Community Support

HIIT supported the Helsinki ICT Community by providing funding for the following activities:

  • Organising events such as workshops, conferences, hackathons, bootcamps, and summer schools.
  • Initiating new collaboration on potentially high-impact research challenges, often in a multi-disciplinary and cross-university setting.
  • Inviting postdoctoral researchers for short visits that may lead to recruitment.
  • Visiting high-profile universities or other organisations abroad.
  • Boosting the careers of young researchers by providing short-term “bridge funding”.

This funding was not limited to the HIIT research programmes, but was open to the whole Helsinki ICT community. In addition, it served an important purpose by being applicable to cases where other funding instruments were not easily available or the funding from other sources was not sufficient.

For a sample of the activities of the HIIT programmes, please see Research Highlights.

In 2018, 35 Community Support proposals received about 180 000 euros in total. Half of this was spent on nurturing new collaboration and about one third on sponsoring events. Career boost funding was granted to one young researcher to enable him to gain international experience after the completion of his award-winning PhD thesis. In addition, HIIT financed six research visits from Finland abroad and one visit of a postdoc candidate from abroad to Finland.

Distribution of Community Support in 2018.

11 initiatives for new collaboration were supported. HIIT provided “seed funding” for several multi-disciplinary projects to enable them to be started in small scale before the main funding from other sources had become available. These included e.g. analysis of data from the Euclid space telescope in virtual supercomputing environments, development of thermal imaging systems to improve energy management in buildings, and experiments with computer vision, augmented reality and collaborative economy in the context of education. HIIT also supported new collaboration by covering travel expenses involved in preparing contracts, research plans and joint funding applications. The partners in these initiatives were The Alan Turing Institute, IE Business School, the University of Washington and the University of Stockholm.

Among the 14 supported events there were international conferences such as ALGO, StanCon and ICER, smaller workshops in e.g. computational social science, astronomy and animal computer interaction, and hands-on programming sprints like the Helsinki Di­gital Hu­man­it­ies Hack­a­thon and the HIIT Open programming contest. Machine Learning Coffee Seminar and Helsinki Algorithms Seminar continued as weekly events with the location alternating between Aalto University and the University of Helsinki.

Examples of supported activities

Multi-disciplinary research is leading to broader perspectives on socio-technical systems

The 2019 ACM Conference on Fairness, Accountability, and Transparency took place in Atlanta at the end of January. Jouni Harjumäki, a data science master’s student at the University of Helsinki, participated in the conference with support from HIIT.

Computer science oriented research in this field has, broadly, followed one of two lines. The first, fairness-aware machine learning, is often concerned with datasets encoding socially unacceptable biases (for example, prejudice against a certain group of people reflected as a lower rate of desirable outcomes), definitions and properties of various bias measures, and methods for mitigating these biases in a supervised learning scenario. The other major area of research has focused on making complex machine learning models more transparent and their decisions more explainable.

While topics around these questions were discussed at the conference, now in its second iteration, there was a trend toward more holistic approaches to socio-technical systems. Instead of merely defining a social phenomenon as a mathematical problem, and then optimizing it, several papers encouraged scholars and practitioners to tackle the issue in much deeper terms, trying to come to terms with the complex interplay of the social and technical aspects of the system.

The diversity of the presenters and other participants made this possible – in addition to people with a computer science background, there were a great number of social scientists, philosophers, legal scholars, and others. Also, not everybody was an academic: industry and non-governmental organizations were also represented at the conference. As machine-learning based and other technical systems are being propagated throughout society with ever increasing impact on people’s lives, computer scientists cannot and should not ignore the social questions – or worse, try to solve them by themselves.

Cooperation with The Alan Turing Institute is moving forward

In early March 2019, Aalto University, the University of Helsinki and The Alan Turing Institute signed a Memorandum of Understanding, which expresses the desire of the parties to develop their cooperation further. The Alan Turing Institute is the national institute for data science and artificial intelligence in the UK, known for its high-quality research and teaching. Attempts will be made to facilitate visits of the academic staff to participate in joint teaching, training and research, and to collaborate on joint publications. Interesting opportunities may also exist for joint funding submissions and exchange of data sets and other scientific materials.

