RESEARCH TEAM

Principal Investigator

Omer T. Inan, PhD

Regents Entrepreneur, Linda J. and Mark C. Smith Chaired Professor of Electrical and Computer Engineering, Adjunct Professor of Biomedical Engineering, Program Faculty Bioengineering

Education
Ph.D., Electrical Engineering, Stanford University, Stanford, CA, 2009
M.Sc., Electrical Engineering, Stanford University, Stanford, CA, 2005
B.Sc., Electrical Engineering, Stanford University, Stanford, CA, 2004

Major Awards
Fellow of IEEE, 2024
Distinguished Lecturer, IEEE EMBS, 2023-2024
Fellow of American Institute for Medical and Biological Engineering (AIMBE), 2022
Outstanding Doctoral Thesis Advisor Award, Georgia Tech, 2021
Academy Award for Technical Achievement, American Academy of Motion Picture Arts and Sciences (Oscars), 2021
Office of Naval Research Young Investigator Award (ONR YIP), 2018
National Science Foundation CAREER Award, 2018
IEEE Sensors Early Career (Young Professional) Award, 2018
Sigma Xi Young Faculty Award, Georgia Tech, 2017
Lockheed Dean’s Excellence in Teaching Award, Georgia Tech, 2016

POST-DOCTORAL RESEARCHERS

Samer Mabrouk, PhD

samer92@gatech.edu

My research interests are to use embedded systems and machine learning to develop miniaturized sensors that can be used in and outside the clinic. My main focus is to develop a miniaturized bioimpedance sensor to detect IV infiltration and evaluate joint health.

Nordine Sebkhi, PhD

sebnor31@gatech.edu

My main research interests are embedded systems and assistive robotics.

Goktug Cihan Ozmen, PhD

goktug@gatech.edu

I am interested in wearable biomechanics to enable patient monitoring in real world settings. My main focus is the development of wearable technologies for measuring novel biosignals. By using signal processing and machine learning methods to analyze these novel biosignals, I aim to help people improve their health and performance.

Quentin Goossens, PhD

qgoossens3@gatech.edu

My research interests focus on developing non-invasive objective measurement methods to assess and detect total knee arthroplasty (TKA) complications by analyzing joint acoustic data using signal processing algorithms. More specifically, these methods are designed for postoperative at home monitoring.

Michael Chan, PhD

mchan81@gatech.edu

My research interests focus on solving common biomedical problems such as scarcity of data, domain discrepancies, and data fusion using deep learning. I am also interested in incorporating prior knowledge of physiological signals to neural network architecture by leveraging its expressiveness.

Zeineb Bouzid, PhD

zbouzid3@gatech.edu

My research interests center around the biomedical applications of signal processing, machine learning, and deep learning. In my current work, I investigate the potential of physiological signals collected from wearable sensors, in identifying latent health markers.

Ruchik Mishra, PhD

rmishra92@gatech.edu

I am passionate about using Artificial Intelligence for healthcare. My current work comprises of making diagnostic and evaluative tools for pediatric rheumatology using AI.

GRADUATE STUDENTS

Oludotun Ode

oode3@gatech.edu

My research interests center around the development of embedded systems and statistical signal processing algorithms for bio-medical applications. Specifically, I am currently working on developing methods for detecting local muscle fatigue during physical exercise.

Christopher Nichols

cnichols46@gatech.edu

My research interests revolve around using non-invasive bio-signal sensing and measurement techniques to help improve patient outcomes. I am especially passionate about acoustics, signal processing, and device design that empowers patients to take ownership of their health both inside and outside of the clinic.

Moamen Soliman

soliman@gatech.edu

I work at the intersection of artificial intelligence and healthcare, focusing on leveraging machine learning to enhance clinical decision-making in critical care. My work involves developing innovative algorithms that integrate data-driven insights with clinician expertise to improve patient outcomes. With a background in deep and reinforcement learning as well as data modeling, I strive to bridge the gap between cutting-edge technology and impactful healthcare solutions.

Cem Okan Yaldiz

cyaldiz3@gatech.edu

My research focuses on applications of signal processing, machine learning, and deep learning in time series signals for the domain of wearables.

Trask Crane

hcrane3@gatech.edu

My research is driven by a commitment to providing clinicians with better tools to improve patient outcomes and quality of life. I develop wearable devices that leverage bioimpedance to assess fluid dynamics, paired with computationally efficient algorithms for real-time monitoring. Beyond my core focus, I contribute to a range of projects, including joint and pulmonary monitoring.

Afra Nawar

anawar3@gatech.edu

My research interests are focused on biomedical sensing systems for investigating stress and mood disorders such as PTSD. This includes assessing and developing non-invasive technology as treatment options and investigating signal processing methods to uncover more about the underlying processes involved in mental health.

Farhan Rahman

frahman39@gatech.edu

My research interests focus on the development of non-invasive hardware for wearable biomedical sensing systems, specifically in neural engineering applications such as stress management, psychiatric disorders, and nerve stimulation therapy. I am also interested in applications of machine learning and signal processing in the non-invasive healthcare space.

Jacob Cook

jacob.cook@gatech.edu

My research interests center around designing wearable continuous monitoring systems for streaming parallel biomarkers such as ECG, PPG, and BIOZ to smart devices. Using statistical machine learning techniques and representative physiological models, I hope to deploy a next generation of medical devices to classify and quantify clinically relevant events in real-time to noninvasively assess, monitor, and potentially treat illnesses primarily in the context of cardiac health and wellbeing.

Gabriela Cestero

gcestero3@gatech.edu

My research is focused on designing novel wearable systems integrated in a life jacket for monitoring cardiovascular health parameters in the ocean. I am also interested in designing signal processing and machine learning algorithms for noninvasive cardiovascular signal processing to advance capabilities in the field.

Michael Cho

mcho314@gatech.edu

My research interests revolve around embedded systems and machine learning applications for bio-medical and mental health applications. I am also interested in applying alternative machine learning paradigms that enhance performance and improve the security and privacy of our bio-medical data.

Vikram Abbaraju

vabbaraju3@gatech.edu

My research interests lie in developing algorithms for the real-time detection/prediction of cardiovascular events/biomarkers from wearable sensor data using signal processing and deep learning. Currently, I am investigating the behavioral and cardiovascular effects of non-invasive vagal nerve stimulation in opioid use disorder patients.

Chuoqi Chen

cchen864@gatech.edu

My research interests fall on developing non-invasive cardiovascular monitoring systems and innovative signal processing algorithms for different applications. Currently, I’m investigating the integration of non-invasive sensors with a life vest and corresponding processing techniques to optimize features extraction.

Onur Selim Kilic

okilic3@gatech.edu

My research interests primarily focus on machine learning algorithms aimed at predicting and reconstructing time series signals, with applications in physiological and biomedical signal processing.

Biya Haile

bhaile3@gatech.edu

My research interests are focused on developing Microelectromechanical systems (MEMS) based gas/PM sensors. With the rise of the lab-on-chip, microfluidic systems are developing at a rapid pace, but embedded sensors that can provide fluidic property information on these size scales do not currently exist. Sensors I am developing will create a path towards sub-millimeter sensing, which has tremendous potential.

Demet Tangolar

dtangolar3@gatech.edu

My research focuses on developing signal processing and machine learning algorithms for biomedical applications. I am working on non-invasive hemodynamic monitoring methods that utilize wearable sensors to enhance health assessments.