, security, and sustainable technologies, bridging the gap between research and practical applications. With a strong academic foundation, she has successfully guided students in research and projects, fostering innovation and academic growth. She has been actively involved in international collaborations, research projects, and academic leadership roles, contributing to the advancement of her field. She is also a committed member of professional organizations, demonstrating her engagement in the broader research community. Her impactful contributions, leadership potential, and dedication to continuous professional development make her a valuable asset to both academia and society.

Professional Profile 

Google Scholar | Scopus Profile | ORCID Profile 

Education

Dr. Puja Gupta holds a strong academic background in computer science and engineering, culminating in a doctoral degree specializing in artificial intelligence and smart systems. Her Ph.D. research focused on the integration of machine learning techniques and IoT frameworks to design intelligent solutions that address complex societal problems. Prior to her doctoral studies, she earned her master’s and bachelor’s degrees in computer science, gaining a solid foundation in algorithms, data structures, and system design. Throughout her academic journey, she demonstrated exceptional commitment to learning, consistently achieving top ranks and recognition for her research contributions. Her advanced education has equipped her with in-depth knowledge of computational intelligence, optimization techniques, and applied research methodologies, enabling her to contribute effectively to both theoretical advancements and practical applications in the field. Her academic background continues to support her innovative research and teaching excellence in the areas of AI, IoT, and emerging technologies.

Professional Experience

Dr. Puja Gupta has extensive professional experience in both academic and research domains, with a focus on artificial intelligence, IoT, and smart computing solutions. She has worked as a faculty member at prestigious institutions, where she has taught and mentored students at undergraduate and postgraduate levels, guiding them in research projects and fostering innovation. Alongside teaching, she has been actively involved in funded research projects, many of which involved international collaborations and multidisciplinary teams. She has successfully published her findings in reputed journals and conferences indexed in IEEE and Scopus, and her work has also resulted in patents and prototypes with practical applications. Beyond academia, she has contributed to the research community by serving as a reviewer, participating in editorial activities, and organizing academic events. Her leadership roles in academic programs and community-driven initiatives further highlight her commitment to advancing knowledge and supporting the development of future researchers.

Research Interest

Dr. Puja Gupta’s research interests revolve around artificial intelligence, machine learning, IoT, big data analytics, and smart system design. She is particularly focused on developing intelligent solutions that address pressing societal challenges in areas such as healthcare, security, and sustainability. Her work often integrates computational intelligence with real-world applications, such as predictive healthcare models, smart monitoring systems, and secure communication frameworks for IoT devices. She is also keen on advancing research in explainable AI and optimization algorithms to ensure reliability and transparency in machine learning systems. Another area of interest is the development of resource-efficient AI models for deployment in edge and cloud environments. Her multidisciplinary approach allows her to collaborate across domains, leveraging data-driven techniques to innovate practical solutions. By combining theoretical knowledge with applied research, she aims to contribute to technological advancements that enhance the quality of life and create sustainable, impactful outcomes for society.

Award and Honor

Dr. Puja Gupta has been recognized with numerous awards and honors that highlight her academic excellence, research contributions, and leadership in the field of computer science and engineering. Her achievements include recognition for publishing impactful research in reputed journals, presenting at leading international conferences, and securing patents that demonstrate the practical value of her work. She has also been honored for her contributions to student mentoring and academic program development, reflecting her dedication to nurturing young talent. Several of her awards acknowledge her innovative approaches in AI and IoT research, particularly for developing solutions with direct societal impact. In addition, she has received appreciation for her involvement in community-driven initiatives and leadership in professional organizations. These honors not only recognize her past accomplishments but also serve as a testament to her commitment, perseverance, and ability to inspire others in the academic and research communities.

Research Skill

Dr. Puja Gupta possesses advanced research skills in artificial intelligence, machine learning, IoT systems, and computational modeling, enabling her to conduct impactful and interdisciplinary research. She is proficient in applying data analysis techniques, optimization algorithms, and predictive modeling to design intelligent solutions for real-world applications. Her expertise includes working with various programming languages, simulation tools, and research frameworks that support scalable and innovative problem-solving. She has developed strong skills in experimental design, result validation, and research dissemination through high-quality publications and conference presentations. Beyond technical expertise, she excels in collaborative research, often working with international teams and multidisciplinary groups to drive innovation. She is also skilled in project management, proposal writing, and securing research funding, which have been instrumental in the successful execution of her projects. Her research skills, combined with her commitment to continuous learning, position her as a versatile and resourceful academic and researcher in her field.

