Jana Lasser

Postdoctoral Researcher at Graz University of Technology

I am a PostDoc at David Garcia's Computational Social Science lab at the Graz University of Technology and the Complexity Science Hub Vienna.

Drawing from my experience in nonlinear dynamical systems, my current research activity centres around emergent phenomena in complex social systems. I employ methods from machine learning, data science, sociophysics to understand a diverse range of topics, from emotion dynamics to the spread of diseases and misinformation in the field of Computational Social Science.

For my PhD in physics, I conducted research on pattern formation in salt deserts at the Max Planck Institute for Dynamics and Self-Organization and received my degree from the Georg-August-University in Göttingen, Germany in 2019.

Next to my research I care deeply about how the scientific community functions and dysfunctions. I try to improve reproducibility and transparency of research by following Open Science practices and being an outspoken and active proponent of Open Science practices. During my time as the president of the Max Planck PhD association I learned about the rampant mental health problems of many academics and joined the COST action on researcher mental health to help change the academic system for the better.

View CV | download CV
View publications | download publications
ORCID | Google Scholar | Research Gate
Email: jana.lasser@tugraz.at


Research

Spread of SARS-CoV-2 in nursing homes and schools

Illustrative image of the spread of an infection through the contact network of patients in a nursing home In this project I created an agent based simulation to explore the spread of COVID-19 in nursing homes and schools. The model follows an SEIRX approach, building on the agent based simulation framework mesa in which agents can be susceptible (S), exposed (E), infected (I), removed (R) or quarantined (X). The model offers the possibility to explore the effectiveness of various testing, tracing and quarantine strategies and implements a real-world contact network of the respective community. more...

Image showing the risk profile of a farm for certain dairy cattle diseases such as ketosis and lameness I simulate several types of agents (inhabitants and employees or students, teachers and familiy members) that interact in the given context. Agents have explicitly defined contact networks that are defined through their daily interactions. The contact network defines which agents interact with which other agents and different contact venues modulate infection transmission risk (for example infection risk is drastically increased for room mates in nursing homes). In every step (day) of the simulation, agents interact according to their interaction rules and can transmit an infection. Depending on their infection state, an agent has one of five states: susceptible (S), exposed (E), infected (I), removed (R) or quarantined (X). In addition, agents can develop symptoms, can be testable and can have a pending test result (tested). The simulation is calibrated using empirical observations of outbreaks in Austrian nursing homes and schools. After the simulation is calibrated, it allows for the implementation of different prevention strategies such as masks, ventilation, contact reductions or preventive testing. For testing, different test technologies with different detection sensitivities and specificities and result turnover times can be used.

Publications

“Personalized medicine” for dairy cattle

Image showing cows Personalized medicine holds great promise for the treatment of complex and multifaceted diseases such as cancer and diabetes these days. In this project I use a large collection of data about dairy cattle, ranging from feed information about farm management and weather to diagnoses, to devise a paradigm framework for the integration of many information streams to predict diseases. In this project I hope to both make dairy farming more animal friendly and efficient and gain new insights for personalized medicine in humans. more...

Image showing the risk profile of a farm for certain dairy cattle diseases such as ketosis and lameness The idea behind the buzzword “personalized medicine” is to integrate all available information about a single patient to devise a prediction for possible disease outcomes and treatments. The information that could be used for such an endeavour includes biomedical data such as bloodwork or incidence of previous diseases but also information about the general way of life of the patient, such as living conditions, demographics and exercise. Dairy cattle make a good paradigm for such an endeavour, as these animals live in a highly controlled and monitored environment that is rich in data sources. On the other hand, data about cows is easier to handle in a proof of concept, as it is not as sensible as health data of humans.

In collaboration with Peter Klimek's group at the CSH I employ a mixed methods approach of random forests to predict diseases such as ketosis and lameness and multivariate regression models to explain the influence of single variables. Next to its use as a paradigm for personalized medicine in humans, this project is of course also of great interest to the dairy cattle industry, as it holds the promise of improving the wellbeing of cows and therefore efficiency of farms.

