Rahma Mani | Artificial Intelligence | Women Researcher Award

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Ms. Rahma Mani | Artificial Intelligence | Women Researcher Award

PhD student, Escuela Técnica Superior de Ingeniería Informática, ETSII, Spain

Rahma Mani is a dedicated Ph.D. candidate in Electrical Engineering and Computer Science at the University of Seville, Spain, with a deep passion for wireless sensor networks, machine learning, and artificial intelligence. With a strong foundation in electrical engineering from the National Engineering School of Monastir, Tunisia, she has demonstrated her expertise through various academic and professional roles. Rahma has contributed to significant research projects and has a keen interest in innovative technologies.

Publication Profile

 

Strengths for the Award:

  1. Academic Excellence: Rahma is currently pursuing a Ph.D. in Electrical Engineering and Computer Science, focusing on cutting-edge fields such as wireless sensor networks, machine learning, and artificial intelligence. Her educational background is robust and well-aligned with emerging technological fields.
  2. Research Contributions: Rahma has multiple publications in reputable journals and conferences, including a submission to the prestigious Pervasive and Mobile Computing Journal by Elsevier. Her research in wireless sensor networks demonstrates innovation and contributes significantly to the field.
  3. Global Perspective: Rahma’s North African upbringing combined with her international academic and professional experiences in Spain, Italy, France, and Tunisia give her a unique global perspective. This diversity enhances her ability to approach problems from different angles, which is a valuable asset in research.
  4. Technical Skills: She possesses a wide range of digital and programming skills, including proficiency in languages like Java, C++, and MATLAB, as well as experience with technologies such as Vivado and Arduino. These skills are critical for her research and development work.
  5. Leadership and Innovation: Rahma demonstrated leadership in her role as the Electrical Committee leader in the ENIM TEAM, where she led the development of an electric car for an international competition. Her involvement in volunteer activities also highlights her leadership abilities and commitment to social causes.
  6. Language Proficiency: Fluent in English, Arabic, and French, with basic Spanish, Rahma’s multilingual capabilities are a significant asset in collaborative international research.

Areas for Improvement:

  1. Broader Research Exposure: While Rahma has a strong publication record, expanding her research impact by collaborating on interdisciplinary projects or participating in more international conferences could further enhance her profile.
  2. Advanced Certifications: Although Rahma has quality management certifications, pursuing advanced certifications related to her research areas (e.g., specialized AI or wireless communication certifications) could strengthen her expertise.
  3. Industry Collaboration: Increasing her engagement with industry partners, beyond internships, through joint research projects or consulting roles could provide practical applications for her research, enhancing its relevance and impact.

 

🎓 Education:

Rahma is currently pursuing her Ph.D. in Electrical Engineering and Computer Science at the University of Seville, Spain, specializing in wireless sensor networks, machine learning, and artificial intelligence. She earned her Electrical Engineering Diploma from the National Engineering School of Monastir, Tunisia, where she also led a team in designing and developing an electric car for an international competition. Rahma began her academic journey with preparatory engineering studies at the Preparatory Institute for Engineering Studies of Monastir, Tunisia.

💼 Experience:

Rahma has gained extensive experience as an adjunct professor at the Higher Institute of Applied Sciences and Technology of Mahdia, Tunisia, where she taught courses on digital signal processing, converters, and electrical machines. She also worked as a Junior Full Stack Engineer at HRDatabank Tunisia (WILL Group, Japan), contributing to the development of HR web applications. Additionally, Rahma has completed internships at Smart Sensors Systems (3S) in Nancy, France, and the Tunisian Electricity and Gas Company in Sousse, Tunisia.

🔬 Research Focus:

Rahma’s research focuses on wireless sensor networks, particularly in the areas of localization algorithms, edge computing, and FPGA-enhanced systems. She is passionate about applying machine learning and artificial intelligence techniques to improve the efficiency and reliability of sensor networks, especially in large-scale and industrial applications.

🏆 Awards and Honors:

Rahma received a merit-based fellowship to pursue her Ph.D. internship in Italy and Spain, recognizing her outstanding academic and research achievements.

📚 Publication Top Notes:

Localizing Unknown Nodes with an FPGA-Enhanced Edge Computing UAV in Wireless Sensor Networks: Implementation and Evaluation (2024)

Improved 3D localization algorithm for large-scale wireless sensor networks (2023).

Improved Distance vector-based Kalman Filter localization algorithm for wireless sensor network (2023) .

