Tuniyazi Abudoureheman | Information Technology | Research Excellence Award

Published on 04/12/2025 by TOT Awards

Dr. Tuniyazi Abudoureheman | Information Technology | Research Excellence Award

Hiroshima University | Japan

Dr. Tuniyazi Abudoureheman is an emerging researcher in intelligent imaging technologies whose work integrates high-frame-rate (HFR) video processing, digital signal processing, and intelligent systems to address complex challenges in robotics, motion analysis, and biological detection. His research focuses on developing advanced computational frameworks capable of extracting subtle temporal and spatial features from high-speed visual data, with applications spanning vibration monitoring, multi-joint robotic manipulators, and biological motion recognition. Tuniyazi’s contributions involve creating novel image- and signal-processing algorithms designed to improve the accuracy, stability, and efficiency of automated systems operating in dynamic environments. His work on HFR-video-based vibration analysis offers enhanced diagnostic capabilities for flexible robotic structures, while his research on hornet detection using wing-beat frequency analysis demonstrates the potential of high-speed imaging for environmental and biological applications. Furthermore, his earlier work on multi-person tracking in complex backgrounds reflects his strong foundation in computer vision and predictive filtering. Tuniyazi’s scholarly visibility continues to grow, with citations indexed in Google Scholar and Scopus, reflecting early-stage but steadily increasing academic impact. According to Google Scholar metrics, his work has accumulated citations, maintaining an h-index of 1 and an i10-index of 0, which is consistent with researchers developing specialized expertise in a rapidly advancing technical domain. His research outputs contribute to international conferences and peer-reviewed journals, demonstrating a commitment to scientific rigor and innovation. Tuniyazi’s ongoing research trajectory aligns strongly with the objectives of the Research Excellence Award, showcasing high-impact potential in intelligent video processing, adaptive computational models, and robotics-oriented signal analysis, reinforcing his role as a promising contributor to next-generation smart robotic and imaging systems.

Publication Profile

Google Scholar

Featured Publications

Li, J., Shimasaki, K., Tuniyazi, A., Ishii, I., Ogihara, M., & Yoshiyama, M. (2023). HFR video-based hornet detection approach using wing-beat frequency analysis. IEEE Sensors, 1–4.
Abudoureheman, T., Wang, F., Shimasaki, K., & Ishii, I. (2025). HFR-video-based vibration analysis of a multi-jointed robot manipulator. Journal of Robotics and Mechatronics, 37(5), 1205–1218.
Tuniyazi Abudoureheman, T., & Abousharara, E. (2018). Multiple people tracking based on Kalman filter in complex background. Proceedings of the Shikoku-Section Joint Convention of Institutes of Electrical and Related Engineers.

Kassem Kallas | Cyber | Best Researcher Award

Published on 08/04/202508/04/2025 by TOT Awards

Prof. Dr. Kassem Kallas | Cyber | Best Researcher Award

Senior Scientist at National Institute of Health and Medical Research, France

Dr. Kassem Kallas, Ph.D., Ing., EMBA, is a Senior Scientist and Junior Professor specializing in Artificial Intelligence and Cybersecurity. He holds a Ph.D. in Information Engineering and Science from the University of Siena and an EMBA in Strategic Leadership from Valar Institute. With experience across academia and industry, Dr. Kallas has worked on major projects funded by DARPA, NIST, ANR, and INRIA. His research tackles adversarial machine learning, federated learning security, and watermarking in deep learning. He previously served as a Research Fellow at NIST and a Scientist at INRIA. Currently affiliated with INSERM and IMT Atlantique, his work focuses on AI privacy in healthcare. Recognized for research excellence, he earned top honors at ICASSP and MMEDIA, among others. He is an IEEE Senior Member, active mentor, and published expert in AI security, image forensics, and signal processing.

