Mr. Md. Asraful Sharker Nirob | Data Science | Best Researcher Award

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Mr. Md. Asraful Sharker Nirob | Data Science | Best Researcher Award

Mr. Md. Asraful Sharker Nirob | Data Science – Researcher at Daffodil International University, Bangladesh

Md. Asraful Sharker Nirob is a highly motivated early-career researcher in computer science with a focus on machine learning, deep learning, and artificial intelligence applications. With a strong academic background and research involvement at the Health and Informatics Lab, he is driven to solve real-world problems in agriculture and healthcare using intelligent systems. His experience spans industry and academia, with a combination of technical expertise and leadership qualities that position him as a rising figure in applied AI research.

Profile:

Orcid | Scopus | Google Scholar

Education:

Nirob completed his Bachelor of Science in Computer Science and Engineering from a well-regarded university in Bangladesh, graduating with a CGPA of 3.70 out of 4.00. Throughout his academic journey, he maintained a high level of performance, actively engaged in research projects, and participated in student organizations. His academic background provided him with a solid foundation in software engineering, machine learning, data science, and algorithmic problem-solving.

Experience:

He is currently serving as a Research Assistant at the Health and Informatics Lab, where he works on AI-based models for disease diagnosis and predictive analysis. His responsibilities include dataset curation, preprocessing, and implementing neural network models using frameworks such as TensorFlow and PyTorch. Previously, he worked as a Junior Software Engineer, contributing to responsive web application development using React.js, JavaScript, and version control systems. He also gained administrative and communication experience as a Student Associate at the university’s career development center.

Research Interest:

Nirob’s research interests lie in machine learning 🤖, computer vision 👁️, deep learning 🧠, and natural language processing 💬. He is particularly passionate about explainable AI, neural network architectures, and hybrid deep learning models. His projects often explore the intersection of AI and practical domains like agriculture and medical imaging, with a goal to enhance classification accuracy, interpretability, and real-world impact.

Award:

Md. Asraful Sharker Nirob is a strong candidate for the Best Researcher Award due to his excellent research contributions, early career productivity, and innovative use of AI in solving domain-specific problems. His technical skills, multi-disciplinary collaborations, leadership in co-curricular activities, and strong academic record make him a well-rounded researcher. His dedication to publishing high-quality research and building accessible datasets adds further weight to his nomination.

Publications:

  • “XSE-TomatoNet” 🍅 – MethodsX, 2025
    Introduced an explainable AI approach using EfficientNetB0; cited for improving agricultural diagnostics.
  • “COLD-12” 🌿 – Franklin Open, 2025
    Hybrid CNN model for cotton disease detection; praised for high accuracy and innovation in multi-level features.
  • “Dragon Fruit Dataset” 🍓 – Data in Brief, 2023
    Created a comprehensive fruit maturity grading dataset; referenced in multiple dataset-driven research works.
  • “Brain Tumor Classification with Explainable AI” 🧠 – ECCE Conference, 2025
    Proposed a multi-scale attention fusion model; appreciated for bridging AI with medical imaging.
  • “Credit Card Fraud Detection” 💳 – IJRASET, 2024
    Leveraged behavioral biometrics and Random Forest; cited in interdisciplinary cybersecurity studies.
  • “Lemon Leaf Dataset” 🍋 – Data in Brief, 2024
    Shared high-quality annotated lemon disease dataset; reused in computer vision-based plant disease research.
  • “Sugarcane Disease Classification” 🌱 – IEEE STI Conference, 2024
    Applied hybrid DL model to agriculture; useful in smart farming systems and cited in precision agri-tech work.

Conclusion:

In summary, Md. Asraful Sharker Nirob demonstrates the qualities of a dedicated and impactful young researcher. With a diverse publication portfolio, technical depth, and ongoing contributions to pressing real-world problems, he stands out as a deserving nominee for the Best Researcher Award. His strong academic background, innovation in AI applications, and leadership in student activities indicate a promising future in academia and research. 🌟

 

 

 

Srujana Manigonda | Data Science | Research Excellence Distinction Award

Posted on by Academic achievements

Ms. Srujana Manigonda | Data Science | Research Excellence Distinction Award 

Ms. Srujana Manigonda | Data Science – Capital One, United States

Srujana Manigonda is an accomplished Data Scientist and Data Analyst with a strong background in statistical data analysis, machine learning, data governance, and business intelligence. With years of expertise in handling large-scale data processing, ETL development, and predictive modeling, she has played a pivotal role in transforming enterprise data ecosystems. Her contributions to data lineage, financial analytics, and scalable reporting solutions have significantly impacted major industries, including finance, manufacturing, and technology. As a recognized researcher, she has published multiple papers in renowned journals, advancing the field of data science and analytics. Through her research and technical proficiency, she has established herself as a leader in data-driven decision-making and AI innovation.

Professional Profile :

Google Scholar

Education

Srujana Manigonda pursued her Master’s in Business and Information Systems from a prestigious institution, equipping her with advanced analytical and technical skills essential for modern data science applications. Prior to that, she earned a Bachelor’s degree in Information Technology, laying the foundation for her expertise in database management, software development, and algorithmic problem-solving. Her academic journey reflects a strong commitment to leveraging data science for industry transformation and shaping the future of data analytics and governance.

Experience

With extensive experience in data analytics, data governance, and AI-driven decision-making, Srujana has worked on high-impact projects across multiple industries. She has led initiatives in enterprise data systems, financial reporting automation, and digital marketing analytics, driving business intelligence and operational efficiency. Her work in cloud computing, data engineering, and machine learning model development has provided businesses with actionable insights, resulting in optimized business processes and cost savings. Throughout her career, she has collaborated with cross-functional teams, data engineers, and executives, ensuring the seamless integration of AI-driven solutions into enterprise frameworks. Additionally, her role as a peer reviewer for reputed scientific journals has contributed to the advancement of research methodologies in data science and AI.

Research Interest

Srujana’s research focuses on data governance, machine learning, data privacy, and AI-driven analytics. She is passionate about developing scalable data infrastructures, ensuring data integrity, security, and ethical AI applications. Her work explores metadata management, financial technology analytics, and predictive modeling to drive efficient business strategies. She is also deeply invested in researching automated data lineage tracking, anomaly detection, and enterprise data security frameworks, which are crucial for ensuring trustworthy AI systems. Through her research, she aims to bridge the gap between industry and academia, fostering innovation in big data analytics and cloud-based AI solutions.

Awards

Srujana Manigonda has received prestigious accolades recognizing her contributions to data analytics and research excellence. She was honored with the Titan Business Award (2024) for her leadership in data-driven innovation. Additionally, she received the Global Recognition Award (2024) for her outstanding research contributions to enterprise data management and analytics. In 2024, she was awarded the International Distinguished Researcher Award in Data Analytics, further solidifying her reputation as a leading expert in data science. Her ability to translate complex data into meaningful insights has earned her widespread recognition from both industry and academia.

Publications

📄 “Scaling Enterprise Data Systems for Complex Reporting and Analytics at the Enterprise Level” – IJACT, 2024
📄 “Empowering Data-Driven Decision Making in Manufacturing” – ESP JETA, 2021
📄 “Data Privacy and Sovereignty in Financial Technology: Governance Strategies for Global Operations” – IJSAT, 2021
📄 “The Role of Metadata Management in Data Governance: Enhancing Visibility and Control Across Complex Pipelines” – IJIRMPS, 2021
📄 “Data Lineage and Traceability in Manufacturing: Achieving End-to-End Data Visibility” – IJIRMPS, 2020
📄 “Data Governance in Manufacturing: Protecting Intellectual Property and Ensuring Data Integrity” – IJIRCT, 2019
📄 “Advanced Data Quality Assurance Techniques in Financial Data Processing: Beyond the Basics” – IJIRMPS, 2022

Conclusion

Srujana Manigonda’s contributions to data science, AI research, and enterprise analytics have positioned her as a pioneer in data-driven innovation. Her ability to bridge the gap between research and industry applications has led to breakthrough advancements in data governance, financial technology, and large-scale data processing. Through her academic excellence, extensive research, and real-world impact, she continues to shape the future of AI-driven business intelligence. With a strong foundation in data science methodologies, cloud computing, and enterprise analytics, Srujana remains committed to driving transformative change in the field. Her visionary approach and relentless pursuit of excellence make her a deserving candidate for the Research Excellence Distinction Award.

Zameer Abbas | Statistics | Best Researcher Award

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Mr.Zameer Abbas | Statistics | Best Researcher Award 

Ph.D Scholar East China Normal University, Shanghai, China

Zameer Abbas is an accomplished academic and researcher in the field of Statistics, currently serving as an Assistant Professor at Govt. Ambala Muslim College, Sargodha, Pakistan. With a rich background in developing and enhancing control charts, his work has significantly contributed to the field of quality process control. He is known for his innovative approaches in statistical methods and has a robust publication record in renowned journals.

Profile

Scopus

🎓 Education

Zameer Abbas holds an M.Phil. in Statistics from the University of Sargodha (2017) with a CGPA of 3.25/4. He also earned a gold medal for his M.Sc. in Statistics from the University of Punjab, Lahore (2008), achieving an impressive 891/1200 marks.

💼 Experience

Zameer has extensive teaching experience, beginning as a Lecturer in Statistics at Govt. Degree College Bhagtanwala and progressing to his current role as Assistant Professor at Govt. Ambala Muslim College. Over his career, he has taught various courses, including Business Statistics, Probability Theory, and Econometrics.

🔬 Research Interests

His research interests encompass the development of new control charts, non-parametric control charts, robust control charts, and enhancing the performance of memory-type control charts. He is also interested in quality process control, econometrics, regression, probability distributions, statistical inference, Bayesian analysis, and sampling techniques.

🏆 Awards

Zameer has received numerous academic distinctions, including:

  • 1st position in M.Sc. Statistics from Punjab University, Lahore.
  • Scholarship from the University of Sargodha for his M.Phil. studies.
  • Best student certificates for the year 2007 from the District Association Jhang and Govt. Postgraduate College Jhang.

📚 Publications

Zameer Abbas has an impressive list of publications, contributing significantly to the field of quality and reliability engineering. Here are some of his notable works:

  1. Abbas, Z., et al. (2019). An enhanced approach for the progressive mean control charts. Quality and Reliability Engineering International, 35(4), 1046-1060. Link
  2. Abbas, Z., et al. (2020). On designing an efficient control chart to monitor fraction nonconforming. Quality and Reliability Engineering International, 36(3), 547-564. Link
  3. Abbas, Z., et al. (2020). On Developing an Exponentially Weighted Moving Average Chart under Progressive setup: An Efficient approach to Manufacturing Processes. Quality and Reliability Engineering International, 36(7), 2569-2591. Link
  4. Abbas, Z., et al. (2020). Enhanced Nonparametric Control Charts under Simple and Ranked Set Sampling Schemes. Transactions of the Institute of Measurement and Control, 42(14), 2744-2759. Link
  5. Abbas, Z., et al. (2020). On Designing a Progressive Mean Chart for Efficient Monitoring of Process Location. Quality and Reliability Engineering International, 36(5), 1716-1730. Link

 

Mohammed Bouasabah | Stochastic Processes | Best Researcher Award

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Prof Dr. Mohammed Bouasabah | Stochastic Processes | Best Researcher Award 

Professor | Ibn Tofail University | Morocco

Short Biography ✨

Mohammed Bouasabah is an accomplished academic and researcher specializing in mathematical modeling, financial analytics, and applied computing. Currently serving as a Maître de Conférences Habilité at the École Nationale de Commerce et de Gestion de Kénitra, he has made significant contributions to the fields of finance and mathematics through both his research and teaching. His academic career is marked by a deep engagement with stochastic modeling, particularly in the context of financial markets, which he integrates with his expertise in mathematical analysis and computing. His journey from an engineering student to a leading academic figure highlights his commitment to advancing knowledge in these complex areas and his passion for fostering the next generation of scholars in the field.

Profile

Scopus

Education 🎓

Mohammed Bouasabah’s educational background is distinguished by a series of achievements that underscore his expertise and dedication to the field of mathematical and computational sciences. He earned his Doctorate in Mathematical Analysis from the École Nationale de Commerce et de Gestion de Kénitra between 2012 and 2016, with his thesis focusing on the stochastic modeling of exchange rates within the framework of asset-liability management. His work explored the EUR/MAD and USD/MAD exchange rates, contributing valuable insights into their behavior and prediction. Prior to this, Bouasabah completed an Engineering Degree in Computer Science and Telecommunications at the Institut National des Postes et Télécommunications in Rabat from 2007 to 2010. His strong performance in preparatory classes for engineering schools, where he was the major of his promotion, laid a solid foundation for his advanced studies. He began his academic journey with a Baccalauréat in Technical Sciences from Lycée Technique Ibn Sina in Kénitra in 2005, where he achieved a commendable mention of “Bien.”

Experience 🏛️

Mohammed Bouasabah’s professional experience spans over a decade, reflecting his expertise and versatility in both teaching and research. Since 2022, he has held the position of Maître de Conférences Habilité at the École Nationale de Commerce et de Gestion de Kénitra. In this role, he leads research projects and delivers advanced courses in mathematics and computing, contributing to the academic and professional development of students and researchers alike. From 2018 to 2022, he served as an Assistant Professor at the same institution, where he focused on teaching and developing curricula related to finance and stochastic processes. His tenure as a State Engineer in Computer Science from 2010 to 2018 involved not only teaching various courses but also managing the training room for financial markets. His role extended to providing additional training and support in the use of financial tools and methodologies, demonstrating his commitment to both education and practical application in the financial sector.

Research Interests 🔍

Mohammed Bouasabah’s research interests are deeply rooted in the intersection of mathematical modeling and financial analysis. His primary focus lies in stochastic modeling, where he examines the behavior of financial variables and develops predictive models to assess their future behavior. This includes extensive work on the stochastic modeling of exchange rates and financial indices, aiming to improve the accuracy of predictions and the management of financial risks. Bouasabah’s research often explores the application of machine learning techniques to financial data, investigating how these modern methods can enhance traditional models and provide more robust forecasts. His work is driven by a desire to bridge theoretical models with practical applications, particularly in the context of financial markets where precision and reliability are crucial.

Awards 🏆

Throughout his career, Mohammed Bouasabah has received recognition for his contributions to academia and research. His work has been published in prestigious journals such as the International Journal of Innovation and Applied Studies and Frontiers in Applied Mathematics and Statistics. His research has not only advanced the understanding of stochastic modeling but also earned him accolades in various international conferences. His presentations on topics like the predictive accuracy of financial models and the impact of COVID-19 on exchange rates have been well-received, highlighting his role as a thought leader in the field.

Publications 📚

Mohammed Bouasabah has an extensive publication record that showcases his research contributions and impact on the field. Some of his notable publications include:

 

Mohammad Arashi | Statistics | Best Researcher Award

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Prof.Mohammad Arashi | Statistics | Best Researcher Award 

Professor Ferdowsi University of Mashhad  Iran

Dr. Mohammad Arashi is a distinguished professor at the Department of Statistics, Faculty of Mathematical Sciences, Ferdowsi University of Mashhad. He specializes in shrinkage estimation, variable selection, and high-dimensional data analysis. His extensive academic and professional journey has positioned him as a leading figure in statistical sciences.

Profile 

Scopus

Education 🎓

Dr. Arashi holds a Ph.D. in Statistics (2008) and an M.Sc. in Mathematical Statistics (2005) from Ferdowsi University of Mashhad, Iran. He completed his B.Sc. in Statistics from Shahid Bahonar University of Kerman in 2003. His rigorous academic background has laid a solid foundation for his research and teaching excellence.

Experience 🏅

Dr. Arashi has held various academic positions, including Professor at Ferdowsi University of Mashhad (2021-present) and Extraordinary Professor at the University of Pretoria (2014-present). He also served as Associate Professor at Shahrood University of Technology (2012-2020). His leadership roles include directing the Data Science Laboratory at Ferdowsi University and serving on several scientific committees.

Research Interests 📊

Dr. Arashi’s research interests are diverse and impactful. He focuses on shrinkage estimation, variable selection, high-dimensional and big data analysis, statistical machine learning, graphical models, and longitudinal data analysis. His work significantly contributes to the advancement of statistical methodologies and their applications.

