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X-WR-CALNAME:Institute of Statistical Research and Training
X-ORIGINAL-URL:https://isrt.ac.bd
X-WR-CALDESC:Events for Institute of Statistical Research and Training
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TZID:UTC
BEGIN:STANDARD
TZOFFSETFROM:+0000
TZOFFSETTO:+0000
TZNAME:UTC
DTSTART:20230101T000000
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BEGIN:VEVENT
DTSTART;TZID=UTC:20260305T120000
DTEND;TZID=UTC:20260305T133000
DTSTAMP:20260424T044600
CREATED:20260221T064222Z
LAST-MODIFIED:20260304T100223Z
UID:8957-1772712000-1772717400@isrt.ac.bd
SUMMARY:Applied Statistics and Data Science Seminar on Thursday 05 March 2026
DESCRIPTION:Title: FertiMeter: A Data-Driven Innovation to Address the Reproductive Health Crisis of Polycystic\nOvary Syndrome \nVenue\, date and time: ISRT\, 5 March 2026\, 12:15 pm \nSpeaker: K. M. Tanvir\, Lecturer\, ISRT\, University of Dhaka \nAbstract: \nBackground:\nPolycystic ovary syndrome (PCOS) affects around 12.5% of women in Bangladesh and is a major cause of infertility and pregnancy complications. Although early detection can help manage symptoms and reduce risks\, nearly 70% of women remain undiagnosed due to limited awareness and inadequate access\nto medical care.\nObjectives:\nThis study aims to develop a data-driven machine learning model that predicts the likelihood of PCOS using non-clinical features and to integrate it into a mobile application\, FertiMeter.\nMethods:\nA total of 546 participants\, including 273 women diagnosed with PCOS and 273 without PCOS\, were enrolled in the study. The CatBoost machine learning algorithm was applied to develop a predictive model for PCOS status and the model was incorporated into the FertiMeter mobile application.\nKey Findings:\nUsing eight SHAP-selected non-clinical features\, the CatBoost model achieved an average cross-validated accuracy of 86%.\nConclusions:\nApproximately 6.7 million women in Bangladesh who remain undiagnosed with PCOS can use FertiMeter mobile application to assess their likelihood of having the condition free of cost.
URL:https://isrt.ac.bd/event/applied-statistics-and-data-science-seminar-on-monday-23-february-2026/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20260105T140000
DTEND;TZID=UTC:20260105T150000
DTSTAMP:20260424T044600
CREATED:20260101T042836Z
LAST-MODIFIED:20260101T042836Z
UID:8479-1767621600-1767625200@isrt.ac.bd
SUMMARY:Applied Statistics and Data Science Seminar on Monday 5 January 2026
DESCRIPTION:Title: A Moment-Based Generalization To Post-Prediction Inference \nVenue\, date and time: ISRT\, 5 January 2026\, 2 pm \nSpeaker: Awan Afiaz\, PhD candidate at the Department of Biostatistics\, University of Washington Seattle\, WA\, USA and ISRT alumnus \nAbstract: \nAs artificial intelligence (AI) and machine learning (ML) become increasingly integrated into scientific research\, investigators frequently substitute predicted outcomes for expensive or difficult-to-measure data. However\, treating these AI/ML-generated predictions as true observations can lead to biased estimates and anti-conservative inference. While high predictive accuracy is often assumed to ensure valid downstream inference\, statistical challenges in inference with predicted data (IPD) fundamentally reduce to two sources of error: bias\, when predictions systematically distort relationships among variables\, and variance\, when uncertainty from prediction models is inadequately propagated. Wang et al. (2020) introduced post-prediction inference (PostPI)\, a pioneering method that addresses this challenge by modeling the relationship between predicted and observed outcomes in a small gold-standard dataset to calibrate inference in larger unlabeled samples. PostPI has been influential in formalizing the IPD problem and demonstrating how naive approaches fail to appropriately reflect uncertainty. However\, PostPI relies on a critical assumption: that prediction errors are uncorrelated with covariates of interest. In realistic settings where prediction algorithms exhibit systematic errors related to input features\, this assumption is often violated\, leading to biased parameter estimates and inadequate error control. We revisit PostPI in light of recent methodological advances and propose a moment-based generalization that relaxes this restrictive assumption. Our extension explicitly accounts for the covariance between prediction errors and covariates by incorporating an additional correction term estimated from the labeled dataset. This approach yields unbiased point estimates under standard conditions while incorporating a simple scaling factor that appropriately reflects the contribution of relationship model uncertainty regardless of sample size allocation. Through extensive simulations across three data-generating scenarios\, we demonstrate that our method maintains nominal Type-I error rates and achieves proper coverage probability\, even when the labeled sample is substantially smaller than the unlabeled sample settings where both naive approaches and original PostPI fail. Our work illustrates the classic bias-variance trade-off inherent to IPD’s challenges and confirms that there is no free lunch when substituting predicted outcomes for true measurements.
