Luca Piccolboni
Ph.D. Student in Computer Science
Columbia University, New York, NY


Summary

Luca Piccolboni is a Ph.D. Student in Computer Science at Columbia University in the city of New York, USA. He works with Professor Luca Carloni and he is a member of the System-Level Design Group. His research interests include design, verification and testing of embedded systems, with particular regard to computer-aided design and high-level synthesis of hardware accelerators.

Education

Luca Piccolboni received a Bachelor's Degree in Computer Science (summa cum laude) in 2013, and a Master's Degree in Computer Science and Engineering (summa cum laude) in 2015 from University of Verona, Italy. During his studies, he worked with Professor Graziano Pravadelli in research projects regarding verification, testing and hardware security of embedded systems.

Teaching

Current TAs:

CSEE-4868: System-on-Chip Platforms

Past TAing Experiences:

Publications

DBLP and Google Scholar provide the updated list of his publications. They are also reported here.

  1. Piccolboni, L., Mantovani, P., Di Guglielmo G. and Carloni, L. P., "COSMOS: Coordination of High-Level Synthesis and Memory Optimization for Hardware Accelerators", in ACM Transactions on Embedded Computing Systems (TECS), Special Issue presented in ACM/IEEE CODES+ISSS 2017, 2017. [slides] [poster]

  2. Piccolboni, L., Menon, A. and Pravadelli, G., "Efficient Control-Flow Subgraph Matching for Detecting Hardware Trojans in RTL Models", in ACM Transactions on Embedded Computing Systems (TECS), Special Issue presented in ACM/IEEE CODES+ISSS 2017, 2017. [slides] [poster]

  3. Piccolboni, L., Mantovani, P., Di Guglielmo G. and Carloni, L. P., "Broadening the Exploration of the Accelerator Design Space in Embedded Scalable Platforms", in Proc. of the IEEE High Performance Extreme Computing Conference (HPEC), 2017. [slides]

  4. Fraccaroli, E., Piccolboni, L. and Fummi, F., "A Homogeneous Framework for AMS Languages Instrumentation, Abstraction and Simulation", in Proc. of the IEEE European Test Symposium (ETS), 2017. [pdf]

  5. Piccolboni, L. and Pravadelli, G., "Stimuli Generation through Invariant Mining for Black-Box Verification", in Proc. of the IEEE International Conference on Very Large Scale Integration (VLSI-SoC), 2016. [pdf]

  6. Bombieri, N., Busato, F., Danese, A., Piccolboni, L. and Pravadelli, G., "Exploiting GPU Architectures for Dynamic Invariant Mining", in Proc. of the IEEE International Conference on Computer Design (ICCD), Special Session on Data Mining for Computer Design, 2015. [pdf]

  7. Danese, A., Piccolboni, L. and Pravadelli, G., "A parallelizable Approach for Mining Likely Invariants", in Proc. of the ACM/IEEE International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS), 2015. [pdf]

  8. Piccolboni, L. and Pravadelli, G., "Simplified Stimuli Generation for Scenario and Assertion Based Verification", in Proc. of the IEEE Latin American Test Workshop (LATW), 2014. [pdf]