Tehreem Sohail | Biomedical Sciences | Innovative Research Award

Innovative Research Award

Tehreem Sohail
Affiliation National University of Sciences & Technology (NUST)
Country Pakistan
Scopus ID 58508924300
Documents 3
Citations 16
h-index 2
Subject Area Biomedical Sciences, Neuroscience, Nanotechnology, Nanomedicine, Drug Delivery
Event World Science Awards

Tehreem Sohail
National University of Science and Technology (NUST), Pakistan

Tehreem Sohail is a biomedical researcher specializing in nanobiotechnology, molecular biology, and computational bioinformatics. Based in Rawalpindi, Pakistan, she completed her Master of Science in Biomedical Sciences from the National University of Sciences & Technology (NUST). Her interdisciplinary research integrates experimental nanomaterial synthesis with computational biological analysis, focusing particularly on carbon nanodot drug delivery systems and immunogenic epitope prediction in infectious disease models. Her work has resulted in peer-reviewed scientific publications and recognition for contributions to translational biomedical research [1].

Abstract

The research activities of Tehreem Sohail focus on bridging experimental biomedical sciences with computational biology. Her work investigates the synthesis and biomedical application of carbon nanodots as drug-delivery systems, combined with bioinformatics approaches to identify vaccine candidates and immunogenic epitopes in infectious diseases. Through wet-lab experimentation, in vivo validation using murine models, and computational data analysis, her research contributes to emerging strategies in translational nanomedicine and molecular therapeutics. Peer-reviewed publications arising from these studies have highlighted the therapeutic potential of nanomaterials and computational vaccine design methodologies [2].

Keywords

Nanobiotechnology; Carbon Nanodots; Bioinformatics; Drug Delivery Systems; Computational Biology; Immunogenic Epitope Prediction; Biomedical Sciences; Translational Research.

Introduction

Advances in nanotechnology and computational biology have significantly expanded the possibilities for biomedical innovation. Researchers working at the intersection of these fields play an important role in developing new therapeutic delivery systems and predictive biological models. Tehreem Sohail represents an emerging generation of biomedical scientists integrating laboratory experimentation with computational bioinformatics pipelines. Her work focuses particularly on nanomaterial-based drug delivery and bioinformatics-driven vaccine target discovery, both of which contribute to contemporary translational biomedical research [2].

Research Profile

  • MSc Biomedical Sciences, National University of Sciences & Technology (NUST), Islamabad.
  • BSc Bioinformatics, COMSATS University Islamabad (Silver Medalist, CGPA 3.56/4.00).
  • Research assistant in biomedical sciences focusing on nanomaterial drug delivery systems.
  • Experience integrating wet-lab experimentation with computational bioinformatics analysis.
  • Contributor to peer-reviewed biomedical research publications.

Research Contributions

  • Synthesis and characterization of carbon nanodots using hydrothermal methods for biomedical drug delivery.
  • Evaluation of nanomaterial biocompatibility through hemolysis and drug release assays.
  • In vivo validation of therapeutic effects using BALB/C murine diabetic neuropathy models.
  • Bioinformatics analysis of pathogen proteins to identify immunogenic vaccine targets.
  • Development of systematic literature review methodologies for nanomedicine research.

Publications

  • Sohail, T. et al. (2025). A Systematic Review of the Applications of Carbon Dots for the Treatment of Diabetes. Journal of Drug Delivery Science and Technology.
  • Sohail, T. et al. (2023). Bioinformatics-based prediction and screening of immunogenic epitopes of Toxoplasma gondii rhoptry proteins 7, 21 and 22 as candidate vaccine target. Heliyon.

Research Impact

Tehreem Sohail’s research integrates nanotechnology with computational biology to address biomedical challenges such as targeted drug delivery and vaccine candidate identification. Her work on carbon nanodots contributes to ongoing efforts to develop nanoscale therapeutic carriers capable of improving treatment efficacy and reducing side effects. Additionally, her bioinformatics research contributes to predictive immunology by identifying potential vaccine epitopes through computational analysis of pathogen proteins [3].

