Dr Daniel Archambault

Associate Professor, Computer Science

+44 (0) 1792 295371

d.w.archambault@swansea.ac.uk

Research Links

https://orcid.org/0000-0003-4978-8479

Google Scholar

ResearcherID

Office - 334
Third Floor
Computational Foundry
Bay Campus

Available For Postgraduate Supervision

About

Daniel Archambault makes visualisation and visual analytics systems scale to the age of data science. He is an expert in network visualisation and analysis and visual interfaces for making sence of machine learning/data analytics systems. His major contributions have been around the effective visualisation of dynamic networks. He has organised and participated in major conferences and workshops in the area and participates in visualisation research activities at the Alan Turing Institute.

Daniel consistently collaborates with top researchers with in the UK and internationally. Giving approximately 6 invited talks internationally per year, he consistantly works with students and researchers on three continents.

Peronal webpage: http://cs.swansea.ac.uk/~csdarchambault/

Areas Of Expertise

Data Visualisation
Information Visualisation
Network Visualisation
Graph Drawing
Network Analysis
Network Mining
Human-Computer Interaction
Data Analysis/Analytics

Career Highlights

Teaching Interests

Information Visualisation
Visualisation
Graph Drawing and Network Analytics

Research Collaborations

Publications

Research Highlights

Chen, M., Abdul-Rahman, A., Archambault, D., Dykes, J., Ritsos, P., Slingsby, A., Torsney-Weir, T., Turkay, C., Bach, B., Borgo, R., Brett, A., Fang, H., Jianu, R., Khan, S., Laramee, B., Matthews, L., Nguyen, P., Reeve, R., Roberts, J...., & Xu, K. (2022). RAMPVIS: Answering the challenges of building visualisation capabilities for large-scale emergency responses. Epidemics, 100569
https://doi.org/10.1016/j.epidem.2022.100569, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa59933
http://dx.doi.org/10.1016/j.epidem.2022.100569
Dykes, J., Abdul-Rahman, A., Archambault, D., Bach, B., Borgo, R., Chen, M., Enright, J., Fang, H., Firat, E., Freeman, E., Gonen, T., Harris, C., Jianu, R., John, N., Khan, S., Lahiff, A., Laramee, R., Matthews, L., Mohr, S...., & Xu, K. (n.d.) Visualization for Epidemiological Modelling: Challenges, Solutions, Reflections & Recommendations. Philosophical Transactions of the Royal Society A
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa59890
Sondag, M., Turkay, C., Xu, K., Matthews, L., Mohr, S., & Archambault, D. (2022). Visual Analytics of Contact Tracing Policy Simulations During an Emergency Response. Computer Graphics Forum
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa59803
Sadler, S., Greene, D., & Archambault, D. (2022). Selecting Informative Features for Post-hoc Community Explanation. In Complex Networks & Their Applications X (pp. 297-308). Springer International Publishing.
https://doi.org/10.1007/978-3-030-93409-5_25, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa58268
Turkay, C., Landesberger, T., Archambault, D., Liu, S., & Chang, R. (2021). Special Issue on Interactive Visual Analytics for Making Explainable and Accountable Decisions. ACM Transactions on Interactive Intelligent Systems, 11(3-4), 1-4.
https://doi.org/10.1145/3471903, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57877
http://dx.doi.org/10.1145/3471903

