prof.dr.ir. A.J. van der Veen
Circuits and Systems (CAS), Department of Microelectronics
Expertise: Array signal processing; Signal processing for communicationsThemes: XG - Next Generation Sensing and Communication
Alle-Jan van der Veen is professor and chair of the Circuits and Systems group at TU Delft. The group covers signal processing and digital system design.
He is a Fellow of the IEEE and of Eurasip. He was Editor-in-Chief of IEEE Transactions on Signal Processing and IEEE Signal Processing Letters, and an elected member of the IEEE Signal Processing Society (SPS) Board of Governors. He was chair of the IEEE SPS Fellow Reference Committee, chair of the IEEE SPS Signal Processing for Communications Technical Committee, member of the IEEE SPS Awards Board, member of the IEEE TAB Periodicals Review and Advisory Committee, and Technical Cochair for ICASSP-2011 (Prague).
He currently is Director of Publications of Eurasip (overlooking 3 Elsevier and 6 Springer journals), chair of the Jack S. Kilby Signal Processing Medal Committee, and chair of the IEEE SPS Signal Processing Theory and Methods Technical Committee.
He received an NWO-STW VICI award (personal research grant of 1.2 ME), and two IEEE SPS Young Author Best Paper awards.
His research interests are in the areas of array signal processing and signal processing for communication, with applications to radio astronomy and sensor network localization.
EE2L21 EPO-4: "KITT" autonomous driving challenge
Make a car drive autonomously from A to B
EE2S11 Signals and systems
Theory of signal transformations and LTI systems
EE2T11 Telecommunications A
A first course in telecommunication, with focus on the physical layer. Includes a lab course related to Signals and Systems (preparing for EPO-4)
EE4C03 Statistical digital signal processing
A second course on digital signal processing: random signals, covariances, linear prediction, Levinson and Schur algorithm, spectrum estimation, optimal filtering, Wiener and Kalman filters, LMS and RLS algorithm
ET4147 Signal processing for communications
Signal separation and parameter estimation using arrays of sensors.
EE2521 Digital signal processing
(not running) First course in digital signal processing: sampling, filter design, filter structures, DFT, multirate filters
ET4385 Introduction to telecommunications and sensing systems
(not running) Overview of the various challenges in the field and introduction to the research groups
Earlier recognition of cardiovascular diseases
Atrial Fibrillation FIngerPrinting: Spotting Bio-Electrical Markers to Early Recognize Atrial Fibrillation by the Use of a Bottom-Up Approach
Data reduction and image formation for future radio telescopes
The future SKA telescope will produce large amounts of correlation data that cannot be stored and needs to be processed quasi real-time. Image formation is the main bottleneck--can compressive sampling and advanced algebraic techniques help?
Sensing Heterogeneous Information Network Environment
How can heterogeneous resources (people, mobile sensors, fixed sensors, social media, information systems, etc.) self-organize for answering information needs?
Radio astronomical calibration and imaging techniques
New, larger and more complex radio telescopes bring new challenges. Foremost among these is the calibration of the data in order to remove atmospheric and instrumental effects which corrupt the exceedingly faint signals from cosmic sources.
Reliable and fast wireless communication for lithography machines
Connecting a sensor network on a moving platform to a control unit; this requires high-speed links with low latency, and accurate wireless clock synchronization.
Separation of AIS Transponder Signals
AIS is a VHF communication system for ship transponders. Seen from a satellite, transponder messages overlap. The aim is to separate these using an antenna array.
Low-frequency distributed radio telescope in space
Below 15 MHz, the ionosphere blocks EM signals from the sky. Therefore, can we design a radio telescope in space, using a swarm of inexpensive nano-satellites? Accurate localization and clock recovery is important.
Last updated: 22 Aug 2017
- Miao Sun
- Tarik Kazaz
- Farnaz Chamanzadeh
- Bahareh Abdikivanani
- Patrick Fuchs
- Jie Zhang
- Jamal Amini
- Jörn Zimmerling
- Shahrzad Naghibzadeh
- Yan Xie
- Sundeep Prabhakar Chepuri (2016)
- Mohd Adib Sarijari (2016)
- Mu Zhou (2015)
- Raj Thilak Rajan (2015)
- Millad Sardarabadi (2015)
- Sumeet Kumar (2015)
- Seyran Khademi (2015)
- Tao Xu (2013)
- Yiyin Wang (2011)
- Claude Simon (2011)
- Vijay Venkateswaran (2010)
- Stefan Wijnholds (2010)
- Kun Fang (2010)
- Bas van der Tol (2009)
- Hieu Dang (2008)
- Zijian Tang (2007)
- Relja Djapic (2006)
- Albert Jan Boonstra (2005)
- Nicolas Petrochilos (2002)
- Lichen Yao
- Vinay Pathi Balaji
- Jack Tchimino
- Derk-Jan Hulsinga
- Jelimo Maswan (2017)
- Iakov Chalegoua (2016)
- Shailja Shukla (2015)
- Francesco Giorgi (2015)
- Joost Geelhoed (2014)
- Viktor Stoev (2013)
- Millad Mouri Sardarabadi (2011)
- Maxim Volkov (2010)
- Deheng Liu (2010)
- Shahzad Gishkori (2009)
- Gert-Jan Schoneveld (2009)
- Yukang Tu (2009)
- Zixia Hu (2009)
MSc project proposals
- Wearable and low power eye tracking system
- Bluetooth Direction Finding
- Next generation WiFi indoor-location systems
- Joint localization and synchronization
- Distributed clock synchronization for energy-efficient wireless sensor networks
- Signal Processing for reduced hardware massive MIMO
- Estimation algorithm for a Phasor Measurement Unit
- Accurate propagation delay estimation for a novel thermal sensor
- Tracking airplanes from space
- DOME algorithms & machines for the SKA radio telescope
- Energy-efficient algorithms for air quality monitoring using sensor networks