Publications

The influence of behavioural factors on measure adherence during the COVID-19 pandemic

Image showing the hypothetical time development of prosiciality, infection rate, and mobility and hygiene behaviour in a population during a pandemic The COVID-19 pandemic is a public health crisis of unprecedented scale in modern times. As long as there is no medical answer, social and behavioural measures are the only available way to curb the spread of the pandemic. The unfolding of the epidemic in a given country therefore greatly depends on its implemented social and behavioural countermeasures and the population’s willingness to adhere to them. There is strong evidence that prosociality drives the willingness to adhere to measures, which is subject to complex social and emotional interaction processes. The aim of this project is to understand how social and emotional interaction processes can sustain prosocial behaviour that prevents the spreading of COVID-19. more...

To do so, I plan to combine large-scale data analysis of social media data with computational modelling of epidemic spreading and human behaviour. To this end I am developing a dynamical model for prosociality which is coupled to a model of epidemic spread. The model of prosociality dynamics is parameterized using empirical measurements of prosocial language on social media and validated by predicting population mobility changes. In collaboration with Allesandro Vespigniani and Viola Priesemann I will combine insights gained in this project with epidemic models, and evaluate if these models can be improved by including behavioural changes and prosocial behaviour.




Completed research projects:

Emotion dynamics and mental health

Image showing three faces: one happy, one sad and one smug Emotions such as happiness, sadness, anxiety and gratefulness accompany us in our daily life. The duration and order in which we experience these emotions can reveal a great deal of insight about the state of our mental health. Using data of consenting users of the emotional health assistant Youper I work with David Garcia to uncover how emotion dynamics influence depression and anxiety. more...

Using the emotional health assistant app Youper, people can track the emotions they experience and their intensity on a regular basis. Using this data for scientific purposes has great value, since it is a rich data set of thousands of users from different countries, with different demographic backgrounds and detailed descriptions of their emotional state. A change in the frequency of switches between certain emotions can herald the onset of a mental health disorder, whereas other emotions are indicative of an improvement in mental health condition. Insights into the influence of emotion dynamics promise new ways to predict changes in mental health state and improve the measures counsellors or emotional health assistant apps can take.

Publications

Pattern formation in salt playa

Image showing salt polygons in a salt desert From fairy circles to patterned ground and columnar joints, natural patterns spontaneously appear in many complex geophysical settings. As part of my research at the MPI for Dynamics and Self-Organization in Lucas Goehring's group I shed light on the origins of polygonally patterned crusts of salt playa and salt pans. These beautifully regular features, approximately a meter in diameter, are found worldwide and are fundamentally important to the transport of salt and dust in arid regions. For my PhD thesis I have combined results from direct field observations, analogue experiments, linear stability theory and numerical simulations to show that the patterns are likely caused by buoyancy-driven convection in the porous soil beneath a salt crust. more...

Image showing a sketch of the convective dynamics in the underground below salt polygons at the surface Salt deserts are not dry - oftentimes the groundwater table reaches up until directly under the salt crust at the top. As their environment is commonly very hot and dry, water constantly evaporates at a high rate through the crust at the surface. As the water evaporates, salt is left behind and accumulates below the surface, forming a layer of saltier and therefore denser and heavier water. For certain conditions, this configuration (heavy salty water on top of light fresh water) becomes unstable and starts convective motion: the salty water sinks down while the fresh water rises to the surface. Convective dynamics are known to form hexagonal patterns and we have shown that the underground below salt patterns shows characteristic salinity distributions indicative of a convective process underneath the pattern.

In our research, we were also able to show that a fast coarsening of the dynamics with time makes the length scale of the expressed patterns independent of the environmental parameters such as soil permeability or the evaporation rate. Lastly, the crust itself interact with the evaporation through the surface that drives the convective motion by inhibiting evaporation at the salt ridges. This helps to "pin" the convection rolls in place and stabilizes the dynamics so intricate salt patterns can grow on the surface.