All Research

Journal Articles

Sondag, M., Turkay, C., Xu, K., Matthews, L., Mohr, S., & Archambault, D. (2022). Visual Analytics of Contact Tracing Policy Simulations During an Emergency Response. Computer Graphics Forum
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa59803
Chen, M., Abdul-Rahman, A., Archambault, D., Dykes, J., Ritsos, P., Slingsby, A., Torsney-Weir, T., Turkay, C., Bach, B., Borgo, R., Brett, A., Fang, H., Jianu, R., Khan, S., Laramee, B., Matthews, L., Nguyen, P., Reeve, R., Roberts, J...., & Xu, K. (2022). RAMPVIS: Answering the challenges of building visualisation capabilities for large-scale emergency responses. Epidemics, 100569
https://doi.org/10.1016/j.epidem.2022.100569, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa59933
http://dx.doi.org/10.1016/j.epidem.2022.100569
Turkay, C., Landesberger, T., Archambault, D., Liu, S., & Chang, R. (2021). Special Issue on Interactive Visual Analytics for Making Explainable and Accountable Decisions. ACM Transactions on Interactive Intelligent Systems, 11(3-4), 1-4.
https://doi.org/10.1145/3471903, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57877
http://dx.doi.org/10.1145/3471903
Wallinger, M., Archambault, D., Auber, D., Nollenburg, M., & Peltonen, J. (2021). Edge-Path Bundling: A Less Ambiguous Edge Bundling Approach. IEEE Transactions on Visualization and Computer Graphics, 28(1), 1-1.
https://doi.org/10.1109/tvcg.2021.3114795, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57597
Lee, A., Archambault, D., & Nacenta, M. (2021). The Effectiveness of Interactive Visualization Techniques for Time Navigation of Dynamic Graphs on Large Displays. IEEE Transactions on Visualization and Computer Graphics, 27(2), 528-538.
https://doi.org/10.1109/tvcg.2020.3030446, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa55105
Baumgartl, T., Petzold, M., Wunderlich, M., Hohn, M., Archambault, D., Lieser, M., Dalpke, A., Scheithauer, S., Marschollek, M., Eichel, V., Mutters, N., Consortium, H., & Landesberger, T. (2021). In Search of Patient Zero: Visual Analytics of Pathogen Transmission Pathways in Hospitals. IEEE Transactions on Visualization and Computer Graphics, 27(2), 711-721.
https://doi.org/10.1109/tvcg.2020.3030437, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa55044
Yoghourdjian, V., Archambault, D., Diehl, S., Dwyer, T., Klein, K., Purchase, H., & Wu, H. (2018). Exploring the limits of complexity: A survey of empirical studies on graph visualisation. Visual Informatics, 2(4), 264-282.
https://doi.org/10.1016/j.visinf.2018.12.006, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa48139
Vogogias, A., Kennedy, J., Archambault, D., Bach, B., Smith, V., & Currant, H. (2018). BayesPiles: Visualisation Support for Bayesian Network Structure Learning. ACM Transactions on Intelligent Systems and Technology, 10(1), 1-23.
https://doi.org/10.1145/3230623, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa39457
https://dlnext.acm.org/doi/abs/10.1145/3230623
Simonetto, P., Archambault, D., & Kobourov, S. (2018). Event-Based Dynamic Graph Visualisation. IEEE Transactions on Visualization and Computer Graphics, 1-1.
https://doi.org/10.1109/TVCG.2018.2886901, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa47911
Wang, Y., Archambault, D., Scheidegger, C., & Qu, H. (2017). A Vector Field Design Approach to Animated Transitions. IEEE Transactions on Visualization and Computer Graphics, 24(9), 2487-2500.
https://doi.org/10.1109/TVCG.2017.2750689, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa35167
Toeda, N., Nakazawa, R., Itoh, T., Saito, T., & Archambault, D. (2017). Convergent drawing for mutually connected directed graphs. Journal of Visual Languages & Computing, 43, 83-90.
https://doi.org/10.1016/j.jvlc.2017.09.004, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa34903
Wu, Y., Cao, N., Archambault, D., Shen, Q., Qu, H., & Cui, W. (2017). Evaluation of Graph Sampling: A Visualization Perspective. IEEE Transactions on Visualization and Computer Graphics (InfoVis 2016), 23(1), 401-410.
https://doi.org/10.1109/TVCG.2016.2598867, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa31205
Archambault, D., Purchase, H., & Archambault, D. (2016). On the effective visualisation of dynamic attribute cascades. Information Visualization, 15(1), 51-63.
https://doi.org/10.1177/1473871615576758, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa20859
Chung, D., Archambault, D., Borgo, R., Edwards, D., Laramee, R., Chen, M., & Laramee, B. (2016). How Ordered Is It? On the Perceptual Orderability of Visual Channels. Computer Graphics Forum, 35(3), 131-140.
https://doi.org/10.1111/cgf.12889, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa27749
Bach, B., Dragicevic, P., Archambault, D., Hurter, C., Carpendale, S., & Archambault, D. (2016). A Descriptive Framework for Temporal Data Visualizations Based on Generalized Space-Time Cubes. Computer Graphics Forum
https://doi.org/10.1111/cgf.12804, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa28386
http://onlinelibrary.wiley.com/doi/10.1111/cgf.12804/full
Archambault, D. & Purchase, H. (2016). Can animation support the visualisation of dynamic graphs?. Information Sciences, 330, 495-509.
