Dr.-Ing. Richard Schroedter

© Sophia Hölzel

Research Associate

Name

Mr Dr.-Ing. Richard Schroedter

Send email

Send encrypted email via the SecureMail portal (for TUD external users only).

Address work

Visitor Address:

Toeplerbau, Room 309 Mommsenstraße 12

01069 Dresden

Deutschland

work Tel.

fax Fax

+49 351 463-37042

Events

© Richard Schroedter

Auf der MEMRISYS 2024 Konferenz in Seoul, Südkorea, wurde Richard Schroedter mit dem Best Poster Award für seine Präsentation "An ErMnO3 memristive spiking neuristor" ausgezeichnet. Das prämierte Poster entstand in Zusammenarbeit mit den Co-Autoren Ahmet Şamil Demirkol, Rong Wu, Catherine Dubourdieu und Ronald Tetzlaff.

© Crispin-I. Mokry

We were super honored and delighted to have Richard Socher (you.com) as a guest speaker at TU Dresden on May 11, 2023. Richard Socher has shared his view on state-of-the-art Natural Language Processing (NLP) research in the field of Machine Learning with us and joined a panel discussion with the local experts, Sunna Torge (TU Dresden, SCADS.AI, OpenGPT-X), Anna Poetsch (TU Dresden, CMCB/MSNZ), Oliver Guhr (Moderator, HTW Dresden) and Peter Steinbach (Moderator, Helmholtz-Zentrum Dresden-Rossendorf, Helmholtz.AI).

You can revisit the talk and the podium discussion here: https://memristec.de/2023/05/11/richard-socher-abend/

The event post on Twitter: https://twitter.com/tudresden_de/status/1656742791173611521/

Teaching 

• Lecture "Neural Networks and Memristive Hardware Accelerators" in winter semester 2024/2025 OPAL
• Supervision of student works, see open topics
• Exercise Grundlagen der Elektrotechnik

Research

Memristive devices for biology-inspired computation of energy-efficient neural networks

• Modeling of memristive and memcapacitive devices and crossbar arrays

• Development of algorithms for efficient control of memristive neural networks
• Investigation of artificial and spiking neural networks
• Design of neuron circuits with locally active memristors (neuristors)
• Neurotransistor-based Memristive Crossbar Memcomputing (NeuroMCross)
• Bio inspired Memcomputing via Crossbar Structures (BioMCross)
• Memristive Devices Toward Smart Technical Systems (MemrisTec)

  • SPICE compact memristor model based on Poole-Frenkel emission featuring analog (gradual) switching derived from a Ti/Al2O3/Nb2O5/Ti bi-layer device fabricated at NaMLab gGmbH, Dresden Download SPICE code or Github.
    
    Please cite: R. Schroedter, A. S. Demirkol, A. Ascoli, R. Tetzlaff, E. Mgeladze, M. Herzig, S. Slesazeck, T. Mikolajick, "SPICE Compact Model for an Analog Switching Niobium Oxide Memristor", International Conference on Modern Circuits and Systems Technologies (MOCAST) on Electronics and Communications, Bremen, 2022, DOI: 10.1109/MOCAST54814.2022.9837726

© IEEE Copyright

© IEEE Copyright

Link to presentation video

Publications

• Google Scholar
• ORCID: 0000-0003-3259-4571

Selected publications:

2025

R. Schroedter, A. S. Demirkol, I. Messaris, C. Bruchatz, E. Mgeladze, S. Slesazeck, T. Mikolajick, R. Tetzlaff, "Model-based write algorithm for memristive crossbar arrays", accepted for presentation at 14th International Conference on Modern Circuits and Systems Technologies (MOCAST2025) on Electronics and Communications, Dresden, 11-13 June 2025, DOI: 10.1109/MOCAST65744.2025.11083963

D. Fejzaj, R. Schroedter, T. Mikolajick, A. Heinzig, "A Vertical Memristive MoS2-exfoliated Device for Applications in Artificial Synapses", accepted for presentation at 14th International Conference on Modern Circuits and Systems Technologies (MOCAST2025) on Electronics and Communications, Dresden, 11-13 June 2025, DOI: 10.1109/MOCAST65744.2025.11083941

2024

R. Schroedter, A.S. Demirkol, R. Wu, C. Dubourdieu, R. Tetzlaff, "An ErMnO3 memristive spiking neuristor", presented at International Conference on Memristive Materials, Devices & Systems, MEMRISYS 2024, 11 Nov. 2024
*** Best Poster Award *** Poster

R. Schroedter, A. Haidar, R. Tetzlaff, “Fault Impact Map for Memristive Crossbar Neural Networks”, 13th International Conference on Modern Circuits and Systems Technologies (MOCAST) on Electronics and Communications, Sofia, Bulgaria, 2024, DOI: 10.1109/MOCAST61810.2024.10615515 Postprint  Presentation