URL:https://isrt.ac.bd/event/applied-statistics-and-data-science-seminar-on-monday-5-january-2026/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251228
DTEND;VALUE=DATE:20251230
DTSTAMP:20260424T044600
CREATED:20240515T141523Z
LAST-MODIFIED:20250808T171935Z
UID:6653-1766880000-1767052799@isrt.ac.bd
SUMMARY:International Conference on Applied Statistics and Data Science (ICASDS) 2025 on December 28-29\, 2025 
DESCRIPTION:The International Conference on Applied Statistics and Data Science (ICASDS) is scheduled to take place on December 28-29\, 2025\, with a pre-conference workshop on December 27\, 2025. Further details and the conference website\, https://icasds2025.isrt.ac.bd will be available soon. \n 
URL:https://isrt.ac.bd/event/international-conference-on-applied-statistics-and-data-science-icasds-2025-on-december-27-29-2025/
CATEGORIES:conference
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20251227T090000
DTEND;TZID=UTC:20251227T170000
DTSTAMP:20260424T044600
CREATED:20251223T081536Z
LAST-MODIFIED:20251223T081536Z
UID:8443-1766826000-1766854800@isrt.ac.bd
SUMMARY:pre-icasds2025 conference workshops
DESCRIPTION:More is given at https://icasds2025.isrt.ac.bd/home/pre-conference-workshops
URL:https://isrt.ac.bd/event/pre-icasds2025-conference-workshops/
CATEGORIES:workshop
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20251107T090000
DTEND;TZID=UTC:20251206T210000
DTSTAMP:20260424T044600
CREATED:20251013T063712Z
LAST-MODIFIED:20251023T053444Z
UID:8191-1762506000-1765054800@isrt.ac.bd
SUMMARY:Training on Stata for Applied Statistics and Data Science from November 07\,2025
DESCRIPTION:The upcoming Stata training program starts from November 07\, 2025\nRegistration Open!\nFollow the website for details: https://isrt.ac.bd/training/stata/\n 
URL:https://isrt.ac.bd/event/stata-for-applied-statistics-and-data-science-2/
LOCATION:ISRT\, ISRT\, University of Dhaka\, Dhaka\, Bangladesh
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20251027T140000
DTEND;TZID=UTC:20251027T150000
DTSTAMP:20260424T044600
CREATED:20251025T044211Z
LAST-MODIFIED:20251025T044211Z
UID:8255-1761573600-1761577200@isrt.ac.bd
SUMMARY:Applied Statistics and Data Science Seminar on Monday 27 October 2025
DESCRIPTION:Title: Causal Inference with Misclassified Exposure: Correcting the IPW Estimator \nVenue\, time and date: ISRT\, 2:00 pm\, October 27\, 2025 \nSpeaker: Tarikul Islam\, Lecturer\, ISRT\, University of Dhaka \nAbstract:  \nThe inverse probability weighting (IPW) estimator is widely used for estimating the average treatment effect (ATE) in causal inference. However\, the IPW estimator is prone to bias when the exposure variable is misclassified\, even if the misclassification is non-differential. In this paper\, we propose a correction for the IPW estimator using the method of moments (MoM) to account for misclassified exposure. We derive the corrected IPW estimator\, demonstrate its unbiasedness under misclassification\, and evaluate its performance through simulation studies. Furthermore\, we discuss techniques for estimating misclassification probabilities\, including scenarios with and without validation data or exposure replication. We also derive ranges of these probabilities for conducting sensitivity analyses when no gold standard is available. Additionally\, we apply the proposed method to real-world data from the Bangladesh Multiple Indicator Cluster Survey (MICS) 2019 to estimate the causal effect of the wealth index on ICT skills among women aged 15-49\, demonstrating the robustness of our method.
URL:https://isrt.ac.bd/event/applied-statistics-and-data-science-seminar-on-monday-27-october-2025/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20250818T140000
DTEND;TZID=UTC:20250818T153000
DTSTAMP:20260424T044600
CREATED:20250814T042935Z
LAST-MODIFIED:20250814T043120Z
UID:8100-1755525600-1755531000@isrt.ac.bd
SUMMARY:Applied Statistics and Data Science Seminar on Monday August 18\, 2025
DESCRIPTION:Title: Sensor Data Analytics with Wearables and mm-Wave Radars for Digital Health \nVenue\, time and date: ISRT\, 2:00 pm\, August 18\, 2025 \nSpeaker: Shekh Md Mahmudul Islam\, Ph.D.\, Associate Professor in the Department of Electrical and Electronic Engineering at the University of Dhaka and Postdoctoral Fellow in the Department of Biomedical Engineering at Duke University\, USA. \nAbstract:  \nThis talk presents an integrated view of sensor data analytics for digital health\, combining wearable sensing and millimeter-wave (mm-Wave) radar technologies. Beyond hardware innovation\, the focus is on transforming raw physiological signals into actionable insights through advanced signal processing\, feature engineering\, and machine learning. Case studies will include digital biomarker extraction for diabetes monitoring\, continuous identity authentication\, and unobtrusive sleep apnea detection. Key topics include multi-sensor fusion of respiration and heart rate variability (HRV) data\, robust analytics pipelines resilient to noise and motion artifacts\, and the use of interpretable machine learning models for health status prediction. The presentation also covers compliance tracking using the radar sensor framework\, validation under real-world and adversarial conditions\, and the translation of analytics into clinical and remote monitoring applications. The talk concludes with opportunities for collaborative research in scaling sensor analytics for aging populations and chronic disease management.