Award Suitability

The Biomedical Research Excellence Award recognizes emerging researchers who demonstrate interdisciplinary innovation and measurable contributions to biomedical science. Sohail’s integration of nanobiotechnology, experimental biomedical techniques, and computational bioinformatics illustrates a multidisciplinary research profile aligned with contemporary translational research priorities. Her peer-reviewed publications, academic distinctions, and laboratory expertise support her recognition as an emerging contributor to biomedical research.

Conclusion

Through a combination of experimental nanomedicine research and computational biological analysis, Tehreem Sohail contributes to evolving biomedical research areas including targeted drug delivery and immunogenic epitope prediction. Her interdisciplinary approach reflects the growing importance of integrating laboratory experimentation with data-driven computational methodologies in biomedical innovation.

References

  1. Elsevier. (n.d.). Scopus author details: Tehreem Sohail, Author ID 58508924300. Scopus.https://www.scopus.com/authid/detail.uri?authorId=58508924300
  2. ORCID. (n.d.). ORCID record for Tehreem Sohail.https://orcid.org/0000-0002-2996-9152
  3. Heliyon Journal. (2023). Bioinformatics-based prediction and screening of immunogenic epitopes of Toxoplasma gondii rhoptry proteins.https://www.cell.com/heliyon/home

Ali Motie Nasrabadi | Biomedical Engineering | Best Researcher Award

Prof. Ali Motie Nasrabadi | Biomedical Engineering | Best Researcher Award

Professor at Shahed University, Iran

Prof. Ali Motie Nasrabadi is a renowned academic and researcher in the field of Biomedical Engineering, specializing in the intelligent processing of EEG signals, computational neuroscience, and artificial intelligence in healthcare applications. He earned his Ph.D. in Biomedical Engineering from Amirkabir University of Technology in 2004, where his research focused on evaluating consciousness and hypnosis depth through EEG signal analysis. With a career spanning decades, Prof. Nasrabadi has contributed extensively to EEG/ERP signal processing, nonlinear and chaotic systems, and physiological modeling. He has published over 100 peer-reviewed papers and continues to influence the fields of biomedical signal processing and neuroscience.

Profile

Education

Prof. Ali Motie Nasrabadi has a distinguished academic background in Biomedical Engineering, with his education centered at the Amirkabir University of Technology in Tehran, Iran. He earned his Ph.D. in Biomedical Engineering in March 2004, with a dissertation titled “Quantitative and Qualitative Evaluation of Consciousness Variation and Depth of Hypnosis through Intelligent Processing of EEG Signals.” His doctoral research focused on advanced signal processing techniques applied to biomedical data. Prior to that, he completed his M.Sc. in Biomedical Engineering in September 1998, where he specialized in the “Design and Implementation of an 8-channel PC-Based Electroencephalograph.” This work demonstrated his early interest in biomedical instrumentation and signal analysis. Prof. Nasrabadi began his academic journey with a B.Sc. in Electronic Engineering in February 1994, focusing on the “Design and Implementation of Control of Satellite Dish to Get Better Signal.” His strong foundation in electronic engineering and biomedical systems has been integral to his success in applying engineering principles to healthcare challenges.

Professional Experience

Prof. Ali Motie Nasrabadi has had a distinguished career across both academic and industrial sectors. He has served as the Vice Chancellor for Support and Resource Management at Shahed University from 2017 to 2021, where he played a pivotal role in overseeing resource management. Prior to this, he was the Director General of Equipment at Shahed University, a position he held from 2004 to 2021. His expertise in biomedical signal processing has led to consultancy roles, including being an EEG Signal Processing Consultant at the National Brain Mapping Laboratory (NBML) since 2016. In this capacity, he has also designed and organized brain signal processing workshops at NBML. Prof. Nasrabadi has been actively involved in industrial and technology consulting as well. Since 2014, he has been a Technology and E-commerce Consultant at Shenasa Venture Capital and Trigup Accelerator. Earlier in his career, he worked as a researcher at the Research Center for Intelligent Signal Processing (RCISP) from 2001 to 2006 and the Laser and Optical Group at the Research Center for Science and Technology in Medicine (RCSTIM) from 1998 to 2004. His wide-ranging experience reflects his strong influence in both academia and industry, particularly in the fields of biomedical engineering and signal processing.

