Dr. Shahid Akbar | Computer Science | Best Researcher Award

Dr. Shahid Akbar currently serves as a Postdoctoral Fellow at the IFFS, University of Electronic Science and Technology of China, where he is engaged in advanced research in bioinformatics and artificial intelligence. Prior to this, he was a Lecturer in the Department of Computer Science at Abdul Wali Khan University Mardan, Pakistan, from August 2015 to June 2023, where he taught various undergraduate courses and contributed to the academic development of students in the field. Before that, he held a similar position at the Government College of Management Sciences in Swabi, Pakistan, from January 2012 to August 2015, where he began his academic career. Through these roles, Dr. Akbar has built a solid foundation in teaching and research, fostering a strong interest in the application of computational methods to solve complex scientific problems.

Research Interest

Dr. Shahid Akbar’s research interests lie at the intersection of bioinformatics and artificial intelligence. He specializes in machine learning, deep learning, pattern recognition, and neural networks, with a particular focus on developing intelligent computational models for identifying anticancer peptides.

Technical Skills

Dr. Akbar is proficient in various programming languages and tools, including Python, Keras, TensorFlow, SQL Server, R, MATLAB, Spark, and Hadoop. His expertise extends to data warehousing and advanced Java programming.

Awards and Distinctions

OIC Scholarship (3 years)

AWKUM Talented PhD Students Scholarship

Courses Taught

Dr. Akbar has taught a range of undergraduate courses, including:

Machine Learning

Data Structures and Algorithms

Introduction to Programming

Pattern Recognition

Object-Oriented Programming

Data Mining and Warehousing

Artificial Intelligence

Junior Project/Graduate Project

Top Notable Publications

Hybrid Residue Based Sequential Encoding Mechanism with XGBoost Improved Ensemble Model for Identifying 5-Hydroxymethylcytosine Modifications

Authors: Uddin, I., Awan, H.H., Khalid, M., Abdolrasol, M.G.M., Alghamdi, T.A.H.

Journal: Scientific Reports

Year: 2024

Volume: 14

Issue: 1

Article Number: 20819

Citations: 0

StackedEnC-AOP: Prediction of Antioxidant Proteins Using Transform Evolutionary and Sequential Features Based Multi-Scale Vector with Stacked Ensemble Learning

Authors: Rukh, G., Akbar, S., Rehman, G., Alarfaj, F.K., Zou, Q.

Journal: BMC Bioinformatics

Year: 2024

Volume: 25

Issue: 1

Article Number: 256

Citations: 0

Deepstacked-AVPs: Predicting Antiviral Peptides Using Tri-Segment Evolutionary Profile and Word Embedding Based Multi-Perspective Features with Deep Stacking Model

Authors: Akbar, S., Raza, A., Zou, Q.

Journal: BMC Bioinformatics

Year: 2024

Volume: 25

Issue: 1

Article Number: 102

Citations: 17

AIPs-DeepEnC-GA: Predicting Anti-Inflammatory Peptides Using Embedded Evolutionary and Sequential Feature Integration with Genetic Algorithm Based Deep Ensemble Model

Authors: Raza, A., Uddin, J., Zou, Q., Alghamdi, W., Liu, R.

Journal: Chemometrics and Intelligent Laboratory Systems

Year: 2024

Volume: 254

Article Number: 105239

Citations: 0

Comprehensive Analysis of Computational Methods for Predicting Anti-Inflammatory Peptides

Authors: Raza, A., Uddin, J., Akbar, S., Zou, Q., Ahmad, A.

Journal: Archives of Computational Methods in Engineering

Year: 2024

Volume: 31

Issue: 6

Pages: 3211–3229

Citations: 3

DeepAVP-TPPred: Identification of Antiviral Peptides Using Transformed Image-Based Localized Descriptors and Binary Tree Growth Algorithm

Authors: Ullah, M., Akbar, S., Raza, A., Zou, Q.

Journal: Bioinformatics

Year: 2024

Volume: 40

Issue: 5

Article Number: btae305

Citations: 9

iAFPs-Mv-BiTCN: Predicting Antifungal Peptides Using Self-Attention Transformer Embedding and Transform Evolutionary Based Multi-View Features with Bidirectional Temporal Convolutional Networks

Authors: Akbar, S., Zou, Q., Raza, A., Alarfaj, F.K.

Journal: Artificial Intelligence in Medicine

Year: 2024

Volume: 151

Article Number: 102860

Citations: 18

Blockchain-Based Logging to Defeat Malicious Insiders: The Case of Remote Health Monitoring Systems

Authors: Javed, H., Abaid, Z., Akbar, S., Alkahtani, H.K., Raza, A.

Journal: IEEE Access

Year: 2024

Volume: 12

Pages: 12062–12079

Citations: 2

Conclusion