URL:https://isrt.ac.bd/event/applied-statistics-and-data-science-seminar-on-monday-august-18-2025/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20250817
DTEND;VALUE=DATE:20250818
DTSTAMP:20260424T044600
CREATED:20250730T181252Z
LAST-MODIFIED:20250730T181252Z
UID:8075-1755388800-1755475199@isrt.ac.bd
SUMMARY:Classes for session 2025-2026 will start on August 17\, 2025
DESCRIPTION:
URL:https://isrt.ac.bd/event/classes-for-session-2025-2026-will-start-on-august-17-2025/
CATEGORIES:class
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20250730T103000
DTEND;TZID=UTC:20250730T120000
DTSTAMP:20260424T044600
CREATED:20250730T152011Z
LAST-MODIFIED:20250730T152011Z
UID:8071-1753871400-1753876800@isrt.ac.bd
SUMMARY:128th Birth Anniversary of Qazi Motahar Husain
DESCRIPTION:This is a reminder to attend the program being organized jointly with the Department of Statistics in memory of the Late Professor Qazi Motahar Husain at the TSC tomorrow at 10:30 a.m. The program will be attended by the Honorable Vice-Chancellor\, DU\, as the Chief Guest. Professor Husain was a leading proponent of statistical education and research in Bangladesh and the founder Director of ISRT.  Furthermore\, students who have excelled in their B.S. and M.S. examinations will be awarded by the  Qazi Motahar Husain Foundation.
URL:https://isrt.ac.bd/event/128th-birth-anniversary-of-qazi-motahar-husain/
LOCATION:TSC\, Bangladesh
CATEGORIES:other
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20250727T080000
DTEND;TZID=UTC:20250727T170000
DTSTAMP:20260424T044600
CREATED:20250704T125422Z
LAST-MODIFIED:20250704T125949Z
UID:7991-1753603200-1753635600@isrt.ac.bd
SUMMARY:M.S. Admission Test is on July 27\, 2025
DESCRIPTION:Details are given on the MS admission site https://isrt.ac.bd/academics/admission
URL:https://isrt.ac.bd/event/ms-admission2025/
LOCATION:ISRT\, ISRT\, University of Dhaka\, Dhaka\, Bangladesh
CATEGORIES:other
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20250707T080000
DTEND;TZID=UTC:20250707T170000
DTSTAMP:20260424T044600
CREATED:20250706T163654Z
LAST-MODIFIED:20250706T163654Z
UID:8007-1751875200-1751907600@isrt.ac.bd
SUMMARY:First-year classes begin July 7\, 2025
DESCRIPTION:Classes for first-year students of the 2024–2025 session will commence on July 7\, 2025.
URL:https://isrt.ac.bd/event/first-year-classes-begin-july-7-2025/
CATEGORIES:class
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20250702T100000
DTEND;TZID=UTC:20250702T110000
DTSTAMP:20260424T044600
CREATED:20250701T091824Z
LAST-MODIFIED:20250703T064954Z
UID:7941-1751450400-1751454000@isrt.ac.bd
SUMMARY:Orientation of first-year students for the 2024-25
DESCRIPTION:The orientation of first-year students for the 2024-25 academic session will be tomorrow (Wednesday\, July 2) at 10:00 a.m. The program will take place in the ISRT seminar room.
URL:https://isrt.ac.bd/event/orientation-of-first-year-students-for-the-2024-25/
LOCATION:ISRT Seminar Room (3rd floor)\, Institute of Statistical Research and Training\, University of Dhaka\, Dhaka\, Please Select\, 1000\, Bangladesh
CATEGORIES:other
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20250505T140000
DTEND;TZID=UTC:20250505T153000
DTSTAMP:20260424T044600
CREATED:20250406T053746Z
LAST-MODIFIED:20250501T071751Z
UID:7545-1746453600-1746459000@isrt.ac.bd
SUMMARY:Applied Statistics and Data Science Seminar on Monday May 5\, 2025
DESCRIPTION:Title: Understanding Causality: Rubin’s Potential Outcome Model and Philosophical Perspectives \nVenue\, time and date: ISRT\, 2:00 pm\, May 5\, 2025 \nSpeaker: Nahian Nujhat\, Bushra Chowdhury\, Md. Mutasim Billah\, Faria Rauf Ria\, Maliha Binte Alauddin\, Institute of Statistical Research and Training\, University of Dhaka. \nAbstract:  \nCausal inference focuses on estimating cause-and-effect relationships\, a key challenge in statistics\, where distinguishing association from causation is crucial. In this talk\, we will explore the foundations of causal inference through the lens of Paul W. Holland’s seminal 1986 Journal of the American Statistical Association paper “Statistics and Causal Inference.” \nRubin’s model formalizes causal effects through the potential outcomes framework\, which requires observing both counterfactuals. The two potential outcomes for a unit refer to the outcome that would be observed if the unit receives the treatment and the outcome that would be observed if the unit does not receive the treatment. The fundamental problem of causal inference is–the impossibility of observing both potential outcomes for the same unit\, which can be overcome under some untestable assumptions. \nSeveral philosophers\, such as Hume\, Mill\, and Suppes\, have contributed to understanding causation. Hume emphasized that causation is observed through temporal succession\, contiguity and constant conjunction rather than direct observation\, which led him to be skeptical about causality. Mill believed that experimental inquiry is required to identify causal relationships. Suppes advanced the discussion by introducing a probabilistic theory of causality. These philosophical views are explored in the context of Rubin’s model. \nFinally\, we will address the question of what can be a cause\, arguing that only manipulable factors can be considered causes in the context of experiments. This will lead to a discussion of the limitations of causal inference in observational studies and the importance of distinguishing between attributes and causes.
