University Lecturer in the Internet of Things
Academic Division: Electrical Engineering
Telephone: +44 1223 7 62426
NOTE: The publication list above is auto-generated by the University and is outdated and inaccurate. See below or here for an up-to-date list.
Summary of Recent Research: My research exploits information about the physical world to make more efficient computing systems that interact with nature. This requires a combination of theory (applied mathematics) and hardware (circuits and computer architecture). My research involves equal parts of equations, proofs, circuits, and hardware prototypes. I spent some time in the mid-nineties working at Bell-Labs in the group that created C, C++, and Unix. Partly as a result, I enjoy designing domain-specific programming languages and compilers (inevitably, for problems involving efficient computing systems that interact with nature).
Capsule Bio: B.Sc., 1999 (Rutgers); M.Sc., 2001 (Rutgers); Ph.D., 2007 (Carnegie Mellon). In the summers of 1995, 1996, and 1999, I worked as an intern / engineer at Bell Labs (Murray Hill, NJ), first in the Microelectronics Division, and then in the Data Networking Division, on a project spun out by the research group that created the C programming language, the Unix, Inferno, and Plan 9 operating systems, and much more. I spent 2006–2008 at Technische Universiteit Eindhoven in the Netherlands, joined IBM Research in Zürich, Switzerland, as a permanent Research Staff Member from 2008–2012, and then joined Apple in Cupertino from 2012–2014. I moved back to academia in 2014: I was in the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) from 2014-2017 and joined the University of Cambridge as a faculty member in 2017. Since 2018, I am also a faculty fellow at the Alan Turing Institute for Data Science and Artificial Intelligence in London.
I lead the Physical Computation Laboratory, a research group with about a dozen members (three postdocs, two directly-supervised PhD students, two PhD project students from the Faculty of Mathematics, and five M.Eng./M.Res./IIB students from the Nano DTC, Graphene CDT, and elsewhere). I teach one third year / IIA project course (RISC-V Processor Design), one fourth-year / IIB course (Embedded Systems), and serve as a cohort leader for the Part IA Integrated Electrical Project. Additionally, I am leading the Embedded Systems Technology-Enabled Learning (TEL) Pilot Program in Cooperation with the Cambridge University Press and edX.
Recent Professional Service
- Program committee, USENIX/ACM European Conference on Computer Systems (EuroSys), 2020.
- Co-Organizer, Dagstuhl International Workshop 20222 on Approximate Systems, Schloss Dagstuhl – Leibniz-Zentrum für Informatik, May 2020.
- Associate Editor, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2019 to present.
- Vice Chair, ACM Special Interest Group on Operating Systems (SIGOPS), 2019 to present.
- Executive Committee, EPSRC Connected Everything NetworkPlus, 2019 to present.
- Steering Committee, EPSRC Centre for Doctoral Training in Sensor Technologies and Applications (Sensor CDT), 2019 to present.
- Steering committee, University of Cambridge Trust and Technology Initiative, 2017 to present.
- Steering committee, USENIX/ACM Hot Topics in Operating Systems (HotOS XVII), 2017, 2019.
- Program committee, USENIX/ACM European Conference on Computer Systems (EuroSys), 2019.
- Program committee, IEEE Symposium on High Performance Computer Architecture (HPCA), 2019.
- Program committee, ACM/IEEE International Symposium on Computer Architecture (ISCA), 2018.
Selected Recent Research Publications
J. T. Meech and P. Stanley-Marbell, “Efficient Programmable Random Variate Generation Accelerator from Sensor Noise". Accepted for publication / to appear in IEEE Embedded Systems Letters, June 2020.
N. J. Tye, J. T. Meech, B. A. Bilgin, and P. Stanley-Marbell, "Generating Non-Uniform Random Variates Using Graphene Field-Effect Transistors". Accepted for publication / to appear in 31st IEEE International Conference on Application-specific Systems, Architectures and Processors, July 2020.
R. Hopper, D. Popa, V. Tsoutsouras, F. Udrea, and P. Stanley-Marbell, "Miniaturized Thermal Acoustic Gas Sensor based on a CMOS Micro-hotplate and MEMS Microphone". Proceedings of 4th Functional Integrated NanoSystems (NanoFIS), May 2020.
P. Stanley-Marbell, A. Alaghi, M. Carbin, E. Darulova, L. Dolecek, A. Gerstlauer, G. Gillani, D. Jevdjic, T. Moreau, M. Cacciotti, A. Daglis, N. Enright Jerger, B. Falsafi, A. Misailovic, A. Sampson, and D. Zufferey, "Exploiting Errors for Efficiency: A Survey from Circuits to Algorithms". ACM Computing Surveys Vol. 53, No. 3, Article 51., 2020. (Nominated for best paper award.) Available as preprint ArXiv:1809.05859.
P. Stanley-Marbell and M. Rinard, "Warp: A Hardware Platform for Efficient Multimodal Sensing With Adaptive Approximation. IEEE Micro, vol. 40, no. 1, pp. 57-66, 1 Jan.-Feb. 2020.
Y. Wang, S. Willis, V. Tsoutsouras, and P. Stanley-Marbell, “Deriving Equations from Sensor Data Using Dimensional Function Synthesis". ACM Transactions on Embedded Computing Systems (best paper award winner), volume 18, issue 5s, (22 pages) October 2019.