CRT-LoRa: An efficient and reliable MAC scheme for real-time industrial applications (2023).

Improved Least-Square DV-Hop Algorithm for Localization in Large Scale Wireless Sensor Network (2022) .

 

Conclusion:

Rahma Mani is a well-qualified candidate for the Research for Women Researcher Award. Her solid academic background, impressive research contributions, technical expertise, and leadership qualities make her a strong contender. With continued focus on expanding her research impact and industry collaborations, she is likely to make significant contributions to the field of Electrical Engineering and Computer Science, particularly in the areas of wireless sensor networks and AI. Her application for the award would be well-justified, showcasing both her achievements and potential for future advancements.

 

 

Shaghaf Kaukab | Technology | Young Scientist Award

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Dr. Shaghaf Kaukab | Technology | Young Scientist Award

scientist, ICAR-CIPHET, India

Shaghaf Kaukab is a dedicated Scientist at ICAR-Central Institute of Post-Harvest Engineering & Technology (ICAR-CIPHET), Ludhiana, specializing in Agricultural Structure and Process Engineering. With over 11 years of combined experience in scientific research and academic exploration within the food engineering and technology platform, Shaghaf has made significant contributions to the domain of extrusion processing, storage technology, drying techniques, and functional food product development. His work emphasizes the application of AI, machine learning, and deep learning techniques in agriculture, leading to innovative solutions that improve post-harvest management and food processing.

Publication Profile

Scopus

Strengths for the Award

  1. Research Contributions: Shaghaf Kaukab has made significant contributions to agricultural structure and process engineering, particularly in post-harvest technology. Her work on projects such as IoT-based monitoring systems and AI-enabled robotic harvesters demonstrates her innovative approach and alignment with modern agricultural challenges.
  2. Academic Excellence: With a Ph.D. in Post Harvest Technology and multiple prestigious academic awards, she has a strong academic background. Her high CGPA scores and ICAR merit medals underscore her academic diligence.
  3. Interdisciplinary Expertise: Shaghaf has expertise in various domains, including AI, machine learning, image processing, and food process engineering, making her research impactful and versatile.
  4. Publications and Impact: She has published extensively in refereed journals and contributed to book chapters, highlighting her active involvement in advancing her field of research. The inclusion of her work in high-impact journals reflects her research’s quality and relevance.
  5. Leadership and Collaboration: Shaghaf has demonstrated leadership by managing several projects, mentoring students, and coordinating training programs. Her collaborative efforts with organizations like CDAC and international exposure (e.g., Purdue University) enhance her profile.

Areas for Improvement

  1. Broader Outreach: While Shaghaf has conducted training and outreach activities, expanding these efforts to reach a more diverse audience, including more international platforms, could enhance her influence and recognition.
  2. Grant Acquisition: Although involved in several projects, focusing on securing more independent research grants could further validate her capabilities and drive her research agenda.
  3. Networking and Professional Development: Increased participation in international conferences, workshops, and collaborations outside of India could further her exposure and contribute to professional growth.

 

🎓 Education

Shaghaf Kaukab earned his Ph.D. in Post-Harvest Technology from the Indian Agricultural Research Institute (IARI), New Delhi, with a stellar CGPA of 9.1/10 in 2019. Prior to this, he completed his M.Tech. in Post-Harvest Engineering & Technology from IARI, New Delhi, with a CGPA of 8.97/10 in 2016. His academic journey has been marked by excellence, laying a strong foundation for his research and scientific endeavors.

💼 Experience

Currently, Shaghaf is a Scientist in Agricultural Structures & Process Engineering at ICAR-CIPHET, Ludhiana, where he has been instrumental in the development of technologies such as the stereo-depth based detection and localization module for apples. He has successfully led and contributed to several ongoing projects, including IoT-based modular systems for cold storage and AI-enabled robotic apple harvesters. His role extends to technical writing, project implementation, and collaboration with academic and industrial partners.

🔍 Research Focus

Shaghaf’s research interests lie in the application of new-age technologies like AI, machine learning, and deep learning in the post-harvest agriculture sector. He focuses on image processing techniques (such as Biospeckle, RGB, X-ray, Hyperspectral imaging) and the analysis of food properties (physical, thermal, mechanical, and micro-structural). His work in food process engineering aims to enhance the efficiency and quality of post-harvest processes.