URL:https://isrt.ac.bd/event/applied-statistics-and-data-science-seminar-on-monday-april-07-2025/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20250310T120000
DTEND;TZID=UTC:20250310T133000
DTSTAMP:20260424T044600
CREATED:20250306T035154Z
LAST-MODIFIED:20250306T035154Z
UID:7503-1741608000-1741613400@isrt.ac.bd
SUMMARY:Applied Statistics and Data Science Seminar on Monday March 10\, 2025
DESCRIPTION:Title: Variational Autoencoder Model for Exploring Latent Spaces in High-Dimensional Datasets \nVenue\, time and date: ISRT\, 12:15 pm\, March 10\, 2025 \nSpeaker: Mashfiqul Huq Chowdhury\, PhD\, Associate Professor at Mawlana Bhashani Science and Technology University \nAbstract:  \nIn this talk\, I will focus on a probabilistic generative model known as the Variational Autoencoder (VAE). The VAE model uses variational Bayes to approximate the intractable posterior distribution over latent variables. I will begin by presenting the derivation of the evidence lower bound (ELBO) and then discuss the optimization procedure of the model. During training\, the VAE learns smooth latent space representations through regularization. This learning paradigm can be applied to various tasks\, including unsupervised clustering\, regression\, and the generation of new instances. To demonstrate its application\, I will showcase how the VAE model can be applied to high-dimensional datasets and highlight the results in terms of clustering performance and sample generation.
URL:https://isrt.ac.bd/event/applied-statistics-and-data-science-seminar-on-monday-march-10-2025/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20250224T140000
DTEND;TZID=UTC:20250224T150000
DTSTAMP:20260424T044600
CREATED:20250222T040452Z
LAST-MODIFIED:20250222T040711Z
UID:7476-1740405600-1740409200@isrt.ac.bd
SUMMARY:Applied Statistics and Data Science Seminar on Monday February 24\, 2025
DESCRIPTION:Venue\, time and date: ISRT\, 2:00 pm\, February 24\, 2025 \nSpeaker: Humayera Islam\, PhD\, Postdoctoral Scholar in Precision Health at the University of Chicago \nTalk 1 \nTitle: From Statistical Models to LLMs: The Evolution of Feature Representation in Predictive Modeling \nAbstract: \nWith the digitization of healthcare and public health systems\, data collection has expanded far beyond traditional numerical and categorical formats to include complex modalities such as natural language (e.g.\, clinical notes)\, medical images (e.g.\, radiology scans)\, genetic data (e.g.\, omics)\, and temporally extensive time-series data (e.g.\, electronic health records). This expansion was driven by advancements in data storage capacity\, enabling the collection of massive\, high-dimensional datasets. As the size and complexity of data grew\, so did the need for more sophisticated feature representation techniques to effectively capture the underlying patterns for predictive tasks to enhance clinical decision making. This seminar traces the evolution of feature representation from traditional statistical models\, which relied on manual feature engineering\, to machine learning models that automated feature extraction\, to deep learning architectures that learned hierarchical and temporal features\, and finally to Large Language Models (LLMs) that leveraged self-attention mechanisms for contextual sequence modeling. The aim is to spark curiosity and inspire students to explore how to effectively handle these diverse data modalities and harness the power of advanced models for innovative research projects. \nTalk 2 \nTitle: Pathways to Growth: Preparing for Data Science and Informatics Graduate Programs in the US \nAbstract: \nThis talk offers a comprehensive roadmap for students aspiring to pursue graduate programs in data science and informatics in the US. It will cover the key skill sets essential for enhancing data science expertise\, including domain knowledge\, emerging methodologies\, technical proficiency\, and leadership in professional development. Additionally\, students will be provided with valuable resources such as open-source datasets and learning platforms to strengthen these skills during their time at ISRT and effectively prepare for graduate studies.