P. Stanley-Marbell and M. Rinard, “Perceived Color Approximation Transforms for Programs that Draw". In IEEE Micro Journal, vol. 38, no. 4, pp. 20-29, July/August 2018.
Selected Recent Patent Grants
P. Stanley-Marbell and M. Rinard, “Method and Apparatus for Reducing Sensor Power Dissipation". US Patent number 10,539,419, granted 21st January 2020.
D. Chan, J. Iarocci, G. Kapoor, K.-M.Wan, P. Stanley-Marbell et al. (Apple, Inc.), "Initiating background updates based on user activity". US Patent number 10,223,156, granted 5th March 2019.
P. Stanley-Marbell and M. Rinard, “System, method, and apparatus for reducing power dissipation of sensor data on bit-serial communication interfaces". US Patent number 10,135,471 B2, granted 20th November 2018.
C. de la Cropte de Chanterac, P. Stanley-Marbell, K. Venkatraman, and G. Kapoor (Apple, Inc.). "Smart Advice To Charge Notification". US Patent 10,083,105, granted 25th September 2018.
P. Stanley-Marbell, G. Kapoor, and U. Vaishampayan (Apple, Inc.). "Dynamic adjustment of mobile device based on voter feedback". US Patent 9,813,990, granted November 7, 2017.
- Programmable Sensing Composites
Funder: EPSRC (EP/V004654/1). Investigators: P. Stanley-Marbell (PI), A. Barbalace (Co-I), S. Pattinson (Co-I)
- OLED Color Power Optimization
Funder: Industrial Sponsor. Investigators: P. Stanley-Marbell (PI).
- Graphene-Based Ambient Light Sensing and Signal Processing
Funder: Industrial Sponsor. Investigators: S. Hofmann (PI) and P. Stanley-Marbell (Co-I).
- Uncertainty Propagating Processor (UPP) Industrial Demonstrator
Funder: EPSRC Impact Acceleration Account (EP/R511675/1). Investigators: P. Stanley-Marbell (PI).
- New Industrial Systems: Optimising Me Manufacturing Systems
Funder: EPSRC EP/R022534/1. Investigators: P. Stanley-Marbell (Co-I). Collaborators: Kent (PI), Bath (Co-I), UWE (Co-I), Imperial College London (Co-I), University College London (Co-I).
- Computational and Sensing Vitamins for Construction and Infrastructure
Funder: Industrial Sponsor. Investigators: P. Stanley-Marbell (PI).
- Programmable In-Powder Sensors (PIPS) for Real Time Metrology and Data Analysis in Powder Processes
Funder: EPSRC (via MAPP Hub). Investigators: P. Stanley-Marbell (PI).
- Continuous In Situ Microstructure and Composition Analysis within 3D-Printed Structures Using In-Chamber Sensors
Funder: EPSRC (via Connected Everything Network Plus). Investigators: P. Stanley-Marbell (PI). Collaborators: Imperial College London (Co-I), Sheffield-Hallam University (Co-I).
- Energy, Information-Leakage, and Noise Characterization for Sensor Fingerprinting and Sensor Privacy Guards
Funder: Royal Society Grant RG170136. Investigators: P. Stanley-Marbell (PI).
- Graphical Programming with Physical Laws for Engineering Students (Grapples)
Funder: Teaching and Learning Innovation Fund (TLIF) award. Investigators: P. Stanley-Marbell (PI).
- Module lecturer, CUED 4B25 (Embedded Systems)
- Project lecturer/leader, CUED GB3 (RISC-V Processor Design)
- Course instructor, MIT 6.S194/IAP (Error-Efficient Computing Systems) in IAP 2017.
- Workshop instructor, MIT 6.S977 (Technical Communication Skills for Graduate Students), spring 2016.
- Course instructor, MIT 6.S194/IAP (Error-Efficient Computing Systems) in IAP 2016.
- Advisor, MIT EECS Communication Laboratory (Communication Skills for Engineers), 2015 to 2017.
- MIT Kaufman Teaching Certificate Program, spring 2015.
- From about 2002 to 2005, I took part in the Carnegie Mellon Eberly Center for Teaching Excellence program.
- Compile-Time Transformations to Induce Optical Illusions in a Vector Drawing Language (available, starting 2020)
- Machine Learning for Sensor Transducer Conversion Routines (available, starting 2020)
- Synthetic Sensors and Digital Sensor Substitution (available, starting 2020)
- Feature Extraction in Multi-Modal Sensor Data by Dimensional Function Synthesis on FPGAs (available, starting 2020)
- Performance and Power Analysis of Sensor Access Schedulers (available, starting 2020)
- Sensor access schedulers (available, starting 2020)
- Virtual Machine / Interpreter for C-like Language on Microcontrollers with Less Than 128k RAM (available, starting in 2020)
Department role and responsibilities
- Designed and introduced new 4th-year undergraduate course, 4B25 Embedded Systems (2017/2018)
- Designed and introduced a new 3rd-year undergraduate project-based course on Computer Architecture with RISC-V, Verilog, and the iCE40 FPGA (2018/2019)
- Cohort leader for IA IEP