https://doi.org/10.1016/j.ins.2015.04.017, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa20860
Wang, Y., Shen, Q., Archambault, D., Zhou, Z., Zhu, M., Yang, S., & Qu, H. (2016). AmbiguityVis: Visualization of Ambiguity in Graph Layouts. IEEE Transactions on Visualization and Computer Graphics (InfoVis 2015), 22(1), 359-368.
https://doi.org/10.1109/TVCG.2015.2467691, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa23061
Simonetto, P., Archambault, D., & Scheidegger, C. (2016). A Simple Approach for Boundary Improvement of Euler Diagrams. IEEE Transactions on Visualization and Computer Graphics (InfoVis 2015), 22(1), 678-687.
https://doi.org/10.1109/TVCG.2015.2467992, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa23062
Archambault, D. & Hurley, N. (2014). Visualization of trends in subscriber attributes of communities on mobile telecommunications networks. Social Network Analysis and Mining, 4(1), 205
https://doi.org/10.1007/s13278-014-0205-5, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa21319
Archambault, D., Purchase, H., & Archambault, D. (2013). The “Map” in the mental map: Experimental results in dynamic graph drawing. International Journal of Human-Computer Studies, 71(11), 1044-1055.
https://doi.org/10.1016/j.ijhcs.2013.08.004, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa23041
http://www.scopus.com/inward/record.url?eid=2-s2.0-84884236180&partnerID=MN8TOARS
Simonetto, P., Archambault, D., Auber, D., & Bourqui, R. (2011). ImPrEd: An Improved Force-Directed Algorithm that Prevents Nodes from Crossing Edges. Computer Graphics Forum (EuroVis 2011), 30(3), 1071-1080.
https://doi.org/10.1111/j.1467-8659.2011.01956.x, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa13914
Archambault, D., Purchase, H., Pinaud, B., & Archambault, D. (2011). Animation, Small Multiples, and the Effect of Mental Map Preservation in Dynamic Graphs. IEEE Transactions on Visualization and Computer Graphics, 17(4), 539-552.
https://doi.org/10.1109/TVCG.2010.78, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa13909
Archambault, D., Munzner, T., Auber, D., & Archambault, D. (2011). Tugging Graphs Faster: Efficiently Modifying Path-Preserving Hierarchies for Browsing Paths. IEEE Transactions on Visualization and Computer Graphics, 17(3), 276-289.
https://doi.org/10.1109/TVCG.2010.60, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa13915
Archambault, D., Purchase, H., & Pinaud, B. (2010). The Readability of Path-Preserving Clusterings of Graphs. Computer Graphics Forum, 29(3), 1173-1182.
https://doi.org/10.1111/j.1467-8659.2009.01683.x, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa13912
Derrick, D., Archambault, D., & Archambault, D. (2009). TreeForm: Explaining and exploring grammar through syntax trees. Literary and Linguistic Computing, 25(1), 53-66.
https://doi.org/10.1093/llc/fqp031, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa23051
http://www.scopus.com/inward/record.url?eid=2-s2.0-77952736367&partnerID=MN8TOARS
Simonetto, P., Auber, D., & Archambault, D. (2009). Fully Automatic Visualisation of Overlapping Sets. Computer Graphics Forum, 28(3), 967-974.
https://doi.org/10.1111/j.1467-8659.2009.01452.x, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa13910
Archambault, D., Munzner, T., Auber, D., & Archambault, D. (2008). GrouseFlocks: Steerable Exploration of Graph Hierarchy Space. IEEE Transactions on Visualization and Computer Graphics, 14(4), 900-913.
https://doi.org/10.1109/TVCG.2008.34, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa13911
Archambault, D., Munzner, T., Auber, D., & Archambault, D. (2007). TopoLayout: Multilevel Graph Layout by Topological Features. IEEE Transactions on Visualization and Computer Graphics, 13(2), 305-317.
https://doi.org/10.1109/TVCG.2007.46, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa23054
http://www.scopus.com/inward/record.url?eid=2-s2.0-33846617291&partnerID=MN8TOARS
Archambault, D., Munzner, T., Auber, D., & Archambault, D. (2006). Smashing Peacocks Further: Drawing Quasi-Trees from Biconnected Components. IEEE Transactions on Visualization and Computer Graphics, 12(5), 813-820.
https://doi.org/10.1109/TVCG.2006.177, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa23055
http://www.scopus.com/inward/record.url?eid=2-s2.0-33845638242&partnerID=MN8TOARS
Archambault, D., Evans, W., Kirkpatrick, D., & Archambault, D. (2005). COMPUTING THE SET OF ALL THE DISTANT HORIZONS OF A TERRAIN. International Journal of Computational Geometry & Applications, 15(06), 547-563.
https://doi.org/10.1142/S0218195905001841, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa23056
http://www.scopus.com/inward/record.url?eid=2-s2.0-30344466388&partnerID=MN8TOARS
Dykes, J., Abdul-Rahman, A., Archambault, D., Bach, B., Borgo, R., Chen, M., Enright, J., Fang, H., Firat, E., Freeman, E., Gonen, T., Harris, C., Jianu, R., John, N., Khan, S., Lahiff, A., Laramee, R., Matthews, L., Mohr, S...., & Xu, K. (n.d.) Visualization for Epidemiological Modelling: Challenges, Solutions, Reflections & Recommendations. Philosophical Transactions of the Royal Society A
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa59890