professional profile

Scopus Profile

Education

Dr. Kallas’s academic journey reflects interdisciplinary depth and global exposure. He is currently pursuing his Habilitation à Diriger des Recherches (HDR) at the University of Western Brittany (2024–2025), emphasizing AI security and intellectual property protection. He recently completed an Executive MBA (2023–2024) with a stellar 94.8 average, leading a consultancy project earning full marks. He earned a Ph.D. in Information Engineering and Science from the University of Siena (2013–2017), focusing on game-theoretic models for cybersecurity. He also completed a second-level Master’s in Wireless Systems from Politecnico di Torino (2012–2013), and holds an M.Sc. and B.Sc. in Telecommunications Engineering from Lebanese International University (2010, 2012). His educational trajectory demonstrates a blend of engineering, management, and strategic thinking that underpins his research and leadership roles.

work Experience

Dr. Kallas has held key roles across top institutions in AI and cybersecurity. Since December 2023, he serves as a Senior Scientist and Junior Professor at INSERM and IMT Atlantique, focusing on federated learning security in healthcare. Previously, he was a Research Scientist at INRIA (2022–2023), contributing to the SAIDA project for defense-oriented AI security. From 2020–2022, he served as a Research Fellow at the U.S. National Institute of Standards and Technology (NIST), enhancing wireless communication systems for nuclear and chemical applications. Earlier, he was an R&D consultant and postdoc at ViDiTrust and the University of Siena. He has also supervised numerous PhD and master’s projects, demonstrating his leadership in guiding AI innovation. His roles bridge research, development, and mentorship across global institutions and startups, with advisory positions in blockchain and digital forensics ventures.

Research Focus

Dr. Kallas’s research intersects AI, cybersecurity, and signal processing. His main focus lies in defending AI systems against adversarial threats—particularly backdoor attacks, watermarking of deep neural networks, and securing federated learning models in sensitive domains like healthcare. His doctoral work applied game-theoretic frameworks to sensor networks for adversarial information fusion. He has advanced the field through research on deep learning robustness, AI watermarking, and privacy-preserving machine learning. As part of SAIDA (INRIA), he investigated defense techniques for deep neural models in defense applications. At INSERM, he now applies these principles to medical data security, contributing to ethical and resilient AI in healthcare. He also co-supervises research on face recognition vulnerabilities and vision transformers. His strategic research outlook combines theory with real-world impact, pushing AI systems toward safety, accountability, and trust.

Awards and honors

Dr. Kallas’s career is marked by international recognition for academic and research excellence. He received the prestigious Top 3% Paper Award at ICASSP 2023 (among 6000+ submissions) and was honored with Springer’s Best-of-the-Best PhD Thesis recognition. At MMEDIA 2017, he earned the Best Paper Award for his contributions to multimedia forensics. His academic prowess was further recognized through the Zenith Scholarship from Valar Institute and an EMBA Excellence Award from Rennes School of Business. In 2022, he was elevated to IEEE Senior Member status, a recognition of his professional impact. He also received multiple research fellowships from EOARD and the University of Siena, supporting advanced studies in adversarial signal processing and game theory. Certified in GANs, Deep Learning, and Blockchain, Dr. Kallas continues to stand out as an influential figure in AI security and innovation.

🧰 Skills

Dr. Kallas brings a versatile skillset blending technical depth with strategic leadership. He is multilingual—fluent in Arabic (native), English (C1), Italian (C1), and French (B2)—and adept at academic writing, teaching, and public speaking. Technically, he excels in adversarial machine learning, image forensics, deep learning, AI system security, and watermarking. His experience includes designing security protocols, implementing AI-based systems, and consulting on wireless and blockchain technologies. He holds certifications in Machine Learning (Stanford), Deep Learning, GANs, and Data Science (IBM), and has completed specialized training in AI applications and doctoral supervision. His business acumen is proven through his EMBA and leadership of consultancy projects. His mentorship and jury participation in PhD and industrial internships further reflect his collaborative, research-driven mindset.

Conclusion

Dr. Kassem Kallas is an outstanding candidate for the Research for Best Researcher Award. His technical mastery, academic leadership, international reputation, and dedication to scientific advancement exemplify the qualities sought in a top-tier researcher. With continued outreach and translational focus, his already-impressive career is poised to reach even greater impact.

