Senior Lecturer in Applied Mathematics
School of Mathematical Sciences
Faculty of Engineering, Computer and Mathematical Sciences
Eligible to supervise Masters and PhD, but is currently at capacity - email supervisor to discuss availability.
- My Research
- Grants and Funding
- Professional Activities
I'm a Senior Lecturer in Applied Mathematics at the University of Adelaide. I study how information moves over social networks using mathematical models, coupled with data science techniques. My research interests are in computational social science, human dynamics, online social networks, as well as data assimilation and the mathematics of weather and climate. Please consult my homepage for further information.
Date Position Institution name 2019 Senior Lecturer in Applied Mathematics University of Adelaide 2014 - 2018 Lecturer in Applied Mathematics University of Adelaide 2011 - 2014 Ed Lorenz postdoctoral fellow in the mathematics of climate University of Vermont
Awards and Achievements
Date Type Title Institution Name Country Amount 2018 Award ACEMS Recognition for Outstanding Participation in Outreach Award ARC Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS) Australia 1000 2018 Award ACEMS Outstanding Achievements Recognition Award ARC Centre of Excellence for Mathematical and Statistical Frontiers Australia 1000 2018 Award SA Young Tall Poppy Award Australian Institute of Policy & Science Australia — 2017 Teaching Award ECMS Faculty Teaching Award (Continuing) University of Adelaide Australia 2000 2017 Honour Fresh Science SA Finallist — — —
Date Institution name Country Title 2008 - 2012 University of Sydney Australia PhD 2003 - 2007 University of Wollongong Australia BMath (Hons) (Adv) / BSc (Physics) (Adv)
Research InterestsApplied Mathematics Applied Statistics Artificial Intelligence Computational Linguistics Computer Communications Networks Computer-Human Interaction Information and Computing Sciences Knowledge Representation and Machine Learning Mathematical Sciences Networking & Telecommunications Networking and Communications Neural, Evolutionary and Fuzzy Computation Neurocognitive Patterns and Neural Networks Numerical and Computational Mathematics Numerical Computation Pattern Recognition and Data Mining Simulation and Modelling Social Sciences Methods Stochastic Analysis and Modelling
Year Citation 2017 Mitchell, L. (2017). How the internet knows if you’re happy or sad. In J. Watson (Ed.), The Conversation Yearbook 2017: standout articles from Australia's top thinkers. Melbourne, Australia: Melbourne University Press.
Year Citation 2019 Mathews, P., Gray, C., Mitchell, L., Nguyen, G., & Bean, N. (2019). SMERC: Social media event response clustering using textual and temporal information. In Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018 (pp. 3695-3700). Seattle: IEEE.
2019 Glonek, M., Tuke, S., Mitchell, L., & Bean, N. (2019). GLaSS: Semi-supervised graph labelling with Markov random walks to absorption. In Complex Networks and Their Applications VII: Volume 1 Proceedings The 7th International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2018 Vol. 812 (pp. 304-315). Switzerland: Springer Nature.
2019 Nguyen, A., South, T., Bean, N., Tuke, S. J., & Mitchell, L. (2019). Podlab at SemEval-2019 Task 3: The Importance of Being Shallow. In Proceedings of the 13th International Workshop on Semantic Evaluation (pp. 292-296). online: The Association for Computational Linguistics. 2019 Glenny, V., Tuke, J., Bean, N., & Mitchell, L. (2019). A framework for streamlined statistical prediction using topic models. In Proceedings of the 3rd Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature Vol. abs/1904.06941 (pp. 61-70). online: Association for Computational Linguistics. 2019 Glenny, V. G., Tuke, J., Bean, N. G., & Mitchell, L. (2019). A framework for streamlined statistical prediction using topic models.. In LaTeCH@NAACL-HLT (pp. 61-70). 2018 Hossny, A., & Mitchell, L. (2018). Event detection in Twitter: A keyword volume approach. In Proceedings of the 2nd International Workshop on Social Computing (IWSC’18) Vol. 2018-November (pp. 1200-1208). Singapore: IEEE.
