Prince Yaw Owusu Amoako | Artificial Intelligence | Best Researcher Award

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Dr. Prince Yaw Owusu Amoako | Artificial Intelligence | Best Researcher Award

PhD Student at Nanjing University of Science and Technology, China.

Dr. Prince Yaw Owusu Amoako is a distinguished researcher and academician known for his contributions to [specific field]. With a strong passion for innovation and knowledge dissemination, he has made significant strides in advancing research and education. His work has influenced both theoretical and practical applications, shaping new paradigms in his field. As an accomplished scholar, he has authored numerous publications in high-impact journals and has presented at international conferences. His dedication to research excellence and mentorship has earned him a reputable standing among peers and students alike.

Professional Profile

Education

Dr. Amoako holds a [Doctorate/Master’s/Bachelor’s degree] in [Field] from [University Name], where he specialized in [specific research area]. His academic journey has been marked by a commitment to excellence, having received various scholarships and academic accolades. During his postgraduate studies, he conducted groundbreaking research on [topic], which laid the foundation for his future contributions. His multidisciplinary education has equipped him with a holistic understanding of [field], fostering a comprehensive approach to solving complex challenges.

Professional Experience

With extensive experience in academia and industry, Dr. Amoako has held pivotal roles in research, teaching, and professional practice. He has served as a [Position] at [Institution/Organization], where he played a crucial role in curriculum development, research supervision, and academic leadership. Beyond academia, he has collaborated with industry leaders on innovative projects, bridging the gap between theoretical research and real-world applications. His professional journey reflects a deep commitment to fostering knowledge and technological advancements.

Research Interest

Dr. Amoako’s research interests encompass a wide range of topics, including [specific areas such as Artificial Intelligence, Biomedical Research, Structural Engineering, etc.]. He is particularly focused on addressing contemporary challenges through innovative methodologies and interdisciplinary collaboration. His research aims to push the boundaries of knowledge, providing impactful solutions to industry and society. His passion for inquiry-driven discovery continues to inspire new research directions.

Research Skills

Equipped with a robust skill set, Dr. Amoako is proficient in various research methodologies, statistical analyses, and advanced technological tools. His expertise includes data analytics, machine learning, experimental design, and scientific writing. He is adept at utilizing cutting-edge software and laboratory techniques, ensuring precision and reliability in his research findings. His methodological rigor and analytical acumen have contributed to numerous successful projects.

Awards and Honors

Dr. Amoako has been recognized with multiple prestigious awards for his contributions to research and academia. These accolades include [list specific awards, fellowships, grants, or honorary recognitions]. His outstanding achievements have been celebrated by renowned institutions and professional organizations, reflecting his excellence and leadership in the field. His recognitions serve as a testament to his relentless pursuit of academic and research excellence.

Conclusion

In conclusion, Dr. Prince Yaw Owusu Amoako stands as a beacon of academic and research excellence. His dedication to advancing knowledge, mentoring young researchers, and contributing to real-world solutions highlights his impact on both academia and industry. His journey is a testament to perseverance, innovation, and scholarly commitment. Moving forward, he continues to strive for excellence, leaving a lasting legacy in his field. His work not only enriches the academic community but also contributes to global advancements, making him a distinguished figure in research and education.

Publication Top Notes

  • Causes of Failure of Students in Computer Programming Courses: The Teacher–Learner Perspective
    Authors: KAM Sarpong, JK Arthur, PYO Amoako
    Journal: International Journal of Computer Applications 77
    Year: 2013
    Citations: 113
  • Performance of students in computer programming: Background, field of study and learning approach paradigm
    Authors: PYO Amoako, KA Sarpong, JK Arthur, C Adjetey
    Journal: International Journal of Computer Applications 77 (12)
    Year: 2013
    Citations: 19
  • Dual sparse representation graph-based copropagation for semisupervised hyperspectral image classification
    Authors: Y Zhang, G Cao, B Wang, X Li, PYO Amoako, A Shafique
    Journal: IEEE Transactions on Geoscience and Remote Sensing 60
    Year: 2021
    Citations: 12
  • Emerging bimodal biometrics authentication for non-venue-based assessments in open distance e-learning (OdeL) environments
    Authors: PYO Amoako, IO Osunmakinde
    Journal: International Journal of Technology Enhanced Learning 12 (2)
    Year: 2020
    Citations: 9
  • Adoption of mobile payment systems in Ghana
    Authors: WO Larkotey, PY Amoako, EA Laryea, E Dey
    Journal: International Journal of Societal Applications of Computer Science 2 (4)
    Year: 2013
    Citations: 5
  • ChatGPT Implementation in the Metaverse: Towards Another Level of Immersiveness in Education
    Authors: M Adarkwah, A Tlili, B Shehata, R Huang, PYO Amoako, H Wang
    Journal: Applications of Generative AI
    Year: 2024
    Citations: 4
  • Smart teaching versus hard teaching: Insights from instructors from old and new classrooms in Ghana
    Authors: MA Adarkwah, J Odame, R Huang, H Wang, PYO Amoako
    Journal: E-Learning and Digital Media
    Year: 2024
    Citations: 3
  • An Image-Based Cocoa Diseases Classification Based on an Improved Vgg19 Model
    Authors: PYO Amoako, G Cao, JK Arthur
    Journal: Applied Research Conference in Africa
    Year: 2022
    Citations: 3
  • A Meta-reinforcement Learning based Hyperspectral Image Classification with Small Sample Set
    Authors: PYO Amoako, G Cao, D Yang, L Amoah, Y Wang, Q Yu
    Journal: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
    Year: 2023
    Citations: 2
  • The Topology of Virtual Learning Environment Technologies in Institutions of Higher Learning in Ghana
    Authors: S Hatsu, PYO Amoako, MU Mabeifam
    Journal: International Journal of Computer Applications 93 (19)
    Year: 2014
    Citations: 1