🏆 Awards and Honors

Shaghaf Kaukab’s work has earned him recognition within the scientific community, including membership in prestigious organizations such as the Indian Society of Agricultural Engineers (ISAE) and the American Society of Agricultural and Biological Engineers (ASABE). He serves as a regular reviewer for scientific journals and has been an external examiner for graduate students at Dr. Rajendra Prasad Central Agricultural University, Bihar.

📚 Publication Top Notes

Shaghaf has published numerous articles in refereed journals and contributed to book chapters and training manuals. His notable works include:

Improving Real-time Apple Fruit Detection: Depth and Multi-modal Information Fusions with Non-targeted Background Removal – Published in Ecological Informatics.

Chickpea Temperature Profile Development and its Implication under Microwave Treatment – Published in Biological Forum – An International Journal.

Osmotic Dehydration of Aloe-vera Gel Discs – Published in Journal of AgriSearch.

Engineering Properties, Processing, and Value Addition of Tamarind: A Review – Published in IJBSM.

Study of Engineering Properties of Selected Vegetable Seeds – Published in Indian Journal of Agricultural Sciences.

 

Conclusion

Shaghaf Kaukab is a strong candidate for the Research for Young Scientist Award. Her innovative research, interdisciplinary expertise, and significant contributions to agricultural engineering, particularly in post-harvest technology, make her a standout. While expanding her outreach and securing more independent funding could strengthen her profile further, her accomplishments thus far demonstrate her potential as a leader in her field.

 

Diego Resende Faria | Multisensory AI | Excellence in Research

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Assoc Prof Dr. Diego Resende Faria | Multisensory AI | Excellence in Research

Reader in Robotics and Intelligent Adaptive Systems, University of Hertfordshire, United Kingdom

Dr. Diego Resende Faria is a Reader (Associate Professor) in Robotics and Intelligent Adaptive Systems at the University of Hertfordshire, UK. He has been contributing to the field of robotics and intelligent systems since 2022. With extensive experience in human-centered robotics, he has led and participated in various high-profile research projects across Europe. His work focuses on the integration of artificial intelligence in robotics to enhance human-robot interaction and autonomous systems. 🤖🌟

Publication Profile

Strengths for the Award

  1. Research Contributions:
    • Diverse Expertise: Dr. Faria’s research covers a broad range of topics, including cognitive robotics, affective robotics, artificial perception, and autonomous systems. His work on human manipulation, robotic grasping, and human-robot interaction is notable and demonstrates a significant contribution to his field.
    • Project Coordination and Leadership: He has successfully coordinated significant projects such as the EU CHIST-ERA InDex project and the Sim2Real project, showcasing his leadership and ability to manage high-impact research.
    • High-Quality Publications: His publications in well-regarded journals, such as Complexity and the Journal of Social Robotics, indicate a strong research output with relevance and impact in his field.
  2. Funding and Grants:
    • Secured Funding: Dr. Faria has obtained substantial funding for various projects, including EU Horizon projects and industry collaborations. His ability to attract significant grants demonstrates recognition and trust in his research capabilities.
  3. Academic and Professional Roles:
    • Positions of Influence: His roles as a Reader (Associate Professor) and past positions at prestigious institutions like Aston University and the University of Coimbra highlight his academic leadership and influence in robotics and intelligent systems.
  4. Editorial and Review Activities:
    • Journals and Conferences: Dr. Faria’s involvement as a guest editor for several journals and his role in program committees and conference chairs showcase his active participation in shaping the research community.

Areas for Improvement

  1. Broader Impact and Outreach:
    • Public Engagement: While his research is robust, there could be more emphasis on how his work impacts broader societal challenges or contributes to public understanding of robotics and artificial intelligence.
  2. Collaborative Networks:
    • Interdisciplinary Collaborations: Expanding his research to include interdisciplinary collaborations beyond robotics and AI could enhance the application and visibility of his work in other fields.
  3. Recognition and Awards:
    • Professional Awards: Achieving recognition through more prestigious awards or accolades specific to his research area could further validate his contributions and enhance his profile.

Conclusion

Dr. Diego Resende Faria is highly suitable for the “Research for Excellence in Research” award due to his extensive research contributions, leadership in significant projects, and strong publication record. His ability to secure substantial funding and his active involvement in the academic community further strengthen his candidacy. Addressing areas such as public engagement and expanding interdisciplinary collaborations could enhance his impact and recognition even further. Overall, his profile demonstrates a high level of excellence in research, making him a strong candidate for this award.