Publications Top Notes

Title: Impact of knowledge management practices on innovative capacity: A study of telecommunication sector
Authors: J Jyoti, P Gupta, S Kotwal
Year: 2011
Citation: 56

Title: A Novel Algorithm for Mask Detection and Recognizing Actions of Human
Authors: P Gupta, V Sharma, S Varma
Year: 2022
Citation: 48

Title: Transcriptional mechanisms underlying sensitization of peripheral sensory neurons by granulocyte-/granulocyte-macrophage colony stimulating factors
Authors: KK Bali, V Venkataramani, VP Satagopam, P Gupta, R Schneider, …
Year: 2013
Citation: 42

Title: Minimally invasive plate osteosynthesis (MIPO) for proximal and distal fractures of the tibia: a biological approach
Authors: P Gupta, A Tiwari, A Thora, JK Gandhi, VP Jog
Year: 2016
Citation: 41

Title: SUMOylation of enzymes and ion channels in sensory neurons protects against metabolic dysfunction, neuropathy, and sensory loss in diabetes
Authors: N Agarwal, FJ Taberner, DR Rojas, M Moroni, D Omberbasic, C Njoo, …
Year: 2020
Citation: 39

Title: An introduction of soft computing approach over hard computing
Authors: P Gupta, N Kulkarni
Year: 2013
Citation: 31

Title: People detection and counting using YOLOv3 and SSD models
Authors: P Gupta, V Sharma, S Varma
Year: 2021
Citation: 30

Title: Challenges in the adaptation of IoT technology
Authors: Neha, P Gupta, MA Alam
Year: 2021
Citation: 20

Title: Role of fine needle aspiration cytology in preoperative diagnosis of ameloblastoma
Authors: S Bisht, SA Kotwal, P Gupta, R Dawar
Year: 2009
Citation: 13

Title: Let the Blind See: An AIIoT based device for real-time object recognition with the voice conversion
Authors: P Gupta, M Shukla, N Arya, U Singh, K Mishra
Year: 2022
Citation: 9

Title: The impact of artificial intelligence on renewable energy systems
Authors: P Gupta, S Kumar, YB Singh, P Singh, SK Sharma, NK Rathore
Year: 2022
Citation: 8

Title: Simultaneous feature selection and clustering of micro-array and RNA-sequence gene expression data using multiobjective optimization
Authors: AK Alok, P Gupta, S Saha, V Sharma
Year: 2020
Citation: 8

Title: Activity detection and counting people using mask-RCNN with bidirectional ConvLSTM
Authors: P Gupta, U Singh, M Shukla
Year: 2022
Citation: 7

Title: Study of cloud providers (azure, amazon, and oracle) according to service availability and price
Authors: A Rajput, P Gupta, P Ghodeshwar, S Varma, KK Sharma, U Singh
Year: 2023
Citation: 6

Title: Machine learning approaches for IoT-data classification
Authors: O Farooq, P Gupta
Year: 2020
Citation: 5

Title: Evaluation of AI system’s voice recognition performance in social conversation
Authors: SK Barnwal, P Gupta
Year: 2022
Citation: 4

Title: Analysis of CNN Model with Traditional Approach and Cloud AI based Approach
Authors: U Kushwaha, P Gupta, S Airen, M Kuliha
Year: 2022
Citation: 4

Title: Analysis of crowd features based on deep learning
Authors: P Gupta, V Sharma, S Varma
Year: 2022
Citation: 4

Title: Acknowledgment of patient in sense behaviors using bidirectional ConvLSTM
Authors: U Singh, P Gupta, M Shukla, V Sharma, S Varma, SK Sharma
Year: 2023
Citation: 3

Title: Study on the NB-IoT based smart medical system
Authors: P Gupta, AK Pandey
Year: 2023
Citation: 3

Conclusion

Dr. Puja Gupta is highly deserving of the Best Researcher Award for her significant contributions to advancing research in artificial intelligence, IoT, and smart technologies, as well as her role in mentoring students and fostering innovation. Her impactful work, including patents, high-quality publications, and practical product development, has addressed societal challenges in healthcare, security, and sustainability. With her strong academic background, leadership in academic and community initiatives, and commitment to continuous growth, she holds great potential to further excel in future research, expand global collaborations, and take on greater leadership roles in the academic and research community.