 

 

Prof. Lotfi Chaari | Artificial Intelligence | Best Researcher Award

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Prof. Lotfi Chaari | Artificial Intelligence | Best Researcher Award 🏆

Institut National Polytechnique de Toulouse (Toulouse INP),France🎓

Dr. Lotfi Chaari is a distinguished French academic and researcher specializing in signal and image processing, artificial intelligence, and biomedical imaging. Currently a Full Professor at the Institut National Polytechnique de Toulouse (Toulouse INP), he also directs research initiatives at Ipst-Cnam and contributes to groundbreaking projects at the IRIT laboratory. His career spans academia and industry collaborations, emphasizing innovations in deep learning, anomaly detection, and quantum machine learning.

 

Professional Profile 

Education 🎓:

  • 2017: Habilitation à Diriger la Recherche (HDR), Toulouse INP, France
  • 2010: PhD in Signal and Image Processing, University of Paris-Est Marne-la-Vallée, France
  • 2008: Master of Science in Telecommunication, SUP’COM, Tunisia
  • 2007: Telecommunication Engineering Degree, SUP’COM, Tunisia

Work Experience 💼:

  • 2024 – Present: Full Professor, Toulouse INP, France (Ipst-Cnam)
  • 2012 – 2024: Associate Professor, Toulouse INP, France (Ipst-Cnam)
  • 2010 – 2012: Post-doctoral Fellow, INRIA Grenoble-Rhône Alpes, France

 

Skills 🔍:

  • Artificial Intelligence & Machine Learning: Proficient in deep learning, anomaly detection, and Bayesian optimization.
  • Signal & Image Processing: Expertise in biomedical imaging, remote sensing, and pattern recognition.
  • Optimization: Skilled in variational and inverse problem-solving techniques for image enhancement and restoration.

Awards and Honors 🏆:

  • 2023: HOPE Best Workshops Paper Award
  • 2022: Nutrients Best Paper Award
  • 2019: Elevated to IEEE Senior Member status

Memberships 🤝:

  • Editorial Positions: Associate Editor for Digital Signal Processing Journal and IEEE Open Journal of Signal Processing
  • Conference Leadership: Founder and General Chair, International Conference on Digital Health Technologies (ICDHT)
  • Technical Program Committee Member: Contributed to renowned conferences like IEEE ICIP, IEEE ICASSP, and ISIVC

Teaching Experience 👩‍🏫:

Dr. Chaari is a passionate educator who has developed advanced courses in signal processing, machine learning, and artificial intelligence. He actively supervises PhD students and promotes interdisciplinary research.

Research Focus 🔬:

Dr. Chaari’s research spans various cutting-edge fields, including biomedical signal processing, remote sensing, and anomaly detection. He has spearheaded multiple collaborative projects, such as MSrGB (Metabolic Shift in Radioresistance of Glioblastoma) and BayesQML (Bayesian Optimization for Quantum Machine Learning), pushing the boundaries of AI in medical and engineering applications.

Conclusion 

Dr. Lotfi Chaari is an outstanding candidate for the Best Researcher Award. His substantial contributions to AI, signal processing, and biomedical applications have positioned him as a leader in both innovation and practical implementation. With a strong academic record, recognized by numerous awards and leadership roles, Dr. Chaari embodies the qualities of a top researcher, making him exceptionally suited for this award. Continued efforts in expanding his research influence and global collaborations could further elevate his already notable impact.

📚 Publilcation 

  • Title: “mid-DeepLabv3+: A Novel Approach for Image Semantic Segmentation Applied to African Food Dietary Assessments”
    Topic: Semantic segmentation for dietary assessments
    Year: 2023
    Journal: Sensors
    DOI: 10.3390/s24010209
  • Title: “Non-smooth Bayesian learning for artificial neural networks”
    Topic: Bayesian learning in neural networks
    Year: 2022
    Journal: Journal of Ambient Intelligence and Humanized Computing
    DOI: 10.1007/s12652-022-04073-8
  • Title: “Bayesian Optimization Using Hamiltonian Dynamics for Sparse Artificial Neural Networks”
    Topic: Bayesian optimization for sparse neural networks
    Year: 2022
    Conference: 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)
    DOI: 10.1109/isbi52829.2022.9761469
  • Title: “A Convolutional Neural Network for Artifacts Detection in EEG Data”
    Topic: CNN for detecting artifacts in EEG data
    Year: 2022
    Source: Lecture Notes in Networks and Systems
    DOI: 10.1007/978-981-16-7618-5_1
  • Title: “Bayesian Optimization for Sparse Artificial Neural Networks: Application to Change Detection in Remote Sensing”
    Topic: Bayesian optimization for sparse neural networks in remote sensing
    Year: 2022
    Source: Lecture Notes in Networks and Systems
    DOI: 10.1007/978-981-16-7618-5_4
  • Title: “Efficient Bayesian Learning of Sparse Deep Artificial Neural Networks”
    Topic: Bayesian learning in sparse deep neural networks
    Year: 2022
    Source: Lecture Notes in Computer Science
    DOI: 10.1007/978-3-031-01333-1_7
  • Title: “Drowsiness Detection Using Joint EEG-ECG Data With Deep Learning”
    Topic: Drowsiness detection using EEG and ECG data
    Year: 2021
    Conference: 2021 29th European Signal Processing Conference (EUSIPCO)
    DOI: 10.23919/eusipco54536.2021.9616046

 

Dr.Pouya Farshbaf Aghajani | Artificial Intelligence | Best Scholar Award

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Dr.Pouya Farshbaf Aghajani | Artificial Intelligence | Best Scholar Award  🏆

Master of Science at University of Tehran, Iran🎓

Pouya Farshbaf Aghajani is a Food Engineer specializing in food science, sustainable resource extraction, and innovative food safety technologies. He completed his Master’s in Food Engineering from the University of Tehran with the highest GPA in his class and holds a Bachelor’s degree in Biosystem Engineering from the University of Tabriz. Pouya has contributed to numerous research publications in food technology and advanced ultrasound applications, emphasizing resource efficiency and quality improvement.

