Tanfer Alan

Dr.-Ing. Tanfer Alan

  • Haid-und-Neu-Str. 7
    Bldg. 07.21
    76131 Karlsruhe

Short Bio

Tanfer Alan received his Ph.D. (Dr.-Ing.) in Computer Science from the Karlsruhe Institute of Technology (KIT), Germany, under the supervision of Prof. Dr. Jörg Henkel in July 2021. Currently, he is a postdoctoral researcher at the Chair for Embedded Systems at KIT. His main research interests are on circuits and architectures for approximate computing, cross-layer design space exploration and automation with a special focus on runtime accuracy configuration.

Tanfer Alan received his B.Sc. degree from Hacettepe University, Turkey, in 2011 and his M.Sc. degree from TU Darmstadt, Germany, in 2014. Before joining CES, he has made internships at Texas Instruments Germany and Intel Labs in the U.S.


Tanfer Alan, Jörg Henkel
Probability-Driven Evaluation of Lower-Part Approximation Adders
in IEEE Transactions on Circuits and Systems II: Express Briefs (Volume 69, Issue 1), DOI, PDF, Jan 2022.
Open Source Contribution
Tanfer Alan, Andreas Gerstlauer, Jörg Henkel
Cross-Layer Approximate Hardware Synthesis for Runtime Configurable Accuracy
in IEEE Transactions on Very Large Scale Integration (VLSI) Systems (Volume 29, Issue 6), DOI, PDF, Apr 2021.
Tanfer Alan, Jörg Henkel
SlackHammer: Logic Synthesis for Graceful Errors Under Frequency Scaling
in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD) (Volume 37, Issue 11), ESWEEK Special Issue, DOI, PDF, Nov 2018.
Additional material: Poster (pdf), Presentation (pptx)
Tanfer Alan, Andreas Gerstlauer, Jörg Henkel
Runtime Accuracy-Configurable Approximate Hardware Synthesis Using Logic Gating and Relaxation (IP)
in IEEE/ACM 23rd Design, Automation and Test in Europe Conference (DATE'20), Grenoble, France, DOI, PDF, Mar 9-13 2020.
Jorge Castro-Godínez, Tanfer Alan and Jörg Henkel
ApproxiMath: Approximating Math Functions with Polynomial Series to Improve Performance on Accurate Hardware
In 7th Workshop on Approximate Computing (AxC22),/(Co-located with DAC'22)/, (accepted to appear), Jul 2022.
Tanfer Alan, Jorge Castro-Godínez and Jörg Henkel
Multiple Approximate Instances in Neural Processing Units for Energy-Efficient Circuit Synthesis (WiP)
in 2021 International Conference on Compilers, Architectures and Synthesis For Embedded Systems (CASES), DOI, PDF, Sep 2021.
PhD Thesis
Tanfer Alan
Cross-Layer Automated Hardware Design for Accuracy-Configurable Approximate Computing
Dissertationsschrift der Universität Karlsruhe, Fakultät für Informatik, Institut für Technische Informatik, DOI, PDF, 2021.

Previous publications

Teahyung Lee, Myung Hwangbo, Tanfer Alan, Omesh Tickoo, Ravishankar Iyer
Method and system of low-complexity histogram of gradients generation for image processing
Patent link
Teahyung Lee, Myung Hwangbo, Tanfer Alan, Omesh Tickoo, Ravishankar Iyer
Low-Complexity HOG for Efficient Video Saliency
in IEEE International Conference on Image Processing (ICIP), Quebec City, QC, Canada, 27-30 Sept. 2015.



Laboratory: Software Entwicklung (PSE)
2016 - 2020
Internet of Things (IoT)
Seminar: Approximate Computing
2016 - 2021