The professors Kimmo Kaski (Aalto), Petri Myllymäki (UH) and Mark Girolami (ATI) have been named as the administrative contact persons of the initiative.

Effectiveness of Augmented Reality explored in a user study in Heureka

Professor Yu Xiao’s group at Aalto ELEC has initiated multi-disciplinary research collaboration with professor Atte Oksanen’s group at the Faculty of Social Sciences of the University of Tampere. They have developed an Augmented Reality quiz for the visitors of the Finnish Science Center Heureka. While walking around, the visitors see questions and problems on augmented objects in the exhibition space.

The focus of the user study is to analyze how people perceive the Augmented Reality and how it influences their social behavior. The experiences of 3 different groups of people are compared: those using the augmented reality application, those using a regular mobile application and those doing a quiz on a sheet of paper. Results from over 400 participants have been collected, and the analysis is in progress.

A video about the research is available on the Aalto Mobile Cloud Computing group website.

Objects in the exhibition space are augmented with quiz questions

Multidisciplinary research project explored possibilities of wearable technology in performing arts

A multidisciplinary research project titled “Digitalising Performance With Wearables and Software” brought together Aalto ARTS, Aalto Science and the University of the Arts Helsinki for fruitful collaboration. The idea was conceived by Dr. Sofia Pantouvaki, a Professor of Costume Design, and Dr. Mario Di Francesco, a Professor of Computer Science. Realising that light was going to be a crucial part of the project, they contacted the Professor of Lighting Design, Dr. Tomi Humalisto from the University of the Arts. This team of three professors from different fields worked out the framework and objectives for the project that would culminate in a technology enhanced art performance.

The artistic content of the project was left open for the students to decide. Three students with diverse backgrounds worked intensely for three months and came up with an interactive performance between a circus artist, costume, lights, space and sounds. Costume design student Tjaša Frumen, computer science research intern Emilio Lopez and lighting design student Mia Jalerva were the core international team, Frumen coming from Slovenia, Lopez from Argentina and Jalerva from Finland.

The group worked on the project in multiple locations around Helsinki and Espoo. The costume of the performer was made at the Costume Design Workshop of Aalto Studios, the software was tested at Motion Lab of Aalto’s computer science department, and the lights were designed and built at VÄS lighting design studio at UniArts. Kallio Stage was the venue for the final performance.

During the course of the work, a number of technical challenges had to be addressed. The costume of the performer, circus artist Aliisa Rinne, contained 16 meters of wire with LED lights, sensors and other technology. These had to be embedded so that she was able to move smoothly and even use the trapeze. The software worked without requiring manual operation during the performance, making the light to either follow the performer or repel her, for example.

The professors were impressed by the results of the work and see great potential in the future of performer-technology interaction. While self-regulating, wearable technology has been used in dance quite a lot already, other performing arts such as theatre, musical theatre and even opera could reach new levels of technology interaction. The project also serves as an inspiring example of multidisciplinary collaboration, in which diverse expertise is utilised and developed further in a creative way.

For more information, please see the write-up of Aalto Studios. A video recording of the final performance is available in YouTube.

Animal Computer Interaction conference: what it means to be an animal participant

In December 2018, researchers in animal science and computer science met for the fifth annual Animal Computer Interaction (ACI) conference, held in Atlanta at Georgia Institute of Technology. Much like humans, animals have also been using computers for a long time. Historically animals have used computer technology in space, used lexigrams (symbol keyboards) to form language, and dolphins have used underwater keyboards.

Drawing parallels to human-computer interaction (HCI) research, which studies how humans use computers, ACI aims to investigate how animals interact with technology and the design of related devices. These technologies are developed to be used with animals in zoos and sanctuaries, working animals, domesticated animals in our homes, and wild animals. In HCI, user-centred design is an established methodology for designing with the user by including them as a participant within the design process itself. However, with animals, it is not so clear what it means to be a ‘participant’. For instance, humans can give feedback and consent to being in research – but how can this be achieved with animals? Being a participant, in some way, within the design processed is important in animal-computing to strive towards better and more informed designs.

