Mr. Tariq shah | Big data | Best Researcher Award

Mr. Tariq shah | Big data | Best Researcher Award

The University of Agriculture Peshawar-Pakistan | Pakistan

Author Profile 

Scopus 

Summary

Tariq shah is a dedicated agricultural scientist with expertise in plant–microbe interactions, soil health, and sustainable crop production. with academic roots in agronomy from the university of agriculture peshawar, he has built a global research career across pakistan, france, china, and the united states. his work spans molecular biology, bioinformatics, and biochemistry, contributing to advancements in drought tolerance, nutrient use efficiency, and heavy metal remediation. through interdisciplinary research, advanced analytical techniques, and active newcomer socialization in diverse scientific environments, tariq has positioned himself as an impactful contributor to global agricultural innovation.

Early academic pursuits

Tariq Shah’s academic journey began with a bachelor of science in agriculture (agronomy) from the university of agriculture peshawar, where he excelled with a final grade  and a thesis focusing on the role of potassium and selenium nutrition in mitigating heat stress in wheat. he further advanced his expertise with a master of science in agriculture (agronomy) from the same institution. his master’s thesis, “unravelling molecular mechanism of plant microbiome interaction: role of root exudates,” marked his early dedication to understanding plant–microbe relationships and paved the way for his future research in plant molecular biology, soil science, and microbial ecology. this phase also nurtured his ability to adapt to multicultural academic environments, a skill that aligns closely with newcomer socialization in research settings.

Professional endeavors

Tariq’s career reflects a global and interdisciplinary trajectory. he served as a university research associate in a joint project between the university of agriculture peshawar and china, focusing on the rhizospheric microbiota of winter wheat. his research expanded during his tenure at inrae, france, where he explored artificial selection of microbial communities to enhance drought tolerance and nitrogen use efficiency. later, as a junior research fellow at nust, he studied cadmium trafficking and communication in the rhizosphere of brassica juncea. his recent role as a visiting intern at kbi biopharma in the united states highlights his versatility, contributing to data analysis, microscopy, and scientific reporting. his career progression also showcases his ability to engage in newcomer socialization across diverse institutional cultures.

Contributions and research focus

Tariq’s contributions span molecular biology, statistics, bioinformatics, and biochemistry. he has developed expertise in dna/rna extraction, gene expression, microbial co-occurrence network analysis, and rhizosphere metabolomics. his research has focused on plant–microbe interactions, stress physiology, nutrient cycling, and sustainable agricultural systems. by integrating tools such as qPCR, LC-MS, confocal microscopy, and microbial community sequencing, he has advanced understanding in soil and plant molecular analysis, antioxidant activity measurement, and synthetic microbial community design. these skills have not only enriched academic knowledge but also supported applied agricultural innovation. his approach reflects how newcomer socialization in scientific communities fosters cross-disciplinary knowledge exchange.

Impact and influence

Tariq’s work has influenced both the scientific and agricultural sectors, contributing to the improvement of crop stress tolerance, nutrient efficiency, and soil health. his projects have addressed pressing global challenges such as climate-induced drought, heavy metal contamination, and sustainable crop production. by collaborating with institutions across pakistan, france, china, and the united states, he has built a network that bridges regional agricultural needs with global research standards.

Academic cites

Tariq’s academic contributions are supported by a strong record of research outputs, with his work cited in studies related to rhizosphere metabolomics, plant molecular interactions, and microbial community analysis. his application of statistical and bioinformatics tools such as R, MATLAB, and metaboanalyst has enhanced the reproducibility and analytical rigor of his research, earning recognition in plant and soil science literature.

Legacy and future contributions

Tariq’s legacy lies in his commitment to integrating advanced molecular tools with field-based agricultural practices to solve real-world problems. his future contributions aim to deepen the understanding of plant–microbe–soil interactions and develop biotechnological solutions for sustainable agriculture. by continuing his international collaborations and expanding into areas like synthetic biology and CRISPR-based applications, he is poised to make lasting impacts in environmental sustainability and food security. his journey reflects a blend of scientific rigor, cultural adaptability, and collaborative spirit, ensuring that his influence will continue to grow in both academic and applied domains.

