Faculty Profile

Shatabda, Swakkhar, Ph.D.

Associate Professor Email : swakkhar@cse.uiu.ac.bd

Swakkhar Shatabda is working as an Associate Professor in the Department of Computer Science and Engineering at United International University (UIU), Bangladesh. He served as Undergraduate Program Coordinator at the same department from 2014 to 2021. He is currently working as an active member in the departmental outcome based education (OBE) coordination committee. He achieved his Ph. D degree from the Institute for Integrated and Intelligent Systems (IIIS), Griffith University in 2014. His thesis was titled “Local Search Heuristics for Protein Structure Prediction”. He completed his BSc. in Computer Science and Engineering from Bangladesh University of Engineering and Technology (BUET) in 2007.

In the Board of Accreditation for Engineering and Technical Education (BAETE), Bangladesh Dr. Shatabda is a member of the coordination committee and also served in the Evaluation Team for accreditation visits. He actively participated in the organization of the first and second International Symposium on Quality Assurance in Engineering Education through Accreditation. He has also got training on outcome based education in several training programs and seminars organized by UIU, BAETE and University Grants Commision (UGC).

Research interest of Dr. Shatabda includes bioinformatics, optimization, search and meta-heuristics, data Mining, constraint programming, approximation Algorithms and graph theory. He works broadly in the area of prediction of functions and structures of proteins and genes. More specifically, he has been applying machine learning and optimization techniques to solve related problems in the field of protein function prediction, protein structure prediction, post translational modification, single cell rna-seq and gene or genomic functional analysis. His focus is in developing novel computational strategies that include machine learning algorithms, feature extraction methods and artificial intelligence guided search algorithms that could be applied to solve a broader range of problems in the relevant area. He has been working to develop effective heuristics, metaheuristics and guiding strategies for local search algorithms, to develop faster algorithms for genomic analysis and protein structure comparison. He has an extended interest in developing and applying deep learning techniques in the relevant fields. In this area, his work is mostly focused on applying transfer learning, multi-task learning, proposing novel stacked and cascaded architectures and generative adversarial networks for synthetic data generation to solve a wide range of problems in the relevant fields aforementioned.

Dr. Shatabda has a number of quality publications in international conferences and journals. He has been serving as an active reviewer for several journals and has been involved in the technical program committee of several International conferences. He has presented his work in formost conferences like AAAI and ACM-BCB. He has published in highly esteemed journals like BMC Bioinformatics, Bioinformatics (Oxford University Press), Scientific Reports (Nature), Proteins (Wiley) and so on. He has joined the editorial board of PLOS One journal as an academic editor. He is awarded a research fund by the Institute for Advanced Research, UIU for his research project on gap filling in genome assembly. He has also served as reviewer in the Grant for Advanced Research for Education (GARE) of the Ministry of Education, Government of the People’s Republic of Bangladesh. He has been serving as session chairs for international conferences and external examiner of bachelor and masters thesis in several universities. As a research supervisor Dr. Shatabda has supervised 30+ undergraduate research projects and 15+ masters theses. He has also worked in several PhD committees. He is author of two introductory books on computers for children published by University Press Limited, Bangladesh.

Dr. Shatabda has worked as a Graduate Researcher in Queensland Research Laboratory, NICTA, Australia. Prior to entering the teaching line he worked as a Software Engineer in Vonair Inc, Bangladesh.

PhD (2010-2014)
Institute for Integrated and Intelligent Systems (IIIS)
Griffith University.
Thesis Title: Local Search Heuristic for Protein Structure Prediction
Supervisors: Professor Abdul Sattar and Dr. Muhammad Abdul Hakim Newton

BSc (2001-2007)
Department of Computer Science and Engineering (CSE)
Bangladesh University of Engineering and Technology (BUET)
Thesis Supervisor: Professor Masud Hasan

HSC (1999-2001)
Notre Dame College

SSC (1991-1999)
Saint Joseph High School

Bioinformatics (http://brl.uiu.ac.bd/)
Protein Structures
Genome Rearrangement
Phylogenetic Trees
Clustering

AI and Machine Learning
Optimization
Search and Satisfiability
Meta-heuristics
Itemset Mining
Constraint Programming

Algorithm and Complexity
Approximation Algorithms
Graph Theory

Associate Professor (January 2018-Present)
Department of Computer Science and Engineering
United International University
Bangladesh

Undergraduate Program Co-ordinator (November 2014-February 2021)
Department of Computer Science and Engineering
United International University
Bangladesh

Assistant Professor (November 2014-December 2017)
Department of Computer Science and Engineering
United International University
Bangladesh

PhD Student (April 2010 – October 2014)
Institute for Integrated and Intelligent Systems (IIIS)
Griffith University
Australia

Graduate Researcher (April 2010 – September 2014)
Advanced Computational Proteomics Group
Queensland Research Laboratory
National ICT Australia (NICTA)

Lecturer (April 2008- November 2014)
Department of Computer Science and Engineering
United International University
Bangladesh

Software Engineer (November 2007 – April 2008)
NextiGen
Bangladesh

Junior Software Engineer (June 2007 – November 2007)
Vonair Inc.
Bangladesh

For details of the publication list, please visit: Google Scholar

Graduate Courses
Advanced Artificial Intelligence
Computation Biology and Bioinformatics
Deep Learning
Financial Informatics

Undergraduate Courses
Algorithms
Data Structures
Artificial Intelligence
Simulation and Modelling