Book Chapters

Purchase, H., Archambault, D., Kobourov, S., Nöllenburg, M., Pupyrev, S., & Wu, H. (2021). The Turing Test for Graph Drawing Algorithms. In David Auber and Pavel Valtr (Ed.), Lecture Notes in Computer Science (pp. 466-481). Springer International Publishing
https://doi.org/10.1007/978-3-030-68766-3_36, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa55001
Simonetto, P., Archambault, D., & Kobourov, S. (2018). Drawing Dynamic Graphs Without Timeslices. Graph Drawing and Network Visualization (pp. 394-409).
https://doi.org/10.1007/978-3-319-73915-1_31, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa35081
https://arxiv.org/abs/1709.00372
Archambault, D., Abello, J., Kennedy, J., Kobourov, S., Ma, K., Miksch, S., Muelder, C., Telea, A., & Archambault, D. (2014). Temporal Multivariate Networks. Multivariate Network Visualization (pp. 151-174).
https://doi.org/10.1007/978-3-319-06793-3_8, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa23039
http://www.scopus.com/inward/record.url?eid=2-s2.0-84901261125&partnerID=MN8TOARS
Tissandier, P., Quang, T., & Archambault, D. (2013). Defining Polycentric Urban Areas Through Commuting Cohesion in France. Methods for Multilevel Analysis and Visualisation of Geographical Networks (pp. 189-206).
https://doi.org/10.1007/978-94-007-6677-8_12, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa23069