Dibyalekha Nayak | Computer vision | Women Researcher Award

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Dr . Dibyalekha Nayak | Computer vision | Women Researcher Award

Assistant professor at Shah and Anchor Kutchhi Engineering College, India

Dr. Dibyalekha Nayak is a dedicated academician and emerging researcher with deep expertise in image processing, adaptive compression, and VLSI design. Her professional journey is marked by a strong commitment to teaching, scholarly research, and technological advancement. With over a decade of teaching experience and a recently completed Ph.D. from KIIT University, Bhubaneswar, her research has produced several publications in SCI-indexed journals and international conferences. Dr. Nayak’s contributions reflect an interdisciplinary approach, combining deep learning techniques with low-power hardware design to address complex challenges in wireless sensor networks and multimedia systems. She has actively participated in faculty development programs and technical workshops, continuously upgrading her knowledge. Her professional philosophy emphasizes ethics, hard work, and continuous learning. Currently serving as an Assistant Professor at Shah and Anchor Kutchi Engineering College in Mumbai, she aspires to make impactful contributions to the field of electronics and communication through research, innovation, and collaboration.

Professional Profile 

Education🎓

Dr. Dibyalekha Nayak holds a Ph.D. in Image Processing from the School of Electronics at KIIT University, Bhubaneswar, where she completed her research between September 2018 and May 2024. Her doctoral work focused on advanced techniques in image compression and saliency detection using deep learning and compressive sensing. She completed her Master of Technology (M.Tech) in VLSI Design from Satyabhama University, Chennai, in 2011, graduating with a commendable CGPA of 8.33. Prior to that, she earned her Bachelor of Engineering (B.E.) in Electronics and Telecommunication from Biju Patnaik University of Technology (BPUT), Odisha, in 2008, with a CGPA of 6.5. Her academic background provides a strong foundation in both theoretical electronics and practical applications in image processing and circuit design. The combination of image processing and VLSI design throughout her academic journey has enabled her to engage in cross-disciplinary research and foster innovation in both hardware and software domains.

Professional Experience📝

Dr. Dibyalekha Nayak has accumulated over 12 years of rich academic experience in various reputed engineering institutions across India. Currently, she serves as an Assistant Professor at Shah and Anchor Kutchi Engineering College, Mumbai, affiliated with Mumbai University, where she joined in July 2024. Prior to this, she worked as a Research Scholar at KIIT University (2018–2024), contributing significantly to image processing research. Her earlier roles include Assistant Professor positions at institutions such as College of Engineering Bhubaneswar (2016–2018), SIES Graduate School of Technology, Mumbai (2014), St. Francis Institute of Technology, Mumbai (2013), and Madha Engineering College, Chennai (2011–2012). Across these roles, she has taught a variety of undergraduate and postgraduate courses, supervised student projects, and contributed to departmental development. Her teaching areas span digital electronics, VLSI design, image processing, and communication systems, demonstrating a strong alignment between her teaching and research activities.

Research Interest🔎

Dr. Dibyalekha Nayak’s research interests lie at the intersection of image processing, deep learning, and VLSI design, with a special focus on adaptive compression, saliency detection, and compressive sensing. Her doctoral research addressed the development of innovative, low-complexity algorithms for image compression using techniques like block truncation coding and DCT, tailored for wireless sensor network applications. She is also deeply interested in integrating deep learning frameworks into image enhancement and compression tasks to improve performance in real-world environments. Additionally, her background in VLSI design supports her interest in low-power hardware architectures for efficient implementation of image processing algorithms. Dr. Nayak is particularly motivated by research problems that bridge the gap between theoretical innovation and practical implementation, especially in the fields of embedded systems and multimedia communication. Her interdisciplinary research aims to create scalable, energy-efficient, and intelligent solutions for future communication and sensing technologies.

Award and Honor🏆

While Dr. Dibyalekha Nayak’s profile does not explicitly mention formal awards or honors, her scholarly achievements speak volumes about her academic excellence and dedication. She has published multiple research articles in prestigious SCI and Web of Science indexed journals such as Multimedia Tools and Applications, Mathematics, and Computers, reflecting the quality and impact of her research. She has been actively involved in reputed international conferences including IEEE and Springer Lecture Notes, where she has presented and published her research findings. Her work on saliency-based image compression and fuzzy rule-based adaptive block compressive sensing has received commendation for its innovation and applicability. Furthermore, her selection and sustained work as a Research Scholar at KIIT University for over five years highlights the recognition she has earned within academic circles. Her consistent participation in technical workshops, faculty development programs, and collaborations also demonstrate her growing reputation and standing in the field of electronics and image processing.