Publications

Biological transport networks

Image showing the venation network of a plant leaf Transport networks are ubiquitous in nature: blood vessels, neurons or veins in plant leaves all transport a quantity or signal that is crucial for an organism to thrive. These networks have evolved over time together with their host organisms. They feature optimized properties such as resilience to damage and transport efficiency. To compare network models with real-life network implementations, the availability of high-quality data is of great importance. This is where my research comes in more...

Image showing the extracted tubular network of Drosophila trachea For my bachelor's thesis, I developed NET, the Network Extraction Tool (code). NET is a freely available, fully Open Source program developed in Python. It can be used to turn digital images of two-dimensional networks into a graph composed of nodes and edges. This creatly compresses the representation of the network while keeping the important information about connections, node positions and edge widths intact.

Using transport networks extracted from high resolution scans of plant leaves, it is possible to classify plants based on the topology and geometry of their transport networks. Next to leaf geometry and size, the network architecture constitutes a new dimension in the phenotypic space of leaves. Evolutionarily younger leaves tend to express more reticulate networks that have a higher resistence to damage at the cost of a higher material need to construct the network. Insights into the properties and evolution of these networks can be used to inform the design of human networks such as the Tokyo subway.

Another application of NET was the extraction of network information from microscopy images of Drosophila trachea. In my master's thesis I analysed the trachea networks of fruit fly larvae and developed metrics to quantify the impact of different gene knockouts on network growth in early developmental stages.

Publications

Talks

Agent-based simulations for optimized prevention of the spread of SARS-CoV-2 in nursing homes

Slides available in English and a shorter German version.


Salt polygons and porous media convection

Slides available here.

Teaching

Data Literacy

Together with colleagues from the Centre for Statistics in Göttingen I developed a course to teach "Data Literacy" to entry level students at the University of Göttingen. The aim of the course is to teach students basic knowledge and practical skills to be able to handle, explore and analyse data and make data driven decisions. The course is split into an introduction to Python - the programming language that is used to perform data handling and analysis tasks - and case studies for different disciplines. All course materials are available in German and English under an open license for re-use. We have published our experiences with the implementation of a novel Data Science curriculum in a series of three blog posts and a publication about the content and structure of our course (preprint available here).

Programming in Python

Image showing the logo of the programming language Python

During my time as doctoral researcher at the University of Göttingen and the MPI for Dynamics and Self-Organization, I developed and taught several introductory level courses to programming in Python. I also taught such a programming course specifically "from women for women" which was a great experience. All course materials are available in English and German under an open license for re-use.

Live hack sessions

Image showing the distribution of lengths of Tweets from Donald Trump, Russian trolls and normal Twitter users

Programming is one of my favourite activities. One of the appeals for me is that it is actually a rather easy and forgiving process, since it gives instantaneous feedback if something works and has a large and supportive community that can help with every problem imaginable. Nevertheless, it is often very hard to get people who never wrote a line of code to give it a try, since it oftentimes seems scary and too hard to learn. To solve this problem, I have started to host "live hack sessions" where I, together with a handful of programming novices, sit down for a couple of hours and we solve an easy but hopefully interesting problem together, using Python. The first of these sessions about analysis of Tweet data of Donald Trump, Russian trolls and normal Twitter users is available here and free to be re-used.


Open Science

Image showing the logo of the Open Science movement

When I was in my undergrad and I first learned about the process of publishing science, my mind was blown. I could not understand how researchers payed by tax money create research, which is then taken by big, for-profit publishing companies and hidden behind a paywall. This motivated me to get into Open Science and start doing something about the situation. At first my interest was focused on Open Access, but quickly was joined by my habit of Open Sourcing my code and creating Open Educational Resources. During my PhD and as part of my service as president of the Max Planck PhDnet I got interested in research integrity. These days I think that employing Open Science practices in research workflows is a great tool to foster good science and research integrity.