Ilyena Hirskyj-Douglas, from Aalto University’s Computer Science department, along with Charlotte Robinson (Sussex University) and Patricia Pons (Polytechnic University of Valencia) brought this topical issue to attention in the form of a world café workshop titled ‘Designing for Animals: Defining “Participation” in Animal-Computer Interaction’ at the ACI 2018 conference. Ilyena recently attained her PhD in England in dog-computing systems where she looked at methods for allowing dogs to interact with screen devices. Bringing her expert knowledge now to Aalto, she has recently published the first literature review on ACI as well as the first dog-driven screen device.

The workshop was attended by more than twenty ACI researchers and students, animal behaviourists, and practitioners bringing a multidisciplinary group together. Here, questions were raised on participation: on how to support the animal involvement in technology, how to define participation, and the different roles animals could take in technology.

Besides group activities, keynote talks were given to stimulate the conversation by Melody Jackson, head of the ACI lab in Georgia Tech.; Clara Mancini, head of the ACI lab at the Open University, who also founded the field; and Yoram Chisik, from Rhein-Waal University of Applied Sciences, who related ACI to child-computer interaction.

For more information, please see

Fairness and bias of the COMPAS algorithm compared to human assessments

The Data Mining Group of Aalto University is collaborating with researchers from the Indian Institute of Science, Polish Academy of Sciences and the University of Turku to explore algorithmic and human fairness and bias in decision making. In particular, they focus on racial bias in the predictions of the Correctional Offender Management Profiling for Alternative Sanctions (COMPAS) algorithm, a criminal risk assessment tool used in sentencing in a number of states in the U.S. The project, titled “Algorithms, fairness, and race: Comparing human recidivism risk assessment with the COMPAS algorithm”, was initiated at the Helsinki Summer Institute in Computational Social Science 2018.

The project consists of two parts. In the first part the team explored a wide set of fairness metrics and demonstrated how data preprocessing performed in previous (published) studies affects the fairness assessment of algorithmic recommendations. In the second part they collected their own data to evaluate human fairness and bias, which they then compared with the COMPAS assessment. In doing so, they drew from sociological concepts of in-group bias, social status, and stereotyping to formulate hypotheses about the patterns of associations between the respondent’s race, the race of the evaluated defendant, and the recidivism predictions.

The second part was based on a vignette survey run on TurkPrime. The respondents were presented with short descriptions of defendants and asked to predict recidivism risk. The survey was designed to have a balanced composition of white and black respondents, who were presented with vignettes of white and black defendants. Defendant descriptions came from real data on pre-trial defendants, which makes it possible to compare their COMPAS scores, real recidivism data, and risk assessment by survey respondents.

The first results were presented as a poster at the European Symposium Series on Societal Challenges in Computational Social Science held in Cologne, Germany on December 5th-7th, 2018. Preliminary analyses show that respondents are more lenient towards the offenders of their own race, but the differences are not large. However, if we exclude the defendants with medium-risk COMPAS scores and cases with high disagreement among the respondents (the majority is supported by less than 3/4 of the respondents of the same race), then race does not play a role and prediction rates agree. This suggests that decisions in ambiguous medium-risk cases are most susceptible to bias. Currently the team is working on finalising the analysis and writing up a paper.

Aalto’s Mobile Cloud Computing Group is collaborating with CMU in Wearable Cognitive Assistance

Cognitive assistance is a promising application area for wearable computing. In the context of mechanical assembly, the user is guided through the step-by-step sequence of a task workflow. The end point of each step (e.g. a particular screw mounted flush into a workpiece) needs to be defined precisely, while being tolerant of alternative paths to reaching that end point (e.g. hand-tightening versus using a screwdriver). Authoring a wearable cognitive assistance application is time-consuming and often requires collaboration between a task expert and a software developer with highly specialized skills in computer vision. Developing a single application typically takes several person-months of effort.

Aalto’s mc2 – Mobile Cloud Computing group is collaborating with Prof. Mahadev Satyanarayanan‘s group at Carnegie Mellon University (CMU) to create more effective tools. The CMU group has developed Gabriel, an edge computing platform for cognitive assistance, and has experience from several applications built on top of it. The mc2 group has complementary expertise in automatic extraction of workflows from first-person videos.