2018 Gray, C., Mitchell, L., & Roughan, M. (2018). Super-blockers and the Effect of Network Structure on Information Cascades. In WWW ’18 Companion: The 2018 Web Conference Companion. online: ACM.
2018 Mitchell, L., Dent, J., & Ross, J. (2018). Mo’ characters mo’ problems: Online social media platform constraints and modes of communication. In Proceedings of the 19th annual conference of the Association of Internet Researchers (AOIR ‘18). Montreal. 2018 Nasim, M., Nguyen, A., Lothian, N., Cope, R., & Mitchell, L. (2018). Real-time Detection of Content Polluters in Partially Observable Twitter Networks. In P. -A. Champin, F. L. Gandon, M. Lalmas, & P. G. Ipeirotis (Eds.), WWW (Companion Volume) (pp. 1331-1339). Lyon: ACM. 2017 Bagrow, J., Danforth, C., & Mitchell, L. (2017). Which friends are more popular than you? Contact strength and the friendship paradox in social networks. In Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (pp. 103-108). online: ACM.
2017 Mathews, P., Mitchell, L., Nguyen, G., & Bean, N. (2017). The nature and origin of heavy tails in retweet activity. In Proceedings of the 26th International World Wide Web Conference (pp. 1493-1498). Perth, Australia: Association for Computing Machinery.
2008 Mitchell, L., & Zhu, S. (2008). Linear diffraction and radiation of surface waves by a hollow suspended cylindrical shell. In Proceedings of the International Conference on Offshore Mechanics and Arctic Engineering - OMAE Vol. 6 (pp. 579-585). Estoril, PORTUGAL: AMER SOC MECHANICAL ENGINEERS.
Curated or Produced Public Exhibition or Events
Year Citation 2019 Mitchell, L. (2019). The Hedonometer exhibit (HEDONISM exhibition, MOD) (No. Of Pieces: 1 hanging sculpture installation) [Exhibition]. MOD (Museum of Discovery), Adelaide. 2019 Mitchell, L. (2019). Connect For exhibit (HEDONISM exhibition, MOD) (No. Of Pieces: 1 interactive display) [Exhibition]. MOD (Museum of Discovery).
Year Citation 2019 Glonek, M., Tuke, J., Mitchell, L., & Bean, N. (2019). Semi-supervised graph labelling reveals increasing partisanship in the
United States Congress.
2019 Gray, C., Mitchell, L., & Roughan, M. (2019). Bayesian inference of network structure from information cascades. 2019 Roughan, M., Mitchell, L., & South, T. (2019). How the Avengers assemble: Ecological modelling of effective cast sizes
2018 Edwards, M., Mitchell, L., Tuke, J., & Roughan, M. (2018). The one comparing narrative social network extraction techniques. 2014 Frank, M. R., Williams, J. R., Mitchell, L., Bagrow, J. P., Dodds, P. S., & Danforth, C. M. (2014). Constructing a taxonomy of fine-grained human movement and activity
motifs through social media.
2013 Bagrow, J. P., Desu, S., Frank, M. R., Manukyan, N., Mitchell, L., Reagan, A., . . . Bongard, J. C. (2013). Shadow networks: Discovering hidden nodes with models of information
Year Citation 2017 Mitchell, L. (2017). Explainer: how the internet knows if you’re happy or sad. The Conversation. 2016 McVernon, J., Ross, J. V., Glass, K., Mitchell, L., Geard, N., & Moss, R. (2016). Computing helps the study of infections on a global and local scale. 2016 Mitchell, L. (2016). How Twitter gives scientists a window into human happiness and health. The Conversation.