Executable papers

Image showing a graphical recording of a talk Jana Lasser gave at the final workshop of the Open Knowledge fellows 2019/20
Picture © 2020 Gabriele Heinzel, CC-BY-SA 4.0

In the years 2019/20 I was an "Open Knowledge" fellow of the Wikimedia foundation, which allowed me to explore a longstanding fascination of mine more deeply: the executable paper. The executable paper is a scientific publication as a dynamic piece of software that combines text, raw data, and the code used for the analysis, that a reader can interact with and that makes the process of the generation of insights transparent. For me it is a way to remedy the problem of non-transparent (and even sloppy) research and support data availability and transparency of methods. I wrote a series of blogposts about how to create an executable paper and what I learned in the process. The result of my work - an executable version of one of my publications about pattern formation in salt deserts is online and ready to be explored .


Open Source

I strive to make all my code openly accessible on my GitHub profile. Most notably I published the software package small community SEIRX , a software package in Python for the simulation of disease spread in small human communities. During my undergrad, I wrote NET , a software package in Python to extract graphs from high-resolution images of networks. Feel free to open issues in the respective repositories if you find bugs or have trouble re-using something I created!

Open Educational Resources

Image showing the logo of the Open Educational Resources movement

Similar to code I create, I make teaching resources I create openly accessible and re-usable on my GitHub profile. So far, I have created


Service

Max Planck PhDnet - combating power abuse in academia

Image showing the logo of the Max Planck PhDnet During my time as doctoral researcher at the Max Planck Institute for Dynamics and Self-Organization, I served as representative for the doctoral researcher community for many years. In 2018 , I was spokesperson of the Max Planck PhDnet, an organization that represents the over 5000 doctoral researchers of the Max Planck Society. During my time as spokesperson, several scandals about power abuse in academia shook the Max Planck Society. This motivated me, together with colleagues, to write a white paper about power abuse and conflict resolution in academia and give several interviews about the subject.

N² network of networks - surveying doctoral researchers

Image showing the logo of the N2 network of networks After I finished my PhD in 2019, I keep serving as advisory board member for , the network of representations of doctoral researchers of non-university research organizations in Germany. In my function as advisory board member, I am mostly involved in the conduction and analysis of large-scale surveys about the working conditions of doctoral researchers. In the 2017 survey the survey, for the first time, focused on the mental health of early career researchers. The survey revealed rampant mental health problems of doctoral researchers - as shown in the figure below. In 2018 the report focused on good scientific practice and supervision quality. In 2019, we returned to mental health, this time in connection with mobbing and power abuse. Expect the report to be online soon... Bar diagram showing the number of doctoral researchers in the Max Planck Society that suffer from symtoms related to poor mental health
During your doctoral research, have you had health problems with any of the following conditions? Multiple answers possible. Also included are percentages of respondents giving multiple affirmative answers to symptoms listed.

COST action researcher mental health

As part of my efforts to improve the environment in which research is conducted, I joined the COST action "Researcher Mental Health" as national member for Austria. We will start our activities in the fall 2020.

Latest Publications

* indicates shared first authorship
  • Peer reviewed article
    Jana Lasser, Lindsey Bultema, Anja Jahn, Michaela Löffler, Vera Minneker, Cornelia van Scherpenberg
    Power abuse and anonymous accusations in academia – Perspectives from early career researchers and recommendations for improvement
    Beiträge zur Hochschulforschung (2021)
    @article{lasser2021power,
    					title = {Power abuse and anonymous accusations in academia – Perspectives from early career researchers and recommendations for improvement},
    					year = {2021},
    					journal = {Beitr\"age zur Hochschulforschung},
    					author = {Lasser, Jana and Bultema, Lindsey and Jahn, Anja and L\"offler, Michaela and Minneker, Veran and van Scherpenberg, Cornelia},
    					volume={1-2},
    					pages = {48--61},
    					url = {https://www.bzh.bayern.de/fileadmin/user_upload/Publikationen/Beitraege_zur_Hochschulforschung/2021/2021-1-2-Lasser-Bultema-Jahn-Loeffler.pdf}
    					}
    										
