Umit Ogras

Gene Amdahl Professor

Umit Ogras is an IEEE Fellow and the Gene Amdahl Professor in the Department of Electrical and Computer Engineering at the University of Wisconsin–Madison. He received his Ph.D. in Computer Engineering from Carnegie Mellon University in 2007. Before joining UW–Madison, he was a research scientist at Intel (2008–2013) and a faculty member at Arizona State University (2013–2020). His research focuses on chiplet-based 2.5D/3D platforms, heterogeneous multicore architectures, domain-specific systems, wearable computing, edge AI, and low-power VLSI design.

His honors include the DARPA Director’s Fellowship and Young Faculty Award, NSF CAREER Award, multiple best paper awards (T-VLSI, T-CAD, TODAES, CODES+ISSS, CASES), and recognition from Intel for both research and technical contributions. He is also a recipient of the EDAA Outstanding Dissertation Award and teaching awards from ASU and CMU.

Department

Electrical & Computer Engineering

Contact

3613, Engineering Hall
1415 Engineering Dr
Madison, WI

p: (608) 263-9317

e: uogras@wisc.edu

PhD 2007, Carnegie Mellon University
MS 2002, Ohio State University
BS 2000, Middle East Technical University

Domain-specific architectures
Edge AI, Embedded Systems
Mobile and Wearable Computing
Multicore Architectures
Flexible Hybrid Electronics

2024 Electrical and Computer Engineering, University of Wisconsin-Madison, Gene Amdahl Professorship
2023 CASES (Intl. Conf. on International Conference on Compilers, Architecture, and Synthesis for Embedded Systems), 2023 Best Paper Award
2022 CASES (Intl. Conf. on International Conference on Compilers, Architecture, and Synthesis for Embedded Systems), 2022 Best Paper Award
2021 ACM Trans. on Design Automation of Electronic Systems (TODAES), 1021 Best Paper Award
2021 Intel, Intel 2021 Outstanding Researcher Award
2020 CODES+ISSS (Intl. Conf. on Hardware/Software Codesign and System Synthesis), 2020 Test of Time
2020 DARPA, Director's Fellowship
2020 ASU Ira Fulton Schools of Engineering , Top 5% Teaching Award
2019 CASES (Intl. Conf. on International Conference on Compilers, Architecture, and Synthesis for Embedded Systems), 2019 Best Paper Award
2018 DARPA, Young Faculty Award
2017 CODES+ISSS (Intl. Conf. on Hardware/Software Codesign and System Synthesis), 2017 Best Paper Award
2017 National Science Foundation, NSF CAREER Award
2013 Intel, Intel Design and Technology Solution (DTS) Division Recognition Award
2012 IEEE, Donald O. Pederson IEEE Trans. on CAD Best Paper Award
2012 Intel, Strategic CAD Labs Research Award
2011 IEEE Circuits and Systems Society, 2011 IEEE VLSI Trans. Best Paper Award
2010 Intel, 2010 Intel Microprocessor Development Group Division Recognition Award
2008 European Design Automation Association (EDAA), 2008 Outstanding PhD. Dissertation Award
2007 Electrical and Computer Engineering, Carnegie Mellon University, 2007 Outstanding Teaching Assistant Award
2000 Middle East Technical University, Valedictorian