Truong-An Pham from the mc2 group made a two-month research visit to CMU in Autumn 2018. Among the results of the collaboration is a three-stage toolchain for generating cognitive assistance applications for mechanical assembly:

  1. A workflow is extracted automatically from videos of experts performing a task. Since the extraction process is imperfect, a workflow editing tool is provided for making corrections.
  2. The vision-based object detectors needed for the task are created. Accurately detecting the presence and location of relevant objects in a video frame is the key to recognizing progress on a task. The work is done by a task expert, who creates training data for deep neural networks using a web-based tool.
  3. The extracted workflow and the object detectors are linked to generate task-specific executable code for the task-independent Gabriel platform. Cognitive assistants are represented as finite state machines (FSMs), in which each state represents a working step or an error case. Changes detected in the input video stream trigger state transitions. Libraries are provided to create, persist and debug the FSMs.

The next major step in the project is a user study conducted at Aalto University in May 2019.

Overview of the toolchain

Rajapintapäivät brought together researchers of social and computer sciences

Digital and computational social science approaches are raising interest among researchers. Rajapintapäivät gathered more than fifty scholars in Otaniemi in mid-November to discuss their research and issues related to interdisciplinary collaboration.

Rajapinta is a scientific association and researcher community that advocates the social scientific study of ICT and ICT applications to social research. The association aims to improve interdisciplinary collaboration and to provide opportunities for meetings and networking. The association’s second annual event Rajapintapäivät, supported by HIIT, was organized in Otaniemi on November 16-17. Despite its Finnish name, the majority of the event’s content was in English.

The event’s themes were related to many forms of interdisciplinary research involving social sciences and computing: for example, using machine learning for social science research, the design of digital systems, coding education, large-scale data collection from social media, and studies of software and developers.

Rajapintapäivät drew together approximately 50 participants in the main event. The majority were academics from different fields of social science or computer science, along with scholars from humanities and legal studies, and a handful of representatives of the public sector, private sector analytics firms and civil society organizations.

The event’s workshop day on November 16th saw three workshops. One focused on the ethical challenges of research projects involving digital data and digital methods. The second workshop discussed infrastructures for data-intensive social sciences in Finland. The third workshop was a thesis seminar aimed for students working on a Master’s thesis on relates to digital society, social scientific study of ICT, or ICT applications to social research.

The main event was an unconference on November 17th. In an unconference, the content is provided by the participants in a self-organized manner, and the space was open for anyone interested to organize a session. There were altogether 24 sessions in the unconference programme. The day included, in addition to regular academic presentations, several more experimental sessions; for example an open fishbowl panel on studying algorithms and spreading knowledge on good digital privacy practices for researchers. A further example was a peer meeting organized by data scientists working in social-scientific projects, covering issues such as the role data scientists could take in an interdisciplinary project, dealing with the need to know both CS and social sciences, and appropriate publication venues for results emerging from such projects. Such peer meetings were seen as a helpful means of fostering collaboration as projects including researchers with different backgrounds are increasingly common.

The event was free of charge to participants thanks to generous support by HIIT. The event was also supported by Kone Foundation.

Researchers in computer vision and natural language processing are finding common ground

Computer vision and natural language processing are normally thought of as two separate research fields. However, significant merger is happening in some areas, such as image and video captioning and visual question answering. This creates interesting opportunities for collaboration.

The Empirical Methods in Natural Language Processing conference (EMNLP) has opened a special track on vision and language. Hamed Rezazadegan Tavakoli, a postdoctoral researcher at Aalto University, attended the 2018 conference in Brussels. Tavakoli and his collaborators build systems that perceive their environment and describe it using natural language. During the conference, he met with Professor Noah Smith from the University of Washington to discuss the grounds for a mutual project.

Foundations of Data Economics explored in a seminar

As the first snow of this winter fell and melted away, Aalto University had the pleasure of hosting Dr. Bruno Carballa Smichowski of Université Paris XIII and Groupe Chronos for a Seminar in Data Economics. The seminar was attended by a dozen of Aalto doctoral and some master’s students, and a few guests from outside of Aalto. For a week from Monday to Friday, we enjoyed every morning Bruno’s elucidative explanations on why data is very different from the other factors of production and how the resulting economy is different. The topics we covered included how data gains its value, data platforms (including platform companies and their business models), the (anti)competitive dynamics in the data economy, and some of the typical and alternative governance models for data. On the final Friday we had an open discussion on how data unions could be provided as a service, and other topics that emerged in the seminar.

