Recent Presentations

Invited Talks: 

1. Small Neurons and Big Data: Biological Justification and Computational Efficiency in Multivariate Modelling of Neural Spike Trains, Iranian Statistical Society, Tehran, Iran (October 2023).

2. Multivariate Point Process Frameworks for Simultaneously Recorded Neural Spike Trains, University of  Victoria, BC, Canada (October 2023).

3. Multiscale Modelling of Neural Spike Trains, University of California, Irvine, USA, (August 2022).

4. Short Course on Machine Learning: Smoothing Methods, Alzahra University, Tehran, Iran, (February 2021).

5. Bridging the Gap: Statistics, Neuroscience, and Spike Trains. Western University, London, Canada, (December 2020).

6. From Neural Integration to a Statistical Model, Applied Mathematics, Modelling and Computational Science Conference (AMMCS), Wilfrid Laurier University, Waterloo, Canada, (August 2019).

7. Multivariate Models for Neural Spike Trains: State of the Art and Challenges, Annual Meeting of Statistical Society of Canada (SSC), Montreal, Quebec, Canada (May 2018).

8. Share the Blame, Collaborate: Small Flies and Big Data, Center for Computational and Applied Mathematics (CCAM), California State University, Fullerton, (March 2017)

9. A Point Process Manifestation of the Integrate-and-Fire Model, Department of Mathematics, University of San Francisco, CA (March 2016).

10. R and Cluster Computing: an Introduction, College of Natural Sciences and Mathematics, California State University, Fullerton, (September 2015),

11. From Neuroscience to Statistics: A Biologically Justified Model for Neural Spike Trains, School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran, (June 2015)

12. A Biologically Justified Approach to Modeling Neural Spike Trains, Department of Statistics, UC Irvine, Irvine, CA, (May 2015).

13. On the Multivariate Analysis of Neural Spike Trains: Skellam Process with Resetting and its Applications, Department of Mathematics and Statistics, McGill University, Montreal, Canada, (February 2014).

14. Skellam Process: A New Approach to Modelling Neural Spike Trains, Annual Meeting of Statistical Society of Canada (SSC), Edmonton, Alberta, Canada (May 2013).

15. Skellam Process and its Applications, Faculty of Life Sciences, The University of Manchester, UK, (November 2012)

Contributed Talks and Posters:

1. A Continuous-Time Multi-Neuron Factor Model for Neural Spike Trains, Joint Statistical Meeting (JSM), Toronto, Canada (August 2023).

2. Functional Connectivity, Continuous-Time Latent Factor Models for Neural Spike Trains, Conference on Cognitive Computational Neuroscience, Oxford, UK, (August 2023).

3. A Multivariate Model for the Analysis of Neural Spike Trains, FENS Forum, International Neuroscience Conference, Paris, France (July 2022).

4. A Multivariate Point Process Model for Simultaneously Recorded Neural Spike Train, Conference on Cognitive Computational Neuroscience, San Francisco, USA, (August 2022).

5. Single Cell Eukaryote Salpingoeca Rosetta Communicate Using Neuron-like Action Potential Spikes within Rosette Colonies Involving Nav2 Sodium and Cav1 Calcium Channels, Canadian Association for Neuroscience Annual Meeting, Toronto (May 2019)

6. Computational Neuroscience: A Romance of Many Disciplines, Annual Meeting of the Statistical Society of Canada (SSC), Univ. of Manitoba, Winnipeg, Canada (June 2017).

7. A Four Lake Latitudinal Comparison Along Coastal Southern to Central California: A Late-Holocene Perspective on the Western US Precipitation Dipole, American Geophysical Union Fall Meeting, San Francisco (December 2016).

8. Simultaneous Modeling of Neural Phenomena from Multiple Time Scales, Annual Meeting of Society for Neuroscience (SfN), San Diego, (upcoming)

9. Time Scale in Neuronal Data: A Multiscale Model, Annual Meeting of the Statistical Society of Canada (SSC), Brock University, St. Catharines, Canada, May-June 2016

10. Neural Spike Trains as Realizations of Skellam Process with Resetting, Joint Statistical Meeting (JSM), Washington State Convention Center, Seattle, Washington, August 2015

11. A Flexible Model with Multivariate Extensions for Neural Spike Trains, International Workshop on Statistical Analysis of Neuronal Data (SAND 7), University of Pittsburgh, Pittsburgh, USA, (May 2015).

12. Teaching Abstract Statistical Concepts with Applied Research Questions, Opportunities and New Directions Conference, University of Waterloo, Canada, (April 2013)

13. Skellam Process and its Applications in Modelling Neural Spike Trains, Annual Meeting of Society for Neuroscience (SfN), New Orleans, U.S.A. (October 2012).

14. On Statistics Anxiety: A Transactional Analysis Approach, Certificate in University Teaching Seminar, Department of Statistics and Actuarial Science, University of Waterloo, Canada (February 2012).

15. When Neuroscience Meets Statistics: Modelling Neural Spike Trains, Department of Statistics and Actuarial Science, University of Waterloo, Canada (November 2011).

16. Multiscale, Multivariate Spike Train Analysis, Applied Mathematics, Modelling and Computational Science Conference (AMMCS), Wilfrid Laurier University, Waterloo, Canada, (July 2011).

17. An Inhibitory-Excitatory Approach for the Analysis of the Neural Spike Trains, The Joint Statistical Meeting (JSM), American Statistical Association, Vancouver, Canada, (August 2010).

18. Analysis of Neural Spike Trains, Annual meeting of the Statistical Society of Canada (SSC), Vancouver, Canada, (June 2009).