Nazanin Bassiri-Gharb joined Georgia Tech in summer 2007 as an assistant professor at the George W. Woodruff School of Mechanical Engineering. Prior to this, she was a senior engineer in the materials and device R&D group of MEMS Research and Innovation Center at QUALCOMM MEMS Technologies, Inc. Her work included characterization and optimization of optical and electric response of IMOD displays and research on novel materials for improved processing and reliability of IMOD. Bassiri-Gharb's research interests are in smart and energy-related materials (e.g. ferroelectric and multiferroic materials) and their application to nano- and micro-electromechanical systems. Her research projects integrate novel micro and nanofabrication techniques and processes and study of the fundamental science of these materials at the nanoscale, at the interface of physical and electrochemical phenomena.

Srinivas Aluru is executive director of the Institute for Data Engineering and Science (IDEaS) and professor in the School of Computational Science and Engineering at Georgia Institute of Technology. He co-leads the NSF South Big Data Regional Innovation Hub which nurtures big data partnerships between organizations in the 16 Southern States and Washington D.C., and the NSF Transdisciplinary Research Institute for Advancing Data Science. Aluru conducts research in high performance computing, large-scale data analysis, bioinformatics and systems biology, combinatorial scientific computing, and applied algorithms. An early pioneer in big data, Aluru led one of the eight inaugural mid-scale NSF-NIH Big Data projects awarded in the first round of federal big data investments in 2012. He has contributed to NITRD and OSTP led white house workshops, and NSF and DOE led efforts to create and nurture research in big data and exascale computing. He is a recipient of the NSF Career award, IBM faculty award, Swarnajayanti Fellowship from the Government of India, the John. V. Atanasoff Discovery Award from Iowa State University, and the Outstanding Senior Faculty Research Award, Dean's award for faculty excellence, and the Outstanding Research Program Development Award at Georgia Tech. He is a Fellow of AAAS, IEEE, and SIAM, and is a recipient of the IEEE Computer Society Golden Core and Meritorious Service awards.

Jason Azoulay is an organic, organometallic and polymer chemist and internationally recognized leader in developing emerging semiconductor materials and devices. He has made significant contributions to the fields of polymer chemistry and materials science,bridging fundamental chemistry with real-world applications. His work focuses on the design, synthesis and characterization of advanced functional materials across numerous technology platforms, with an emphasis on organic semiconductors and conjugated polymers.

Azoulay co-directs the Center for Organic Photonics and Electronics, and his lab adds great strength to Georgia Tech’s leadership in soft-matter and hybrid optoelectronics. His work also complements numerous efforts at Georgia Tech that develop and apply advanced functional materials. 

I have a broad range of interests in soft condensed matter physics and adjacent fields like statistical physics, physics of living systems and hard condensed matter. My particular focus is on the relationship between the geometric structure of a system and its mechanical response. Both biological and engineered systems often have some structure, such as networks of struts, particles jammed together or patterns of creases in thin sheets, that grant them flexibility and strength with a minimum of weight. These structures can lead to subtle and surprising mechanical response:

The Raman Group has two main thrusts.  The team utilizes sophisticated tools to cool atoms to temperatures less than one millionth of a degree above absolute zero. Using these tools, they explore topics ranging from superfluidity in Bose-Einstein condensates (BECs) to quantum antiferromagnetism in a spinor condensate.  In another effort the team partners with engineers to build cutting edge atomic quantum sensors on-chip that can one day be mass-produced.