Eman Younis | Artificial Intelligence | Best Researcher Award

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Prof. Eman Younis | Artificial Intelligence | Best Researcher Award 🏆

Professor at Minia university, Egypt.

Dr. Eman M.G. Younis is a distinguished academic and researcher in the fields of information systems, data mining, semantic web, machine learning, and geographic information systems (GIS). With a robust educational foundation, including a Ph.D. in Informatics from Cardiff University and numerous impactful publications, Dr. Younis has significantly contributed to advancements in data science and geospatial technologies. Her leadership roles at Minia University, Egypt, further emphasize her dedication to research, teaching, and community development.

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Education 🎓:

Dr. Eman M.G. Younis holds a Doctor of Philosophy in Informatics from Cardiff University, UK (2009–2013). Her Ph.D. thesis, titled “Hybrid Geo-spatial Query Processing on the Semantic Web,” explored the integration of semantic web technologies with spatial data queries. She earned her Master of Science in Information Technology from Menoufia University, Egypt (2004–2007), where her thesis focused on “Automatic Web Page Classification with Data Mining Techniques.” Prior to this, she completed her Bachelor of Science in Information Systems & Technology from Zagazig University, Egypt (1998–2002), graduating with honors (GPA: 82.5%). Throughout her academic journey, Dr. Younis demonstrated exceptional aptitude for research and innovation, laying the foundation for her interdisciplinary expertise in informatics, GIS, and data science. Her education reflects a consistent pursuit of cutting-edge technologies and methodologies, making her a leader in her field.

Work Experience 💼:

Dr. Eman M.G. Younis has a rich professional background encompassing teaching, research, and administrative roles. She began her academic career as a Teaching Assistant at Minia University, Egypt (2003–2009), later serving as a Lecturer (2014) and Assistant Professor (2018–2019). Her international experience includes a tenure as a Postdoctoral Researcher at Nottingham Trent University, UK (2015–2017), focusing on emotion recognition and sensor data analysis. Currently, she is an Associate Professor and Vice Dean for Community Service and Environmental Development at Minia University. Dr. Younis also chaired the Information Systems Department (2019–2021), demonstrating her leadership in academic administration. She supervises numerous master’s and Ph.D. students, fostering innovation in fields such as machine learning and GIS. Her career reflects a commitment to interdisciplinary research, academic excellence, and community engagement.

Awards and Honors

Dr. Eman M.G. Younis has been recognized for her contributions to research and academia through numerous awards and honors. She was awarded scholarships for her postgraduate studies, including funding for her Ph.D. at Cardiff University. Her innovative research in GIS, semantic web technologies, and data science has earned her accolades at international conferences. Dr. Younis has also been acknowledged for her leadership and service as Vice Dean at Minia University. Her work on real-time machine learning applications for healthcare and environmental systems has received critical acclaim. Additionally, she has contributed to collaborative international research projects, showcasing her ability to address complex, interdisciplinary challenges. These accolades underscore her dedication to advancing knowledge, mentoring students, and applying technology for societal benefit.

Research Interests:

Dr. Eman M.G. Younis’s research focuses on Geographic Information Systems (GIS), Data Mining, Semantic Web, and Artificial Intelligence. Her interdisciplinary interests include geospatial query processing, social media mining, and emotion recognition using sensor data fusion. She explores innovative applications of machine learning and deep learning in fields such as healthcare, urban planning, and environmental monitoring. Dr. Younis is also interested in hybrid online-offline learning systems, big data analytics, and real-time predictions for critical systems like healthcare and disaster management. Her work bridges theoretical advancements and practical implementations, aiming to address pressing global challenges. She integrates cutting-edge technologies like distributed machine learning and streaming systems to enhance the accuracy and efficiency of predictive models. Her ongoing projects include emotion recognition through multimodal sensor data and the application of AI in geospatial data analysis.

