Emily Sanders

Emily Sanders
emily.sanders@me.gatech.edu

Dr. Emily D. Sanders is an Assistant Professor in the Woodruff School of Mechanical Engineering at Georgia Tech. She obtained her Ph.D. at Georgia Tech in 2021, where she developed new topology optimization methods for design of tension-only cable nets, elastostatic cloaking devices, and multiscale structures and components. Dr. Sanders hold a bachelor’s degree from Bucknell University and a master’s degree from Stanford University.

Assistant Professor

Farzaneh Najafi

Farzaneh Najafi
fnajafi3@gatech.edu
Najafi Lab Website

Overview:
Our brain not only processes sensory signals but also makes predictions about the world. Generating and updating predictions are essential for our survival in a rapidly changing environment. Multiple brain regions including the cerebellum and the cortex are thought to be involved in the processing of prediction signals (aka predictive processing). However, it is not clear what circuit mechanisms and computations underlie predictive processing in each region, and how the cortical and cerebellar prediction signals interact to support cognitive and sensorimotor behavior. Our lab is interested in figuring out these questions by using advanced experimental and computational techniques in systems neuroscience.

Assistant Professor
Phone
2672519137
Office
IBB 3314
Additional Research
Research Interests: Systems and behavioral neuroscience; Computational neuroscience; Predictive processing; Brain area interactions; Cortex and cerebellum; Population coding

Amirali Aghazadeh

Amirali Aghazadeh
aaghazadeh3@gatech.edu
Profile Page

Amirali Aghazadeh is an Assistant Professor in the School of Electrical and Computer Engineering and also program faculty of Machine Learning, Bioinformatics, and Bioengineering Ph.D. programs. He has affiliations with the Institute for Data Engineering and Science (IDEAS) and Institute for Bioengineering and Biosciences. Before joining Georgia Tech, Aghazaeh was a postdoc at Stanford and UC Berkeley and completed his Ph.D. at Rice University. His research focuses on developing machine learning and deep learning solutions for protein and small molecular design and engineering.
 

Assistant Professor
Phone
713-257-5758
Office
CODA S1209
Google Scholar
https://scholar.google.com/citations?hl=en&user=87wBxzUAAAAJ&view_op=list_works&sortby=pubdate

Shaheen Dewji, Ph.D.

Shaheen Dewji, Ph.D.
shaheen.dewji@gatech.edu

Shaheen Azim Dewji, Ph.D., (she/her/hers) is an Assistant Professor in the Nuclear & Radiological Engineering and Medical Physics Programs at the Georgia Institute of Technology, where she leads the Radiological Engineering, Detection, and Dosimetry (RED²) research group. Dewji joined Georgia Tech following three years as faculty at Texas A&M University in the Department of Nuclear Engineering, and as a Faculty Fellow of the Center for Nuclear Security Science and Policy Initiatives (NSSPI). In her prior role at Oak Ridge National Laboratory, where she remained for almost 9 years, Dewji was Radiological Scientist in the Center for Radiation Protection Knowledge. Her research interests include development of dose coefficients, shielding design, and nuclear material detection assay using gamma-ray spectroscopy. Her recent work has focused on associated challenges in uncertainty quantification in dose estimation/reconstruction associated with the external exposure and internal uptake of radionuclides associated with applications of emergency response, defense, nuclear medicine, and occupational/public safety using Monte Carlo radiation transport codes and internal dose modeling. Dewji completed her Masters and Ph.D. degrees in Nuclear and Radiological Engineering at the Georgia Institute of Technology in Atlanta, GA and was a fellow of the Sam Nunn Security Program. She received her Bachelor of Science in Physics from the University of British Columbia. Dewji currently serves on the National Academies of Science, Engineering, and Medicine – Nuclear and Radiation Studies Board and is a member of the Board of Directors for both the American Nuclear Society and Health Physics Society.
   

Assistant Professor
Phone
404.894.5800
Office
Boggs 3-15
Lab

Saurabh Sinha, Ph.D.

Saurabh Sinha, Ph.D.
Lab

Saurabh Sinha received his Ph.D. in Computer Science from the University of Washington, Seattle, in 2002, and after post-doctoral work at the Rockefeller University with Eric Siggia, he joined the faculty of the University of Illinois, Urbana-Champaign, in 2005, where he held the positions of Founder Professor in Computer Science and Director of Computational Genomics in the Carl R. Woese Institute for Genomic Biology until 2022. He joined Georgia Institute of Technology in 2022, as Wallace H. Coulter Distinguished Chair in Biomedical Engineering, with joint appointments in Biomedical Engineering and Industrial & Systems Engineering. Sinha’s research is in the area of bioinformatics, with a focus on regulatory genomics and systems biology. Sinha is an NSF CAREER award recipient and has been funded by NIH, NSF and USDA. He co-directed an NIH BD2K Center of Excellence and was a thrust lead in the NSF AI Institute at UIUC. He led the educational program of the Mayo Clinic-University of Illinois Alliance, and co-led data science education for the Carle Illinois College of Medicine. Sinha has served as Program co-Chair of the annual RECOMB Regulatory and Systems Genomics conference and served on the Board of Directors for the International Society for Computational Biology (2018-2021). He was a recipient of the University Scholar award of the University of Illinois, and selected as a Fellow of the AIMBE in 2018.