URL:https://isrt.ac.bd/event/applied-statistics-and-data-science-seminar-on-monday-february-24-2025/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20250204T113000
DTEND;TZID=UTC:20250204T130000
DTSTAMP:20260424T044600
CREATED:20250201T174134Z
LAST-MODIFIED:20250201T174134Z
UID:7409-1738668600-1738674000@isrt.ac.bd
SUMMARY:Applied Statistics and Data Science Seminar on Tuesday February 4\, 2025
DESCRIPTION:Title: Imputation-Based Q-Learning for Optimizing Dynamic Treatment Regimes with Right-Censored Survival Outcome \nVenue\, time and date: ISRT\, 11:30 pm\, February 4\, 2025 \nSpeaker: Abdus S. Wahed\, PhD\, Professor of Biostatistics\, Department of Biostatistics and Computational Biology\, University of Rochester\, USA \nAbstract: \nQ-learning has been one of the most commonly used methods for optimizing dynamic treatment regimes (DTRs) in multistage decision-making. Right-censored survival outcome poses a significant challenge to Q-Learning due to its reliance on parametric models for counterfactual estimation which are subject to misspecification and sensitive to missing covariates. In this paper\, we propose an imputation-based Q-learning (IQ-learning) where flexible nonparametric or semiparametric models are employed to estimate optimal treatment rules for each stage and then weighted hot-deck multiple imputation (MI) and direct-draw MI are used to predict optimal potential survival times. Missing data are handled using inverse probability weighting and MI\, and the nonrandom treatment assignment among the observed is accounted for using a propensity-score approach. We investigate the performance of IQ-learning via extensive simulations and show that it is more robust to model misspecification than existing Q-Learning methods\, imputes only plausible potential survival times contrary to parametric models and provides more flexibility in terms of baseline hazard shape. Using IQ-learning\, we developed an optimal DTR for leukemia treatment based on a randomized trial with observational follow-up that motivated this study. \nPaper link: \nImputation-Based Q-Learning for Optimizing Dynamic Treatment Regimes with Right-Censored Survival Outcome | Biometrics | Oxford Academic 
URL:https://isrt.ac.bd/event/applied-statistics-and-data-science-seminar-on-tuesday-february-4-2025/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20250127T140000
DTEND;TZID=UTC:20250127T150000
DTSTAMP:20260424T044600
CREATED:20250125T043720Z
LAST-MODIFIED:20250125T043905Z
UID:7375-1737986400-1737990000@isrt.ac.bd
SUMMARY:Applied Statistics and Data Science Seminar on Monday\, January 27\, 2025
DESCRIPTION:Title: Bridging Theory and Practice – A Journey Through Applied Statistics Across Academia\, Industry\, and Consulting (Part 2) \nVenue and time: ISRT\, 2:00 pm \nSpeaker: Yeasmin Khandakar\, PhD\, Senior Data Scientist\, Transurban Limited\, Australia \nAbstract: \nIn this presentation\, Dr. Yeasmin Khandakar will share her journey emphasizing how challenges can be transformed into opportunities. The first part of the presentation highlights the outcome achieved by navigating a steep learning curve and embracing uncertainties. illustrating how these challenges have been pivotal in her career and personal growth. Dr. Khandakar will highlight key moments from her career\, including her influential work on automatic ARIMA forecasting with Prof. Rob J. Hyndman. \nThe second part of the presentation will focus on the practical application of her current research in the industry. Yeasmin will discuss her role at Transurban\, where she leverages time series forecasting models and data analysis to address real-world problems. The presentation aims to inspire and equip students with insights and strategies for navigating their own professional paths.
URL:https://isrt.ac.bd/event/applied-statistics-and-data-science-seminar-on-monday-january-27-2025/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20250120T140000
DTEND;TZID=UTC:20250120T150000
DTSTAMP:20260424T044600
CREATED:20250116T043311Z
LAST-MODIFIED:20250119T044955Z
UID:7369-1737381600-1737385200@isrt.ac.bd
SUMMARY:Applied Statistics and Data Science Seminar on Monday\, January 20\, 2025
DESCRIPTION:Title: Bridging Theory and Practice – A Journey Through Applied Statistics Across Academia\, Industry\, and Consulting \nVenue and time: ISRT\, 2:00 pm \nSpeaker: Roman Ahmed\, PhD\, Senior Analytics Specialist (Statistics and Machine Learning) at Optus Australia \nAbstract: \nThis presentation traces the learning and professional journey of a statistician who has navigated a diverse career across academic\, industrial\, commercial research\, government\, and corporate consulting sectors. Beginning with a BSc in Applied Statistics and PhD in Econometrics and Business Statistics in the early 2000s\, the speaker will share key insights from their evolution as a statistician\, highlighting the ways in which their expertise in applied statistics has been shaped by each environment. From theoretical foundations in academia to practical applications in industry\, government\, and consulting\, the presentation will focus on the challenges\, strategies\, and tools employed to bridge the gap between statistical theory and real-world problem-solving. Through personal anecdotes and case studies\, the speaker will demonstrate the versatility of statistical knowledge in solving complex problems across various domains\, emphasizing the importance of adaptability\, communication\, and continuous learning in a dynamic professional landscape. This reflection on their journey offers valuable lessons for aspiring statisticians seeking to understand the breadth of opportunities and challenges that exist beyond the classroom.
