Students may apply to one or more of the below projects, indicating this in their statement of interest, or they may apply for "Chemistry: General," indicating in their statement of interest their skills and background and some faculty with whom they would be interested in working.  Chemistry Faculty List

Title Name Email Project Name Project Description Requirements
Prof. P. V. Ramachandran Synthesis of potential anti-tuberculosis agents Discovery and development of new agents to treat multi-drug resistant tuberculosis (MDR-TB) is a very active area of research in drug discovery.  Our laboratories have discovered certain new agents that are potent anti-TB agents.  We are preparing several analogs of these agents for biological screening.  The students will be trained in organic synthesis methodologies and in the preparation of intermediates necessary for these analogs of potential anti-TB agents.Knowledge of basic organic chemistry.  Knowledge of purification techniques will be beneficial. Knowledge of basic organic chemistry.  Knowledge of purification techniques will be beneficial.
 Prof. Alexander Wei  Low-cost chemical sensors for breath analysis  Patients and health workers lack simple, readily available, and cost-efficient methods for self-testing of stress, fatigue, or disease. However, many molecular markers of these symptoms can be found in exhaled breath. We have initiated a project for developing low-cost, disposable sensors that can detect volatile organic compounds (VOCs) released from breath or skin during respiration. Carbon nanomaterials will be coated as thin films on disposable substrates and sprayed with sensor molecules that can differentiate one or more VOCs for specific detection, using an electrochemical (conductometric) approach.  Desiderata:
1. organic chemistry laboratory experience (handling organic solvents)
2. Basic knowledge of electronics and electrochemistry
Asst. Prof. Gaurav Chopra Virtual reality environment toolbox for molecular exploration Molecular structure and interactions that determine the nature of biomolecules are difficult to imagine, even with the aid of graphics in textbooks. Several programs have been developed to visualize molecular structures but they typically require moderate to advanced knowledge to learn how to use the program. To understand biomolecular structure and interactions in detail requires a 3D, dynamic perspective, and educational research indicates an inquiry-led approach is more effective than a didactic approach. Motivated by the need to enhance education and visual learning experience of students, we have developed a virtual reality (VR) educational “game” for visualization and manipulation of biomolecules based on concepts of molecular interactions that are taught in a dynamic immersive environment. Using our immersive VR game, the students are able to manipulate a molecule in 3D to optimize its interactions to discover the factors responsible for optimum binding, guided by a live score based on our CANDOCK software indicating the strength of interaction in real-time. We believe this platform will enhance student learning experience through exploration in an immersive environment by repurposing a well- adopted gaming technology for teaching. Students interested in this project will develop tools to enhance our existing platform with new features of manipulating and exploring structures for the VR environment. They will work with graduate student developers to include new graphics and features to enhance this chemical environment. Knowledge of game development, experience with VR development environment, and working with C# programming language is preferred. Basic knowledge of chemical interactions molecular conformations will be useful but not required.
Asst. Prof. Gaurav Chopra Chemical Immunology: design, synthesis, and validation of cell-specific immunomodulators for cancer and neurodegeneration Immune system is a fascinating complex chemical system that consists of cells that respond to its environment to produce a desired effect. You all have experience with your immune system whenever you got an infection but the immune system can be used to treat devastating diseases like cancer and Alzheimer’s disease. Undergraduate students in my lab will have the opportunity to work on projects in the area of chemical immunology. This includes, design, synthesis and validation (mouse work) of small molecules drugs and using the immune “cells as drugs” for chemically perturbing the inflamed environment in neurological (Alzheimer's disease) and cancers. Each student will be working with a graduate student or postdoctoral scholar with work ranging (depending on their interest) from computational drug design, synthesis of the compounds, cell culture and primary cells/tissue work to develop immunomodulatory drugs. The immune system is affected in almost every disease and using the immune system to find treatments for diseases is a major interest in our lab. Experience with chemical synthesis, and/or biological assays and/or handling animals will be preferred, depending on the area of interest. Basic knowledge of the immune system will be useful for your project but not required.
Asst. Prof. Gaurav Chopra 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. 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.

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