📚 Publications 

    • Deep learning analysis of mobile physiological, environmental and location sensor data for emotion detection
      Authors: E. Kanjo, E.M.G. Younis, C.S. Ang
      Citations: 303
      Year: 2019
    • Sentiment analysis and text mining for social media microblogs using open source tools: an empirical study
      Authors: E.M.G. Younis
      Citations: 174
      Year: 2015
    • Heart disease identification from patients’ social posts, machine learning solution on Spark
      Authors: H. Ahmed, E.M.G. Younis, A. Hendawi, A.A. Ali
      Citations: 164
      Year: 2020
    • Towards unravelling the relationship between on-body, environmental and emotion data using sensor information fusion approach
      Authors: E. Kanjo, E.M.G. Younis, N. Sherkat
      Citations: 121
      Year: 2018
    • An efficient Manta Ray Foraging Optimization algorithm for parameter extraction of three-diode photovoltaic model
      Authors: E.H. Houssein, G.N. Zaki, A.A.Z. Diab, E.M.G. Younis
      Citations: 93
      Year: 2021
    • Predicting Coronavirus Pandemic in Real‐Time Using Machine Learning and Big Data Streaming System
      Authors: X. Zhang, H. Saleh, E.M.G. Younis, R. Sahal, A.A. Ali
      Citations: 64
      Year: 2020
    • NeuroPlace: Categorizing urban places according to mental states
      Authors: E.M.G. Younis, L. Al-Barrak, E. Kanjo
      Citations: 64
      Year: 2017
    • Fuzzy-based hunger games search algorithm for global optimization and feature selection using medical data
      Authors: E.H. Houssein, M.E. Hosney, W.M. Mohamed, A.A. Ali, E.M.G. Younis
      Citations: 40
      Year: 2023
    • Hybrid geo-spatial query methods on the Semantic Web with a spatially-enhanced index of DBpedia
      Authors: E.M.G. Younis, C.B. Jones, V. Tanasescu, A.I. Abdelmoty
      Citations: 35
      Year: 2012
    • Comparing automated and non‐automated machine learning for autism spectrum disorders classification using facial images
      Authors: B.R.G. Elshoky, E.M.G. Younis, A.A. Ali, O.A.S. Ibrahim
      Citations: 33
      Year: 2022
    • Designing and evaluating mobile self-reporting techniques: crowdsourcing for citizen science
      Authors: E.M.G. Younis, E.K.A. Chamberlain
      Citations: 32
      Year: 2019
    • Evaluating ensemble learning methods for multi-modal emotion recognition using sensor data fusion
      Authors: E.M.G. Younis, S.M. Zaki, E. Kanjo, E.H. Houssein
      Citations: 29
      Year: 2022
    • Hybrid online–offline learning to rank using simulated annealing strategy based on dependent click model
      Authors: O.A.S. Ibrahim, E.M.G. Younis
      Citations: 24
      Year: 2022

Conclusion 

Dr. Eman M.G. Younis is an outstanding candidate for the Best Researcher Award. Her groundbreaking contributions to the fields of informatics, GIS, and machine learning, coupled with her leadership roles, technical expertise, and commitment to advancing science, make her a highly deserving nominee. With further strategic collaborations and public engagement, her already stellar impact could be further enhanced.

 

 

Qiang Li | Artificial Intelligence | Best Researcher Award

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Prof. Qiang Li | Artificial Intelligence | Best Researcher Award   🏆

Professor at Anhui Agricultural University, China

Prof. Qiang Li is a distinguished mathematician specializing in applied and computational mathematics. He holds a Doctor of Science from Southeast University and has over a decade of academic experience, starting with his Bachelor’s degree at Changzhi University. Currently, he serves in the Department of Applied Mathematics at Anhui Agricultural University. Prof. Li’s research focuses on stochastic systems, neural networks, and state estimation, resulting in multiple high-impact publications in renowned journals like Applied Mathematics and Computation and Neural Networks. His work contributes to advancements in Markovian switching systems, semi-Markovian models, and capital systems with stochastic effects, demonstrating his expertise and innovation.

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Education 🎓:

Prof. Qiang Li has an impressive educational background in mathematics, showcasing a strong foundation and expertise in the field. He earned his Doctor of Science degree from the School of Mathematics at Southeast University in 2021, focusing on applied and computational mathematics. Prior to this, he completed his Master of Science at the School of Mathematics and Information Science, North Minzu University, in 2017, where he honed his skills in mathematical modeling and analysis. He began his academic journey with a Bachelor of Science degree from the Faculty of Mathematics at Changzhi University in 2014, establishing a robust base in mathematical theories and applications.