2023

R. Schroedter, A. S. Demirkol, A. Ascoli, B. Max, F. Nebe, T. Mikolajick,  R. Tetzlaff, "A pseudo-memcapacitive neurotransistor for spiking neural networks", 12th International Conference on Modern Circuits and Systems Technologies (MOCAST) on Electronics and Communications, Athens, Greece, pp. 1-4, 2023, DOI: 10.1109/MOCAST57943.2023.10176398
Postprint, SPICE code

R. Schroedter, R. Tetzlaff, "Modeling an analog switching memristor", 1.Memristor-Symposium, 27.-28.02.2023, Bamberg, Germany, pp. 3-4, 2023, DOI: https://doi.org/10.26127/BTUOpen-6348

2022

E. Mgeladze, M. Herzig, R. Schroedter, R. Tetzlaff, S. Slesazeck, T. Mikolajick, „An Analog Memristive and Memcapacitive Device for Neuromorphic Computing”. 29th IEEE International Conference on Electronics Circuits and Systems (ICECS), Glasgow, pp. 1-4, 2022, DOI: 10.1109/ICECS202256217.2022.9970915

R. Schroedter, A. S. Demirkol, A. Ascoli, R. Tetzlaff, E. Mgeladze, M. Herzig, S. Slesazeck, T. Mikolajick, "SPICE Compact Model for an Analog Switching Niobium Oxide Memristor", International Conference on Modern Circuits and Systems Technologies (MOCAST) on Electronics and Communications, Bremen, 2022
DOI: 10.1109/MOCAST54814.2022.9837726
*** Best Paper Award *** Postprint Video, SPICE code

R. Schroedter, E. Mgeladze, M. Herzig, A. Ascoli, S. Slesazeck, T. Mikolajick, R. Tetzlaff,  „Physics-based modeling of a bi-layer Al2O3/Nb2O5 analog memristive device“, IEEE International Symposium on Circuits and Systems  (ISCAS), pp. 1097-1101, TX, USA, 2022,
DOI: 10.1109/ISCAS48785.2022.9937966
Postprint

2014-2021

R. Schroedter, H. W. Yoo, D. Brunner, G. Schitter. "Charge-based Capacitive Self-Sensing with Continuous State Observation for Resonant Electrostatic MEMS Mirrors" in IEEE Journal of Microelectromechanical Systems, vol. 30, no. 6, 2021

R. Schroedter, H. W. Yoo, D. Brunner, G. Schitter,  „Capacitive Charge-based Self-Sensing for Resonant Electrostatic MEMS mirrors“, Proc.  of 21st IFAC World Congress, Volume 53, Issue 2, pp. 8553-8558, 2020

R. Schroedter, E. Csencsics, G. Schitter, „Towards the Analogy of Electrostatic and lectromagnetic Transducers“. ,Proc.  of 21st IFAC World Congress, Volume 53, Issue 2, pp. 8941-8946, 2020

R. Schroedter, J. Grahmann, K. Janschek. „Silicone oil damping for quasi-static micro scanners with electrostatic vertical staggered comb drives“, in 8th IFAC Symposium on Mechatronic Systems (Mechatronics), vol. 52, issue 15, pp. 37-42, 2019

R. Schroedter. „Modellbasierter Systementwurf zur Steuerung und Regelung quasi-statischer Mikroscannerspiegel mit elektrostatischem Kammantrieb“, Jörg Vogt Verlag, Dresden, Dissertation, 340 Seiten, ISBN: 9783959470308, 2018
URN:  urn:nbn:de:bsz:14-qucosa2-882591

R. Schroedter, M. Schwarzenberg, J. Grahmann, T. Sandner, K. Janschek. „Repetitive nonlinear control for linear scanning micro mirrors“, in Proceedings of SPIE 10545, MOEMS and Miniaturized Systems XVII, 1054511, 2018

R. Schroedter, M. Roth, K. Janschek, T. Sandner. „Flatness-based open-loop and closed-loop control for electrostatic quasi-static microscanners using jerk-limited trajectory design“, Mechatronics, vol. 56, pp. 318-331, 2017

R. Schroedter, M. Schwarzenberg, A. Dreyhaupt, R. Barth, R. Sandner, K. Janschek. „Microcontroller based closed-loop control of a 2D quasi-static/resonant microscanner with on-chip piezo-resistive sensor feedback“, in Proceedings of SPIE 10116, MOEMS and Miniaturized Systems XVI, 1011605, 2017

R. Schroedter, T. Sandner, K. Janschek, M. Roth, C. Hruschka. „Real-time closed-loop control for micro mirrors with quasistatic comb drives“, in Proceedings of SPIE 9760, MOEMS and Miniaturized Systems XV, 976009, 2016

R. Schroedter, K. Janschek, T. Sandner. „Jerk and current limited flatness-based open loop control of foveation scanning electrostatic micromirrors“, in Proceedings of 19th IFAC World Congress, vol 47 (3), pp. 2685-2690, 2014

Scientific career