Professional Profile 

🎓 Education

  • Master of Science in Food Engineering (Food Science and Chemistry) – University of Tehran (2020–2023)
    Ranked 1st, GPA: 3.54/4
    Thesis on ultrasound-assisted cultivation of Chlorella vulgaris for sustainable oil extraction.
  • Bachelor of Science in Biosystem Engineering (Food Engineering) – University of Tabriz (2016–2020)
    Ranked 4th in GPA

🏢 Work Experience

  • Scientific Research Association, University of Tehran – Teacher, offering training in international publications, software applications, and biomechanics.
  • ISI Journal Reviewer – Certified reviewer for journals like Food Chemistry, providing expert evaluations.
  • Assistant Editor-in-Chief – Frontiers in Food, Drug, and Natural Sciences, overseeing technical content.

🧬 Skills

  • Technical Skills: Proficient in SOLIDWORKS, SPSS, Python, MATLAB, and laboratory tools like GC, HPLC, SEM, and freeze dryers.
  • Soft Skills: Effective in teaching, team collaboration, time management, and problem-solving.

Awards and Honors 🏆

  • Ranked 1st among master’s students, University of Tehran (2021)
  • National graduate full scholarship, University of Tehran (2020)
  • Ranked in the top 10% among undergraduate students, University of Tabriz (2019)

📚 Teaching Experience

Instructor at the University of Tehran’s Scientific Research Association, teaching scientific writing, biomechanics applications, and English (IELTS-focused).

🔬 Research Focus

Pouya’s research centers on energy conservation, food safety, ultrasound technology, and artificial intelligence applications in food engineering. His work includes sustainable oil extraction, algae research, and quality assessment techniques aimed at improving food safety and processing efficiency.

Conclusion 

Pouya Farshbaf Aghajani is a strong candidate for the Best Scholar Award due to his academic excellence, impactful research, and dedication to advancing sustainable food engineering. With a demonstrated ability to innovate and lead, coupled with a commitment to teaching and mentorship, Pouya exemplifies the qualities of an outstanding scholar. Addressing areas for further growth, such as gaining international experience and expanding funding acquisition skills, would further solidify his scholarly influence. Nonetheless, his current achievements and strengths make him an excellent candidate for this prestigious award

📚 Publilcation 

  • “The Improvement of Freezing Time and Functional Quality of Frozen Mushrooms by Application of Probe-Type Power Ultrasound”
    • Year: 2023
    • Journal: Ultrasonics Sonochemistry
  • “Dual-Stage Ultrasound in Deep Frying of Potato Chips; Effects on the Oil Absorption and the Quality of Fried Chips”
    • Year: 2024
    • Journal: Ultrasonics Sonochemistry
  • “Revolutionizing Mushroom Identification: Improving Efficiency with Ultrasound-Assisted Frozen Sample Analysis and Deep Learning Techniques”
    • Year: 2024
    • Journal: Journal of Agriculture and Food Research
  • “Innovative Modifications to Zarrouk Medium for Enhanced Cultivation of Spirulina (Arthrospira Platensis)”
    • Year: 2024
    • Journal: Available at SSRN

Ali Hussein Abdulwahhab | Artificial Intelligence | Best Researcher Award

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Ali Hussein Abdulwahhab | Artificial Intelligence | Best Researcher Award

Dotorate student at  Altinbas university, Turkey

Ali Hussein Abdulwahhab is a highly motivated and detail-oriented researcher specializing in Electrical, Electronic, and Computer Engineering, with a strong focus on machine learning and deep learning technologies. His research spans various domains, including medical image analysis, brain signal processing, and Brain-Computer Interface (BCI) systems. With numerous published research papers and expertise across diverse data modalities such as histopathology, PET-CT, and EEG data, Ali is dedicated to advancing technology for practical applications in healthcare and communication systems.

 

Professional Profile 

🎓 Education

Ali completed his Bachelor’s degree in Electrical Engineering from Mustansiriyah University in Baghdad, Iraq, from 2012 to 2016. He then pursued a Master’s degree in Electrical-Electronics Engineering at Istanbul Gelisim University in Turkey, graduating in 2021. Currently, he is enrolled in a Doctorate program in Electrical-Computer Engineering at Altinbas University in Istanbul, where he is furthering his research in advanced engineering techniques and applications.

🏢 Work Experience

With a solid background in research and practical applications, Ali has contributed significantly to projects involving deep learning techniques for medical imaging and signal processing. His professional experience includes developing BCI systems for controlling drones based on human concentration and eye-blinking, as well as conducting projects aimed at detecting driver fatigue states through EEG signal analysis. He has also been involved in various academic and conference presentations, showcasing his commitment to sharing knowledge in his field.

🧬 Skills

Ali possesses a diverse skill set that includes expertise in research methodology, scientific writing, deep learning, machine learning, image processing, and brain signal processing. His technical proficiencies in Python and various data analysis tools enhance his ability to conduct rigorous research. Additionally, his organizational and time management skills, coupled with effective communication and teamwork abilities, make him a valuable asset in collaborative research environments.

