Biography
Prof. Dr. Md. Shamim Akhter, SMIEEE
Dept. of Computer Science and Engineering
Ahsanullah University of Science and Technology
Bangladesh
Title
Digital Transformation & Industry 4.0 using AI-Driven Intelligent and Scalable Systems
Abstract
The rapid evolution of digital technologies is transforming industries worldwide, moving organizations beyond simple digitization and digitalization toward comprehensive digital transformation. This transformation is a key driver of business growth, operational efficiency, innovation, and competitiveness. At its core, digital transformation is closely aligned with the vision of Industry 4.0, where smart factories leverage interconnected systems, intelligent automation, and real-time decision-making to create agile and efficient production environments.
Achieving this vision requires significant research efforts in the development of scalable AI-driven frameworks, the seamless integration of Cyber-Physical Systems (CPS) with intelligent analytics, and the design of sustainable and resource-efficient solutions capable of addressing real-world challenges. These research implications form the foundation of next-generation intelligent systems that support automation, optimization, and data-driven decision-making across various sectors.
The Applied Intelligence System and Information Processing (AISIP) Laboratory contributes to these research challenges through several interconnected research domains. Its work on AI-Driven Industrial Automation and Smart Manufacturing focuses on intelligent quality control, predictive analytics, and manufacturing optimization. Research in IoT, Cyber-Physical Systems, and Edge Computing enables real-time monitoring, distributed intelligence, and scalable system architectures. The laboratory also develops AI-Driven Decision Support Systems that transform data into actionable insights for diverse application domains.
Furthermore, AISIP explores Multi-Agent AI Systems to address complex societal challenges. Notable applications include Intelligent Hospital Workflow Optimization in Bangladesh, which aims to improve healthcare efficiency and resource utilization, and AI-enabled Financial Systems for an Inclusive Agro-Economy, which support financial accessibility and decision-making for agricultural stakeholders.
The presentation concludes by discussing the key challenges and risks associated with these research directions, including scalability, data quality, interoperability, security and privacy concerns, ethical implications of AI, infrastructure limitations, and the need for sustainable deployment strategies. Addressing these challenges is essential for realizing the full potential of Digital Transformation and Industry 4.0 in both industrial and societal contexts.
Key Message: Digital Transformation and Industry 4.0 are not merely technological upgrades; they represent a paradigm shift toward intelligent, interconnected, and scalable systems. Through research in AI, CPS, IoT, and multi-agent systems, AISIP is contributing to the development of innovative solutions that support sustainable economic growth and societal advancement.
Biography
Prof. Dr. Md. Shamim Akhter is a Professor of Computer Science and Engineering at Ahsanullah University of Science and Technology (AUST), Bangladesh, and an accomplished academic leader with more than two decades of experience in higher education, research, and institutional development. He has held several key leadership positions, including Head of Department, Director of IQAC, Graduate Program Head, and Chair of major academic committees, contributing significantly to academic governance, quality assurance, curriculum innovation, and research capacity building.
He earned his PhD from Tokyo Institute of Technology, Japan, and completed postdoctoral research at the National Institute of Informatics (NII), Japan under the JSPS Fellowship program. These international experiences have significantly shaped his perspective on global higher education systems, research ecosystems, and innovation-driven academic models. His research focuses on Artificial Intelligence, Machine Learning, IoT, Intelligent Systems, and High-Performance Computing, with more than 100 publications in IEEE, Springer, Elsevier, and other indexed venues.
Prof. Akhter has led and contributed to national and international research projects, supervised more than 50 postgraduate theses, participated in PhD supervision, and mentored over 300 undergraduate research projects. He is an IEEE Senior Member and has received several distinctions, including the JSPS Postdoctoral Fellowship, Asia Top 100 Scholar recognition, and Best Paper awards. Prof. Akhter is widely recognized for his contributions to research, academic leadership, and institutional transformation. His professional vision centers on fostering excellence in teaching and research, strengthening international collaboration, promoting digital transformation in higher education, and developing universities as engines of innovation, societal impact, and sustainable national development.
Biography
Dr. Ahmedur Rahman Shovon
Postdoctoral Appointee
Mathematics and Computer Science Division
Argonne National Laboratory, USA
Title
High-Performance Computing for Science in the Age of AI
Abstract
Computation has become a primary way of doing science, alongside experiment and theory. Fields from cosmology to drug design now depend on calculations that would occupy an ordinary computer for centuries, and some questions, such as how a fusion reactor will behave before one is built, can be studied no other way. Two changes brought this about. Processors stopped becoming faster about twenty years ago and became parallel instead, so scientific software had to be rewritten to run on thousands of processors at once. More recently machine learning arrived on the same hardware, and training a model and running a simulation now compete for the same machines.
Using the supercomputers at Argonne National Laboratory as the example, this talk describes what these machines are, what science they make possible, and how research groups get access to them. It covers the move from writing programs to directing software agents that plan and run computations on their own, and it closes on a constraint now shaping the field, which is that the energy a calculation consumes matters as much as the time it takes.
Biography
Dr. Ahmedur Rahman Shovon is a Postdoctoral Appointee in the Mathematics and Computer Science Division at Argonne National Laboratory. His research lies at the intersection of high-performance computing (HPC) and data analytics, focusing on system software and runtime infrastructures for energy-efficient, large-scale scientific data streaming workflows.
He received his Ph.D. in Computer Science in 2025 from University of Illinois Chicago, where he developed one of the first multi-node, multi-GPU Datalog engine and applied topological data analysis to brain imaging. His publications span computing and interdisciplinary venues, including ICS, ASPLOS, USENIX ATC, IEEE Access, and Human Brain Mapping.
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