About the project
Objective
Asreen Rostami joined RISE Cybersecurity as an ERCIM postdoctoral fellow. Her research was focused on “humanising” Internet of Things (IoT) security to provide an understanding of the technical, design, social and political issues that arise when considering IoT systems from a human-centred perspective. Her current research under the Digital Futures postdoctoral fellowship program is centred around bringing marginalised perspectives into cyber security, starting with looking at the deviant use of smart home devices.
She aims to develop gender-inclusive cyber security, a human-centred approach to security that encompasses feminist principles such as diversity, autonomy, respect, and consent and applies them in a digital context.
About the Digital Futures Postdoc Fellow
Asreen Rostami holds a PhD in the area of HCI from Stockholm University. Her doctoral research was focused on the incorporation of interactive technologies in designing and experiencing interactive and mixed-reality performances, during which she developed a design concept (frictions) used to create an immersive and engaging VR experience and co-designed and staged a mixed-reality performance (Frictional Realities, 2019) in collaboration with a group of Swedish artists.
Main supervisor
Barry Brown, Professor, Department of computer and systems sciences, Stockholm University.
Co-supervisor
Shahid Raza, Associate Professor, RISE Cybersecurity, RISE Research Institutes of Sweden.
About the project
Objective
My research plan focuses on the second-order, online, and robust algorithms for decentralized machine learning, aiming to propose efficient algorithms with convergence guarantees and study the applications. For example, distributed training with multi-core processors enables faster and more efficient training of machine learning models; wireless sensor networks serve for smart buildings and automatic driving in decentralized manners; hospitals cooperatively study disease prevention and treatment while protecting patients’ privacy.
Background
Big data over geographically distributed devices is the new oil of the digital future. However, we cannot mine it within data centres due to privacy preservation and communication efficiency issues. Instead, we resort to learning over networks. My research plans to develop second-order, online, and robust decentralized algorithms with convergence guarantees. This plan perfectly fits the themes of Digital Futures: trust, cooperation, and learning.
About the Digital Futures Postdoc Fellow
Jiaojiao Zhang received a B.E. degree in automation from the School of Automation, Harbin Engineering University, Harbin, China, in 2015 and a master’s degree in control theory and control engineering from the University of Science and Technology of China, Hefei, China, in 2018. She received her PhD in operations research from the Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong (CUHK), Hong Kong, in 2022. She received the Hong Kong PhD Fellowship Scheme (HKPFS) in August 2018. Her current research interests include distributed optimization and algorithm design.
Main supervisor
Mikael Johansson, Professor, Division of Decision and Control Systems, KTH.
Co-supervisor
Joakim Jaldén, Professor, Division of Information Science and Engineering, KTH.
Watch the recorded presentation at the Digitalize in Stockholm 2023 event.
About the project
Objective
This project aims to develop a deep learning-based methodology to enhance the ability to model complicated dynamics for sequential data. With a special focus on the recent progress of transformer-based models, which have shown great potential in modelling very long sequences, we are inspired to integrate them with other state-of-the-art techniques, such as learning dynamic structures and self-supervised learning. By exploring such directions, we expect our results to be applicable to the sequence modelling research and provide good insights for other fundamental deep learning research areas.
Background
Sequence modelling is the fundamental problem of other time series related tasks, including future forecasting. Since being proposed in 2018, transformers have become the de facto choice for most sequence modelling tasks due to their superior performance over traditional RNN-based approaches. However, it appears that transformers usually need a significant amount of training data to achieve their full potential, making them an expensive and impractical option for many real-world scenarios. Thus, it becomes increasingly imperative to develop methods to effectively train transformers with limited labelled data, which is quite common for sequence modelling.
