Anna Maria Feit

I am a doctoral candidate in Human-Computer Interaction in the User Interfaces Group of Prof. Antti Oulasvirta at Aalto University in Helsinki. I did my Master's degree in Computer Science at Saarland University, Germany.

The goal of my thesis is to optimize the performance of manual input methods, in particular for text entry. To this end, I try to understand and model various aspects of user performance, and develop algorithms for the application of these models in the optimization of user interfaces. This systematic approach to design allows to fully explore very large design spaces and make optimal use of the users' and technological capacities.

I have applied this approach in several projects, including performance modeling and optimization of mid-air gestures, and the transfer of musical expertise to text entry. During an internship at Microsoft Research in Redmond, I worked with the MSR Enable Group and Meredith Ringel Morris on characterizing the accuracy and precision of eye tracking during practical use and implications for gaze-enabled applications.


School of Electrical Engineering
G208, Otakaari 5
PO Box 13000
00076 Aalto, Finland


+358 50 435 5023



“A keyboard is for typing words. A piano is for typing emotions.” by @drayzee via twitter


How we type

Eye tracking quality

Eye tracking quality can vary a lot in practical scenarios. We analyze the extent of this variation, optimize filter parameters and give recommendations for the design of adaptive gaze-enabled applications.

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How we type

How we type

Don't worry if you never took a typing course. The number of fingers does not determine your text entry speed! The first study of movement strategies in typing since the introducation of personal computers.

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Mid-Air Text Entry

Mid-Air Text Entry

Entering text in mid-air without any surface to touch and keys to aim for! But what are the fastest hand gestures? How independent can each finger move? And how can we find the optimal gesture set for fast text entry?

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Turn any midi-capable piano keyboard into a text entry device. Making use of chords, redundant letters and the pianist's musical skill, it allows text entry rates of over 80 wpm!

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Other Code and Resources

Automatic Labeling of Motion Capture Markers (for Hand tracking)

As part of the How We Type project I developed Python scripts to automatically label motion capture markers based on a nearest neighbor approach. The scripts are free to use and can be found on GitHub


Honorable Mention AwardToward Everyday Gaze Input: Accuracy and Precision of Eye Tracking and Implications for Design
Full Paper, CHI 2017. Honourable Mention Award.
PDF, 7.8MB BibTeX

Anna Maria Feit, Shane Williams, Arturo Toledo, Ann Paradiso, Harish Kulkarni, Shaun Kane, and Meredith Ringel Morris

For eye tracking to become a ubiquitous part of our everyday interaction with computers, we first need to understand its limitations outside rigorously controlled labs, and develop robust applications that can be used by a broad range of users and in various environments. Toward this end, we collected eye tracking data from 80 people in a calibration-style task, using two different trackers in two lighting conditions. We found that accuracy and precision can vary between users and targets more than six-fold, and report on differences between lighting, trackers, and screen regions. We show how such data can be used to determine appropriate target sizes and to optimize the parameters of commonly used filters. We conclude with design recommendations and examples how our findings and methodology can inform the design of error- aware adaptive applications.

How We Type: Movement Strategies and Performance in Everyday Typing
Full Paper, CHI 2016
PDF, 3.51MB BibTeX Project page

Anna Maria Feit, Daryl Weir, and Antti Oulasvirta.

This paper revisits the present understanding of typing, which originates mostly from studies of trained typists using the ten-finger touch typing system. Our goal is to characterise the majority of present-day users who are untrained and employ diverse, self-taught techniques. In a transcription task, we compare self-taught typists and those that took a touch typing course. We report several differences in performance, gaze deployment and movement strategies. The most surprising finding is that self-taught typists can achieve performance levels comparable with touch typists, even when using fewer fingers. Motion capture data exposes 3 predictors of high performance: 1) unambiguous mapping (a letter is consistently pressed by the same finger), 2) active preparation of upcoming keystrokes, and 3) minimal global hand motion. We release an extensive dataset on everyday typing behavior.

Investigating the Dexterity of Multi-Finger Input for Mid-Air Text Entry
Full Paper, CHI 2015
PDF, 3.51MB BibTeX Project page

Srinath Sridhar, Anna Maria Feit, Christian Theobalt, and Antti Oulasvirta.

This paper investigates an emerging input method enabled by progress in hand tracking: input by free motion of fingers. The method is expressive, potentially fast, and usable across many settings as it does not insist on physical contact or visual feedback. Our goal is to inform the design of high-performance input methods by providing detailed analysis of the performance and anatomical characteristics of finger motion. We conducted an experiment using a commercially available sensor to report on the speed, accuracy, individuation, movement ranges, and individual differences of each finger. Findings show differences of up to 50% in movement times and provide indices quantifying the individuation of single fingers. We apply our findings to text entry by computational optimization of multi-finger gestures in mid-air. To this end, we define a novel objective function that considers performance, anatomical factors, and learnability. First investigations of one optimization case show entry rates of 22 words per minute (WPM). We conclude with a critical discussion of the limitations posed by human factors and performance characteristics of existing markerless hand trackers.

Redesigning the Piano Keyboard for Text Entry
Full Paper, DIS 2014
PDF, 5.56 MB BibTeX Project page

Anna Maria Feit and Antti Oulasvirta.