Sharma, H., Narang, G., Doppa, J. R., Ogras, U., & Pande, P. P. (2024). Dataflow-Aware PIM-Enabled Manycore Architecture for Deep Learning Workloads. In 2024 Design, Automation & Test in Europe Conference & Exhibition (DATE) (pp. 1–6).
Wang, Z., Sun, J., Goksoy, A., Mandal, S. K., Liu, Y., Seo, J., Chakrabarti, C., Ogras, U., Chhabria, V., Zhang, J., & others, (2024). Exploiting 2.5 D/3D Heterogeneous Integration for AI Computing. In 2024 29th Asia and South Pacific Design Automation Conference (ASP-DAC) (pp. 758–764).
Lin, D., Ogras, U., Miguel, J. S., & Huang, T. (2024). TaroRTL: Accelerating RTL Simulation using Coroutine-based Heterogeneous Task Graph Scheduling. In European Conference on Parallel Processing (pp. 151–166).
Park, J., Kanani, A., Pfromm, L., Sharma, H., Solanki, P., Tervo, E., Doppa, J. R., Pande, P. P., & Ogras, U. (2024). Thermal Modeling and Management Challenges in Heterogenous Integration: 2.5 D Chiplet Platforms and Beyond. In 2024 IEEE 42nd VLSI Test Symposium (VTS) (pp. 1–4).
Jantsch, A., Ghosh, S., Ogras, U., & Meinerzhagen, P. (2024). ISLPED 2023: International Symposium on Low-Power Electronics and Design. IEEE Design & Test, 41(1), 93--94.
Chen, X., Krishnakumar, A., Ogras, U., & Chakrabarti, C. (2024). PED: Probabilistic Energy-efficient Deadline-aware scheduler for heterogeneous SoCs. Journal of Systems Architecture, 147, 103051.
Mack, J., Krishnakumar, A., Ogras, U., & Akoglu, A. (2024). Tutorial: A Novel Runtime Environment for Accelerator-Rich Heterogeneous Architectures. ACM Transactions on Embedded Computing Systems.
An, S., Tuncel, Y., Basaklar, T., & Ogras, U. (2023). A survey of embedded machine learning for smart and sustainable healthcare applications. In Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing: Use Cases and Emerging Challenges (pp. 127–150). Springer Nature Switzerland Cham.
Krishnan, G., Mandal, S. K., Goksoy, A. A., Wang, Z., Chakrabarti, C., Seo, J., Ogras, U., & Cao, Y. (2023). End-to-End Benchmarking of Chiplet-Based In-Memory Computing. In Neuromorphic Computing. IntechOpen.
Krishnan, G., Mandal, S. K., Chakrabarti, C., Seo, J., Ogras, U., & Cao, Y. (2023). In-Memory Computing for AI Accelerators: Challenges and Solutions. In Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing: Hardware Architectures (pp. 199–224). Springer International Publishing Cham.

COMP SCI 755 - VLSI Systems Design (Spring 2025)
E C E 699 - Advanced Independent Study (Spring 2025)
E C E 755 - VLSI Systems Design (Spring 2025)
E C E 790 - Master's Research (Spring 2025)
E C E 890 - Pre-Dissertator's Research (Spring 2025)
COMP SCI 352 - Digital System Fundamentals (Fall 2024)
E C E 352 - Digital System Fundamentals (Fall 2024)
E C E 699 - Advanced Independent Study (Fall 2024)
E C E 790 - Master's Research (Fall 2024)
E C E 890 - Pre-Dissertator's Research (Fall 2024)
E C E 790 - Master's Research (Summer 2024)
E C E 890 - Pre-Dissertator's Research (Summer 2024)
E C E 990 - Dissertator's Research (Summer 2024)
COMP SCI 755 - VLSI Systems Design (Spring 2024)
E C E 755 - VLSI Systems Design (Spring 2024)
E C E 790 - Master's Research (Spring 2024)
E C E 890 - Pre-Dissertator's Research (Spring 2024)
E C E 990 - Dissertator's Research (Spring 2024)
E C E 699 - Advanced Independent Study (Fall 2023)
E C E 790 - Master's Research (Fall 2023)
E C E 890 - Pre-Dissertator's Research (Fall 2023)
E C E 990 - Dissertator's Research (Fall 2023)
E C E 699 - Advanced Independent Study (Summer 2023)
E C E 790 - Master's Research (Summer 2023)
E C E 890 - Pre-Dissertator's Research (Summer 2023)
E C E 990 - Dissertator's Research (Summer 2023)

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