Wallace H. Coulter Distinguished Chair in Biomedical Engineering
Professor
Office
3108 UAW

Vida Jamali

Vida Jamali
vida@gatech.edu
Jamali Lab

Vida Jamali earned her Ph.D. in chemical and biomolecular engineering from Rice University under the guidance of Professor Matteo Pasquali and her B.S. in chemical engineering from Sharif University of Technology. Jamali was a postdoctoral researcher in Professor Paul Alivisato's lab at UC Berkeley and Kavli Energy Nanoscience Institute before joining Georgia Tech. The Jamali Research Group uses experimental, theoretical, and computational tools such as liquid phase transmission electron microscopy, rheology, statistical and colloidal thermodynamics, and machine learning to study the underlying physical principles that govern the dynamics, statistics, mechanics, and self-organization of nanostructured soft materials, in and out of thermal equilibrium, from both fundamental and technological aspects.

Assistant Professor, School of Chemical and Biomolecular Engineering
Phone
404.894.5134
Office
ES&T 1222
Additional Research
Studying dynamics and self-assembly of nanoparticles and macromolecules in heterogeneous chemical and biological environmentsInvestigating individual to collective behavior of active nanomachinesHarnessing the power of machine learning to understand physical rules governing nanostructured-soft materials, design autonomous microscopy experimentation for inverse material design, and develop new statistical and thermodynamic models for multiscale phenomena
ChBE Profile Page

Alex Abramson

Alex Abramson
aabramson6@gatech.edu
Abramson Lab

Alex Abramson is an assistant professor in the School of Chemical and Biomolecular Engineering at Georgia Tech. His research, which focuses on drug delivery and bioelectronic therapeutics, has been featured in news outlets such as The New York Times, NPR, and Wired. Abramson has received several recognitions for scientific innovation, including being named a member of the Forbes 30 Under 30 Science List and the MIT Technology Review Innovators Under 35 List. He is passionate about translating scientific endeavors from bench to bedside. Large pharmaceutical companies have exclusively licensed a portfolio of his patents to bring into clinical trials, and Abramson serves as a scientific advisor overseeing their commercialization. In addition to his scientific endeavors, Abramson plays an active role in his community by leading diversity and inclusion efforts on campus and volunteering as a STEM tutor to local students.

Abramson received a B.S. in chemical and biomolecular engineering from Johns Hopkins University and a Ph.D. in chemical engineering from MIT as an NSF Graduate Research Fellow under the direction of Professors Robert Langer and Giovanni Traverso. He conducted postdoctoral work at Stanford University as an NIH fellow with Professors Zhenan Bao and the late Sanjiv S. Gambhir.

The Abramson Lab develops ingestible, implantable, and wearable robotic therapeutic devices that solve key healthcare problems and provide measurable therapeutic outcomes. Our translationally focused research spans a multitude of areas, including (1) drug delivery devices for optimal drug adherence, (2) soft materials for bioelectronic sensors and therapeutics, and (3) preclinical drug screening technologies.

Assistant Professor, School of Chemical and Biomolecular Engineering
Office
MoSE 4120B
Additional Research
Biosensors
Google Scholar
https://scholar.google.com/citations?user=9-E5owYAAAAJ
ChBE Profile Page

Hannah Choi

Hannah Choi
hannahch@gatech.edu
https://hannahchoi.math.gatech.edu/

Hannah Choi is an Assistant Professor in the School of Mathematics at Georgia Tech. Her research focuses on mathematical approaches to neuroscience, with primary interests in linking structures, dynamics, and computation in data-driven brain networks at multiple scales. Before coming to Georgia Tech, she was a postdoctoral fellow at the University of Washington and also a visiting scientist at the Allen Institute for Brain Science, and spent one semester at the Simons Institute for the Theory of Computing at the University of California, Berkeley as a Patrick J McGovern Research Fellow. She received her Ph.D. in Applied Mathematics from Northwestern University and her BA in Applied Mathematics from the University of California, Berkeley.

Assistant Professor
University, College, and School/Department

Jun Ueda, Ph.D.

Jun Ueda, Ph.D.
jun.ueda@me.gatech.edu
Website

Jun Ueda received his B.S., M.S., and Ph.D. degrees from Kyoto University, Japan, in 1994, 1996, and 2002 all in Mechanical Engineering. From 1996 to 2000, he was a Research Engineer at the Advanced Technology Research and Development Center, Mitsubishi Electric Corporation, Japan. He was an Assistant Professor of Nara Institute of Science and Technology, Japan, from 2002 to 2008. During 2005-2008, he was a visiting scholar and lecturer in the Department of Mechanical Engineering, Massachusetts Institute of Technology. He joined the G. W. Woodruff School of Mechanical Engineering at the Georgia Institute of Technology as an Assistant Professor in 2008 where he is currently a Professor. He received Fanuc FA Robot Foundation Best Paper Award in 2005, IEEE Robotics and Automation Society Early Academic Career Award in 2009, Advanced Robotics Best Paper Award in 2015, and Nagamori Award in 2021. 

Professor
Phone
404.385.3900
Office
Love 219

Vince Calhoun

Vince Calhoun
vcalhoun@gatech.edu
Learn more

Vince Calhoun, Ph.D., is the founding director of the tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) where he holds appointments at Georgia State, Georgia Tech and Emory. He is the author of more than 900 full journal articles. His work includes the development of flexible methods to analyze neuroimaging data including blind source separation, deep learning, multimodal fusion and genomics, neuroinformatics tools. Calhoun is a fellow of the Institute of Electrical and Electronic Engineers, The American Association for the Advancement of Science, The American Institute of Biomedical and Medical Engineers, The American College of Neuropsychopharmacology, The Organization for Human Brain Mapping (OHBM) and the International Society of Magnetic Resonance in Medicine. He currently serves on the IEEE BISP Technical Committee and is also a member of IEEE Data Science Initiative Steering Committee as well as the IEEE Brain Technical Committee.

Director TReNDS
Director CABI
Distinguished University Professor