The seminar continues now until the end of the year with the students writing essays on select topics. The current plan is then to arrange a small workshop on data economy, with an open CFP, in the March-April time frame. For further information, feel free to contact Prof. Pekka Nikander or Dr. Ruth Kaila.

Utilising Generative Adversarial Networks (GANs) in Creative Agent Societies

Simo Linkola visited Falmouth, UK for two months to collaborate with Prof. Rob Saunders. The visit was part of Simo’s PhD studies and was organized under the current ICT 2023 project Collaboration Awareness and Creative Self-adaptivity (CACS). The goal of the collaboration is to study how GANs may be utilized in creative multi-agent systems where each agent controls the training of its own GAN. A proof-of-concept system was built to study technological and theoretical aspects of the problem, and the initial results were promising enough to warrant continuing the work after the visit. The collaboration is expected to result in at least one peer reviewed publication.

Computer vision applied to analysis of learning interactions

Professor Yu Xiao’s group in Aalto ELEC received seed funding from HIIT to initiate multi-disciplinary research collaboration with professor Kristiina Kumpulainen’s group at the Faculty of Educational Sciences of the University of Helsinki. The objective is to develop tools for analyzing student-student and student-supervisor interactions on videos captured in classrooms. An approach based on using a deep neural network for pose recognition was presented in the CICERO workshop on digitalization and artificial intelligence.

The convolutional neural network (CNN) can extract skeleton key-points from a video and this information can be used to analyze learning interactions.

Research collaboration with MIPT on Chatbot System development

Luiza Sayfullina, a doctoral candidate at Aalto University, made a 2 month research visit to the iPavlov lab, which is one of the most progressive labs in Russia in Natural Language Processing and Chatbot Systems in particular. The lab belongs to Moscow Institute of Physics and Technology and is honored with Facebook AI Academic Partnership and NVIDIA GPU Research Center status. It is led by Professor Mikhail Burtsev, who kindly agreed to host Luiza during her stay.

Luiza was working with the open source DeepPavlov library that contains NLP components such as Named Entity Recognition, Question Answering, Intent Classification and Insult Detection for developing Chatbot Systems. She focused on researching available knowledge bases and how they can be used to improve a Question Answering system (Q&A system). In particular, Luiza and her collaborators employed Microsoft Probase and Wikidata word relations to form relation-specific embeddings to be used with a Sequence to Sequence model for a Q&A system. At the moment, they continue their experiments and plan to publish a paper on this topic.

Luiza’s research visit was supported by HIIT and she also wishes to thank the iPavlov lab for an educational and pleasant stay.

StanCon 2018 conference in Helsinki

StanCon 2018 was organised in Helsinki on August 29-31. Stan is a probabilistic programming and statistical modeling language used by tens of thousands of scientists, engineers, and other researchers for statistical modeling, data analysis, and prediction. StanCon 2018 consisted of one day of tutorials and two days of talks, open discussions, and statistical modeling. 271 participants from all over the world attended the conference.

StanCon introduced cutting-edge methods and applications for statistical modelling – ranging from galaxy clusters to social media, brain research, and anthropology. In Finland, AI research is particularly strong in the field of medicine.

“Statistical modeling can be used, for example, to improve the safety of drug testing in children. The time it takes for a child’s body to metabolise a drug depends not only on the weight of the child, but also on the ability of the liver to process the drug. The dosage size of the drug should, then, be reduced more than the weight alone would suggest. Modelling methods can be used to evaluate the effects of drugs on an individual level,” says Professor Aki Vehtari of Aalto University.

One of the keynote speakers at the conference, Maggie Lieu, a researcher at the European Space Agency, uses statistical modeling to determine the mass of galaxy clusters. “Hierarchical modeling has several advantages when there are millions of variables and a lot of noisy data in space. Using modelling, I can get meaningful results in up to ten minutes and study clusters of galaxies in one go instead of a single galaxy group at a time.”