Research Interest

Prof. Ali Motie Nasrabadi’s research interests are deeply rooted in the intersection of biomedical engineering and signal processing. His primary focus is on artificial intelligence in healthcare applications, where he explores the potential of AI to enhance medical diagnostics and treatments. He is also heavily involved in computational neuroscience, studying the brain’s complex systems through computational models. Prof. Nasrabadi specializes in chaotic and nonlinear signal processing, applying advanced techniques to understand irregular biological signals. A significant portion of his research is dedicated to the recording and processing of EEG/ERP/LFP/ECoG signals, where he analyzes brain activity patterns for medical and cognitive insights. Additionally, he is interested in the modeling of physiological systems, where he creates mathematical representations of biological processes to better understand and predict their behavior. This broad array of research areas positions Prof. Nasrabadi as a leading figure in applying advanced computational methods to solve complex challenges in healthcare and neuroscience.

Research Skills

Prof. Ali Motie Nasrabadi possesses a diverse set of skills that span across various domains of biomedical engineering and computational analysis. He is an expert in MATLAB and C programming, which he uses for designing and implementing algorithms for signal processing and neural network modeling. His proficiency with EEGLAB and SPM software makes him adept at processing and analyzing EEG and brain signals, essential for neuroscience research. Additionally, Prof. Nasrabadi is skilled in SPSS, which he uses for statistical data analysis, allowing him to interpret complex biomedical data. His deep understanding of chaos theory and nonlinear dynamics further complements his expertise, enabling him to analyze and quantify irregular physiological signals. These technical and computational skills are integral to his contributions in fields such as artificial intelligence, signal processing, and healthcare.

Award and Recognition

Prof. Ali Motie Nasrabadi has received several awards and recognitions throughout his distinguished academic and research career. He achieved First Rank in his B.Sc. program from the Department of Electrical Engineering at Amirkabir University of Technology, with an impressive average score of 18.16 out of 20. Similarly, he was awarded First Rank in his M.Sc. program from the Department of Biomedical Engineering at Amirkabir University of Technology, with an outstanding average score of 18.63 out of 20. His significant contributions to the field of biomedical engineering, particularly in signal processing and artificial intelligence applications, are reflected in his high H-index of 31 in Google Scholar and H-index of 23 in Scopus, underscoring the impact of his research in the global scientific community.

Conclusion

Considering Prof. Ali Motie Nasrabadi’s extensive academic achievements, innovative research in biomedical signal processing, significant publication record, industry-related activities, and leadership roles, he is highly suitable for the Research for Best Researcher Award. His work has had a profound impact on the field of biomedical engineering, particularly in the analysis and processing of EEG signals, making him a deserving candidate for this prestigious recognition.

Publications Top Notes

  • Title: EEG Classification of ADHD and Normal Children Using Non-linear Features and Neural Network
    • Citations: 220
    • Year: 2016
  • Title: Detecting Driver Mental Fatigue Based on EEG Alpha Power Changes During Simulated Driving
    • Citations: 153
    • Year: 2015
  • Title: A New Automatic Sleep Staging System Based on Statistical Behavior of Local Extrema Using Single Channel EEG Signal
    • Citations: 110
    • Year: 2018
  • Title: Determining Fault’s Type and Accurate Location in Distribution Systems with DG Using MLP Neural Networks
    • Citations: 105
    • Year: 2009
  • Title: A Review on EEG Signals Based Emotion Recognition
    • Citations: 103*
    • Year: 2018
  • Title: The Emotion Recognition System Based on Autoregressive Model and Sequential Forward Feature Selection of Electroencephalogram Signals
    • Citations: 83
    • Year: 2014
  • Title: EEG-based Mental Task Classification: Linear and Nonlinear Classification of Movement Imagery
    • Citations: 69
    • Year: 2006
  • Title: Emotion Classification Through Nonlinear EEG Analysis Using Machine Learning Methods
    • Citations: 68
    • Year: 2018