URL:https://isrt.ac.bd/event/applied-statistics-and-data-science-seminars-on-monday-january-20-2025/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20250113T140000
DTEND;TZID=UTC:20250113T170000
DTSTAMP:20260424T044600
CREATED:20250107T065038Z
LAST-MODIFIED:20250107T065038Z
UID:7360-1736776800-1736787600@isrt.ac.bd
SUMMARY:Applied Statistics and Data Science Seminars on Monday\, January 13\, 2025
DESCRIPTION:Seminar 1\nTitle: Opportunities and Challenges in Single-Cell RNA-Seq: Revealing Biomarkers and Regulatory Networks in Early Brain Development \nVenue and time: ISRT\, 2:00 pm \nSpeaker: Dr. Md. Alamin\, Assistant Professor\, Department of Mathematics & Physics\, School of Engineering and Physical Sciences\, North South University \nAbstract: \nUnraveling the molecular mechanisms of early neuronal development is critical to understanding the genetic and regulatory factors driving human brain formation. Leveraging single-cell RNA sequencing (scRNA-seq)\, we profiled the transcriptional dynamics during the differentiation of human embryonic stem cells (hESCs) into neurons at two key time points: Day 26 (D26) and Day 54 (D54). Our analysis uncovered 539 differentially expressed genes (DEGs)\, revealing that up-regulated DEGs are involved in neurogenesis\, while down-regulated DEGs play roles in synapse regulation. Reactome pathway analysis highlighted significant contributions of down-regulated DEGs to synaptic protein interactions. Furthermore\, we identified 20 critical transcription factors and explored miRNA-DEG and TF-miRNA interactions\, advancing our understanding of gene regulatory networks during early brain development. These findings offer valuable insights into the genetic underpinnings of intelligence\, mental health\, and neurodevelopmental disorders. Moreover\, I will address the emerging challenges for statisticians and mathematicians in analyzing and interpreting high-dimensional single-cell data. These include handling data sparsity\, developing robust computational models\, and integrating multimodal datasets to uncover complex biological interactions. By bridging the gaps between biology\, statistics\, and mathematics\, we can push the boundaries of our understanding and foster innovation in neuroscience research. \nSeminar 2\nTitle: A reflection on the recent development of the subject area of Statistics and some specific issues of concern for further research \nVenue and time: ISRT\, 3:00 pm \nSpeaker: Dr. Moudud Alam\, Associate Professor in Microdata Analysis\, Dalarna University\, Sweden \nAbstract: \nThis talk is divided into two parts. In first part the recent development of the subject area of Statistics\, particularly the development of Data Science\, is discussed from the speaker’s experience along the way to develop a master’s and a PhD programme in Data Science\, and Data Analytics at a Swedish university. The media outcry and the popularity of the computing technology\, and artificial intelligence has pushed the Statistics community to rethink about its longstanding branding. Dedication of the 2024 Nobel prize in Physics and partly in Chemistry\, to the contribution in the development of artificial neural network\, and artificial intelligence can be considered as yet another dictation from the scientific community of the future direction of the filed. The contemporary labour market demands of the computing and soft skills is a non-negligible factor influencing the current trend of the subject. In this talk the experience of the speaker’s journey from Statistics to Data Science is discussed\, in connection with the related Swedish and European initiatives. Yet\, in this impassionate outrage it seems the scientific community is undermining (if not missing) the core assignment\, as all researchers concentrate too much to the practical applications driven by the contemporary problems\, mainly coming from the industry. In the second part\, the speaker draws attention\, using literature review and own research towards a number of statistical core issues that need special attention. In particular\, the limitation of ad hoc (such as cross validation) inferential procedure is exemplified using variable selection problem as an example\, from the literature. Using the speaker’s own research on service lifetime estimation of traffic signs in Sweden the speaker highlights the need for core statistical skills in dealing with unconventional data sources in the Data Science era. \n  \n 
URL:https://isrt.ac.bd/event/applied-statistics-and-data-science-seminars-on-monday-january-13-2025/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20241223T140000
DTEND;TZID=UTC:20241223T150000
DTSTAMP:20260424T044600
CREATED:20241222T010115Z
LAST-MODIFIED:20241222T011925Z
UID:7338-1734962400-1734966000@isrt.ac.bd
SUMMARY:Applied Statistics and Data Science Seminar on Monday\, December 23\, 2024
DESCRIPTION:Title: Postpartum family planning counselling during maternity care visits in Bangladesh and its effect on contraceptive initiation \nVenue and time: ISRT\, 2:00 pm \nSpeaker: Md. Moinuddin Hiader\, Associate Scientist\, icddr\,b \nThe speaker will initiate the talk by briefly discussing what he and his team expect from a fresh graduate as employers and what helps in career growth in public health research. He will conclude the talk by discussing 2-3 research ideas using publicly available data.
URL:https://isrt.ac.bd/event/applied-statistics-and-data-science-seminar-on-monday-december-23-2024/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20241125T150000
DTEND;TZID=UTC:20241125T163000
DTSTAMP:20260424T044600
CREATED:20241124T163439Z
LAST-MODIFIED:20241124T163655Z
UID:7283-1732546800-1732552200@isrt.ac.bd
SUMMARY:ISRT Football Match on November 25 at 3 PM
DESCRIPTION:ISRT football team will play the second match of the inter-department tournament on November 25. The match is scheduled against the Department of Geography & Environment and will take place at 3:00 PM at the Central field\, DU.