Conference Contributions

Sadler, S., Greene, D., & Archambault, D. (2022). Selecting Informative Features for Post-hoc Community Explanation. In Complex Networks & Their Applications X (pp. 297-308). Springer International Publishing.
https://doi.org/10.1007/978-3-030-93409-5_25, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa58268
Krawczyk, K. & Archambault, D. (2022). Animating Disease Spread with Location Type. Graph Drawing and Network Visualization Poster Proceedings.
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57785
Sondag, M., Turkay, C., Mohr, S., Matthews, L., Xu, K., & Archambault, D. (2022). What is R? A graph drawer’s perspective?. In 29th International Symposium on Graph Drawing and Network VisualizationPoster Publication.
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57784
Arleo, ., Miksch, S., & Archambault, D. (2021). A Multilevel Approach for Event-Based Dynamic Graph Drawing. In Eurographics Conference on Visualization (Short Papers)Eurographics Proceedings.
https://doi.org/10.2312/evs.20211063, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56743
http://diglib.eg.org/handle/10.2312/evs20211063
Purchase, H., Stirling, N., & Archambault, D. (2020). Proximity, Communities, and Attributes in Social Network Visualisation. In 2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (pp. 65-72). IEEE.
https://doi.org/10.1109/asonam49781.2020.9381332, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa55525
Vogogias, A., Archambault, D., Bach, B., & Kennedy, J. (2020). Visual Encodings for Networks with Multiple Edge Types. In Proceedings of the International Conference on Advanced Visual Interfaces (pp. 1-9). ACM.
https://doi.org/10.1145/3399715.3399827, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53990
Pantekis, F., James, P., O'Reilly, L., Archambault, D., & Moller, F. (2020). Visualising Railway Safety Verification. In Osman Hasan, Frederic Mallet (Ed.), Formal Techniques for Safety-Critical Systems. FTSCS 2019. Communications in Computer and Information Science. (pp. 95-105). Springer International Publishing.
https://doi.org/10.1007/978-3-030-46902-3_6, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53283
Lee, A., Archambault, D., & Nacenta, M. (2019). Dynamic Network Plaid. In CHI '19 Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (pp. 1-14). CHI Glasgow 2019.
https://doi.org/10.1145/3290605.3300360, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa48160
Wang, Y., Archambault, D., Haleem, H., Moeller, T., Wu, Y., & Qu, H. (2019). Nonuniform Timeslicing of Dynamic Graphs Based on Visual Complexity. In 2019 IEEE Visualization Conference (VIS)IEEE.
https://doi.org/10.1109/visual.2019.8933748, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53579
Lee, A. & Archambault, D. (2016). Communities Found by Users -- not Algorithms: Comparing Human and Algorithmically Generated Communities. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (pp. 2396-2400). CHI-2016.
https://doi.org/10.1145/2858036.2858071, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa26488
10.1145/2858036.2858071
Archambault, D., Purchase, H., & Archambault, D. (2014). On the application of experimental results in dynamic graph drawing. In Diagrams Workshop on Graph Visualization in Practice
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa23040
http://www.scopus.com/inward/record.url?eid=2-s2.0-84924980279&partnerID=MN8TOARS
Bach, B., Dragicevic, P., Archambault, D., Hurter, C., & Carpendale, S. (2014). A Review of Temporal Data Visualizations Based on Space-Time Cube Operations. In Eurovis STAR Report (EuroVis 2014) (pp. 23-41).
https://doi.org/10.2312/eurovisstar.20141171, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa23057
Nicholas, M., Archambault, D., & Laramee, B. (2014). Interactive Visualisation of Automotive Warranty Data Using Novel Extensions of Chord Diagrams. In Proceedings of EuroVis Short Papers 2014
https://doi.org/10.2312/eurovisshort.20141167, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24646
http://dx.doi.org/10.2312/eurovisshort.20141167
Archambault, D., Hurley, N., Tu, C., & Archambault, D. (2013). ChurnVis: Visualizing mobile telecommunications churn on a social network with attributes. In The IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2013) (pp. 894-901).
https://doi.org/10.1145/2492517.2500274, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa23042
http://www.scopus.com/inward/record.url?eid=2-s2.0-84893229189&partnerID=MN8TOARS
Archambault, D., Purchase, H., & Archambault, D. (2012). The mental map and memorability in dynamic graphs. In IEEE Pacific Visualization (PacificVis 2012) (pp. 89-96).
https://doi.org/10.1109/PacificVis.2012.6183578, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa23043
http://www.scopus.com/inward/record.url?eid=2-s2.0-84860677854&partnerID=MN8TOARS
Harrigan, M., Archambault, D., Cunningham, P., Hurley, N., & Archambault, D. (2012). EgoNav: Exploring networks through egocentric spatializations. In Advanced Visual Interfaces (AVI 2012) (pp. 563-570).
https://doi.org/10.1145/2254556.2254661, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa23044
http://www.scopus.com/inward/record.url?eid=2-s2.0-84863569581&partnerID=MN8TOARS
Archambault, D. & Purchase, H. (2012). Mental Map Preservation Helps User Orientation in Dynamic Graphs. In Graph Drawing (GD 2012) (pp. 475-486). Springer.
https://doi.org/10.1007/978-3-642-36763-2_42, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa13913
Wade, K., Greene, D., Lee, C., Archambault, D., & Cunningham, P. (2011). Identifying Representative Textual Sources in Blog Networks. In Fifth International AAAI Conference on Weblogs and Social Media (ICWSM 2011) (pp. 393-400).
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa23068
Brew, A., Greene, D., Archambault, D., Cunningham, P., & Archambault, D. (2011). Deriving insights from national happiness indices. In ICDM SENTIRE Sentiment Elicitation from Natural Text for Information Retrieval and Extraction (pp. 53-60).
https://doi.org/10.1109/ICDMW.2011.61, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa23047
http://www.scopus.com/inward/record.url?eid=2-s2.0-84857184525&partnerID=MN8TOARS
Archambault, D., Purchase, H., Pinaud, B., & Archambault, D. (2011). Difference Map Readability for Dynamic Graphs. In Graph Drawing (GD 2010) (pp. 50-61).
https://doi.org/10.1007/978-3-642-18469-7_5, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa23046
http://www.scopus.com/inward/record.url?eid=2-s2.0-79952261554&partnerID=MN8TOARS
Archambault, D., Greene, D., Cunningham, P., Hurley, N., & Archambault, D. (2011). ThemeCrowds: Multiresolution summaries of twitter usage. In CIKM 3rd International Workshop on Search and Mining User-generated Contents (SMUC 2011) (pp. 77-84).
https://doi.org/10.1145/2065023.2065041, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa23045
http://www.scopus.com/inward/record.url?eid=2-s2.0-83255173804&partnerID=MN8TOARS
Koenig, P., Zaidi, F., Archambault, D., & Archambault, D. (2010). Interactive searching and visualization of patterns in attributed graphs. In Graphics Interface (GI 2010) (pp. 113-120).
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa23048
http://www.scopus.com/inward/record.url?eid=2-s2.0-77955604567&partnerID=MN8TOARS
Zaidi, F., Archambault, D., Melançon, G., & Archambault, D. (2010). Evaluating the Quality of Clustering Algorithms Using Cluster Path Lengths. In Advances in Data Mining. Applications and Theoretical Aspects (pp. 42-56).
https://doi.org/10.1007/978-3-642-14400-4_4, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa23049
http://www.scopus.com/inward/record.url?eid=2-s2.0-77954867692&partnerID=MN8TOARS
Archambault, D. & Archambault, D. (2009). Structural differences between two graphs through hierarchies. In Graphics Interface (GI 2009) (pp. 87-94).
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa23052
http://www.scopus.com/inward/record.url?eid=2-s2.0-70450092459&partnerID=MN8TOARS
Simonetto, P., Koenig, P., Zaidi, F., Archambault, D., Gilbert, F., Phan-Quang, T., Mathiaut, M., Lambert, A., Dubois, J., Sicre, R., Brulin, M., Vieux, R., Melançon, G., & Archambault, D. (2009). Solving the traffic and flitter challenges with tulip. In IEEE Symposium on Visual Analytics Science and Technology (pp. 247-248).
https://doi.org/10.1109/VAST.2009.5334456, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa23053
http://www.scopus.com/inward/record.url?eid=2-s2.0-72849142621&partnerID=MN8TOARS
Archambault, D., Munzner, T., Auber, D., & Archambault, D. (2009). TugGraph: Path-preserving hierarchies for browsing proximity and paths in graphs. In IEEE Pacific Visualization Symposium (PacificVis 2009) (pp. 113-120).
https://doi.org/10.1109/PACIFICVIS.2009.4906845, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa23050
http://www.scopus.com/inward/record.url?eid=2-s2.0-67650524432&partnerID=MN8TOARS
Archambault, D., Munzner, T., & Auber, D. (2007). Grouse: Feature-Based, Steerable Graph Hierarchy Exploration. In Proceedings of the 9th Joint Eurographics / IEEE VGTC conference on Visualization (EuroVis 2007)) (pp. 67-74).
https://doi.org/10.2312/VisSym/EuroVis07/067-074, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa23058
Archambault, D., Evans, W., & Kirkpatrick, D. (2004). Computing All the Distant Horizons of A Terrain. In Canadian Conference on Computational Geometry (CCCG 2004) (pp. 76-79).
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa23059

