Project Details
Program
Electrical Engineering
Field of Study
Electrical Engineering, Computer science, physics, neurosciences
Division
Computer, Electrical and Mathematical Sciences and Engineering
Faculty Lab Link
Project Description
Conventional computing based on Von Neumann architecture has been shown to be approaching its limits in scalability and power consumption. If solved with contemporary machines, today’s applications in science and industry related to data analysis, pattern recognition and prediction would demand a huge computing power. In the era of ubiquitous sensing and data acquisition, a way to cheaply and power efficiently make sense of the collected ‘big data’ is of utmost importance. Here, human brain’s efficiency becomes the ultimate standard and inspiration for any future technology. Such trend of understanding the brain behavior is currently gaining a huge attention worldwide. At the sensors lab, students under the supervision of Prof. K.N. Salama are exploring new computing technologies miming the way our brains process and store data.
About the Researcher
Khaled Nabil Salama
Professor, Electrical and Computer Engineering
Affiliations
Education Profile
- Ph.D. Electrical Engineering, Stanford University, Palo Alto, CA, United States, 2005
- M.S. Stanford University, Palo Alto, CA, U.S., 2000
- B.S. Cairo University, Egypt, 1997
Research Interests
a€‹Professor Salama's research interests cover a variety of interdisciplinary aspects of electronic circuit design and semiconductors' fabrication. He is engaged in developing devices, circuits, systems, and algorithms to enable inexpensive analytical platforms for a variety of industrial, environmental, and biomedical applications. Recently he has been working on neuromorphic circuits for brain emulation.Selected Publications
- Y. Lei, W. Zhao, Y. Zhang, Q. Jiang, J. H. He, A. J. Baeumner, O. Wolfbeis, Z. L. Wang, K. N. Salama, H. N. Alshareef, ""A MXene-Based Wearable Biosensor System for High-Performance In Vitro Perspiration Analysis,"" Small 1901190 (2019).
- EloA¯se Bihar, Shofarul Wustoni, Anna Maria Pappa, Khaled N. Salama, Derya Baran and Sahika Inal, A fully inkjet-printed disposable glucose sensor on paper, npj Flexible Electronics, 2, 1, (2018). 10.1038/s41528-018-0044-y
- Rafiq Ahmada , Otto S. Wolfbeisa , Yoon-Bong Hahna , Husam N. Alshareefa , Luisa Torsia and Khaled N. Salamaa ""Deposition of nanomaterials: A crucial step in biosensor fabrication,"" Materials Today Communications, Vol. 17, pp. 289-321, 2018. doi:10.1016/j.mtcomm.2018.09.024
- Saurabh Kumar, Yongjiu Lei, Niman H. Alshareef, M.A. Quevedo-Lopez, Khaled N. Salama ""Biofunctionalized Two-Dimensional Ti3C2 MXenes for Ultrasensitive Detection of Cancer Biomarker"", Biosensors and Bioelectronics, Vol 121, pp 243-249, 2018 DOI: 10.1016/j.bios.2018.08.076
- Rafiq Ahmad, Tutku BedA¼k, Sanjit Manohar Majhi and Khaled Nabil Salama, One-step synthesis and gold nanoparticle decoration of nickel oxide nanosheets for hydrazine sensing application, Sensors & Actuators: B. Chemical, Vol. 286, pp139-147, 2019 https://doi.org/10.1016/j.snb.2019.01.132
- Sandeep G.Surya, Harshil N.Raval, RafiqAhmad, PrashantSonar, Khaled N.Salama, V.Ramgopal Rao, Organic field effect transistors (OFETs) in environmental sensing and health monitoring: A review, Trends in Analytical Chemistry, vol 111, pp 27-36, 2019. https://doi.org/10.1016/j.trac.2018.11.027
- Mohamed Tchalala, Prashant Bhatt, Karumbaiah Chappanda, SA©rgio Tavares, Karim Adil, Youssef Belmabkhout, Aleksander Shkurenko, Amandine Cadiau, Nicolas Heymans, Guy Deweireld, Guillaume Maurin, Khaled Nabil Salama, and Mohamed Eddaoudi, ""Fluorinated MOF platform for selective removal and sensing of SO2 from flue gas and air"" Nature Communications, vol10, no. 1328, 2019
- Zhengyuan Zhou, Tiantian Kong, Hend Mkaouar, Khaled N.Salama and Jia Ming Zhang ""A hybrid modular microfluidic device for emulsion generation,"" Sensors and Actuators A: Physical, volume 280, pp 422-428, 2018 doi:10.1016/j.sna.2018.08.005
Desired Project Deliverables
Report of state of art brain inspired computers; Implementation of state of art;
Exploration of neuromorphic architectures;
Simulation and comparison of various alternatives.