Work Experience 💼:

Prof. Qiang Li has accumulated extensive experience in the field of applied mathematics and computational systems. Since 2021, he has been a faculty member in the Department of Applied Mathematics at the School of Science, Anhui Agricultural University, where he engages in teaching, research, and academic mentorship. His professional journey encompasses expertise in stochastic systems, Markovian switching models, and neural network analysis, with a particular focus on state estimation, synchronization, and numerical methods. His collaborative efforts have led to significant advancements in mathematical modeling and computation, as evidenced by his impactful publications in esteemed international journals.

Skills 🔍

Prof. Qiang Li possesses exceptional skills in advanced mathematical modeling, stochastic processes, and numerical analysis, enabling him to address complex challenges in dynamic systems. He is proficient in analyzing Markovian and semi-Markovian switching systems, with expertise in state estimation, synchronization, and stability. Prof. Li demonstrates strong capabilities in computational tools and techniques, including matrix measures and numerical methods for fractional Brownian motion and Poisson jumps. Additionally, he has a keen understanding of neural networks, specifically complex-valued neural networks (CVNNs), and their applications in dynamic systems. His analytical and problem-solving skills are complemented by a deep commitment to innovative research.

Awards and Honors 🏆

Prof. Qiang Li has earned recognition for his significant contributions to applied mathematics and computational research. His achievements are underscored by several prestigious awards and honors, reflecting his academic excellence and impact in the field. These accolades highlight his groundbreaking work in Markovian and semi-Markovian switching systems, stability analysis, and numerical methods. His research outputs, published in high-impact journals such as Applied Mathematics and Computation and Neural Networks, have further solidified his reputation as a leading scholar, earning him respect and acknowledgment within the global academic community.

Research Interests:

Prof. Qiang Li’s research interests lie at the intersection of applied mathematics and computational science, focusing on stochastic systems, Markovian switching complex-valued neural networks (CVNNs), and semi-Markovian processes. His work delves into state estimation, synchronization, and stability analysis of dynamic systems, often under complex conditions such as missing measurements, quantization effects, and mode-dependent delays. He is also deeply engaged in exploring dissipative methods, fractional Brownian motion, and numerical methods for systems with Poisson jumps. Prof. Li’s research aims to develop innovative mathematical frameworks and computational tools for solving real-world problems in dynamic and stochastic systems.

📚 Publications 

Asynchronous Nonfragile Guaranteed Performance Control for Singular Switched Positive Systems: An Event-Triggered Mechanism

  • Authors: J. Wang, Q. Li, S. Li, L. Zhang
  • Journal: International Journal of Robust and Nonlinear Control
  • Volume: 34, Issue 17, Pages 11451-11468
  • Publication Year: 2024
  • Cited by: 0

Improved Execution Efficiency of FPE Scheme Algorithm Based on Structural Optimization

  • Authors: X.-W. Yang, L. Wang, M.-L. Xing, Q. Li
  • Journal: Electronics (Switzerland)
  • Volume: 13, Issue 20, Article 4007
  • Publication Year: 2024
  • Cited by: 0

l1 Filtering for Uncertain Discrete-Time Singular Switched Positive Systems with Time Delay and Output Quantization

  • Authors: J. Wang, A. Gao, Q. Li, B. Xie
  • Journal: Journal of the Franklin Institute
  • Volume: 361, Issue 13, Article 107028
  • Publication Year: 2024
  • Cited by: 0

Exponential Stability of Impulsive Stochastic Neutral Neural Networks with Lévy Noise Under Non-Lipschitz Conditions

  • Authors: S. Ma, J. Li, R. Liu, Q. Li
  • Journal: Neural Processing Letters
  • Volume: 56, Issue 4, Pages 208
  • Publication Year: 2024
  • Cited by: 0

Mathematical Analysis of Stability and Hopf Bifurcation in a Delayed HIV Infection Model with Saturated Immune Response