ALGO 2018 conference in Helsinki

In August 2018, more than 300 computer science researchers, practitioners, and students from all over the world gathered in Helsinki. ALGO is a premier event in algorithmics featuring the European Symposium on Algorithms and co-locating with 6 specialized conferences and workshops (IPEC, WABI, WAOA, ALGOCLOUD, ALGOSENSORS, and ATMOS). The event is organized annually at the end of summer, and this year it took place at Aalto University from the 20th to the 24th of August. ALGO 2018 attracted an all-time record number of participants since the birth of the event.

Algorithms are a key engine in modern data science. With the growth of data size nowadays, the need for algorithmic innovation has become more important than ever. ALGO conferences feature contributed presentations on cutting-edge algorithms designs, engineering, and applications in various areas of studies: sensor networking, biology, economics, and transportation systems.

Besides attracting researchers from topmost institutes in the world, ALGO 2018 was greatly honoured by an impressive lineup of 5 keynote speakers and 5 other invited speakers. The keynote talks addressed the roles of algorithms arising in practical settings, e.g. French college admission and in auctions.

For more information, please see

ICER 2018 conference in Espoo

ACM Conference on International Computing Education Research (ICER 2018) was organised in Espoo on August 13-15. The conference started with co-located workshops and Doctoral Consortium (DC) on Sunday 12th. A total of 127 participants from 18 difference countries attended the main conference between Monday and Wednesday. In addition, there was a Works in Progress workshop held right after the Conference, providing participants with an opportunity to gain critical and in-depth feedback on their research ideas or projects.

ICER 2018 provided a forum for presenting and publishing high-quality research in computing education. The main focus was computing education in higher education level, but research in K-12 level was also presented. Research foci were diverse covering aspects such as teaching and learning methods, software tools supporting learning, topical misconceptions, recruitment and students’ background factors, career tracks and teachers.

The conference was designed to encourage authors and audience to engage in lively discussion about each work presented. The 28 accepted research papers provided the main focus of the conference. However, the submission categories allowed for different types of participation, supporting work at different levels ranging from formative work to a completed research study. Students accepted for the doctoral consortium participated in an all-day workshop conducted by prominent leaders in the computing education research community, and presented their work at the conference in a dedicated poster session. In addition, ICER 2018 offered a track for lightning talks, 3-minute presentations that articulate an idea for a research study, provided an update on current research, or invited collaborators. The keynote speaker at the conference was Kirsti Lonka from the University of Helsinki. Her keynote addressed “Growing minds – 21st century competences and digitalisation among Finnish youth?”

Results of Aalto’s game workshop showcased at Flow Festival

Aalto University was present at the Flow Festival in a big way. Among the attractions was a game exhibition, where the visitors could e.g. interact with robotic pets and team up with another player to defeat colorful lights in a retro arcade-game. They could make connections with the mind and the body to save the environment and collectively light up Aika-lava, a large wooden structure by Aalto’s Architecture programme.

These and other creative ideas were developed during a one-week workshop given by Robin Baumgarten. Presenting the results at Flow 2018 intensified the motivation of the students to learn about combining software and electronics for high-quality user experiences and enhanced Helsinki’s brand as an ICT talent hotspot. The workshop and the exhibition were supported by HIIT.

Models of drug behaviour in adults can be recalibrated for children

Eero Siivola recently returned from a 3 month research visit to Novartis, Switzerland. The visit was a part of a collaboration project between Novartis and Aalto. During the visit, Eero and his collaborators studied how non-parametric regression methods can be used to find out how a model describing drug behaviour in a body differs between adults and kids. The studied method was tested with real medical data and the early stage results are promising. The collaboration continues after the visit and the aim is to publish the results in the form of a journal article.

Aalto’s Mobile Cloud Computing group deepens collaboration with IE Business School

In a world where the functionality of products and services is rapidly growing, artificial intelligence (AI) could provide new tools for understanding the structure and dynamics of the ideation challenge in innovation, e.g. where do original and creative ideas come from, and how AI tools could enhance this important part of the often ad hoc and sub optimal innovation process.

