Tenured Professors’ Installation Talks

Sanna-Katriina Asikainen (born 1974, Finland) received her D.Sc. (Tech.) degree in industrial engineering and management from Lappeenranta University of Technology (LUT), Department of Industrial Engineering and Management, Finland, in 2002. At LUT in 2010 Asikainen was appointed as full professor in business administration. She has been a visiting scholar at SCANCOR, Stanford University, US in 2014 and worked as visiting professor at the Loughborough University, School of Business and Economics, UK.

Asikainen’s research covers strategic management, international marketing, and international entrepreneurship as she has focused on studying strategic decisions and behaviors of international firms. During her career, she has received multiple awards. For example, in 2010 her review article was nominated as the Top 10 Most Cited Articles in Industrial Marketing Management. She was also the recipient of The Douglas C. Mackay Outstanding Paper Award in International Entrepreneurship in 2004, and Highly Commended Award Winner at the Literati Network Awards for Excellence in 2013. In addition, she has won several conference best paper awards (most recent in 2019).

Paula Hohti Erichsen is Associate Professor of the History of Art and Culture at Aalto University, School of Arts, Design and Architecture, and scientific director of the ERC-funded  international research project Refashioning the Renaissance: Popular Groups and the Material and Cultural Significance of Clothing in Europe, 1550-1650. She is specialized in studies of early modern dress, material culture, and decorative arts, with a special focus on their role and function within the classes of artisans and shopkeepers.

Hohti Erichsen has worked in several international research institutions. Having received her PhD in Art History in 2006 from the University of Sussex in the UK, she has held research positions at the Helsinki Collegium for Advanced Studies, European University Institute in Florence, University of Copenhagen and Bard Graduate Centre in New York. She has also been a principal investigator in two major UK-based international research projects—the Material Renaissance: Costs and Consumption in Italy 1350–1600 and Fashioning the Early Modern: Creativity and Innovation in Europe, 1500–1850. In 2016, she received €2 million European Research Council (ERC) Consolidator grant in order to develop reconstruction as a methodology in cultural studies of dress.

Janne Lindqvist (born 1978, Finland) received his Doctor of Science degree in Computer Science and Engineering from Helsinki University of Technology. He is the recipient of the NSF CAREER award, which is NSF’s most prestigious awards in support of early-career faculty. He is an associate professor of electrical and computer engineering at Rutgers University and an associate professor of computer science at Aalto University. Janne is the director of Helsinki-Aalto Center for Information Security (HAIC) and has directed the Rutgers Human-Computer Interaction and Security Engineering Lab. Prior to Rutgers, Janne was a post-doc with Carnegie Mellon University’s School of Computer Science Human-Computer Interaction institute.

Janne Lindqvist's work has received sustained attention in the global media with over 1000 mentions including Scientific American, IEEE Spectrum, MIT Technology Review, NPR, International Business Times, ABC News, CBS News, Fox News, Fortune, Computerworld, Der Spiegel, London Times, New Scientist, PBS, Slashdot, The Register, Wired (UK), Tietoviikko, Tekniikka ja Talous. Janne’s awards include the Best Paper Award from MobiCom’12, the Best Paper Nominee Award from UbiComp’14, and Sustainable Jersey Creation & Innovation Award 2014. You can find more about his group’s work at https://www.lindqvistlab.org.

Esa Ollila (born 1974, Finland) received his Ph.D. degree in statistics from the University of Jyväskylä, in 2002, and the D.Sc. (Tech) degree in signal processing from Aalto University, in 2010. He has held positions of Post-doctoral Fellow (2004-2007) and  Academy Research Fellow (2010-2015) of the Academy of Finland at Aalto University.  He has also been deputy Senior Lecturer at the University of Oulu, where he is also an adjunct Professor (statistics) since 2010.  Fall-term 2001 he was a Visiting Researcher at Pennsylvania State University, USA, while the academic year 2010-2011 he spent as a Visiting Post-doctoral Research Associate at Princeton University, USA. In 2015, he received an associate professor's position in the Aalto University School of Electrical Engineering, where he is also leading the Information Technology BSc major since 2016.

His research interests lie in the intersection of the fields of statistical signal processing, high-dimensional statistics, and machine learning. One of his long-lasting interests has been robust multivariate statistics, and he has recently co-authored a text-book published by Cambridge University Press (Nov. 2018) on this topic. He is an author or coauthor of roughly 80 papers in the top journals and conferences in signal processing and statistics.

Aki Vehtari (born 1972, Finland) obtained Doctor of Science (Tech.) degree in Computational Science from Helsinki University of Technology in 2001.  He is a docent of statistics at the University of Helsinki since 2006 and in 2008 he received an academy research fellowship of the Academy of Finland. Vehtari was appointed and associate professor of computational probabilistic modeling at Aalto University in 2014. Since 2014 he has also been a visiting professor at the Technical University of Denmark, and has visited Columbia University, New York, for six months. He is a fellow of European Laboratory for Learning and Intelligent Systems and a coordinating professor of Agile Probabilistic AI research program of Finnish Center for Artificial Intelligence.

Vehtari is well known for his work on Bayesian model assessment and selection, Gaussian processes, approximative inference methods and inference diagnostics.

He is a co-author of the best-selling and award-winning textbook Bayesian Data Analysis, 3rd ed, and over 100 articles. He is one of the core developers of the probabilistic programming platform Stan, which has tens of thousands of users in science and industry.