URL:https://isrt.ac.bd/event/isrt-football-match-on-november-25-at-3-pm/
LOCATION:Playing Ground\, DU
CATEGORIES:Football
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20241118T030000
DTEND;TZID=UTC:20241118T030000
DTSTAMP:20260424T044600
CREATED:20241117T155455Z
LAST-MODIFIED:20241117T155613Z
UID:7255-1731898800-1731898800@isrt.ac.bd
SUMMARY:First match of ISRT in inter-department football tournament 2024 is on Monday\, 18 Nov 2024 at 3:00 PM
DESCRIPTION:ISRT is delighted to announce that the ISRT football team is going to play the first match in the inter-department football tournament 2024 on Monday\, 18 July 2024\, at 3:00 PM against department of Performance and Theater Studies.. The game will be held at the university’s central ground field. \nLet’s come together and make our presence felt on the field.
URL:https://isrt.ac.bd/event/first-match-of-isrt-in-inter-department-football-tournament-2024-is-on-monday-18-nov-2024-at-300-pm/
LOCATION:Playing Ground\, DU
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20241111T140000
DTEND;TZID=UTC:20241111T150000
DTSTAMP:20260424T044600
CREATED:20241104T043223Z
LAST-MODIFIED:20241104T043223Z
UID:7206-1731333600-1731337200@isrt.ac.bd
SUMMARY:Applied Statistics and Data Science Seminar on Monday\, November 11\, 2024
DESCRIPTION:Title: Engineering Energy Efficiency among Residential Customers in Dhaka using Home Energy Reports (HERs) \nVenue and time: ISRT\, 2:00 pm \nSpeaker: Atonu Rabbani\, Ph.D\, Professor\, Department of Economics\, University of Dhaka \nAbstract: \nIn this study\, we estimated the potential impacts of home energy reports (HERs) on energy efficient behaviours among residential customers of Dhaka\, the capital of Bangladesh. We partnered with one of the two major retail power distribution companies. Using administrative consumption data\, we developed HERs with social feedback or descriptive norms\, where customers received comparisons between their own consumption and the averages of their neighbours. Using a randomized control trial\, we compared the electric energy consumption of a group who received “placebo” reports based only on their own consumption and without any comparison groups. Our findings suggest that the energy consumption declined by about 5 percent. However\, these impacts were short-lived and there was also suggestive evidence of possible rebound effects. Consistent with prior findings\, we also found that the impacts were larger for consumers who had higher consumption based on pre-intervention energy consumption. The point estimates suggest that households who received feedbacks based on their expenditure exhibited a larger impact compared to the households who received quantity-based feedbacks. The preliminary analyses suggest that behavioural nudges can be effective in the short run and that more intense and continuous feedback may be necessary for longer-term effects.
URL:https://isrt.ac.bd/event/applied-statistics-and-data-science-seminar-on-monday-november-11-2024/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20241110T180000
DTEND;TZID=UTC:20241201T210000
DTSTAMP:20260424T044600
CREATED:20240915T162436Z
LAST-MODIFIED:20240929T034137Z
UID:7025-1731261600-1733086800@isrt.ac.bd
SUMMARY:Stata for Applied Statistics and Data Science
DESCRIPTION:Details are given at https://isrt.ac.bd/training/stata
URL:https://isrt.ac.bd/event/stata-for-applied-statistics-and-data-science/
LOCATION:ISRT\, ISRT\, University of Dhaka\, Dhaka\, Bangladesh
CATEGORIES:training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20240927T090000
DTEND;TZID=UTC:20240928T210000
DTSTAMP:20260424T044600
CREATED:20240915T164043Z
LAST-MODIFIED:20240926T031839Z
UID:7036-1727427600-1727557200@isrt.ac.bd
SUMMARY:SPSS Hands-on for Data Science (short training course)
DESCRIPTION:Details are given at https://isrt.ac.bd/training/spss
URL:https://isrt.ac.bd/event/spss-hands-on-for-data-science-short-training-course-2/
LOCATION:ISRT\, ISRT\, University of Dhaka\, Dhaka\, Bangladesh
CATEGORIES:training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20240918T100000
DTEND;TZID=UTC:20240918T113000
DTSTAMP:20260424T044600
CREATED:20240915T033016Z
LAST-MODIFIED:20240916T045507Z
UID:7018-1726653600-1726659000@isrt.ac.bd
SUMMARY:A talk by Awan Afiaz on 18 September 2024
