Aarhus University – More facts 44,500 Full-time students (52% graduate level students) 4,500 international students (103 nationalities) 3,400 full-degree int. students 1,100 exchange students 80 Bachelor programmes 120 Master degree programmes - 60 % are taught in English FUTURE ELECTRONICS May 2019 Thomas S. Toftegaard

AU Engineering – history 2012 : Initiation of Engineering Sciences (ENG) at Aarhus University (AU) and merge of a local engineering college (ASE) into AU. 2019 : Short Status - No. of Enrolled Engineering Students approx. 3.500 students - Annual Turnover approx. 60 Mio.€ - Executed Research Funding approx. 16 Mio.€ 2025 : Ambitious 10-year (2016-2025) Investment and Growth Plan - Initiate six new bachelor of science engineering programs. No. of engineering students is 5000+. - Recruit 180 permanent engineering science researchers. - AU ENGINEERING turnover of 133 Mio.€, with almost all growth from ENG engineering science.

Electrical and Computer Engineering

ECE-2019 – Research Areas & Groups Department process in 2018 to establish research areas each containing a number of research groups: Communications and Networks Control and Automation Electronics Photonics Signal Processing Software and Computing Systems

Research area - Electronics STARDUST - in vivo optogeneticS, elecTrophysiology and phArmacology with an ultRasonically-powered DUST for Parkinson's Disease H2020 FET-OPEN – 3.8 Mio EUR 2017-2021 – Coordinator AU Wireless implantable and independent micro-scale device (200x200x200 µm3) powered by ultrasonic energy harvesting Research broad spectrum of digital, analog, mixed-signal and radiofrequency electronic circuits and systems for future emerging tech. Applications include e.g. next-generation (5G and beyond) low-power multi-Gb/s wireless data communications, neuromorphic computing, brain-computer interfaces, and cardiac devices Research groups H2020 FET-OPEN – 3.3 Mio EUR 2019-2022 – Coordinator AU IQUBITS - Integrated Qubits Towards Future High-Temperature Silicon Quantum Computing Hardware Technologies The objectives of the interdisciplinary project IQubits are to (i) develop and demonstrate experimentally high-temperature (high-T) Si and SiGe electron/hole-spin qubits and qubit integrated circuits (ICs) in commercial 22nm Fully-Depleted Silicon-on-Insulator (FDSOI) CMOS foundry technology as the enabling fundamental building blocks of quantum computing technologies. Bioelectrical Instrumentation and Signal Processing Docent Preben Kidmose Cardiovascular Instrumentation and Devices Associate professors Peter Johansen Integrated Nanoelectronics Associate professor Farshad Moradi Wireless Transceivers Professor Domenico Zito

Research area - Photonics SPICE - Spintronic-Photonic Integrated Circuit platform for novel Electronics New spintronic-photonic memory chip demonstrator with 3 orders of magnitude higher write speed and 2 orders of magnitude lower Energy consumption than state-of-the-art spintronic memory echnologies. H2020 FET-OPEN – 3.4 Mio EUR 2016-2020 – Coordinator AU (Photonic Integrated Circuits & Integrated Nanoelectronics) Proof of concept: an optically switched 8-bit memory with write efficiency of 600 fJ per bit Research and develop technologies based on the generation, manipulation, and detection of light Lasers, modulators, and photodetectors, in free space, in a fiber-optic system, or integrated on an optical chip Research groups AUFF – 2.5 Mio DKK 2018-2021 Individual grant THz Photonics Lab - Terahertz Imaging for Solar Cell Materials THz technology is ideal for studying electrons in semiconductors such as integrated circuits and solar cells. General problem with conventional THz technology is that the diffraction-limit consequences that only a limited spatial resolution can be obtained which is typically on the order of few hundred microns Addressing this by building up a multimodal THz imaging platform offering both functional imaging and an improved spatial resolution on the order of 1 µm. . Optical Sensors Professor Martin Kristensen Photonic Integrated Circuits Associate professor Martijn Heck Terahertz Photonics Assistant professor Pernille Pedersen

Research area - Signal processing RoboWeedMaps – The aim is to make everyday life easier for farmers, so that the computer itself finds where the weeds are located, what type they are, and which type of herbicide should be used at precisely that spot in the field. The computer will thus control the dosage when farmers are spraying their fields, and even regulate different types of herbicides and dosages depending on the type of weed – an important part of the future smart farming. InnoFD – 34 Mio DKK 2017-2020 – Partners Agro Intelligence, I-GIS, IPM Consult, Danfoil A/S, Datalogisk A/) Research in topics of machine learning, pattern recognition, control signal generation, data mining etc. Applications in several fields, including computer vision, autonomous systems, precision agricultural, geophysical methods, and computational finance Research groups IFD– 15 mio DKK 2014-2018 – Partners AU Dept. Geoscience, SkyTem We participated with research on new signal processing strategies for an all-digital TEM receiver system Airtech4water – a helicopter-borne antenna system, scientists can identify underground water resources, even in areas where the subsurface is very complex. The technology makes it possible to map the subsurface and its conductivity, thereby identifying water resources. Computer Vision and Biosystem Signal Processing Docent Henrik Karstoft and Sr. researcher Rasmus Jørgensen Data-Driven Analytics Associate professor Alexandros Iosifidis Geophysics Instrumentation and Signal Processing Associate professor Jakob Larsen