With the aim to research these tools, Giancarlo Pastor Figueroa, a Postdoctoral Researcher in the mc2 – Mobile Cloud Computing group, has made three one-week visits to IE Business School, an institution recently ranked 3rd by Financial Times in a comparison of European business schools.

The visits have strengthened Giancarlo’s collaboration with Professor Peter Bryant to combine technical expertise with deep understanding of business. Some current research tasks include:

  • To derive functions to assess the compound functionality of products and services.
  • To design machine learning models to replicate the process of innovation.

In addition, Giancarlo and his collaborators at IE Business School are preparing a Horizon 2020 proposal on automated mobility, and exploring other cooperation opportunities with Aalto University.

Summer Institute in Computational Social Science organised in Helsinki

Summer Institute in Computational Social Science (SICSS) was organised at Duke University by Matthew Salganik and Chris Bail. However, around the globe, in New York, Chicago, Cape Town, Seattle and Boulder – and Helsinki – alumna of the previous SICSS organised satellite locations: places for their local community to support learning and increase skills for both social scientists and computer scientists in this new emerging multidisciplinary field.

During the first week, at the SICSS Helsinki partner site, we have discussed and worked on research ethics, automated data collection and machine learning techniques for social science research. The instruction included materials developed by Matthew and Chris as well as materials developed by the SICSS Helsinki organiser team: Matti Nelimarkka, Juho Pääkkönen and Pihla Toivanen, all from Aalto University. Furthermore, they followed and discussed video lectures from other SICSS sites, including David Lazer and Duncan Watts.

“The goal of this first week is to get everyone up to speed with skills like coding and data-analysis, but also think how these novel methods and approaches relate and extend the existing theories and background of social sciences. This problem demonstrates the interdisciplinary nature of computational social science as a field.” says Matti Nelimarkka, the lead organiser.

The second week group work projects reflect on how computational social science research and approaches can be used to study various social and computer science questions. The four groups focused on versatile topics. One of them conducted a methodological investigation of computational methods themselves by comparing unsupervised methods and traditional qualitative methods. Another group utilised computational methods to address methodological problems in psychology and survey questionnaires. Other groups focused on more empirical investigations: how does opinion change occur – a traditional question asked by communication and media studies people and political scientists. We also had a group which focused on addressing fairness through survey mechanics and algorithmic investigations.

This article is based on previous blog posts at Rajapinta-blog.

We thank the generous financial support from the Russell Sage Foundation, the Alfred P. Sloan Foundation as well as from the Helsinki Institute for Information Technology HIIT, which allowed organisation of this event.

Elements of collaborative economy introduced to Aalto’s design management courses

Thinking of a course as a collaborative economy leads to new ways of keeping track of the contributions of students. “Inside the course, master’s level students will be able to take part in many projects and do daily evaluation of other students that they have worked with” says Jenni Huttunen. Students can contribute by working, helping or reusing knowledge, material or contribution that others have made. Besides being motivating to the students, monitoring the data is helpful for the teaching staff, enabling them to have a more detailed understanding of the work of each student. Evaluation can be more dependent on peer-reviews than before.

The planned collaborative setting would be different from the group work we see today in Aalto. The objective is to promote a collaborative economy style of working where each student would be free to contribute to many projects, not just the one their designated team is working on.

The collaborative economy idea will be introduced on two courses of Neppi – Networked Partnering and Product Innovation: design and technology. The Neppi courses will be part of Aalto’s International Design Business Management curriculum in 2018 and will welcome students from other disciplines.

The digital solution is based on the idea that by promoting sharing of information and skills freely, a course accumulates more “revenue”, such as better learning and thus most likely, better products. Therefore the solution should lower the barriers between groups and disciplines, and promote knowledge sharing, which is not an easy task. The idea phase solution was realised by Raffaella Tran as part of her diploma project. The objective was to capture the initial ideas to a concrete form in order for them to be evaluated and co-developed further. The project is currently looking for co-developers interested in collaborative economy and education development. The working group has been happy to see there has been some initial interest in using the app on other workshop style courses also.