Supervision

Visual Analytics for Explainable Graph-Based Machine Learning (current)

PhD

Other supervisor: Dr Michael Edwards
VisualisationofLonginTimeDynamic NetworksonLargeTouchDisplays (awarded 2021)

PhD

Other supervisor: Dr Gary Tam
Geo-spatial Visualization of Public Health Care Data (awarded 2019)

PhD

Other supervisor: Dr Bob Laramee
Benefits of and Barriers to Public Engagement with Research (PE-R) for Researchers, Institutions and the Public (current)

PhD

Other supervisor: Prof Huw Bowen

Other supervisor: Prof John Tucker
Interactive Visualization of Many Trajectories from Molecular Dynamics Simulations in Polar Space (awarded 2021)

MSc

Other supervisor: Dr Sean Walton
'Centrality Metrics Detection of Terrorist Networks.' (awarded 2018)

MSc

Other supervisor: Dr Monika Seisenberger

Taught Modules

CS-115 Programming 2

This module is a continuation of the module CS-110 Programming 1. In it, students will continue to enhance their skills in programming, as well as gain a basic understanding of algorithms and data structures.
CSCM27 Human-Centred Visual Analytics

Visual analytics is a human-centred area of computing that studies systems to support exploration and explanation of features in data sets. The course will provide an introduction to visual analytics and supporting necessary concepts in information visualisation. Visual analytics is the combination of visualisation and data analytics, which includes machine learning, to create effective data analysis systems.
CSGD00 Taught Masters Dissertation (Computer Science:Informatique)