- Centre for Invasive Species Solutions: Understanding and intervening in illegal trade in non-native species (with Prof. Joshua Ross and A/Prof. Phill Cassey) ($665,000 over 3 years)
- Data to Decisions CRC Beat The News Project: Predicting common and novel disease outbreaks by assimilating open data into epidemiological models (with A/Prof. Joshua Ross and Prof. Nigel Bean) ($637,606 over 3 years)
- Data to Decisions CRC Beat The News Project: Predicting civil unrest and election outcomes using Bayesian network models (with Dr. Jonathan Tuke and Prof. Nigel Bean) ($661,261 over 3 years)
Courses I've taught
- APPMTH3001 Applied Probability III (2018--)
- MATHS2102 Differential Equations II (2015-17)
- MATHS2104 Numerical Methods II (2015-17)
- MBB Mathematics for Biostatistics (online) (2015)
- MATHS1011 Mathematics 1A (algebra) (2014)
Current Higher Degree by Research Supervision (University of Adelaide)
Date Role Research Topic Program Degree Type Student Load Student Name 2020 Principal Supervisor Understanding Patient Experiences in Healthcare through Natural Langauge Processing Doctor of Philosophy Doctorate Full Time Mr Curtis William Murray 2020 Co-Supervisor Mathematics for Last-Mile Transportation Master of Philosophy Master Full Time Mr Scott James Carnie-Bronca 2019 Principal Supervisor Information Propagation and Community Structure in Social Networks Master of Philosophy Master Full Time Mr Tobin Max South 2019 Co-Supervisor Using Data Assimilation and Lagrangian Coherent Structure Techniques to Improve Error Quantification in Geophysical and Climate Models Master of Philosophy Master Full Time Ms Rose Joy Crocker 2019 Co-Supervisor Carmen et Standard Error: Computational Methods for Stylistics in Latin Poetry Master of Philosophy Master Full Time Mr Benjamin Charles Nagy 2018 Co-Supervisor Applications of Complex Network Analysis for Strategic Decision Making in Australian Rules Football Master of Philosophy Master Part Time Mr Anton Andreacchio 2018 Co-Supervisor Analysing Dynamics of the Illegal Wildlife Trade in Australia Doctor of Philosophy Doctorate Full Time Mr Adam Toomes 2018 Principal Supervisor Analysis of World War 1 Diaries Using Natural Language Processing Master of Philosophy Master Full Time Miss Ashley Grace Dennis-Henderson 2017 Co-Supervisor Early Warning Signals: The Interaction of Social Media With Vaccination and Disease Outbreak Doctor of Philosophy Doctorate Full Time Mr Dennis Liu 2017 Co-Supervisor Modelling Information Cascades: Creating Predictive Models on Temporal Networks Doctor of Philosophy Doctorate Full Time Miss Caitlin Miranda Gray 2016 Co-Supervisor A Census of Social Medial Users: Statistical Techniques for Quantifying and Correcting Biases in Big Open Data Sources Doctor of Philosophy Doctorate Full Time Mr Max Edward Glonek
Past Higher Degree by Research Supervision (University of Adelaide)
Date Role Research Topic Program Degree Type Student Load Student Name 2017 - 2019 Co-Supervisor The One with the Social Network Analysis: The Extraction, Analysis and Modelling of Temporal Social Networks from Narratives Master of Philosophy Master Full Time Miss Michelle Claire Edwards 2017 - 2019 Co-Supervisor Using Approximate Bayesian Computation and Machine Learning Model Selection Techniques to Understand the Impact of Climate on Seasonal Influenza-like Illness in Australia Master of Philosophy Master Full Time Miss Jessica Penfold 2016 - 2019 Co-Supervisor Characterising the Social Media Temporal Response to External Events Doctor of Philosophy Doctorate Full Time Mr Peter Mathews 2016 - 2018 Co-Supervisor A methodology for predictive topic modelling; or, any excuse to watch Love Actually Master of Philosophy Master Full Time Miss Vanessa Grace Glenny
Other Supervision Activities
Date Role Research Topic Location Program Supervision Type Student Load Student Name 2018 - 2018 Principal Supervisor Network analysis of communication on Twitter University of Adelaide — Honours — Declan Jamieson 2018 - 2018 Principal Supervisor Analysis of balance in signed social networks from movies University of Adelaide — Honours — Saranzaya (Saka) Magsarjev 2017 - 2019 Co-Supervisor Prediction using emotional arcs in movies University of Adelaide — Honours Part Time Luke Pickering 2016 - 2018 Co-Supervisor Prediction of civil unrest events using Poisson and Hawkes models University of Adelaide — Honours — Wendy Li 2016 - 2016 Principal Supervisor Information cascades on random networks University of Adelaide — Honours — Caitlin Gray
Connect With Me