Helsinki Di­gital Hu­man­it­ies Hack­a­thon #DH­H18

Helsinki Digital Humanities Hackathon #DH­H18 brought together students and researchers of humanities, social sciences and computer science. Digital humanities, as understood here, is about applying modern data processing to solve research questions in the humanities and social sciences. At its best, such close collaboration offers unique benefits for both fields: scholars in the humanities are able to tackle questions too labour-intensive for manual study, while computer scientists encounter new and challenging use cases for the tools and algorithms they develop.

The participants of #DHH18 worked in small groups for one week, formulating research questions with respect to particular data sets, applying and developing methods and tools, and giving public presentations in the end. A number of themes were suggested by the organisers as a starting point:

  • People in the News. The National Library of Finland’s Newspaper corpus contains nearly all newspapers and periodicals published in Finland from 1771 to 1919. Computational tools are applicable to interesting questions regarding the people who appeared in the news and the way they were presented.
  • Russia <=> Finland. Large fulltext corpora of contemporary media can be used for analysing how Russia is and has been portrayed in Finnish newspapers and Finland in Russian ones.
  • Early Mod­ern Pub­lish­ing. The proposed objective was to analyse computationally changes in publication practices, genres, and roles of publishers, using large databases of English literature in the early modern period.
  • The Death Psalm of Bishop Henry. Computational tools can be used for addressing some of the methodological challenges involved in studying orally transmitted literature. The Death Psalm of Bishop Henry is the oldest and most prominent Finnish example of a story that written down only centuries after the incident.
  • Helsinki in Geot­agged So­cial Me­dia. Social media data can provide valuable clues about cities and what their inhabitants do, where, when and why. Large volumes of geotagged Twitter, Instagram and Flickr posts from Helsinki are available, and working with such data entails many interesting challenges.

#DHH18 was the fourth hackathon in the series, following #DHH15, #DHH16 and #DHH17. Digital humanities is an inherently multidisciplinary field, and the participants gain valuable experience of working in multidisciplinary research projects. The hackathons also broaden the participants’ understanding of digital humanities, and what is possible to achieve with such collaboration.

For participant reflections on #DHH18, see for example David Rosson’s and Markku Roinila’s blogs.

HIIT Open 2018 programming contest

16 teams took part in the HIIT Open 2018 programming contest on 26 May 2018 in Otaniemi. The contest was open to everyone interested in programming and algorithmic challenges – this year we had a record number of participants, with 16 teams and a total of 42 contestants. In addition to the participants from the universities in Helsinki region, we also had participants from Finnish companies and high schools, and for the first time we also got three teams from the Tallinn University of Technology.

The winning team was “Ukkonen Fan Club”, with Antti Röyskö, Kalle Luopajärvi, and Hannes Ihalainen, all of them from the University of Helsinki. The 2nd place went to the team “Wave of Technology”, with Janne Kokkala (Aalto University) and Ville Pettersson (Valas Media), and the 3rd place went to the team “Karhukopla”, with three high school students: Juha Harviainen, Siiri Kuoppala, and Roope Salmi.

The teams had 13 tasks to solve, and 5 hours of time. In each task the teams had to write a computer program that solves a given task correctly and efficiently. The winning team solved 11/13 tasks correctly; all tasks are available at

For more information on the HIIT Open programming contest, please see – the contest has been organised since 2016 in collaboration between HIIT, Aalto University, and the University of Helsinki.

Panagiotis Papapetrou visited Aalto University in spring 2018

Panagiotis Papapetrou was a visiting professor at the Department of Computer Science of Aalto University in March 2018. Panagiotis Papapetrou is a professor at the Department of Computer and Systems Sciences of Stockholm University, Sweden. During his visit professor Papapetrou gave a course in Aalto University, which was titled “Learning from electronic health records”. The course focused on recent research developments on the topics of representing and summarizing electronic health records as well as algorithms for predictive modeling of complex health data. In addition, professor Papapetrou collaborated with the group of Aristides Gionis on the problem developing novel algorithms for interpretable and actionable classification of time-series data. The visit of professor Papapetrou was co-funded by the Aalto University School of Science Institute (AScI) and the Helsinki Institute for Information Technology (HIIT).