This module will provide students with the opportunity of exploring a particular topic in computer science in some considerable depth. It is only open to students studying MSc Computer Science, MSc Advanced Computer Science, MSc Advanced Software Technology or the MSc in High Performance and Scientific Computing.
CSGM01 Dual Award Swansea Grenoble MSc - Semester

This module aggregates the Semester 1 (French: Semestre 7) modules that form part of the Grenoble delivery of the Dual Award MSc in Informatics. The module consists of six compulsory topics related to technical computer science, as well as material on technical writing and a four-week programming project.
CSGM02 Dual Award Swansea Grenoble MSc - Semester 2

This module aggregates the Semester 2 (French: Semestre 8) modules that form part of the Grenoble delivery of the Dual Award MSc in Informatics. The module consists of three compulsory topics related to research preparation; and a choice of seven of 12 technical topics (see syllabus for details).
CSGM31 Dual Award Swansea Grenoble MSc - Semester 3 - Advanced Information Systems and Software Engineering

This module aggregates the Semester 3 (French: Semestre 9) modules that form part of the Grenoble delivery of the Dual Award MSc in Informatics. The module consists of six compulsory and three optional technical topics related to the fields of Advanced Information Systems and Software Engineering.
CSGM32 Dual Award Swansea Grenoble MSc - Semester 3 - AI and the Web

This module aggregates the Semester 3 (French: Semestre 9) modules that form part of the Grenoble delivery of the Dual Award MSc in Informatics. The module consists of four compulsory and 4 (of 5) optional technical topics related to AI and the Web.
CSGM33 Dual Award Swansea Grenoble MSc - Semester 3 - Graphics, Vision and Robotics

This module aggregates the Semester 3 (French: Semestre 9) modules that form part of the Grenoble delivery of the Dual Award MSc in Informatics. The module consists of three compulsory and three optional technical topics related to the fields of Graphics, Vision and Robotics.
CSGM34 Dual Award Swansea Grenoble MSc - Semester 3 - Data Science

This module aggregates the Semester 3 (French: Semestre 9) modules that form part of the Grenoble delivery of the Dual Award MSc in Informatics. The module consists of eight compulsory and three optional technical topics related to the field of Data Science.
CSGM35 Dual Award Swansea Grenoble MSc - Semester 3 - High-confidence Embedded and Cyberphysical Systems

This module aggregates the Semester 3 (French: Semestre 9) modules that form part of the Grenoble delivery of the Dual Award MSc in Informatics. The module consists of three compulsory and three optional technical topics related to the fields of High-confidence Embedded and Cyberphysical Systems.
CSGM36 Dual Award Swansea Grenoble MSc - Semester 3 - Parallel, Distributed and Embedded Systems

This module aggregates the Semester 3 (French: Semestre 9) modules that form part of the Grenoble delivery of the Dual Award MSc in Informatics. The module consists of four compulsory and three optional technical topics related to the fields of Parallel, Distributed and Embedded Systems.
CSGM37 Dual Award Swansea Grenoble MSc - Semester 3 - Ubiquitous and Interactive Systems

This module aggregates the Semester 3 (French: Semestre 9) modules that form part of the Grenoble delivery of the Dual Award MSc in Informatics. The module consists of four compulsory and three optional technical topics related to the fields of Ubiquitous and Interactive Systems.
CSGM40 Dual Award Swansea Grenoble MSc - Semester 4 - Project

This module represents a substantial scientific research project undertaken at Universite Grenoble Alpes as part of the Dual Degree MSc in Informatics.

Key Grants and Projects

Drawing and Visualisation of Dynamic Multivariate Graphs for Social Networks 2015 - 2017

Career History

Post Doctoral Researcher, University College Dublin

February 2010 - December 2012
Post Doctoral Researcher, INRIA Bordeaux Sud-Ouest

September 2008 - January 2010
Graduate Studies (M.Sc. and Ph.D.), University of British Columbia

September 2001 - July 2008

Invited Presentations, Lectures and Conferences

Succeeding by Failing: The Iceberg in VIS Careers

2018

IEEE VIS
How do recent machine learning advances impact the data visualization research agenda?

2017

IEEE VIS
Why Social Networks Matter: Social Network Analysis, Visualisation, and the Cambridge Scandal

August 2019

Not-Equal Summer School, Swansea University.
The Influence of Data Science and AI on Visualisation Perception

September 2019

#VizTIG Symposium, Alan Turing Institute.
Drawing and Visualising Event-Based Dynamic Graphs

December 2019

Cambridge Intelligence, Cambridge, UK.