Inspired by the high keying rates of skilled pianists, we study the design of piano keyboards for rapid text entry. We review the qualities of the piano as an input device, observing four design opportunities: 1) chords, 2) redundancy (more keys than letters in English), 3) the transfer of musical skill and 4) optional sound feedback. Although some have been utilized in previous text entry methods, our goal is to exploit all four in a single design. We present PianoText, a computationally designed mapping that assigns letter sequences of English to frequent note transitions of music. It allows fast text entry on any MIDI-enabled keyboard and was evaluated in two transcription typing studies. Both show an achievable rate of over 80 words per minute. This parallels the rates of expert Qwerty typists and doubles that of a previous piano-based design from the 19th century. We also design PianoText-Mini, which allows for comparable performance in a portable form factor. Informed by the studies, we estimate the upper bound of typing performance, draw implications to other text entry methods, and critically discuss outstanding design challenges.

Towards Multi-Objective Optimization for UI Design
Workshop Paper, CHI 2015
PDF, 228KB BibTeX

Anna Maria Feit, Myroslav Bachynskyi and Srinath Sridhar.

In recent years computational optimization has been applied to the problem of finding good designs for user interfaces with huge design  spaces. There, designers are struggling to integrate many different objectives into the design process, such as ergonomics, learnability or  performance. However, most computationally designed interfaces are optimized with respect to only one objective. In this paper we argue that multi-objective optimization is needed to improve over manual designs. We identify 8 categories that cover design principles from UI design and usability engineering. We propose a multi-objective function in form of a linear combination of these factors and discuss benefits and pitfalls of multi-objective optimization.

Text is in the Air... Investigating Multi-Finger Gestures for Mid-Air Text Entry
ACM womEncourage 2015
PDF, 676KB

Anna Maria Feit, Srinath Sridhar, Christian Theobalt and Antti Oulasvirta.

Mid-air input, enabled by recent progress in computer vision based marker-less hand tracking, is an exciting candidate for text entry  where direct touch input is not practicable or not available. In this paper we investigate the use of chord-like multi-finger gestures for entering text in mid-air. In contrast to previous methods, they require no extrinsic targets and can be performed eyes-free. We   systematically explore the design space of hand gestures by computationally optimizing the letter-to-gesture mapping with respect to multiple objectives: performance, anatomical comfort, learnability and mnemonics. First investigations of one optimization case show entry rates of 22 words per minute. While this is promising, our study reveals several limitations of both, the mapping design as well as the available tracking methods. We discuss open challenges in mid-air input and conclude with recommendations for future work.


Education and Skills
I studied Computer Science at the Saarland University in Saarbrücken, Germany, which ranks among the top universities for Computer Science worldwide. I graduated with an honours degree, being among the top 5%.

As a doctoral researcher in human-computer interaction, my areas of expertise are in the optimization of user interfaces, text entry systems, and user modelling In particular, my skills include the software development in Java and Python, with Matlab and Python,

During my studies and research projects I gained a strong background across the multiple disciplines of Computer Science, and skills relevant for academic and industrial work, including:
  • Data analysis and modelling
  • Empirical methods for quantitative and qualitative research
  • Integer programming and meta-heuristic optimization
  • User modeling
  • Eye tracking
  • Crowdsourcing
  • Music signal processing
  • Computational logic and automated theorem proofing


Doctoral Student, Aalto University- since 2014

Doctoral studies in the User Interfaces group of Prof. Antti Oulasvirta in Helsinki, Finland.

Research topic: Performance Optimization of Input Methods.

M.Sc. Computer Science, Saarland University- 2012 - 2013

Master studies in Computer Science at the Saarland University in Saarbrücken, Germany.
GPA: 1.2, Honours Degree (range: 1.0 (best) - 4.0)

Thesis topic: PianoText: Transferring Musical Expertise to Text Entry.

B.Sc. Computer Science, Saarland University- 2008 - 2012

Bachelor studies in Computer Science at the Saarland University in Saarbrücken, Germany. Minor in Computational Linguistics.
GPA: 1.6 (range: 1.0 (best) - 4.0)

Thesis topic: 3D Room Designer: a Collaborative Web Application Based on XML3D and Sirikata.


Aalto University- since 2014

Doctoral researcher in the User Interfaces group of Prof. Antti Oulasvirta in Helsinki, Finland.

Research topic: Performance Optimization of Input Methods.

Microsoft Research- Summer 2016

Summer intern at Microsoft Research, Redmond, with the MSR Enable Group and Meredith Ringel Morris

Research topic: Eye tracking, text entry by eye gaze, adaptive gaze-enabled applications.

Max-Planck Institute for Informatics- 2012-2014

Researcher and student assistant in the Human-Computer Interaction group of Prof. Antti Oulasvirta at the Max-Planck Institue for Informatics and the Cluster of Excellence on Multimodal Computing and Interaction (MMCI) in Saarbrücken, Germany.

Research topics included, the transfer of musical expertise to text entry and the optimization of text entry methods.

German Research Center for AI (DFKI)- 2010-2011

Student assistant in the research group for Agents and Simulated Reality by Prof. Philipp Slusallek at the German Research center for artificial intelligence (DFKI), in Saarbrücken, Germany.

Research topics included the development of 3D web applications with XML3D.


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School of Electrical Engineering
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Postal address:
PO Box 15400
00076 Aalto, Finland