Publications to Noted

Title: Strategic safeguarding: A game theoretic approach for analyzing attacker-defender behavior in DNN backdoors
Authors:

Kassem Kallas

Quentin Le Roux

Wassim Hamidouche

Teddy Furon
Journal: EURASIP Journal on Information Security
Year: 2024

Title: A Double-Edged Sword: The Power of Two in Defending Against DNN Backdoor Attacks
Authors:

Quentin Le Roux

Kassem Kallas

Teddy Furon

vasavi S | Computer Science | STEM Education Leadership

Published on 12/11/202412/11/2024 by TOT Awards

Prof. Dr. vasavi S | Computer Science | STEM Education Leadership

Professor & Head at Velagapudi Ramakrishna Siddhartha Engineering College, India

Dr. S. Vasavi, Professor and Head of the AI & DS Department, boasts a robust 27-year career in teaching and research. Her work spans extensive funded projects with organizations such as ISRO, DST, and IEEE, totaling approximately 1.3 crores INR. Dr. Vasavi collaborates with international universities and national R&D institutions on projects in remote sensing, predictive analytics, and big data, producing more than 100 publications in SCI, Scopus, and Google Scholar-indexed journals, along with several patents. Recognized with numerous awards, she is an influential figure in the field, committed to developing educational programs and advancing AI applications in STEM.

professional profiles

Scopus Profile

Google Scholar

ORCID

Education

Dr. Vasavi has a robust academic foundation with advanced degrees in Computer Science and Engineering. She pursued her undergraduate studies in Computer Science and later obtained her M.Tech, specializing in Artificial Intelligence and Data Science. Following her master’s, she completed a Ph.D., with research focusing on AI-driven solutions in remote sensing and data analytics. Her continuous professional development includes specialized training and certifications from global institutions, broadening her expertise in areas like geospatial analysis, drone technology, and cloud data analytics. Dr. Vasavi has also been a visiting scholar at prominent institutions such as Illinois State University and Saint Augustine’s University in the United States. Her education has played a critical role in forming her research approach, blending technical expertise with a passion for solving real-world problems. This educational background has laid the groundwork for her impactful research contributions to AI applications and interdisciplinary STEM fields.

work Experience

Dr. S. Vasavi brings a diverse and rich experience portfolio, with 26 years in academia and one year in industry. Currently, she is the Head of the AI & DS Department at VR Siddhartha Engineering College, where she has spearheaded multiple funded projects and collaborated with renowned institutions like ISRO and NRSC. Her international collaborative research with universities across the U.S., Singapore, Canada, and Mexico has led to impactful publications and solutions in geospatial analysis, disaster management, and healthcare analytics. As an active member of various IEEE groups, she has chaired sessions and delivered keynote lectures at significant conferences worldwide, enhancing her global research network. Dr. Vasavi’s blend of academic, research, and administrative roles positions her as a key driver in advancing AI and data science education, and she continues to inspire her students by guiding them through hands-on research and industry-driven projects.

Awards and honors

Dr. Vasavi’s achievements have been recognized through numerous awards. She has received the Best Teacher Award and Outstanding Women in Engineering Award for her contributions to STEM education and research. Her groundbreaking research has earned her accolades such as the Best Paper Award at the IEEE IEMCON conference at the University of British Columbia, Canada, and at ICACI 2020 in Mysore, India. She is also an honored Senior Member of IEEE and received travel grants for presenting her work in the U.S. and Thailand. Dr. Vasavi’s exceptional contributions in AI have earned her the title of Academic Titan Achievement Award and Vishitta Mahila Award, celebrating her role as a trailblazer in engineering and education. Furthermore, as an Honorary Rosalind Member of London Journals Press, Dr. Vasavi’s influence extends internationally, reinforcing her position as an esteemed researcher and advocate for women in STEM.

