Electrical & Computer Engineering
Students may apply to one or more of the below projects, indicating this in their statement of interest, or they may apply for "Electrical & Computer Engineering: General," indicating in their statement of interest their skills and background and some faculty with whom they would be interested in working. ECE Faculty List
|Title||Name||Project Name||Project Description||Requirements|
|Assoc Prof.||Peter Bermelemail@example.com||Electrically pumped Mie sphere single photon sources||On-demand single photon sources play a crucial role in integrated optical quantum information systems. Solid-state color centers, such as xenon (Xe) vacancies in diamond, have recently been demonstrated to provide single photon emission. However, using these color centers directly as single photon sources often fails to provide adequate environmental isolation, emission rate and coherence-time. In this project, we will investigate the design and fabrication of a high-efficiency, silicon-based Multilayer-Mie-sphere design having electrically controlled Xe vacancy-based diamond nano-rod. The objective will be to reliably emit single photons repeatedly at high speeds (up to GHz frequencies). These systems will then be coupled to fibers and other components to enable long-distance quantum communications.||Familiarity with introductory electromagnetism is required. A working ability to read and modify scientific code is also needed. An understanding of basic (first-quantized) quantum mechanics, including Schrodinger’s equation and perturbation theory is a plus. Finally, the ability to quickly learn a new scientific topic is desired.|
|Asst. Prof.||Gaurav Choprafirstname.lastname@example.org||Artificial Intelligence (AI) in Chemistry||
We really live in special times where we have so much data, e.g. Jean-Louis Reymond at U. Berne in Switzerland has collected a list of 166 Billion compounds that are chemically feasible organic molecules. Our lab is interested in developing methodology to model chemical systems. We discover “chemical rules” from large datasets and known databases of experiments and chemical reactions along the use of machine learning to guide further experiments. We develop CPU, GPU (graphical processing unit) based cheminformatics, chemical/structural modeling, machine learning methods for retrosynthesis prediction, docking and drug design tools for our software suite, namely, CANDIY (Computational Algorithms for Novel Drug Identification/Informatics for You). Undergraduate students in my lab will have the opportunity to work on projects in the area of using machine learning and chemical data to do retrosynthetic route prediction before doing synthesis, developing “computational assays” that are essential for predicting biological activity of the molecules in cells, etc. We are interested in developing molecules that perturb the immune cells for the treatment of neurological (Alzheimer's disease) and cancers.
(Listed primarily in the Department of Chemistry. Choose CHM while applying.)
|Some experience in scripting (perl, python, etc) and programming (C++) will be very useful with a basic knowledge of tools existing in machine learning (optional). Basic knowledge of organic synthesis, chemical interactions, or experiments done to test compounds in biological assays will be preferred but not required.
Students in Chemistry, Physics, CS, Math and ECE are all welcome to apply.