Research area - Control and Automation AIR lab - Artificial Intelligence in Robotics Lab The Artificial Intelligence in Robotics (AiR) Lab is a fascinating environment with 15x15x4.5m flight arena Air Lab allows us to test next-generation ground and flying robots for a variety of applications, including but not limited to tracking control, aerial manipulation and formation flight. AUST – 5 Mio DKK Equipped with 12 Vicon V8 tracking cameras, capable of tracking multiple flying objects in 6 degrees of freedom with a range of millimeter accuracy. Build next-generation smart systems Research in control theory, modelling, operations management, adaptive and intelligent semi-autonomous and autonomous systems Application examples are autonomous ground and aerial systems for smart farming systems Research groups EU Framework Programme for Research and Innovation – 35 Mio EUR 2017-2020 – Partners 73 Internet of Food & Farm 2020 Large Scale Pilots H2020 aims to deploy IoT solutions in European agriculture through integration of advanced IoT technologies across the value chain, demonstration of multiple IoT applications at scale and in a usage context Artificial Intelligence in Robotics Associate professor Erdal Kayacan Operations Management Senior researchers Claus Sørensen, Michael Nørremark, Allan Jensen, Erik Kristensen Social Robots Assistant professor Nicolas Guerrero

Research area - Communications and Networks SCALE-IoT – Scalable Systems for Massive IoT Content Danish Council for Independent Research DFF Sapere Aude – 5.9 Mio DKK 2017-2020 – Individual grant A dramatic reduction in the carbon footprint of networking and Cloud systems because we will require ten times less infrastructure to store data due to the results of the project. Igniting a revolution in networks and storage to cope with the Internet of Things: A theory for Cloud-scale compression  Advanced topics in cutting-edge wireless communications and network technology Founded on a strong theoretical base Research and development of secure, efficient, and cost-effective networks for 5G, future internet, IoT, as well as personal communication services Research groups Innovation Fund Denmark – 10 Mio DKK 2017-2019 – Partners 2operate and GomSpace Create a new platform that can monitor hundreds of small satellites in a single mega constellation MegaMan - Mega-Constellations Services Management Satellite communication technology to support constellation of hundreds of low-altitude tiny satellites (about 1,000 km) such creating better signal, cheaper and more efficient than current giant satellites Networks and Analytics Associate professor Rune H. Jacobsen Network Computing, Communications and Storage Associate professors Daniel Lucani and Qi Zhang Cryptography for Networks and Systems Assistant professor Diego Aranha AU Cube-sat Delphi-1

Research area - Software and Computing Systems Intelligent Software, Healing Environments. An AI-based system for health and safety constraint checking in large public buildings In this project we will develop new artificial intelligence-based Computer-Aided Architecture Design (CAAD) tools, with real-world impact, for analysing the health and safety of public buildings (risk identification, assessment, mitigation). These tools will incorporate concepts of people, perception and behaviour into the building model itself within the CAAD tool, at a fundamental level. DFF (FTP1) – 2.4 Mio DKK 2018-2021 Research and innovation activities focus on theories, methods, principles, and technologies spanning a wide range of abstractions of dependable software and computing systems Appl. integrated tools for model-based design of Cyber-Physical Systems, formal modeling and verification, and computationally efficient algorithms for pattern recognition Research groups Donation from PDJ foundation – 12.5 Mio DKK 2019-2022 – Coordinated by ENG ECE AARHUS UNIVERSITY CENTRE FOR DIGITAL TWINS The overall goal of the Aarhus University Centre for Digital Twins is to understand how to leverage existing engineering multi-models for the construction of digital twins. This entails improving the SoTA in co-simulation algorithms, understanding which multi-models are adequate for digital twin construction, and what kind of faults can be detected/diagnosed. Applied Formal Methods Associate professor Stefan Hallerstede and Assistant professor Jalil Boudjadar Cyber-Physical Systems Professor Peter Larsen and Assistant professor Carl Schultz Signal Processing and Distributed Computing Associate professors Christian Pedersen and Stefan Wagner

ECE Research labs Deep Tech Hub AIR lab CAVE lab Neurotechnology lab Computer Vision lab - 2012 Neuro Technology lab - 2012 ICE lab -2012 Photonics lab - 2013 AIR lab - 2018 Agile Cloud Computing lab - 2018 NAN lab - 2018 Wireless Transceiver lab – 2019 Printing Electronics lab – In preparation …… CAVE lab Neurotechnology lab Photonics lab Agile Cloud Computing lab ICE lab Wireless Transceiver lab