About the Digital Futures Postdoc Fellow
Hao Hu is a postdoc researcher at KTH RPL working with Hossein Azizpour. Before joining KTH, he worked as a research scientist in FX Palo Alto Laboratory (FXPAL), California, United States. Hao got his PhD in Computer Science from the University of Central Florida (UCF) in 2019. His research interests include various topics in machine learning and computer vision, with a special focus on temporal modelling and deep learning.
Main supervisor
Hossein Azizpour, Assistant Professor, Robotics, Perception and Learning, KTH.
Co-supervisor
Arne Elofsson, Professor in Bioinformatics, Stockholm University.
About the project
Objective
In the Deep Wetlands project, we are developing a machine learning platform to monitor water extent changes in wetlands by integrating multiple data sources from satellite images, altimetry radars, and other space sensors. Wetlands are vital ecosystems for the functioning of the Earth system and necessary to achieve sustainable development. Water availability determines whether wetlands can thrive and deliver services to humans. However, thick vegetation mostly covers water changes, impairing their remote detection from space. Wetlands are disappearing rapidly; approximately 70% have been lost in the last 120 years.
Despite the danger that wetlands are currently facing, there is no global high-resolution assessment of wetland changes. This limits the in-depth and temporal analysis of wetlands from space. Changes in wetlands are unnoticed as most space-based technologies cannot fully account for water below vegetation and are limited to large water bodies. Our grand challenge is quantifying the wetland surface area changes on existing wetlands.
About the Digital Futures Postdoc Fellow
Francisco J. Peña is a postdoctoral researcher working in the field of artificial intelligence and remote sensing. He works jointly at the Software and Computer Systems (SCS) division of KTH Royal Institute of Technology and the Department of Physical Geography of Stockholm University in Sweden. Francisco is also a member of the Distributed Computing at KTH (DC@KTH). Before that, he was a postdoctoral researcher at University College Dublin (2018-2020). He obtained his PhD from University College Cork in June 2019.
His research interests include:
- Natural Language Processing
- Computer Vision
- Deep Learning
- Recommender Systems
- Remote Sensing
Main supervisor
Fernando Jaramillo, Assistant Professor, Stockholm University.
Co-supervisor
Amir Payberah, Assistant Professor, Division of Software and Computer Science, KTH.
Watch the recorded presentation at Digitalize in Stockholm 2022 event.
About the project
Objective
Dragons seeks to support inclusive, safe, resilient, and sustainable urban development by merging computational methods to gain insights into urban SET systems with governance approaches to act on these insights. Hence, its guiding questions are: (Q1) How can we combine available data to monitor inclusiveness, safety, resilience, and sustainability in urban SET systems? (Q2) How can we understand the evolution and interaction of structures and processes related to these goals? (Q3) How can urban governance incorporate the findings from Q1 and Q2?
Background
With over half of the world’s population living in cities and most population growth projected to occur in urban areas, making cities inclusive, safe, resilient, and sustainable is a key policy concern expressed in the eleventh UN Sustainable Development Goal (SDG 11). To ensure these properties in urban development, policymakers need to navigate the complex interplay between social (including economic and political), ecological, and technological factors shaping and shaped by human urban activity. This requires an interdisciplinary approach to urban areas as Social-Ecological-Technological Systems (SET systems).
About the Digital Futures Postdoc Fellow
Corinna Coupette studied law at Bucerius Law School and Stanford Law School, completing their First State Exam in Hamburg in 2015. They obtained a PhD in law (Dr. iur.) from Bucerius Law School and a BSc in computer science from LMU Munich, both in 2018, as well as an MSc in computer science in 2020 and a PhD in computer science (Dr. rer. nat.) in 2023, both from Saarland University. Their legal dissertation was awarded the Bucerius Dissertation Award in 2018, and the Otto Hahn Medal of the Max Planck Society in 2020, and their interdisciplinary research profile was recognized by the Caroline von Humboldt Prize for outstanding female junior scientists in 2022.