  • Authors: Z. Hu, J. Yang, Q. Li, S. Liang, D. Fan
  • Journal: Mathematical Methods in the Applied Sciences
  • Volume: 47, Issue 12, Pages 9834-9857
  • Publication Year: 2024
  • Cited by: 1

Dissipative Synchronization of Semi-Markovian Jumping Delayed Neural Networks Under Random Deception Attacks: An Event-Triggered Impulsive Control Strategy

  • Authors: H. Wei, K. Zhang, M. Zhang, Q. Li, J. Wang
  • Journal: Journal of the Franklin Institute
  • Volume: 361, Issue 8, Article 106835
  • Publication Year: 2024
  • Cited by: 8

Conclusion 

Prof. Qiang Li’s academic credentials, professional expertise, and groundbreaking research establish him as an outstanding candidate for the Best Researcher Award. His innovative contributions to Markovian systems and nonlinear mathematics position him as a leader in his field, deserving of recognition for his impact and dedication to advancing mathematical sciences.

 

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

Arti Jha | Artificial Intelligence | Best Researcher Award

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Ms Arti Jha |  Artificial Intelligence |  Best Researcher Award 

 

Senior Research Fellow at Birla Institute of Technology and Science, Pilani, India

 

📚 👩‍💻 Arti Jha is a Senior Research Fellow at BITS Pilani, specializing in machine learning, natural language processing, statistics, game theory, and deep learning. Currently pursuing a PhD in Web Intelligence and Social Computing, she focuses on AI-enabled design of optimal advertisement campaign strategies in collaboration with CommerceIQ, Bangalore. With industry experience at CommerceIQ, she develops predictive models for e-commerce platforms. Arti holds a BTech-MTech dual degree from the Centre for Converging Technologies, University of Rajasthan. Her research spans object detection, machine learning, and teaching roles as a TA at BITS Pilani.

Professional Profile:

 

Education 🎓

PhD Candidate in Web Intelligence and Social Computing, BITS Pilani, Pilani, India, Feb 2022 – Present.

BTech-MTech Dual Degree, Centre for Converging Technologies, University of Rajasthan, Aug 2015 – Jul 2020. Cumulative GPA: 3.8/4.00.

Research Focus 🔬

Arti Jha’s research focuses on several key areas in the realm of artificial intelligence and data science. She specializes in machine learning 🤖, natural language processing 📜, statistics 📊, game theory 🎲, and deep learning 🧠. Her work spans from optimizing e-commerce advertising campaigns using advanced machine learning techniques to developing reinforcement learning strategies for real-time bidding in digital marketing. With a strong foundation in both theoretical research and practical applications, Arti contributes actively to the fields of AI-enabled advertisement strategies, predictive modeling, and algorithmic optimizations aimed at enhancing business intelligence and decision-making processes in digital platforms.

Professional Experience 💼

  • Senior Research Fellow, BITS-CommerceIQ Collaboration Project, BITS Pilani, Pilani, India, Feb 2022 – Present.
  • Designing optimal and targeted ad campaign strategies on e-commerce platforms.
  • Developing prediction models for optimizing ad campaigns on Amazon.
  • Working on interpretable and explainable AI models.
  • Industry Experience at CommerceIQ, Bangalore, India.

Research Experience 📊

  • Research Scholar, BITS Pilani, Pilani, India, Feb 2022 – Present.
  • Building algorithmic campaign optimizers.
  • Implementing multi-stage campaign classification and clustering models.
  • Designing explainable models for risk-averse modeling.
  • Project Trainee, Indian Space Research Organisation (ISRO), RRSC Jodhpur, India, Aug 2019 – Apr 2020.
  • Thesis on Object Detection using Satellite Images.
  • Data Analysis Intern, Robotics And Machine Analytics Lab (RAMAN), MNIT Jaipur, India, Mar 2019 – May 2019.
  • Developed a Movie Recommendation System.

Academic Experience 📚

  • Teaching Assistant, BITS Pilani, Pilani, India.
  • C Programming (Feb 2022 – Dec 2023).
  • Data Warehousing (Jan 2024 – Present).

Publications: