Dr. Abhishekh is an accomplished academician and researcher specializing in Mathematics, Applied Mathematics, Fuzzy Mathematics, Fuzzy Time Series, Fuzzy Optimization, and Intuitionistic Fuzzy Sets. He has more than 8 years of teaching experience in higher education and has served as an Assistant Professor at several reputed institutions. He is currently serving as an Assistant Professor at Vellore Institute of Technology (VIT) University, Bhopal, where he continues to contribute to teaching, research, and academic development.

Prior to joining VIT Bhopal, he served as an Assistant Professor at VIT-AP University, Dr. Rammanohar Lohia Avadh University, Ayodhya, and Vishwavidyalaya Engineering College, Ambikapur, including service under the TEQIP-III programme.

Dr. Abhishekh has demonstrated strong academic credentials by qualifying CSIR-NET in Mathematical Sciences twice in 2015 and GATE in Mathematics in 2013.

Research Expertise

His research interests primarily encompass fuzzy time series forecasting, intuitionistic fuzzy sets, type-2 fuzzy systems, fuzzy optimization, multi-objective optimization, fuzzy transportation problems, decision-making techniques, and mathematical modelling. His doctoral research focused on “A Study on Forecasting of Some Models Using Fuzzy Time Series.”

His research explores the development of computational and mathematical forecasting models capable of addressing uncertainty and imprecision in real-world datasets. His work has applications in areas such as production forecasting, enrollment forecasting, financial forecasting, rainfall prediction, ranking problems, and optimization.

Research Publications & Scholarly Contributions

Dr. Abhishekh has established a substantial publication record in international peer-reviewed journals and edited academic volumes. He has contributed more than 25 research publications, including articles published by major academic publishers such as Springer, Elsevier, Taylor & Francis, and World Scientific.

His research has addressed advanced topics including:

• High-order fuzzy time series forecasting
• Type-2 fuzzy time series models
• Intuitionistic fuzzy time series forecasting
• Moving-average forecasting approaches
• Fuzzy multi-objective linear programming
• Fuzzy transportation problems
• Fuzzy number ranking
• TOPSIS-based multi-criteria decision-making
• Hesitant fuzzy time series forecasting
• Frequency-based forecasting techniques
• Machine-learning approaches for mathematical equations

Notable recent contributions include research on hesitant fuzzy time-series forecasting published in Engineering Applications of Artificial Intelligence by Elsevier, as well as work on annual rainfall forecasting, machine-learning solutions for the Lane–Emden equation, and frequency-oriented fuzzy time-series forecasting.

Recent Research & Emerging Interdisciplinary Work

Dr. Abhishekh has progressively expanded his research toward the integration of fuzzy mathematics, computational intelligence, machine learning, and data-driven mathematical modelling. His recent work demonstrates an interdisciplinary orientation, particularly through the application of machine-learning and neural-network methodologies to mathematical problems.

His research agenda focuses on developing new forecasting methodologies using soft computing, type-2 fuzzy sets, and intuitionistic fuzzy sets, with the objective of improving forecasting accuracy under uncertain and complex conditions.

Teaching & Academic Contributions

With over eight years of teaching experience, Dr. Abhishekh has contributed extensively to undergraduate and postgraduate education in Mathematics and Engineering Mathematics. His teaching interests include:

• Algebra and Linear Algebra
• Real Analysis
• Complex Analysis
• Topology and Metric Spaces
• Differential and Integral Equations
• Engineering Mathematics
• Optimization Techniques
• Fuzzy Set Theory
• Data Mining
• Time Series Forecasting
• Intuitionistic Fuzzy Sets

His teaching philosophy emphasizes conceptual understanding, student interaction, problem-solving, and the application of mathematical theory to contemporary computational problems. He also aims to develop advanced courses integrating optimization, fuzzy set theory, data science, and forecasting.

Professional Service & Academic Engagement

Dr. Abhishekh has actively contributed to the academic community through editorial responsibilities, peer review, institutional committees, workshops, seminars, and academic programme coordination.

He has served as an Editorial Board Member of the SCIREA Journal of Mathematics since 2018 and the Journal of Science Innovations and Nature of Earth since 2022. He has also reviewed manuscripts for several peer-reviewed journals, including publications associated with Springer and Taylor & Francis.

He has participated in and contributed to numerous national and international conferences, workshops, faculty development programmes, and training programmes covering fuzzy mathematics, optimization, differential equations, time-series analysis, data science, pedagogy, digital tools, and research methodologies.

Awards & Recognition

Dr. Abhishekh's academic and research achievements have received international recognition. His distinctions include:

• Best Researchers Award in Science, Technology and Management, INSO, 2022.
• Young Scientist Award in Engineering, Science and Medicine, INSO, 2022.
• Qualification of CSIR-NET in Mathematical Sciences twice.
• Qualification of GATE in Mathematics.
• Recognition through editorial and peer-review services for international journals.

These achievements reflect his sustained engagement with research, academic excellence, and professional service.

Leadership & Institutional Contributions

Beyond teaching and research, Dr. Abhishekh has demonstrated academic leadership through programme coordination and institutional responsibilities. He coordinated a 21-day induction programme for first-semester B.E. students and participated in organizing national seminars and academic programmes.

He has also served on NBA and twinning committees and worked as a coordinator for GATE and employability classes, contributing to student development and institutional academic activities.

Future Research Vision

Dr. Abhishekh intends to advance research in fuzzy time-series forecasting and soft computing by integrating type-2 fuzzy systems, intuitionistic fuzzy sets, machine learning, and other computational techniques. His objective is to develop robust forecasting models capable of improving predictive performance in uncertain and data-intensive environments.

His future research direction reflects a strong interdisciplinary approach connecting mathematics, artificial intelligence, data science, optimization, and computational modelling.

Eligibility for Best Scientist Award

Dr. Abhishekh is strongly eligible for the Best Scientist Award in Scientific Laurels based on his sustained contributions to mathematical and computational research. His eligibility is supported by his 8+ years of academic experience, extensive international research publications, contributions to fuzzy mathematics and forecasting, interdisciplinary research involving artificial intelligence and machine learning, international awards, editorial and peer-review responsibilities, conference presentations, and continued research innovation.

His substantial body of work in fuzzy time-series forecasting, intuitionistic fuzzy systems, fuzzy optimization, computational mathematics, and emerging machine-learning applications demonstrates both research productivity and scientific relevance. His progression from classical fuzzy forecasting methodologies toward interdisciplinary AI-enabled mathematical modelling further strengthens his profile as a researcher contributing to the advancement of contemporary mathematical sciences.

Dr. Abhishekh represents a dedicated mathematician, educator, and interdisciplinary researcher whose work bridges mathematical theory, fuzzy systems, forecasting, optimization, and computational intelligence. His research productivity, academic experience, professional recognition, scholarly service, and continuing efforts toward innovative forecasting methodologies make him a compelling candidate for the Best Scientist Award in Scientific Laurels.