Research Skill🔬

Dr. Dibyalekha Nayak possesses a versatile and robust set of research skills aligned with modern-day challenges in image processing and electronics. She is proficient in developing image compression algorithms, saliency detection models, and adaptive techniques using block truncation coding, fuzzy logic, and DCT-based quantization. Her technical expertise extends to deep learning architectures tailored for image enhancement and compressive sensing in wireless sensor networks. Additionally, she has a strong command of VLSI design methodologies, enabling her to work on low-power circuit design and hardware implementation strategies. Dr. Nayak is also skilled in scientific programming, using tools such as MATLAB and Python, along with LaTeX for research documentation. She has a clear understanding of research methodologies, simulation frameworks, and performance analysis metrics. Her experience in preparing manuscripts for SCI-indexed journals and conference presentations showcases her technical writing abilities. Overall, her analytical mindset and hands-on skills make her a competent and impactful researcher.

Conclusion💡

Dr. Dibyalekha Nayak is a highly dedicated and emerging researcher in the fields of Image Processing, Deep Learning, and VLSI. Her academic journey reflects perseverance, scholarly depth, and a clear focus on impactful research. Her SCI-indexed publications, teaching experience, and cross-domain knowledge make her a deserving candidate for the Best Researcher Award.

Publications Top Noted✍

  • Title: Fuzzy Rule Based Adaptive Block Compressive Sensing for WSN Application
    Authors: D. Nayak, K. Ray, T. Kar, S.N. Mohanty
    Journal: Mathematics, Volume 11, Issue 7, Article 1660
    Year: 2023
    Citations: 6

  • Title: A novel saliency based image compression algorithm using low complexity block truncation coding
    Authors: D. Nayak, K.B. Ray, T. Kar, C. Kwan
    Journal: Multimedia Tools and Applications, Volume 82, Issue 30, Pages 47367–47385
    Year: 2023
    Citations: 4

  • Title: Walsh–Hadamard Kernel Feature-Based Image Compression Using DCT with Bi-Level Quantization
    Authors: D. Nayak, K. Ray, T. Kar, C. Kwan
    Journal: Computers, Volume 11, Issue 7, Article 110
    Year: 2022
    Citations: 3

  • Title: Sparsity based Adaptive BCS color image compression for IoT and WSN Application
    Authors: D. Nayak, T. Kar, K. Ray
    Journal: Signal, Image and Video Processing, Volume 19, Issue 8, Pages 1–7
    Year: 2025

  • Title: Hybrid Image Compression Using DCT and Autoencoder
    Authors: D. Nayak, T. Kar, K. Ray, J.V.R. Ravindra, S.N. Mohanty
    Conference: 2024 IEEE Pune Section International Conference (PuneCon), Pages 1–6
    Year: 2024

  • Title: Performance Comparison of Different CS based Reconstruction Methods for WSN Application
    Authors: D. Nayak, K.B. Ray, T. Kar
    Conference: 2021 IEEE 2nd International Conference on Applied Electromagnetics, Signal Processing, & Communication (AESPC)
    Year: 2021

  • Title: A Comparative Analysis of BTC Variants
    Authors: D. Nayak, K.B. Ray, T. Kar
    Conference: Proceedings of International Conference on Communication, Circuits, and Systems (LNEE, Springer)
    Year: 2021

  • Title: Low Power Error Detector Design by using Low Power Flip Flops Logic
    Authors: D. Chaini, P. Malgi, S. Lopes
    Journal: International Journal of Computer Applications, ISSN 0975-8887
    Year: 2014

Prof Dr. Amar Hassan Khamis | Machine Learning for Computer Vision | Best Researcher Award

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Prof Dr. Amar Hassan Khamis | Machine Learning for Computer Vision | Best Researcher Award

Prof Dr. Amar Hassan Khamis | Mohammed Bin Rashid University of Medicine and Health Sciences | United Arab Emirates

Dr. Amar Hassan Khamis holds a Ph.D. in Biostatistics & Genetic Epidemiology (2003) from the University of Méditerranée AIX Marseille and the University of Gazira under a sandwich program. He also earned a DEA in Biostatistics from the University of Paris XI (1994) and a certificate in Medical and Biological Studies with a focus on epidemiology and biostatistics (1991).