The overarching goal of Corinna’s research is to understand how we can combine code, data, and law to better model, measure, and manage complex systems. To this end, they explore novel ways of connecting computer science and law, such as using algorithms to collect and analyze legal data as networks or formalizing and implementing legal and mathematical desiderata for responsible data-centric machine learning with graphs.
Main supervisor
Aristides Gionis, WASP Professor of Computer Science, EECS, KTH.
Co-supervisor
Örjan Bodin, Professor, Stockholm Resilience Center and Stockholm University.
About the project
Objective
This research takes the experiential notion of being a foreigner as the starting point to represent how crises unfold in distant territories digitally. This ethnographic research utilises earthquakes as case studies to show how everyday experiences are shaped by how our bodies are connected to geographic singularities. By alluding to our human capacity for adaptability, this research aims to (a) generate novel interactive experiences to communicate the changing nature of the Anthropocene Era. Furthermore, (b) to generate design methods considering the global citizen’s perspective.
Background
Amidst the Anthropocene Era and the COVID pandemic, the resolution of traditionally ill-defined problems in design requires the recognition of non-dominant paradigms and cultural perspectives. Moreover, living in a world of shared uncertainties due to a series of political, environmental and social changes demands cultivating adaptability to face unexpected future scenarios.
From a methodological perspective, this research engages in first-person Soma Design research, which places the locus on the body and experience. This somatic epistemology is becoming increasingly influential in developing digital and interactive technologies in the last decade.
About the Digital Futures Postdoc Fellow
Claudia Núñez-Pacheco is an interaction design researcher and artist. She holds a PhD and a master’s degree from the Sydney School of Design at the University of Sydney in interaction design and electronic arts. Her research investigates how bodily ways of knowing can be used as crafting materials to design aesthetic experiences. In her research journey, Claudia has engaged in a multidisciplinary exploration that merges material thinking, wearable technology, human-computer interaction (HCI) and design methods with tools from experiential psychology. Claudia has been awarded twice by the National Commission for Scientific and Technological Research Scholarship (Chile), in addition to disseminating her research through various international HCI and design academic fora.
Main supervisor
Kia Höök, Professor, Division of Media Technology and Interaction design, KTH.
Co-supervisor
Thiemo Voigt, Professor, RISE Computer Science.
About the project
Objective
This research aims to design a new frontier for wireless extended reality (XR), achieved by intelligent reflecting surface (IRS)-aided terahertz (THz) communications, for providing reliable, low-latency and energy-efficient wireless XR services. Advanced machine learning algorithms will be exploited to develop intelligent, green, wireless XR solutions. The results are expected to apply to the wireless XR research and provide good insights for other fundamental wireless communication research areas.
Background
Extended reality (XR) is changing people’s lifestyles through the interaction of physical and virtual spaces. Wireless XR enables users to move freely and have a better quality of experience. However, wireless XR faces critical challenges such as high data rates, low interaction latency and limited power budget. Terahertz (THz) communications have emerged as a promising solution towards wireless XR due to its abundant spectrum. Meanwhile, intelligent reflecting surfaces (IRSs) can be deployed to compensate for the severe signal attenuation at THz frequencies. Although THz communications and IRS have been widely exploited for wireless communications, how to employ them in wireless XR is still an open question.
About the Digital Futures Postdoc Fellow
Chen Chen is a Digital Futures Postdoctoral Researcher at KTH Royal Institute of Technology. He received the B.E. degree from the East China University of Science and Technology, China, in 2018 and the PhD from the University of Sheffield, UK, in 2022. He was a Marie Curie PhD Fellow. From 2022 to 2023, he was a Postdoctoral Research Associate at the University of Liverpool, UK. His research interests include massive MIMO, wireless intelligence, wireless security, mmWave/THz networks, signal processing, and machine learning.
Main supervisor
Carlo Fischione, Professor, Division of Network and Systems Engineering, KTH.
Co-supervisor
Emil Björnson, Professor, Division of Communication Systems, KTH.