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Join us for exciting plenary sessions at the 5th International Statistical Conference 2021 (ISM-V 2021).

Academic Plenary

Plenary Session:


Professor Christian Martin Hennig

Professor at Department of Statistical Sciences “Paolo Fortunati”
University of Bologna, Italy

Testing in Models that are Not True


The starting point of my presentation is the apparently popular idea that in order to do hypothesis testing (and more generally frequentist model-based inference) we need to believe that the model is true, and the model assumptions need to be fulfilled. I will argue that this is a misconception. Models are, by their very nature, not “true” in reality. Mathematical results secure favourable characteristics of inference in an artificial model world in which the model assumptions are fulfilled. For using a model in reality we need to ask what happens if the model is violated in a “realistic” way. One key approach is to model a situation in which certain model assumptions of, e.g., the model-based test that we want to apply, are violated, in order to find out what happens then. This, somewhat inconveniently, depends strongly on what we assume, how the model assumptions are violated, whether we make an effort to check them, how we do that, and what alternative actions we take if we find them wanting. I will discuss what we know and what we can’t know regarding the appropriateness of the models that we “assume”, and how to interpret them appropriately, including new results on conditions for model assumption checking to work well, and on untestable assumptions. 

Plenary Session:

collocated event  ISMI2021

Professor Graeme Wake

Adjunct Professor of Industrial Mathematics, Department of Mathematical Sciences, Auckland University of Technology, New Zealand

Sustainable Farming: Monitoring Catchment Pollution


Many agricultural projects begin by making sense of data, which has been collected in a (sometimes) arbitrary fashion without some real goal or purpose, and most likely the reason for its collection is not very clear.  It is very important to know what is wanted and what is needed to understand before data is assembled. Therefore, having a pre-determined model is important.

In many circumstances quite basic statistical techniques are used by practitioners, who are often unfamiliar with the recent agricultural systems-techniques now available internationally to understand, use and process this data. Often few attempts are made to track “cause- to effect”,


Industrial Plenary

 Industry Plenary Session

Dr. Dzaharudin Mansor

 National Technology Officer
Microsoft (Malaysia) Sdn. Bhd.

Intensifying Tech Intensity: Staying Relevant and Succeeding in The 4th Industrial Revolution


Data and AI is accelerating the 4th Industrial Revolution, but COVID-19 has forced upon us digital transformation much sooner than expected. While our customers today need to continue run their matured business efficiently and successfully, it is no longer an option for them to continuously embark on bold and rapid innovation to seek new disrupt or protect against being disrupted. This requires companies to leverage on the democratized digital platforms to enable them to engage the modern customers effectively and optimally, while constantly exploring new business models in ways that manages the risks. In addition, the people need to have the right skills to harness the value of data using the digital platforms. The core body of knowledge in STEM plays a central role data science that enables organizations to unlock the power of Data and AI. With the fast-changing use of technology, it is important for all of us to strengthen the relatively timeless fundamentals, and supplement these with applied skills that we need to constantly learn to be successful in this new world. This interplay of technology adoption and skilling is we term as “Tech Intensity” which is needed by all organizations to stay relevant and succeed in this new world.


Industry Plenary Session

Ts. Dr. Mohamed Ackiel Mohamed  

Senior Vice President, Special Projects Serba Dinamik Group Bhd.

Innovation: The Inevitable Process


This presentation discusses about the very meaning of innovation, understating its relevance and implementation in the current scenario. It also shares some typical types of innovations and example study cases with actual market experience sharing along the lines of Innovation in products, services, marketing, business models, process as well as organizational. Indeed, innovation is inevitable, hence, innovate or you will evaporate.


Department of Mathematical Sciences,

Faculty of Science, UTM,

81310 Johor Bahru,

Johor, Malaysia

+607-553 2715