Research Focus

Dr. Vasavi’s research spans multiple domains within AI, with a core focus on remote sensing, predictive analytics, and big data. She collaborates extensively on AI-driven projects addressing societal issues, such as disaster management, environmental sustainability, and healthcare innovations. Her ongoing work includes developing algorithms for urban GIS change detection, multi-object detection using edge computing frameworks, and crowd surveillance through hybrid deep learning. Dr. Vasavi’s interdisciplinary research bridges the gap between academia and industry, partnering with institutions like ISRO and the National Remote Sensing Center (NRSC) to create impactful AI applications in space and geospatial analysis. Her involvement in drone-based video processing and climate change analysis emphasizes her dedication to using AI for real-world solutions. With her guidance, these projects not only enhance AI applications but also foster meaningful research opportunities for her students and collaborators, advancing STEM education in the process.

Skills

Dr. Vasavi’s skill set encompasses a wide range of technical and research abilities. She is proficient in Big Data Analytics and Predictive Analytics, leveraging tools like Hadoop, MongoDB, and Spark for large-scale data processing. Her expertise in Remote Sensing allows her to apply AI techniques to analyze high-resolution images and develop models for urban change detection. She is skilled in Deep Learning and Computer Vision for applications in surveillance and object detection, using frameworks like TensorFlow and OpenCV. Her knowledge extends to Cloud Computing and Edge Computing, with experience in real-time processing for satellite data. Dr. Vasavi’s project management and collaboration skills have enabled her to lead funded research projects and international partnerships successfully. Additionally, her communication and leadership skills are evident through her role as an educator, mentor, and active participant in conferences, solidifying her position as an influential leader in AI and STEM education.

Conclusion

Dr. S. Vasavi’s extensive experience, international collaborations, funded projects, and high-impact research position her as a strong candidate for the STEM Education Leadership Award. Her work demonstrates excellence in advancing STEM-related research and applications, particularly in AI and remote sensing. With a slight increase in educationally-focused initiatives, Dr. Vasavi’s profile would align even more closely with the award’s emphasis on leadership in STEM education, potentially making her an ideal recipient for this honor.

Publications to Noted

“Invariant feature-based darknet architecture for moving object classification”

Authors: S. Vasavi, N.K. Priyadarshini, K. Harshavaradhan

Citations: 59

Year: 2020

“Extracting hidden patterns within road accident data using machine learning techniques”

Authors: S. Vasavi

Citations: 31

Year: 2018

“Study on Techniques for Providing Enhanced Security During Online Exams”

Authors: N. Sai Soujanya, T., Dr. S. Vasavi, S. Anusha

Citations: 26

Year: 2012

“Predictive analytics as a service for vehicle health monitoring using edge computing and AK-NN algorithm”

Authors: S. Vasavi, K. Aswarth, T.S.D. Pavan, A.A. Gokhale

Citations: 24

Year: 2021

“Prediction of temperature anomaly in Indian Ocean based on autoregressive long short-term memory neural network”

Authors: M.S. Pravallika, S. Vasavi, S.P. Vighneshwar

Citations: 18

Year: 2022

“Framework for Predictive Analytics as a Service using ensemble model”

Authors: S.K. Babu, S. Vasavi, K. Nagarjuna

Citations: 18

Year: 2017

“Detection of solitary ocean internal waves from SAR images by using U-Net and KDV solver technique”

Authors: S. Vasavi, C. Divya, A.S. Sarma

Citations: 16

Year: 2021

“Hadoop framework for entity resolution within high velocity streams”

Authors: S.P. Benny, S. Vasavi, P. Anupriya

Citations: 16

Year: 2016

“A Survey on Extracting Hidden Patterns within Road Accident Data using Machine Learning Techniques”

Authors: S. Vasavi

Citations: 14

Year: 2016

“Age detection in a surveillance video using deep learning technique”

Authors: S. Vasavi, P. Vineela, S.V. Raman

Citations: 12

Year: 2021

Kassem Kallas | Cyber | Best Researcher Award

Prof. Dr. Kassem Kallas | Cyber | Best Researcher Award

professional profile

Education

work Experience

Research Focus

Awards and honors

🧰 Skills

Conclusion

Publications to Noted

vasavi S | Computer Science | STEM Education Leadership

Prof. Dr. vasavi S | Computer Science | STEM Education Leadership

professional profiles

Education

work Experience

Awards and honors

Research Focus

Skills

Conclusion

Publications to Noted

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