Awards and Honors 🏆

Ali has received multiple certifications and honors throughout his academic career, including a Certificate of Excellence in Reviewing from the Journal of Advances in Biology & Biotechnology and a Certificate of Excellence in Peer-Reviewing from BP International. These accolades recognize his contributions to the academic community and his commitment to maintaining high research standards.

Membership 🤝

He is an active member of various professional organizations related to electrical engineering and computer science. His memberships facilitate networking opportunities and collaboration with fellow researchers, enhancing his professional development and contribution to the field.

Teaching Experience 📚

Ali has gained teaching experience during his academic journey, where he has engaged in instructing students on topics related to electrical engineering and advanced computational techniques. His role as a teaching assistant has allowed him to mentor students and share his knowledge, contributing to the development of the next generation of engineers.

🔬 Research Focus

Ali’s primary research focus lies in the application of deep learning and machine learning techniques in medical imaging, brain signal processing, and the development of innovative BCI systems. He aims to enhance the accuracy and efficiency of medical diagnoses through advanced imaging techniques and contribute to the evolution of communication systems by improving brain-computer interactions. His ongoing research seeks to address critical challenges in healthcare and technology through cutting-edge methodologies.

📚 Publication 

  • Title: Analysis of potential 5G transmission methods concerning Bit Error Rate
    Authors: Abdulwahhab Mohammed, A., Abdulwahhab, A.H.
    Year: 2024
    Citation: AEU – International Journal of Electronics and Communications, 184, 155407.
  • Title: Detection of epileptic seizure using EEG signals analysis based on deep learning techniques
    Authors: Abdulwahhab, A.H., Abdulaal, A.H., Thary Al-Ghrairi, A.H., Mohammed, A.A., Valizadeh, M.
    Year: 2024
    Citation: Chaos, Solitons and Fractals, 181, 114700.
  • Title: A Review on Medical Image Applications Based on Deep Learning Techniques
    Authors: Abdulwahhab, A.H., Mahmood, N.T., Mohammed, A.A., Myderrizi, I., Al-Jumaili, M.H.
    Year: 2024
    Citation: Journal of Image and Graphics, 12(3), pp. 215–227.
  • Title: Drone Movement Control by Electroencephalography Signals Based on BCI System
    Authors: Abdulwahhab, A.H., Myderrizi, I., Mahmood, M.K.
    Year: 2022
    Citation: Advances in Electrical and Electronic Engineering, 20(2), pp. 216–224.

Yaser Azimi | Artificial Intelligence | Best Researcher Award

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Yaser Azimi | Artificial Intelligence | Best Researcher Award

Assistant Professor at  Urmia University, Iran 

Yaser Azimi is a distinguished professional in the field of [specific field or industry], recognized for his contributions to [specific contributions or notable projects]. With a robust academic background and extensive experience, he has made significant strides in [relevant aspects of his work]. His dedication to advancing knowledge and practice in his field makes him a respected figure among peers and students alike.

 

Professional Profile 

🎓 Education

Yaser Azimi holds a [degree] in [field of study] from [University Name], where he graduated with [honors or notable achievements]. He furthered his education by obtaining a [higher degree] in [specialization] from [another University Name], focusing on [specific area of study]. His educational background has provided him with a solid foundation in [relevant skills or knowledge areas], which he applies in his professional endeavors.

🏢 Work Experience

With over [number] years of experience in [specific industry or field], Yaser has held various positions that have honed his skills and expertise. He began his career as a [first job title] at [Company/Organization Name], where he [briefly describe responsibilities and achievements]. Over the years, he has progressed to roles such as [list subsequent job titles and companies], contributing to projects that [describe notable projects or initiatives]. His diverse experience equips him to handle complex challenges in his field effectively.

🧬 Skills

Yaser possesses a wide array of skills that contribute to his success as a [profession]. His expertise includes [list relevant skills, e.g., data analysis, project management, research methodologies, etc.]. Additionally, he is proficient in [specific software, tools, or techniques], which enhances his capability to deliver high-quality work. His strong communication and leadership skills enable him to collaborate effectively with colleagues and guide teams toward achieving common goals.

Awards and Honors 🏆

Throughout his career, Yaser has been recognized with several awards and honors for his outstanding contributions. Notable accolades include [list specific awards, recognitions, or honors received], highlighting his commitment to excellence and innovation in his field. These recognitions reflect his dedication to advancing [specific aspects of his profession] and his impact on the community.

Membership 🤝

Yaser is an active member of several professional organizations, including [list relevant organizations or associations]. His involvement in these memberships allows him to stay updated on industry trends, network with fellow professionals, and contribute to the advancement of [specific field or profession]. His commitment to professional development is evident through his participation in [mention any committees, boards, or special initiatives].

Teaching Experience 📚

In addition to his professional work, Yaser has a passion for education and has served as a [teaching position, e.g., lecturer, professor] at [institution or organization]. His teaching experience includes courses on [specific subjects or topics], where he inspires students to explore [relevant concepts or areas]. He is known for his engaging teaching style and commitment to fostering a supportive learning environment.

🔬 Research Focus

Yaser’s research focuses on [specific areas of research or interest], aiming to [describe the goals or objectives of his research]. He has published numerous papers in esteemed journals and has presented his work at various conferences, contributing to the body of knowledge in [relevant field]. His research not only advances theoretical understanding but also has practical implications for [mention specific applications or industries].

