Dr. Riasat Azim

Dr. Riasat Azim

Assistant Professor, Dept. of CSE

ROOM: 337(1-3) A

PABX: 5114

Email: riasat@cse.uiu.ac.bd

Education

Ph.D. Computer Science & Technology, Hunan University, Changsha, Hunan, China.

M.Sc. Engg. Computer Science and Technology,  Wuhan University of Technology, Wuhan, Hubei, China.

B.Sc. Engg. Computer Science and Engineering,  Khulna University, Bangladesh.

Higher Secondary Certificate: Cantonment Public School & College, Parbatipur, Dinajpur.

Secondary School Certificate: Cantonment Public School & College, Parbatipur, Dinajpur.

Research Interest

Research Interest
Single-Cell RNA-Sequence, Genetics, Biological Networks, Genomics, Medical Computing, DNA Methylation, Deep Neural Networks, Cancer, Belief Networks, Bioinformatics, Diseases, Evolutionary Computation, Genetic Algorithms, Optimization, Probability, Tumors, Pattern Classification, Molecular Biophysics, Support Vector Machines, Proteins, Cellular Biophysics.

Ongoing Projects

  • Deep Neural Network based Cancer Prediction from RNA-seq.
  • Cellular Heterogeneity and Single-cell lineage Analysis using single-cell RNA-seq.
  • Spatial transcriptome profiling and Heterogeneity Analysis.

Professional Experiences

• August 2012 – September 2014 : Software Engineering, SmartAspects, Dhaka, Bangladesh.

• June 2015 – March 2016 Teaching Assistant, Wuhan University of Technology, Wuhan, Hubei, P.R. China.

• July 2016 – August 2017: Data Analyst & software engineer, S3Innovate Pte. Ltd., Singapore.

• May 2021 – December 2022: Lecturer, Computer Science & Engineering Northern University Bangladesh, Bangladesh.

 

Technical Expertise

Bioinformatics

Introduction to Bioinformatics, Statistical Analysis in Bioinformatics, Introduction to Bioconductor: Annotation and Analysis of Genomes and Genomic Assays, Genome data science. Experience with next-generation sequencing tools and techniques, statistics and bioinformatics, relational databases, and data mining. Also, have expertise on

  • miRNA disease Association.
  • Single Cell RNA-Sequence analysis.
  • Methylation analysis.
  • Differential gene expression analysis.
  • Spatial Transcriptome.

Programming Languages & Systems

  • R, Python, .Net, C#, Java SE, Java EE, Angular JS, C, Java Script, Ajax, C++, LATEX,
  • SQL, MySQL.
  • Windows, Linux, Ubuntu.

Statistics

Good understanding of biostatistical methodology and tools. Excellent statistical analysis skills of high-throughput biological data, including RNA-seq, protein array and Illumina Methylation Assay.

Artificial Intelligence & Machine Learning

Extensive working knowledge of working with Artificial Intelligence and Machin learning algorithms such as deep convolutional network, artificial neural network, support vector machine, component analysis, attribute reduction, regression, clustering and classification algorithms.  Experience with Algorithms development and Scientific computing. Hands-on experience in developing Bioinformatics Analysis Algorithms for sequencing data analysis using Artificial Intelligence and Machin learning algorithm.

Application & Tools

  • David: Functional Annotation Bioinformatics Microarray Analysis
  • GSEA: Gene Set Enrichment Analysis(GSEA)
  • Cytoscape: complex network visualization.
  • G Profiler.
  • Kaplan Meier plotter.
  • DrugMap

General Capabilities

Algorithm development with a particular focus on performance; automated, database-assisted or custom bioinformatics pipeline-controlled evaluation of complex biological data; data visualization; automated statistical evaluation.

Publication

Journal Papers

2025

CoDNet: Controlled Diffusion Network for Structure Based Drug Design

Computational BiologyDeep Learning

Publication: Bioinformatics Advances

Author List: Riasat Azim

GBDTSVM: Combined Support Vector Machine and Gradient Boosting Decision Tree Framework for efficient snoRNA-disease association prediction

Computational Biology

Publication: Computers in Biology and Medicine

Author List: Ummay Maria Muna, Shanta Biswas, Fahim Hafiz, Riasat Azim

Optimizing stability of heart disease prediction across imbalanced learning with interpretable Grow Network

Artificial Intelligence

Publication: Computer Methods and Programs in Biomedicine

Author List: Simon Bin Akter, David Eisenberg, Sumya Akter, Riasat Azim, Md. Mahadi Hasan, Tanmoy Sarkar Pias, Rakibul Hasan, Jorge E. Fresneda

FVCM-Net: Interpretable privacy-preserved attention driven lung cancer detection from CT scan images with explainable HiRes-CAM attribution map and ensemble learning

Artificial Intelligence

Publication: Biomedical Signal Processing and Control

Author List: Abu Sayem Md. Siam, Sayed Hossain Jobayer, Riasat Azim, Md. Mehedi Hasan, Md Muzadded Chowdhury, Fahim Hafiz, Yeasir Arafat

2023

A patient-specific functional module and path identification technique from RNA-seq data

Computational BiologyNetworking

Publication: Computers in Biology and Medicine

Author List: Dr. Riasat Azim

Conference Papers

2024

Deep Multi-Modal Approach for Protein Function Prediction and Classification

Computational BiologySignal Processing for Biomedical Applications

Conference: 2024 6th International Conference on Electrical Engineering and Information & Communication Technology

Author List: Riasat Azim

ENRNN-AU-Net: A Hybrid Deep Learning Model to Classify and Segment Histopathology Images of Breast Cancer

Conference: Advances in Computing,Communication, Electrical, and Smart Systems (iCACCESS)

Author List: Riasat Azim