Awards 🏆

Dr. Arashi has received numerous awards, including the DSI-NRF CoE-MaSS Statistics Publication Impact Award (2023) and multiple teaching and research excellence awards from Ferdowsi University of Mashhad and Shahrood University of Technology. He is also an ISI Elected Member and an NRF rated researcher (C2).

Publications 📚

Dr. Arashi has published extensively in reputed journals. Notable publications include:

  1. “Shrinkage Estimation in Big Data” (2023), Journal of Statistical Computation and Simulation. Cited by Article 1, Article 2.
  2. “Variable Selection in High-Dimensional Models” (2021), Computational Statistics & Data Analysis. Cited by Article 3, Article 4.
  3. “Advanced Statistical Machine Learning Techniques” (2019), Journal of Machine Learning Research. Cited by Article 5, Article 6.

Thangaraja Arumugam | Analytics | Best Researcher Award

Posted on by Academic achievements

Dr.Thangaraja Arumugam | Analytics | Best Researcher Award

Assistant Professor Vellore Institute of Technology , Chennai India

Dr. A. Thanga Raja is a distinguished academician and researcher with a Ph.D. in Business Administration. With over twelve years of teaching experience and two years of industrial expertise, he is currently an Assistant Professor at Vellore Institute of Technology (VIT), Chennai. He has also completed advanced programs in business analytics, digital marketing, and marketing strategies from esteemed institutions like the University of Texas and IIM-K. His research interests are deeply rooted in marketing analytics, consumer psychology, and business intelligence.

profile

Scopus

🎓 Education

  • Ph.D. in Business Administration from Manonmaniam Sundaranar University, Tamilnadu, India (October 2016)
  • Master of Business Administration (M.B.A) from Manonmaniam Sundaranar University, Tamilnadu, India (2008)
  • Bachelor of Business Administration (BBA) from Manonmaniam Sundaranar University, Tamilnadu, India (2006)
  • Postgraduate Diploma in Marketing Management (PGDMM) from Madurai Kamaraj University, Tamilnadu, India (2014)
  • M.Sc. in Psychology from Tamilnadu Open University, Tamilnadu, India (2018)
  • Professional Certification in Business Analytics and Business Intelligence (PGP-BABI) from University of Texas & Great Lakes (2020)
  • Advanced Marketing Strategies & Analytics Certification from IIM-K (2022)
  • Advanced Digital Marketing and Communications Certification from MICA (2024)

💼 Experience

Dr. Thanga Raja has held various academic positions, including:

  • Assistant Professor at VIT, Chennai (2019-Present)
  • Assistant Professor at SCMS School of Technology and Management, Cochin (2017-2019)
  • Assistant Professor at LEAD College of Management, Palakkad (2017)
  • Assistant Professor at Manonmaniam Sundaranar University, Tirunelveli (2012-2016)
  • Lecturer at M. D. T. Hindu College, Tirunelveli (2010-2012)

In the industry, he has served as a Sales Manager at ASMI enterprises and as a Financial Planning Manager at Max New York Life Insurance.

🔬 Research Interests

Dr. Thanga Raja’s research interests include:

  • Marketing Analytics 📊
  • Consumer Psychology 🧠
  • Business Analytics 📈
  • People Analytics
  • Fraud Analytics

He is proficient in tools such as SPSS, AMOS, NVIVO, MAXQDA, and various open-source software like RStudio, Python, and Gephi.

🏆 Awards

  • Faculty Research Award for four consecutive academic years (2019-2023) by VIT, Chennai
  • Visionary Leader Award for academic performance and contribution by Thames International University, France (2023)
  • Best Paper Award for “Revolutionizing Consumer Engagement: Exploring AI-Powered Advertising in the Social Media Era” at Asia Pacific Education Summit & Awards (2023)

📃 Publications

Dr. Thanga Raja has published extensively in reputable journals and conferences. Some of his notable publications include:

  • “Marketing Analytics: Strategies for Data-Driven Decisions” (2023), Journal of Marketing Analytics
  • “Consumer Behavior and Digital Marketing: An Empirical Study” (2022), International Journal of Business and Management
  • “Artificial Intelligence in Business: Opportunities and Challenges” (2021), Journal of Business Research