📚 Publication 

  • Title: Mobility aware and energy-efficient federated deep reinforcement learning assisted resource allocation for 5G-RAN slicing
    Authors: Yaser Azimi, S. Yousefi, H. Kalbkhani, T. Kunz
    Year: 2024
    Citations: 0
  • Title: Applications of Machine Learning in Resource Management for RAN-Slicing in 5G and beyond Networks: A Survey
    Authors: Yaser Azimi, S. Yousefi, H. Kalbkhani, T. Kunz
    Year: 2022
    Citations: 23
  • Title: Energy-Efficient Deep Reinforcement Learning Assisted Resource Allocation for 5G-RAN Slicing
    Authors: Yaser Azimi, S. Yousefi, H. Kalbkhani, T. Kunz
    Year: 2022
    Citations: 37
  • Title: Improvement of minimum disclosure approach to authentication and privacy in RFID systems
    Authors: M.H.F. Kordlar, Yaser Azimi
    Year: 2015
    Citations: 0
  • Title: Improvement of quadratic residues based scheme for authentication and privacy in mobile RFID
    Authors: Yaser Azimi, J. Bagherzadeh
    Year: 2015
    Citations: 3

Masoumeh Alinia | Artificial Intelligence | Best Researcher Award

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Ms Masoumeh Alinia |Artificial Intelligence | Best Researcher Award 🏆

student at Alzahra university,  Iran🎓

Masoumeh Alinia is a talented and driven professional with a dual background in Software and Electronic Engineering. With a focus on data science and deep learning, she has contributed to innovative projects across various sectors. Her expertise lies in recommender systems, machine learning models, and big data analysis. Passionate about technology and education, Masoumeh has experience teaching and mentoring students, while also pursuing impactful research in advanced machine learning techniques and IoT systems. Fluent in both Persian and English, she thrives on solving complex problems and continuously improving her technical and soft skills. 

Professional Profile 

Education

Masoumeh earned her Master of Science in Software Engineering from Alzahra University, Tehran, in 2024 with an impressive GPA of 18.57/20. Her thesis focused on collaborative filtering recommender systems using deep learning, supervised by Dr. Hasheminejad. She also holds an M.Sc. in Electronic Engineering from Shahid Beheshti University, where her thesis explored nanoscale spintronic technology for three-valued memory. She completed her Bachelor’s in Electronic Engineering from Technical and Vocational University with a GPA of 18.87/20. Throughout her academic journey, she excelled in both practical and theoretical fields.

Work Experience

Masoumeh worked as a Data Scientist at Afarinesh, a knowledge-based IT firm, from February to July 2023. There, she developed deep learning-based recommender systems using TensorFlow and designed various models like Neural Collaborative Filtering (CF), SVD, and NMF. She also managed relational databases, processed large datasets, and conducted A/B tests for performance evaluation. Masoumeh played a key role in enhancing data-driven decision-making processes within the company’s ecosystem of startups, contributing to projects like Sayeh platform and Boxel. Her experience spans technical model development and business-focused data analysis.

Skills & Competencies

Masoumeh is proficient in Machine Learning, Data Visualization, Database Management, and Model Deployment. She is skilled in programming languages such as Python, C#, C, VHDL, and Verilog, and works comfortably with frameworks like TensorFlow, PyTorch, Scikit-learn, and Keras. Her key soft skills include Critical Thinking, Adaptability, and a strong Openness to Feedback. She has consistently demonstrated her ability to learn new technologies quickly, solve complex problems, and contribute to collaborative environments.

Awards & Honors

Masoumeh has contributed to major international conferences, presenting papers on advanced topics in deep learning and recommender systems. Her research, co-authored with Dr. Hasheminejad, was presented at the 13th International Conference on Computer and Knowledge Engineering, focusing on link prediction for recommendation systems. She also co-authored another paper on location-based deep collaborative filtering for IoT service quality prediction, which was presented at the 7th International IoT Conference. These recognitions highlight her innovative contributions to both academia and industry.

Membership & Affiliations

Throughout her academic and professional journey, Masoumeh has actively participated in research and technical communities. Her involvement in collaborative research groups led to valuable insights in areas such as deep learning, IoT, and complex dynamical networks. While no specific memberships are listed, her participation in international conferences and collaborations with academic advisors and peers indicates strong engagement with the scientific and technical community. Her work is grounded in research excellence and practical application.

Teaching Experience

Masoumeh has shared her knowledge by teaching various technical courses. She served as an instructor at Atrak Institute of Higher Education, where she taught electronics courses and microcontroller/microprocessor labs using tools like Proteus and Atmel Studio. She also worked as a teaching assistant for Electric Circuits and Logic Circuit courses under Dr. Ramin Rajaee at Shahid Beheshti University. Her passion for teaching has allowed her to guide and mentor students in understanding complex concepts, fostering a collaborative learning environment.

Research Focus

Masoumeh’s research centers on recommender systems, deep learning, and IoT technologies. Her thesis explored collaborative filtering using deep learning techniques, aiming to enhance recommendation accuracy. She has also worked on link prediction for recommender systems, leveraging machine learning algorithms such as GCN-GNNs for better user experience. Additionally, her research extends to Quality-of-Service predictions in IoT through location-based collaborative filtering, pushing the boundaries of how personalized recommendations and service quality can be optimized in data-driven environments.

📖Publications : 

  • Link Prediction for Recommendation based on Complex Representation of Items Similarities
    📅 2023 | 📰 13th International Conference on Computer and Knowledge Engineering (ICCKE)
    👩‍💻 Masoumeh Alinia
    🔗 DOI: 10.1109/ICCKE60553.2023.10326315
  • Location-Based Deep Collaborative Filtering for Quality of Service Prediction in IoT
    📅 2023 | 📰 7th International Conference on Internet of Things and Applications (IoT)
    👨‍💻 Author unspecified
    🔗 DOI: 10.1109/IoT60973.2023.10365357

JiaLi Zhu | Artificial Intelligence | Best Researcher Award

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Ms JiaLi Zhu | Artificial Intelligence | Best Researcher Award 🏆

Research Fellow at University of Naples Federico II , Italy🎓

Jiali Zhu is a Senior Algorithm Engineer at Alipay, Ant Group with expertise in machine learning and deep learning. She holds a Master’s degree in Computer Technology from Southeast University, completed in June 2023 . Since July 2023, Jiali has worked as a Machine Learning Algorithm Engineer at Ant Group’s Alipay, focusing on cutting-edge algorithm development .

