Dr Emma Holian is a lecturer and researcher in Statistical Science and Learning.Statistical modelling interests include Mixture modelling to cluster longitudinal data profiles and to model the group features via generalized linear mixed models and penalized smoothing models, leading to the formulation of the Regression Cluster Model (RCM). This includes analysis into capability of the RCM to handle missing data within profiles or profiles measured at variable time-points. Extensions of the RCM have been formulated to longitudinal profiles measured on discrete or categorical scales, P-Splines, and mixed effects model clustering with an extension to multivariate applications.Recent biostatistics applications include building prognostic models in Breast Cancer, applications in Genomics Data Science, modelling composition response data for Blood Clot Composition. Interests also include Climate trend modelling and statistical challenges in environmental impact studies, in particular a recent focus on groundwater, sets some interesting features in left-censored values.Dr Emma Holian also is prominent in initiatives that improve approaches to Mathematical and Statistical learning through Education and Outreach, Curriculum Design, and Student Support, having experience within a number of key Directorship roles.

With experience in supporting a wide genre of students with different interests and backgrounds, this experience in statistical learning spans across probability theory, probability models, statistical inference and modelling, for undegraduates and postgraduates in Science, Arts, Engineering and Commerce programmes.Student experience in statistical learning is supported with applications MINITAB, or SPSS,R programming,andRmarkdownreport-writing. Activities in module development also include practiced initiatives in success in online-distance learning and success in blended learning, activity workshops.In addition to module delivery of statistics content Emma has committed roles supporting learning, teaching, assessment, and programme developments, important and relevant to programme design and management and student experience. These include:College of Science, Learning, Teaching and Assessment Committee 2018-2020, and continuing in that role throughout the college merger, i.e. the College of Science and Engineering, Education and Students Committee , 2020-present.Programme Director GY301 B.Sc. Undenominated Science, 2021-present (cohort size approx. 300) Programme Director B.Sc. Mathematical Science, 2008-2018 (cohort size approx. 25)CÉIM peer-shared learning, Science Academic Lead, 2021-present.CoSE Extenuating Circumstances Submissions Committee, 2021-present.Designing Futures Work-package 1 Implementation team and Trans-Disciplinary Modules Approval Committee, 2021-present.Director of Learning, Teaching and Assessment (LTA), School of Mathematical and Statistical Sciences, 2018-2021, member of School LTA committee from 2008.Hamilton Prize assessment committee, 2018-2022Funded Initiatives include:SATLE 2019, Initiative Title: Teaching, Learning, and Engagement in Science amp; Engineering a Collective Endeavour , Member, sub-project: T eaching Practices Inventory, 2021. SATLE 2021, Transforming Teaching and Learning for Student Success - Seed Funding Scheme, Developing Interactive Online Learning and Assessment Tools for Statistical Science , 5000 euro.Personal Development: Postgraduate Certificate in Teaching amp; Learning in Higher Education, 2023