  • Peer reviewed article
    Jana Lasser*, Marcel Ernst*, Lucas Goehring
    Stability and dynamics of convection in dry salt lakes
    Journal of Fluid Mechanics (2021)
    @article{lasser2020stability,
      					title={Stability and dynamics of convection in dry salt lakes},
      					author={Lasser, Jana and Ernst, Marcel and Goehring, Lucas},
      					journal={Journal of Fluid Mechanics},
      					DOI={https://doi.org/10.1017/jfm.2021.225},
      					year={2021}
    					}
    					
  • Preprint
    Jana Lasser, Johannes Sorger, Lukas Richter, Stefan Thurner, Daniela Schmid, Peter Klimek
    Assessing the impact of SARS-CoV-2 prevention measures in schools by means of agent-based simulations calibrated to cluster tracing data
    arXiv (2020)
    @article{Lasser2021,
    				  url = {https://www.medrxiv.org/content/10.1101/2021.04.13.21255320v1},
    				  year = {2021},
    				  month = apr,
    				  publisher = {medRxiv},
    				  author = {Jana Lasser and Johannes Sorger and Lukas Richter and Stefan Thurner and Daniela Schmid and Peter Klimek},
    				  title = {Assessing the impact of SARS-CoV-2 prevention measures in schools by means of agent-based simulations calibrated to cluster tracing data}
    				}
                
  • Preprint
    Jana Lasser, Caspar Matzhold, Christa Egger-Danner, Birgit Fuerst-Waltl, Franz Steininger, Thomas Wittek, Peter Klimek
    Integrating diverse data sources to predict disease risk in dairy cattle
    BioRxiv (2021)
    @article{Lasser2021,
    				  doi = {10.1101/2021.03.25.436798},
    				  url = {https://doi.org/10.1101/2021.03.25.436798},
    				  year = {2021},
    				  month = mar,
    				  publisher = {Cold Spring Harbor Laboratory},
    				  author = {Jana Lasser and Caspar Matzhold and Christa Egger-Danner and Birgit Fuerst-Waltl and Franz Steininger and Thomas Wittek and Peter Klimek},
    				  title = {Integrating diverse data sources to predict disease risk in dairy cattle}
    				}
                
  • Python Package
    Jana Lasser
    Agent based simulation of the spread of COVID-19 in confined spaces
    PyPi (2021)
    @misc{lasser2021small,
                        doi = {https://doi.org/10.5281/zenodo.4613202},
                        url = {https://pypi.org/project/scseirx/1.3.0/},
                        author = {Lasser, Jana},
                        title = {Agent based simulation of the spread of COVID-19 in confined spaces},
                        publisher = {PyPi},
                        year = {2021},
                        copyright = {MIT license}
                      }
                
  • Blog article
    Cornelia van Scherpenberg, Lindsey Bultema, Anja Jahn, Michaela Löffler, Vera Minneker, Jana Lasser
    Manifestations of power abuse in academia and how to prevent them
    Elephant in the Lab (2021)
    @article{https://doi.org/10.5281/zenodo.4596397,
                        doi = {10.5281/ZENODO.4596397},
                        url = {https://zenodo.org/record/4596397},
                        author = {Scherpenberg,  Cornelia and Bultema,  Lindsey and Jahn,  Anja and L\"{o}ffler,  Michaela and Minneker,  Vera and Lasser,  Jana},
                        title = {Manifestations of power abuse in academia and how to prevent them},
                        publisher = {Elephant in the Lab},
                        year = {2021},
                        copyright = {Creative Commons Attribution 4.0 International}
                      }
                
  • Peer reviewed article
    Julia S. Yarrington* Jana Lasser*, David Garcia, Jose H. Vargas, Diego D. Couto, Thiego Marafon, Michelle G. Craske, Andrea N. Niles
    Impact of the COVID-19 Pandemic on Mental Health among 157,213 Americans
    Journal of Affective Disorders (2021)
    @article{yarringon2020impact,
    	            title={Impact of the COVID-19 Pandemic on Mental Health among 157,213 Americans},
    	            author={Julia S. Yarrington and Jana Lasser and David Garcia and Jose Hamilton Vargas and Diego Dotta Couto and Thiago Marafon and Michelle G. Craske and Andrea N. Niles},
    	            journal={Journal of Affective Disorders},
    	            pages={64--70},
    	            year={2021},
    	          }
    	          