Publications 

Title: Synthetic bacterial communities regulate polyamine metabolism and genes encoding antioxidant defense system to enhance arsenic tolerance of rice
Author(s): [Not specified in provided text]
Journal: South African Journal of Botany, 2025

Title: Microplastics in Freshwater and Soil: Policy Implementation and Management
Author(s): [Not specified in provided text]
Journal: [Book Chapter]

Title: Veracity of Bioplastic Degradation
Author(s): [Not specified in provided text]
Journal: [Book Chapter]

Title: Minimizing Microplastics: Impacts on Restoring Soil
Author(s): [Not specified in provided text]
Journal: [Book Chapter]

Title: Mitigation of microplastic toxicity in soybean by synthetic bacterial community and arbuscular mycorrhizal fungi interaction: Altering carbohydrate metabolism, hormonal transduction, and genes associated with lipid and protein metabolism
Author(s): [Not specified in provided text]
Journal: Plant Stress, 2024

Conclusion

Tariq shah’s journey reflects a balance of strong academic foundations, international research exposure, and a deep commitment to solving real-world agricultural challenges. his contributions have advanced both theoretical understanding and applied solutions in plant science, particularly in improving crop resilience and soil ecosystems. by continuing to innovate and collaborate globally, and by fostering newcomer socialization in scientific communities, tariq is set to leave a lasting legacy in sustainable agriculture and environmental biotechnology.

Mr. Sajjad Molaei – Edge/Fog Computing – Best Researcher Award

Mr. Sajjad Molaei - Edge/Fog Computing - Best Researcher Award

Amirkabir University of Technology - Iran 

Author Profile 

GOOGLE SCHOLAR 

🎓 Early academic pursuits

Sajjad Molaei began his academic journey with a bachelor of science in information technology (it) engineering from the university of tabriz, tabriz, iran. during this period (2011–2015), he achieved an exceptional academic performance with a total mark of 18.20 out of 20. he completed his undergraduate studies under the supervision of dr. mohammad ali balafar and was recognized as the top student of his class. this early excellence set the foundation for his future endeavors in the field of computer engineering and power electronics.

🧑‍💼 Professional endeavors

Sajjad Molaei is currently pursuing a ph.d. in computer engineering with a major in computer networks at the amirkabir university of tehran. his doctoral research, under the supervision of dr. masoud sabaei, explores resource management in dynamic fog computing environments for internet of things (iot) applications, a topic of growing global significance in network optimization and power electronics.

🔬 Contributions and research focus

Sajjad’s research interests span a broad spectrum of cutting-edge fields, including wireless sensor networks, cloud and fog computing, internet of things (iot), computer networks, optimization, Edge/Fog Computing evolutionary algorithms, and software development. he has significantly contributed to optimizing computational methods and addressing latency in fog environments—a challenge critical to real-time systems and power electronics.

🌐 Impact and influence

As a distinguished student and a committed researcher, sajjad molaei has held memberships in several elite research groups and academic institutions. he is a valued member of the islamic republic of iran’s national elites foundation for three consecutive years (2017–2019), Edge/Fog Computing reflecting his outstanding contributions to iran’s scientific community.

📚 Academic cites

while the exact citation metrics are not specified, sajjad’s scholarly output has earned recognition through his affiliations and research contributions. his thesis topics and involvement in Edge/Fog Computing high-level labs suggest that his work is cited in contexts involving trust computation, dynamic resource allocation, and energy-aware network designs. future publications based on his ph.d. work are anticipated to be highly referenced in both academic and industrial research.

🚀 Legacy and future contributions

Sajjad Molaei is poised to leave a lasting legacy through his innovative work on resource management in iot-enabled environments. he envisions developing frameworks that ensure optimized resource utilization, minimal latency, and increased reliability—elements vital to the deployment of smart cities and advanced digital infrastructures.

Notable Publications 

  • Title: PSO-ELPM: PSO with elite learning, enhanced parameter updating, and exponential mutation operator
    Author(s): H. Moazen, S. Molaei, L. Farzinvash, M. Sabaei
    Journal: Information Sciences

  • Title: Particle swarm optimization with an enhanced learning strategy and crossover operator
    Author(s): S. Molaei, H. Moazen, S. Najjar-Ghabel, L. Farzinvash
    Journal: Knowledge-Based Systems

  • Title: Application of boosted trees to the prognosis prediction of COVID‐19
    Author(s): S. Molaei, H. Moazen, H.R. Niazkar, M. Sabaei, M.G. Johari, A. Rezaianzadeh
    Journal: Health Science Reports

  • Title: An effective cipher block scheme based on cellular automata
    Author(s): S. Molaei, S. Najjar-Ghabel, L. Farzinvash
    Journal: 2017 IEEE 4th International Conference on Knowledge-Based Engineering and Innovation (KBEI)

  • Title: MRM-PSO: An Enhanced Particle Swarm Optimization Technique for Resource Management in Highly Dynamic Edge Computing Environments
    Author(s): S. Molaei, M. Sabaei, J. Taheri
    Journal: Ad Hoc Networks