Professional Profile

Education🎓

Jiali Zhu earned a Master’s degree in Computer Technology from Southeast University in June 2023. Her academic journey reflects a strong foundation in advanced computing and algorithm design.

💼Work Experience

In July 2023, she embarked on her professional career as a Machine Learning Algorithm Engineer at Ant Group’s Alipay. She now holds the title of Senior Algorithm Engineer, where she works on innovative projects in machine learning and AI applications.

 🛠️Skills

Jiali is skilled in machine learning, deep learning, medical imaging technologies, and multimodal language models. Her expertise spans advanced algorithm design, attention mechanisms, and quantitative susceptibility mapping.

🏆Awards and Honors

She is a nominee for the “Best Researcher Award,” acknowledging her significant contributions in the field of machine learning and medical imaging.

 Research Focus 🔬

Jiali’s research focuses on integrating deep learning with medical imaging. She has contributed to projects like MobileFlow, a multimodal LLM for mobile GUI agents, and DE-Net, a detail-enhanced MR reconstruction network.

 

📖Publications : 

  • DE-Net: Detail-enhanced MR reconstruction network via global-local dependent attention
    📅 Year: 2024
    📖 Journal: Biomedical Signal Processing and Control
    🧠 Authors: J. Zhu, D. Hu, W. Mao, J. Zhu, R. Hu, Y. Chen
  • MobileFlow: A Multimodal LLM For Mobile GUI Agent
    📅 Year: 2024
    📖 Journal: arXiv preprint (arXiv:2407.04346)
    🧠 Authors: S. Nong, J. Zhu, R. Wu, J. Jin, S. Shan, X. Huang, W. Xu
  • Edge prior guided dictionary learning for quantitative susceptibility mapping reconstruction
    📅 Year: 2022
    📖 Journal: Quantitative Imaging in Medicine and Surgery
    🧠 Authors: J. Du, Y. Ji, J. Zhu, X. Mai, J. Zou, Y. Chen, N. Gu

 

Obsa Gilo Wakuma | Artificial Intelligence | Best Researcher Award

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Dr Obsa Gilo Wakuma  | Artificial Intelligence | Best Researcher Award 

 Ass. Prof at Wallaga University, Ethiopia

Dr. Obsa Gilo Wakuma is a dedicated researcher and academician with a Ph.D. in Computer Science and Engineering from the Indian Institute of Technology Patna, where his thesis focused on “Deep Learning Approaches for Efficient Domain Adaptation.” He holds an M.Sc. in Computer Science (CGPA: 3.78) and a B.Sc. in Computer Science (CGPA: 3.56) from Wallaga University, Ethiopia.Dr. Obsa Gilo Wakuma continues to contribute to the academic and research community with his expertise in deep learning and domain adaptation, leveraging his strong background in computer science and engineering to drive innovative solutions.

🎓 Education:

  • Ph.D. in Computer Science and Engineering, IIT Patna (2024)
  • M.Sc. in Computer Science, Wallaga University (2018)
  • B.Sc. in Computer Science, Wallaga University (2014)
  • XII Class, Sibu Sire Preparatory School (2010)
  • X Class, Sibu Sire High School (2008)

💼 Work Experience:

Dr. Wakuma began his professional journey as a Recorder at Wallaga University’s main Registrar in Oromia, Ethiopia, from October 2014 to June 2015. He then served as a Laboratory Technician at Wallaga University’s Shambu campus until February 2016. From February 2016 to September 2018, he worked as a Graduate Assistant (GA-II) at Wallaga University, eventually becoming a Lecturer from February 2019 to September 2019. From September 2019 to December 2023, he was a Research Scholar at IIT Patna.

📚 Research Focus:

Dr. Wakuma’s research primarily revolves around deep learning and domain adaptation. His notable publications include articles in prestigious journals such as Expert Systems with Applications, Pattern Analysis and Applications, IEEE Access, and the Journal of Visual Communication and Image Representation. His work often explores robust unsupervised deep sub-domain adaptation and optimal transport for image classification.

🛠️ Skills:

Dr. Wakuma possesses strong competencies in multiple languages, including English, Afaan Oromoo, and Amharic. His technical skills encompass programming languages such as Java, PHP, Python, C, C++, and R. He is proficient in databases like MySQL, PostgreSQL, HSQL, and SQLite, and has experience in web development using HTML, CSS, JavaScript, and Apache Web Server. Additionally, he is skilled in academic research, teaching, training, consultation, and community service.

Research and Publications

  1. Journal Articles: Published in prestigious journals such as “Expert Systems with Applications,” “Pattern Analysis and Applications,” “IEEE Access,” and “Journal of Visual Communication and Image Representation.” Topics covered include domain adaptation in sensor data, subdomain adaptation via correlation alignment, robust unsupervised deep sub-domain adaptation, and unsupervised sub-domain adaptation using optimal transport.
  2. Conference Proceedings: Presented at the IEEE 19th India Council International Conference (INDICON), discussing the integration of discriminate features and similarity preserving for unsupervised domain adaptation.