Invited Presentations continued

TU Wien, Vienna, Austria, September 2019.
Apple Inc., Seattle, USA, July 2019.
Tableau Software, Seattle, USA, July 2019.
INRIA Sarclay, Paris, France, May 2019.
LIP6, Sorbonne University, Paris, France, May 2019.
Effective Visual Analytics of Networks, University of Vienna, Austria, June 2018.
Luxembourg Institute of Science and Technology (LIST), Luxembourg, May 2018.
BBC Marketing and Audiences, London, UK, March 2018 (shorter version)
BBC Research, Manchester, UK, January 2018.
Perceptual Issues in Dynamic Graph Drawing: Animation, Small Multiples and Drawing Stability, NII Shonan Meeting 085: Dynamic Network Visual Analytics, Japan, August 2016.
Luxembourg Institute of Science and Technology (LIST), Luxembourg, July 2016.
University of St. Andrews, UK, April 2016.
Edinburgh Napier University, UK, April 2016.
Hong Kong University of Science and Technology, Hong Kong, March 2016.
Ochanomizu University, Tokyo, Japan, January 2015.
University of Kent, Canterbury, UK, November 2013.
Oxford Internet Institute, Oxford, UK, June 2013.
Social Media Visualization: The Themes and Sentiment of the Crowd, University of Glasgow (Institute of Health and Wellbeing), UK, September 2016.

Luxembourg Institute of Science and Technology (LIST), Luxembourg, July 2016

Middlesex University, London, UK, July 2013.
Towards a Better Integration of Information Visualisation and Graph Mining
Hong Kong University of Science and Technology, Hong Kong, April 2017.
University of Glasgow (Cross-School Seminar), UK, September 2016.
A Simple Approach for Boundary Improvement of Euler Diagrams, University of Glasgow (Dept. of Computer Science), UK, April 2016.

Dr Daniel Archambault

Telephone number

Email address

Research Links

About

Areas Of Expertise

Career Highlights

Research Highlights

All Research

Visual Analytics for Explainable Graph-Based Machine Learning (current)

VisualisationofLonginTimeDynamic NetworksonLargeTouchDisplays (awarded 2021)

Geo-spatial Visualization of Public Health Care Data (awarded 2019)

Benefits of and Barriers to Public Engagement with Research (PE-R) for Researchers, Institutions and the Public (current)

Interactive Visualization of Many Trajectories from Molecular Dynamics Simulations in Polar Space (awarded 2021)

'Centrality Metrics Detection of Terrorist Networks.' (awarded 2018)

CS-115 Programming 2

CSCM27 Human-Centred Visual Analytics

CSGD00 Taught Masters Dissertation (Computer Science:Informatique)

CSGM01 Dual Award Swansea Grenoble MSc - Semester

CSGM02 Dual Award Swansea Grenoble MSc - Semester 2

CSGM31 Dual Award Swansea Grenoble MSc - Semester 3 - Advanced Information Systems and Software Engineering

CSGM32 Dual Award Swansea Grenoble MSc - Semester 3 - AI and the Web

CSGM33 Dual Award Swansea Grenoble MSc - Semester 3 - Graphics, Vision and Robotics

CSGM34 Dual Award Swansea Grenoble MSc - Semester 3 - Data Science

CSGM35 Dual Award Swansea Grenoble MSc - Semester 3 - High-confidence Embedded and Cyberphysical Systems

CSGM36 Dual Award Swansea Grenoble MSc - Semester 3 - Parallel, Distributed and Embedded Systems

CSGM37 Dual Award Swansea Grenoble MSc - Semester 3 - Ubiquitous and Interactive Systems

CSGM40 Dual Award Swansea Grenoble MSc - Semester 4 - Project

Post Doctoral Researcher, University College Dublin

Post Doctoral Researcher, INRIA Bordeaux Sud-Ouest

Graduate Studies (M.Sc. and Ph.D.), University of British Columbia

Succeeding by Failing: The Iceberg in VIS Careers

How do recent machine learning advances impact the data visualization research agenda?

Why Social Networks Matter: Social Network Analysis, Visualisation, and the Cambridge Scandal

The Influence of Data Science and AI on Visualisation Perception

Drawing and Visualising Event-Based Dynamic Graphs