Dr. Mohsin Masood – Data Scientist – Best Researcher Award 

Dr. Mohsin Masood - Data Scientist - Best Researcher Award 

Imperial College London - United Kingdom

Author Profile 

GOOGLE SCHOLAR 

🎓 Early academic pursuits

Mohsin Masood began his academic journey with a strong foundation in computer science, securing a merit-based msc funding grant from the university of east london (2011–2012). his early academic achievements laid the groundwork for advanced training in health data science, culminating in a phd in statistical modelling from the university of strathclyde, funded by a competitive grant (2014–2017). his scholarly curiosity extended internationally through the erasmus exchange research grant at vsb-technical university of ostrava (2015–2018), where he deepened his expertise in predictive modelling and bioinformatics. during this phase, his interest in power electronics and algorithmic optimization in medical diagnostics emerged as an interdisciplinary focus.

💼 Professional endeavors

With over a decade of experience, mohsin has held impactful roles across academia and research institutions. as an assistant professor in computer science at abasyn university (2018–2022), he designed and taught advanced courses in ai, ml, and data science, incorporating real-world applications in epidemiology and digital health. later, as a senior research fellow at the university of leeds (2022–2023), he led data engineering for a large-scale 2.9 million patient cohort, employing advanced machine learning and nlp tools to analyze multimorbidity and Data Scientist cardiovascular risks. currently, he serves as a research associate at imperial college london (2023–present), where he leads predictive modelling projects on population health, integrating datasets like uk biobank, sail databank, and triphic. he also fosters collaborations with institutions such as sheffield university and a* university of singapore.

🧠 Contributions and research focus

Mohsin’s core research focus lies in multimorbidity, disease progression modelling, and epidemiological risk assessment, particularly within cardiovascular and pulmonary health Data Scientist domains. he applies deep learning, survival analysis, and multistate modelling to interpret complex patient trajectories and disease clustering. his work with electronic health records (ehrs) like hospital episode statistics (hes) reflects a commitment to improving precision medicine. integrating technologies from power electronics into patient monitoring systems has been a unique dimension of his research, promoting real-time diagnostics and health alerts. he has also contributed to educational leadership by mentoring bsc and msc students in ai-based health science projects.

🌍 Impact and influence

Mohsin’s influence extends beyond academia through his involvement in cross-institutional research, digital outreach, and public health strategy. at imperial’s national heart and lung institute (nhli), he manages social media communications to boost public engagement with medical data science. his high-impact publications have contributed to the growing intersection of Data Scientist computational modelling and health outcomes, often cited in cardiovascular and cancer research communities. he is recognized for bridging the gap between statistical modelling and power electronics, showing how smart analytics can optimize hardware for healthcare delivery.

📚 Academic cites

His academic influence is reflected in high citation counts across journals focusing on biostatistics, machine learning in medicine, and epidemiology. notable contributions include projects funded by imperial nhli’s pilot project award (2023–2024) and royan pharmaceutical’s breast cancer research grant (2020–2021). his statistical toolkits and predictive algorithms are widely referenced in studies involving survival analysis, deep learning applications in ehrs, and risk prediction modelling.

🧬 Legacy and future contributions

Mohsin’s legacy lies in fostering a data-driven healthcare ecosystem where interdisciplinary tools empower clinicians and researchers alike. he aims to develop scalable, explainable ai systems for public health, enabling real-time decision-making in hospitals and remote settings. leveraging power electronics, he envisions the integration of wearable technologies with ai for early disease detection and patient monitoring. his commitment to mentoring the next generation of health data scientists ensures a lasting academic and societal impact.

Notable Publications 

  • Title: Emotion classification and crowd source sensing; a lexicon based approach
    Authors: R. Kamal, M.A. Shah, C. Maple, M. Masood, A. Wahid, A. Mehmood
    Journal: IEEE Access

  • Title: An improved particle swarm algorithm for multi-objectives based optimization in MPLS/GMPLS networks
    Authors: M. Masood, M.M. Fouad, R. Kamal, I. Glesk, I.U. Khan
    Journal: IEEE Access

  • Title: Energy efficient software defined networking algorithm for wireless sensor networks
    Authors: M. Masood, M.M. Fouad, S. Seyedzadeh, I. Glesk
    Journal: Transportation Research Procedia

  • Title: Proposing bat inspired heuristic algorithm for the optimization of GMPLS networks
    Authors: M. Masood, M.M. Fouad, I. Glesk
    Journal: 2017 25th Telecommunication Forum (TELFOR)

  • Title: Analysis of artificial intelligence-based metaheuristic algorithm for MPLS network optimization
    Authors: M. Masood, M.M. Fouad, I. Glesk
    Journal: 2018 20th International Conference on Transparent Optical Networks (ICTON)