Education

Dr. Faria earned his Ph.D. in Electrical and Computer Engineering from the University of Coimbra, Portugal, in 2014. His academic journey continued with a postdoctoral fellowship at the Institute of Systems and Robotics, where he specialized in human-centered robotics. 🎓📚

Experience

Before joining the University of Hertfordshire, Dr. Faria was a Lecturer and Senior Lecturer at Aston University, UK, from 2016 to 2022. His career includes leading the EU CHIST-ERA InDex project, which was funded by EPSRC UK, and serving as PI for the Sim2Real project funded by the Royal Society. He is also involved in several industry-linked projects focusing on autonomous vehicles and multimedia retrieval. 🏛️🔬

Research Focus

Dr. Faria’s research interests include Neuro-Affective Intelligence, Cognitive Robotics (including Affective Robotics, Grasping and Dexterous Manipulation, and Human-Robot Interaction), Artificial Perception, Autonomous Systems, and Applied Machine Learning. His work aims to advance the capabilities of robotics in human-centered applications. 🧠🤖📊

Award and honors

Dr. Faria has received recognition for his contributions to robotics and intelligent systems, including significant project funding and accolades from international research bodies. His innovative work in autonomous systems and human-robot interaction has earned him a prominent place in the field. 🏆🔍

Publications Top Notes

  1. A Study on CNN Transfer Learning for Image Classification
  2. A Study on Mental State Classification using EEG-based Brain-Machine Interface
  3. A Probabilistic Approach for Human Everyday Activities Recognition using Body Motion from RGB-D Images
  4. Mental Emotional Sentiment Classification with an EEG-based Brain-Machine Interface
  5. Cross-domain MLP and CNN Transfer Learning for Biological Signal Processing: EEG and EMG

 

Muhammad Sajjad | Computer Science | Best Researcher Award

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 Dr.  Muhammad Sajjad | Computer Science | Best Researcher Award

Faculty (Visiting), Quaid-I-Azam University Islamabad, Pakistan

Muhammad Sajjad is a Pakistani mathematician specializing in cybersecurity and cryptography. With a Ph.D. from Quaid-i-Azam University, his research focuses on advanced coding and cryptographic schemes, published extensively in renowned journals. He’s received numerous awards, including the International Research Award on Cybersecurity and Cryptography. Sajjad’s expertise extends to teaching and international collaborations, contributing significantly to academia. 🎓 His innovative work bridges theoretical mathematics with practical applications, ensuring data security in the digital age. 🛡️

Profile 

ORCID

🎓 Education

Muhammad Sajjad holds a Doctor of Philosophy (Ph.D.) in Mathematics from Quaid-i-Azam University, Islamabad. He also completed his Master of Philosophy (M.Phil.) and Master of Science (M.Sc.) degrees from the same institution.

💼 Experience

He has significant experience in academia, having taught various mathematics courses at Quaid-i-Azam University, National University of Modern Languages, Bahria University, and FG Sir Syed College. He has also been involved in research conferences and international collaborations.

🔍 Research Interests

Sajjad’s research interests span across several areas including Mathematics, Electrical Engineering, Vector Algebra, Non-commutative Algebra, Number Theory, Coding Theory, Channel Coding, and Cryptography.

🏆 Awards

He has received numerous awards and scholarships throughout his academic journey, including the International Research Award on Cybersecurity and Cryptography and being a finalist for PakCrypto by the National Centre for Cyber Security (NCCS).

📚 Publications

Sajjad, M., Shah, T., Haq, T.U., Almutairi, B., & Xin, Q., “SPN based RGB Image Encryption over Gaussian Integers,” Heliyon, vol. 10, 2024. Link (Cited by: 0)

Sajjad, M., & Shah, T., “Decoding of cyclic codes over quaternion integers by modified Berlekamp–Massey algorithm,” Computational and Applied Mathematics, 43(2), 2024. Link (Cited by: 0)

Sajjad, M., Shah, T., Alsaud, H., & Alammari, M., “Designing pair of nonlinear components of a block cipher over quaternion integers,” AIMS Mathematics, vol. 8, 2023. Link (Cited by: 0)

Sajjad, M., Shah, T., Xin, Q., & Almutairi B., “Eisenstein field BCH codes constructions and decoding,” AIMS Mathematics, vol. 8. Link (Cited by: 0)

Sajjad, M., Shah, T., Alammari, M., & Alsaud, H., “Construction and Decoding of BCH-Codes Over the Gaussian Field,” IEEE Access, vol. 11, 2023. Link (Cited by: 0)