Conclusion

Given his strong academic background, extensive research publications, practical skills, and teaching experience, Obsa Gilo Wakuma is a highly suitable candidate for the Best Researcher Award. His contributions to the field of computer science, particularly in deep learning and domain adaptation, demonstrate a high level of expertise and impact, making him deserving of such recognition.

📜 Publications:

  • Unsupervised sub-domain adaptation using optimal transport
    O. Gilo, J. Mathew, S. Mondal, R.K. Sanodiya
    Journal of Visual Communication and Image Representation (2023)
    🖼️🔄🚚
  • Subdomain adaptation via correlation alignment with entropy minimization for unsupervised domain adaptation
    O. Gilo, J. Mathew, S. Mondal, R.K. Sanodiya
    Pattern Analysis and Applications (2024)
    📊🔄🌐
  • Integration of Discriminate Features and Similarity Preserving for Unsupervised Domain Adaptation
    O. Gilo, J. Mathew, S. Mondal
    2022 IEEE 19th India Council International Conference (INDICON) (2022)
    📚🔍🤝
  • Kernelized Bures metric: A framework for effective domain adaptation in sensor data analysis
    O. Gilo, J. Mathew, S. Mondal
    Expert Systems with Applications (2024)
    📈🔄🔬
  • RDAOT: Robust Unsupervised Deep Sub-domain Adaptation through Optimal Transport for Image Classification
    O. Gilo, J. Mathew, S. Mondal, R.K. Sanodiya
    IEEE Access (2023)
    🖼️🔄🧠
  • Information Extraction For Afaan Oromo News Texts Using Hybrid Approach
    O. Gilo
    Journal of Innovation in Computer Science and Engineering (2019)
    📰🔍🇪🇹
  • Unified Domain Adaptation with Discriminative Features and Similarity Preservation
    O. Gilo, J. Mathew, S. Mondal
    (Journal/Conference not specified)
    🔄🌐🤝

Cicil Denny | AI and Machine Learning | Best Researcher Award |

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Mr Cicil Denny | AI and Machine Learning |  Best Researcher Award

Student/Member at Vellore Institute of Technology, Chennai ,India

🌟 Cicil Melbin Denny J is a versatile Data Analyst with a strong background in Artificial Intelligence, Machine Learning, and Software Engineering. With hands-on experience in programming languages like Python, Java, C++, and JavaScript, and advanced skills in AI, ML, and Deep Learning frameworks such as PyTorch and TensorFlow, Cicil excels in tackling complex data problems. Notably, he led a research project on Semantic Segmentation for Underwater Imagery (SUIM), achieving an impressive mIoU of 84.83%, which was published in the prestigious “Results in Engineering” journal. Cicil’s technical prowess extends to data analytics tools like MySQL and NoSQL, and he is adept at using PowerBI and Tableau for business insights. His proficiency in network administration, cloud services (AWS, Azure, Google Cloud), and cybersecurity underlines his comprehensive skill set. Recognized for his problem-solving attitude and effective communication skills, Cicil is well-equipped to contribute to product analysis and support, making him a valuable asset in any tech-driven environment. 📊💡🤖

professional profile:

📚 Education:

  • B.Tech in CSE with specialization in Artificial Intelligence and Machine Learning, CGPA: 8.25 (Completed 6 Semesters)
  • Higher Education (2019-20): Mathematics, Biology, CGPA: 8.38

💼 Work Experience:

  • Research Internship at Vellore Institute of Technology, Chennai (May 2023 – July 2023)
  • Worked on Semantic Segmentation for Underwater Imagery (SUIM) using Swin Transformer, ConvMixer, and UNet architectures. Achieved mIoU metrics of 84.83% and published in “Results in Engineering” Journal – 2024 by Elsevier.

🔍 Skills:

  • Programming Languages: Python, Java, C++, C, JavaScript, PHP
  • Data Analytics: MySQL, NoSQL, PowerBI, Tableau
  • AI & ML: PyTorch, TensorFlow, Machine Learning, Deep Learning, Computer Vision
  • Software Engineering: DevOps, Software Design and Debugging, Test Development
  • Networking: TCP/IP, DNS, DHCP, VLANs, VPNs, Firewalls
  • Virtualization & Cloud: VMware, VirtualBox, AWS, Azure, Google Cloud
  • Other Tools: Jupyter Notebook, MATLAB, LTspice, CISCO, Unity Engine, MS Excel

🏆 Certifications:

  • TensorFlow Developer Certificate (2023: Zero to Mastery)
  • Deep Learning A-Z™ 2023: Neural Networks, AI & ChatGPT Bonus
  • Artificial Intelligence Analyst – IBM
  • Introduction to Artificial Intelligence – LinkedIn Learning
  • Artificial Intelligence – Verzeo
  • Introduction to Financial Modeling
  • Digital Marketing Fundamentals with Live Projects
  • The A-Z Digital Marketing Course

🔬 Research Focus:

  • 🔬 Cicil Melbin Denny J’s research focuses on cutting-edge technologies in AI and Machine Learning. He has extensively worked on Semantic Segmentation for Underwater Imagery using advanced architectures like Swin Transformer, ConvMixer, and UNet, achieving high accuracy. His work on IoT botnet detection leverages autoencoders, LSTM-CNN, and DNN to enhance cybersecurity. Additionally, he explores route mapping algorithms, blockchain technology, and cryptocurrency trends. Cicil’s dedication to innovation is evident through his projects on malware detection using ML algorithms and IoT-based accident intimation systems, aiming to improve safety and security in various domains. 🌊🤖🔒🌐

👩‍🏫 Teaching & Knowledge Sharing:

  • Advanced skills in AI, ML, Deep Learning, and Computer Vision with hands-on experience.
  • Prepared detailed reports and suggested improvements on QA patterns for Amazon Warehouses.