  • Preprint
    Jana Lasser, Johannes Zuber, Johannes Sorger, Elisabeth Klager, Maria Kletečka-Pulker, Harald Willschke, Katrin Stangl, Sarah Stadtmann, Christian Haslinger, Peter Klimek, Thomas Wochele-Thoma
    Agent-based simulations for optimized prevention of the spread of SARS-CoV-2 in nursing homes
    arXiv (2020)
    @article{Lasser2021,
    				  url = {https://arxiv.org/abs/2104.00550},
    				  year = {2020},
    				  month = nov,
    				  publisher = {arXiv},
    				  author = {Jana Lasser and Johannes Zuber and Johannes Sorger and Elisabeth Klager and Maria Kletečka-Pulker and Harald Willschke and Katrin Stangl and Sarah Stadtmann and Christian Haslinger and Peter Klimek and Thomas Wochele-Thoma},
    				  title = {Agent-based simulations for optimized prevention of the spread of SARS-CoV-2 in nursing homes}
    				}
                
  • Peer reviewed article
    Jana Lasser, Jo Nield, Lucas Goehring
    Surface and subsurface characterisation of salt pans expressing polygonal patterns
    Earth System Science Data (2020)
    @article{lasser2020surface,
    	            title={Surface and subsurface characterisation of salt pans expressing polygonal patterns},
    	            author={Lasser, Jana and Nield, Joanna M and Goehring, Lucas},
    	            journal={Earth System Science Data},
    	            pages={1--31},
    	            year={2020},
    	            publisher={Copernicus GmbH}
    	          }
    	          
  • Peer reviewed article
    Jana Lasser , Verena Ahne, Georg Heiler, Peter Klimek, Hannah Metzler, Tobias Reisch, Martin Sprenger, Stefan Thurner and Johannes Sorger
    Complexity, Transparency and Time Pressure: Practical Insights into Science Communication in Times of Crisis
    Journal of Science Communication (2020)
    @article{Lasser2020,
    					  doi = {10.22323/2.19050801},
    					  url = {https://doi.org/10.22323/2.19050801},
    					  year = {2020},
    					  month = sep,
    					  publisher = {Sissa Medialab},
    					  volume = {19},
    					  number = {05},
    					  author = {Jana Lasser and Verena Ahne and Georg Heiler and Peter Klimek and Hannah Metzler and Tobias Reisch and Martin Sprenger and Stefan Thurner and Johannes Sorger},
    					  title = {Complexity,  transparency and time pressure: practical insights into science communication in times of crisis},
    					  journal = {Journal of Science Communication}
    					}
    					
  • Peer reviewed article
    Amélie Desvars-Larrive et al.
    A structured open dataset of government interventions in response to COVID-19
    Nature Scientific Data (2020)
    @article{DesvarsLarrive2020,
    					  doi = {10.1038/s41597-020-00609-9},
    					  url = {https://doi.org/10.1038/s41597-020-00609-9},
    					  year = {2020},
    					  month = aug,
    					  publisher = {Springer Science and Business Media {LLC}},
    					  volume = {7},
    					  number = {1},
    					  author = {Amélie Desvars-Larrive and Elma Dervic and Nils Haug and Thomas Niederkrotenthaler and Jiaying Chen and Anna Di Natale and Jana Lasser and Diana S. Gliga and Alexandra Roux and Johannes Sorger and Abhijit Chakraborty and Alexandr Ten and Alija Dervic and Andrea Pacheco and Ania Jurczak and David Cserjan and Diana Lederhilger and Dominika Bulska and Dorontinë Berishaj and Erwin Flores Tames and Francisco S. àlvarez and Huda Takriti and Jan Korbel and Jenny Reddish and Joanna Grzyma{\l}a-Moszczyǹska and Johannes Stangl and Lamija Hadziavdic and Laura Stoeger and Leana Gooriah and Lukas Geyrhofer and Marcia R. Ferreira and Marta Bartoszek and Rainer Vierlinger and Samantha Holder and Simon Haberfellner and Verena Ahne and Viktoria Reisch and Vito D. P. Servedio and Xiao Chen and Xochilt María Pocasangre-Orellana and Zuzanna Garncarek and David Garcia and Stefan Thurner},
    					  title = {A structured open dataset of government interventions in response to {COVID}-19},
    					  journal = {Scientific Data}
    					}
    					