Professional Profiles

Google Scholar

Scopus

Orcid

🎓Academic  Qualifications 

Dr. Khamis boasts a robust academic background, having completed a PhD in Biostatistics & Genetic Epidemiology through a sandwich program between University of Méditerranée AIX Marseille, France, and University of Gazira, Sudan in 2003. His other qualifications include a DEA in Biostatistics from the University Paris XI, France, and a Certificate in Medical and Biological Studies with a focus on Epidemiology and Biostatistics. Additionally, he holds a B.Sc. in Statistics & Computer Science from the University of Khartoum, Sudan.

🏢Professional Career Highlights  

Dr. Amar Hassan Khamis is a distinguished Professor of Biostatistics, currently serving at the Hamdan Bin Mohammed College of Dental Medicine, part of the Mohammed Bin Rashid University of Medicine and Health Sciences (MBRU) in Dubai since January 17, 2018. Renowned for his expertise, he has also contributed as an Adjunct Professor at Ajman University, teaching Biostatistics and Research Methods for postgraduate dentistry programs. Over his extensive career, Dr. Khamis has held key academic roles at esteemed institutions like the University of Dammam, KSA, University of Khartoum, Sudan, and the Ahfad University for Women, Sudan, demonstrating unwavering commitment to the field of Biostatistics and health sciences.

📚🧑‍🏫Teaching and Mentorship 

Dr. Khamis has a prolific teaching portfolio, having taught a variety of courses across undergraduate and postgraduate levels, including Mathematics, Biostatistics, Research Methodology, Clinical Trials, and Epidemiology. His professional workshops on Meta-Analysis, Advanced Biostatistics, and Respondent Driven Sampling are highly acclaimed. Moreover, he has supervised numerous higher diploma, MSc, and PhD theses, playing a pivotal role in advancing biostatistical research and application.

🌐🤝Global Collaboration and Leadership 

Dr. Khamis has played significant roles in global health initiatives, including consulting for WHO EMRO and conducting missions across the Eastern Mediterranean region. As a member of the Board of Research Committee of ALBASAR International Foundation and other international scientific associations, he has facilitated cross-border collaborations. His contributions to achieving the Millennium Development Goals (MDGs) in Africa highlight his dedication to improving public health outcomes.

🛠️💻Training and Skill Development 

An expert in statistical computing, Dr. Khamis is proficient in tools like SPSS, Stata, R-language, and Comprehensive Meta-Analysis (CMA). He has attended several advanced training programs worldwide, including courses on Meta-Analysis, Health Management, and Population Surveys at renowned institutions such as Johns Hopkins Bloomberg School of Public Health and Oxford University.

🏅🌟Recognition and Honors 

Dr. Khamis has been acknowledged as a pioneer in biostatistics, playing a transformative role in his academic and professional engagements. He has served as an external examiner for universities across Africa and the Middle East and as a member of research ethics committees in Sudan, Saudi Arabia, and the UAE.

Publications Top Noted 📝

Three-dimensional computed tomography analysis of airway volume in growing class II patients treated with Frankel II appliance

Authors: Ahmed, M.J.; Diar-Bakirly, S.; Deirs, N.; Hassan, A.; Ghoneima, A.

Journal: Head and Face Medicine

Year: 2024

Comparative Assessment of Pharyngeal Airway Dimensions in Skeletal Class I, II, and III Emirati Subjects: A Cone Beam Computed Tomography Study

Authors: AlAskar, S.; Jamal, M.; Khamis, A.H.; Ghoneima, A.

Journal: Dentistry Journal

Year: 2024

High-fidelity simulation versus case-based tutorial sessions for teaching pharmacology: Convergent mixed methods research investigating undergraduate medical students’ performance and perception

Authors: Kaddoura, R.; Faraji, H.; Otaki, F.; Khamis, A.H.; Jan, R.K.

Journal: PLoS ONE

Year: 2024

Enamel demineralization around orthodontic brackets bonded with new bioactive composite (in-vitro study)

Authors: Ali, N.A.M.; Nissan, L.M.K.; Al-Taai, N.; Khamis, A.H.

Journal: Journal of Baghdad College of Dentistry

Year: 2024

Do Hall Technique Crowns Affect Intra-arch Dimensions? A Split-mouth Quasi-experimental Non-randomized Feasibility Pilot Study

Authors: Alramzi, B.; Alhalabi, M.; Kowash, M.; Ghoneima, A.; Hussein, I.

Journal: International Journal of Clinical Pediatric Dentistry

Year: 2024