DESCRIPTION:Title: Optimal Sandwich Variance Estimator in Penalized GEE for Nearly Separated Longitudinal Binary Data with Small Samples \nVenue and time: ISRT\, 10:00 am \nSpeaker: Awan Afiaz\, PhD candidate at the Department of Biostatistics\, University of Washington Seattle\, WA\, USA and ISRT alumnus \nAbstract: \nData separation arises in both independent and correlated binary data in biomedical studies and poses a substantial challenge that can lead to unreliable estimates and misleading inferences. This problem can occur due to a small sample size\, a rare exposure or event\, a very strong predictor or a linear combination of predictors\, high within-subject correlation (ICC)\, or any combination of these issues. Penalized generalized estimating equations (GEE) have been shown to be the superior approach for handling separation in binary longitudinal data\, along with bias-corrected sandwich variance estimators. Although the sandwich variance estimator is valid under misspecification of the working correlation structure in GEE\, it is downward biased by design for small samples and requires large samples for the asymptotic advantages to take effect. This has led to the development of several modified robust variance estimators for GEE for small samples\, which motivates finding the optimal sandwich estimator in the context of penalized GEE when there is near separation (sparsity) in the data. The current study proposed a bias-corrected sandwich variance estimator for penalized GEE and compared its performance with ten extant sandwich estimators for nearly separated data using a simulation study. To motivate the need for an optimal sandwich estimator in penalized GEE\, we demonstrated that the existing small-sample based estimators provided contradictory results when using dermatophyte-toe onychomycosis trial data. The proposed sandwich estimator does not require any additional assumptions beyond those already employed by the original sandwich estimator for GEE. We evaluated the proposed sandwich estimator by assessing the ratio of the average SEs and the empirical SD and by calculating the type-I error rates for Wald tests of the regression coefficients. Our simulation studies showed that the proposed estimator yielded nominal-level type-I error rates based on Wald tests of regression coefficients\, regardless of whether the working correlation model was correctly specified. Furthermore\, while existing approaches performed well when the number of subjects was high\, the proposed estimator achieved nominal type-I error rates with sample sizes as low as 10\, even in the most extreme scenarios. Even though all existing sandwich estimators performed better as the number of subjects increased\, exhibiting the usual asymptotic behavior of sandwich estimators\, no other estimator uniformly achieved optimal performance faster (with respect to the number of subjects and ICC) than our proposed estimator
URL:https://isrt.ac.bd/event/a-talk-by-awan-afiaz-on-18-september-2024/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20240808T180000
DTEND;TZID=UTC:20240831T213000
DTSTAMP:20260424T044600
CREATED:20240612T144902Z
LAST-MODIFIED:20240612T151157Z
UID:6768-1723140000-1725139800@isrt.ac.bd
SUMMARY:Stata for Applied Statistics and Data Science training program
DESCRIPTION:Stata for Applied Statistics and Data Science training program. Details on https://isrt.ac.bd/training/stata
URL:https://isrt.ac.bd/event/6768/
CATEGORIES:training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20240719T100000
DTEND;TZID=UTC:20240720T193000
DTSTAMP:20260424T044600
CREATED:20240612T145921Z
LAST-MODIFIED:20240711T122546Z
UID:6774-1721383200-1721503800@isrt.ac.bd
SUMMARY:SPSS Hands-on for Data Science (short training course)
DESCRIPTION:SPSS Hands-on for Data Science (short training course).\n\nDetails on https://isrt.ac.bd/training/spss \nRegistration form
URL:https://isrt.ac.bd/event/spss-hands-on-for-data-science-short-training-course/
LOCATION:ISRT Seminar Room (3rd floor)\, Institute of Statistical Research and Training\, University of Dhaka\, Dhaka\, Please Select\, 1000\, Bangladesh
CATEGORIES:training
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20240211
DTEND;VALUE=DATE:20240212
DTSTAMP:20260424T044600
CREATED:20240109T051730Z
LAST-MODIFIED:20240109T051730Z
UID:6403-1707609600-1707695999@isrt.ac.bd
SUMMARY:Research Publication Fair to be held on February 11\, 2024 at the IBA premises
DESCRIPTION:The Institutes of the University of Dhaka will be participating in a day-long Research Publication Fair to be held on February 11\, 2024 at the IBA premises. This year\, ISRT is responsible for organizing the fair.
URL:https://isrt.ac.bd/event/research-publication-fair-to-be-held-on-february-11-2024-at-the-iba-premises/
LOCATION:IBA
CATEGORIES:other
ATTACH;FMTTYPE=image/png:https://isrt.ac.bd/wp-content/uploads/2024/01/Screen-Shot-2024-01-09-at-10.47.42-AM.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20240205T140000
DTEND;TZID=UTC:20240205T153000
DTSTAMP:20260424T044600
CREATED:20240204T022109Z
LAST-MODIFIED:20240204T022109Z
UID:6480-1707141600-1707147000@isrt.ac.bd
SUMMARY:Applied Statistics and Data Science Seminar on Monday\, February 5\, 2024
DESCRIPTION:Two talks (20 minutes each) \nVenue and time: ISRT\, 2:00 pm \nTalk 1 \nTopic : Data Tracker Table \nSpeaker: Nur Mohammad\, 2nd year student\, ISRT \n  \nTalk 2 \nTopic : Introduction to Typst: a modern typesetting system \nSpeaker: Md. Aminul Islam Shazid\, MS student\, ISRT
URL:https://isrt.ac.bd/event/applied-statistics-and-data-science-seminar-on-monday-february-5-2024/
CATEGORIES:seminar
END:VEVENT
END:VCALENDAR