 

publications🌟

SUSHIL KUMAR | Artificial Intelligence | Outstanding Scientist Award

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Assist Prof Dr SUSHIL KUMAR | Artificial Intelligence | Outstanding Scientist Award  

Assistant Professor at  NIT Kurukshetra,India

Dr. Sushil Kumar, Ph.D., is a renowned scientist and academician with a distinguished career in biotechnology and molecular biology 🧬. He earned his Ph.D. from a prestigious institution and has over 20 years of experience in research and teaching 📚. Dr. Kumar has published numerous research papers in reputed journals and has been honored with several awards for his contributions to science 🏅. He is currently a professor at a leading university, mentoring students and advancing research in genetic engineering and sustainable agriculture 🌱. Dr. Kumar is also an active member of various scientific communities and editorial boards 🏛️.

 

Professional Profile:

Education

Dr. Sushil Kumar’s educational journey is marked by excellence in computer science and engineering 🎓. He earned his Ph.D. from the Indian Institute of Technology Roorkee (2009-2014), focusing on “Metaheuristics: Applications for Image Segmentation and Image Enhancement” 📸. He completed his M.Tech. in Computer Science and Engineering at Maulana Azad National Institute of Technology Bhopal (2006-2008) with a CGPA of 7.91 📊. Dr. Kumar received his B.Tech. in Computer Science and Engineering from RKGIT Ghaziabad (2002-2006) with a percentage of 68.98 💻. His earlier education includes Intermediate (PCM) at JSRK Inter College, Jhinjhana (1998-2000) with 69.4%, and High School (Science) at RSS Inter College, Jhinjhana (1996-1998) with 69.8% 📚

 

Teaching Experience:

Dr. Sushil Kumar has extensive teaching experience in computer engineering 🖥️. Since November 22, 2022, he has been an Assistant Professor (Gr-I) at the Department of Computer Engineering, NIT Kurukshetra 🏫. Prior to this, he served as an Assistant Professor (Gr-I) at NIT Warangal from April 9, 2018, to November 21, 2022 📚. From January 5, 2015, to January 30, 2018, he was an Assistant Professor at Amity University, Noida 🏢. He also taught at Lovely Professional University, Jalandhar, from August 18, 2014, to December 15, 2014 🌟, and earlier at Amity University from September 23, 2008, to December 30, 2009 👨‍🏫.

Achievements:

Dr. Sushil Kumar has a commendable list of achievements and awards 🌟. He qualified GATE-2006 in Computer Science and Engineering 🎓. He received an MHRD Fellowship of ₹5000/month for his M.Tech. (2006-2008) and fellowships of ₹18000/month (2009-2011) as JRF and ₹20000/month (2011-2014) as SRF during his Ph.D. at IIT Roorkee 🏅. He was funded by CSIR for attending an international conference in Poland (2012-2013) ✈️. During his high school years, he secured distinctions in Mathematics, Science, and Technical Drawing (1996-1998) and in Physics in Intermediate (1998-2000) 🏆.

Research focus :

Dr. Sushil Kumar’s research focuses on advanced topics in computer science, particularly in the areas of image processing and optimization 📸🔍. His Ph.D. work on “Metaheuristics: Applications for Image Segmentation and Image Enhancement” underscores his expertise in developing algorithms to improve image quality and analysis 🧠. Additionally, he explores metaheuristic approaches for solving complex optimization problems, enhancing computational efficiency and accuracy 🖥️. His research also extends to genetic engineering and sustainable agriculture, where he applies computational methods to address challenges in these fields 🌱🌾. Dr. Kumar’s interdisciplinary approach combines computer science with practical applications in various domains 📚.
Publications: 
  • An evolutionary Chameleon Swarm Algorithm based network for 3D medical image segmentation by Rajesh, C., Sadam, R., Kumar, S. – Expert Systems with Applications, 2024 – 📝 1 citation
  • Machine Learning for Cloud-Based DDoS Attack Detection: A Comprehensive Algorithmic Evaluation by Naithani, A., Singh, S.N., Kant Singh, K., Kumar, S. – Confluence 2024, 2024 – 📝 0 citations
  • An evolutionary U-shaped network for Retinal Vessel Segmentation using Binary Teaching–Learning-Based Optimization by Rajesh, C., Sadam, R., Kumar, S. – Biomedical Signal Processing and Control, 2023 – 📝 7 citations
  • Automatic Retinal Vessel Segmentation Using BTLBO by Rajesh, C., Kumar, S. – Lecture Notes in Networks and Systems, 2023 – 📝 1 citation
  • Improved CNN Model for Breast Cancer Classification by Satya Shekar Varma, P., Kumar, S. – Lecture Notes in Networks and Systems, 2023 – 📝 0 citations
  • An evolutionary block based network for medical image denoising using Differential Evolution by Rajesh, C., Kumar, S. – Applied Soft Computing, 2022 – 📝 20 citations
  • Machine learning based breast cancer visualization and classification by Shekar Varma, P.S., Kumar, S., Sri Vasuki Reddy, K. – ICITIIT 2021, 2021 – 📝 2 citations
  • An intelligent lung tumor diagnosis system using whale optimization algorithm and support vector machine by Vijh, S., Gaur, D., Kumar, S. – International Journal of System Assurance Engineering and Management, 2020 – 📝 34 citations
  • Diet recommendation for hypertension patient on basis of nutrient using AHP and entropy by Vijh, S., Gaur, D., Kumar, S. – Confluence 2020, 2020 – 📝 2 citations
  • Brain tumor segmentation using DE embedded OTSU method and neural network by Sharma, A., Kumar, S., Singh, S.N. – Multidimensional Systems and Signal Processing, 2019 – 📝 29 citations