  • Commentary
    Jana Lasser
    Creating an executable paper is a journey through Open Science
    Communication Physics (2020)
    @article{lasser2020creating,
      					title={Creating an executable paper is a journey through Open Science},
      					author={Lasser, Jana},
      					journal={Communication Physics},
      					year={2020},
      					doi={10.1038/s42005-020-00403-4}
    					}
    					
  • Peer reviewed article
    Max Pellert, Jana Lasser , Hannah Metzler and David Garcia
    Dashboard of sentiment in Austrian social media during COVID-19
    Frontiers in Big Data (2020)
    @article{pellert2020dashboard,
      					title={Dashboard of sentiment in Austrian social media during COVID-19},
      					author={Pellert, Max and Lasser, Jana and Metzler, Hannah and Garcia, David},
      					journal={Front. Big Data},
      					year={2020},
      					doi={10.3389/fdata.2020.00032}
    					}
    					
  • Preprint
    Jana Lasser, Joanna M Nield, Marcel Ernst, Volker Karius, Giles FS Wiggs, Lucas Goehring
    Salt Polygons are Caused by Convection
    arXiv (2020)
    @article{lasser2019salt,
    				  		title={Salt polygons are caused by convection},
    				  		author={Lasser, Jana and Nield, Joanna M and Ernst, Marcel and Karius, Volker and Wiggs, Giles FS and Goehring, Lucas},
    				  		journal={arXiv preprint arXiv:1902.03600},
    				  		year={2019}
    						}
    					
  • Commentary
    Charley M Wu, Benjamin Regler, Felix K Bäuerle, Martin Vögele, Laura Einhorn, Sofia Elizarova, Stefanie Förste, Justin Shenolikar, Jana Lasser
    Perceptions of publication pressure in the Max Planck Society
    Nature Human Behaviour (2019)
    @article{wu2019perceptions,
    			  			title={Perceptions of publication pressure in the Max Planck Society},
    			  			author={Wu, Charley M and Regler, Benjamin and B{\"a}uerle, Felix K and V{\"o}gele, Martin and Einhorn, Laura and Elizarova, Sofia and F{\"o}rste, Stefanie and Shenolikar, Justin and Lasser, Jana},
    			  			journal={Nature human behaviour},
    			  			volume={3},
    			  			number={10},
    			  			pages={1029--1030},
    			  			year={2019},
    			  			publisher={Nature Publishing Group}
    						}
    					

Contact & services

Speaker

Image showing Jana Lasser on a discussion panel
Picture © 2020 Judith Affolter
I am an outspoken advocate of Open Science and research integrity and am open to sharing my expertise as a researcher and academic in interviews, as conference speaker and on discussion panels. Don't hesitate to contact me to speak about the following topics

  • Power abuse in academia
  • Open Science
  • Mental health in academia
  • Data Science and Data Literacy


Teacher

Picture showing Jana Lasser and a laptop
Picture © 2019 Damian Gorczany

I am open to teaching seminars and holding workshops about

  • Programming in Python
  • Introduction to Data Science
  • Preventing power abuse in academia




Reach me at

Profile picture of Jana Lasser
Picture © 2018 Timotheus Hell. You can use this high resolution image for the purpose of reporting about my research and related activities after contacting me via email.

Jana Lasser
Complexity Science Hub Vienna
Josefstädterstraße 39
1080, Vienna

Mail: jana.lasser@tugraz.at
Twitter: @janalasser
ORCID: 0000-0002-4274-4580