Alexander Opitz
Associate Professor, McKnight Presidential Fellow
- PhD in Theoretical and Computational Neuroscience, University of Göttingen, Germany
- Diploma in Physics, University of Tübingen, Germany
Alex is an Associate Professor in the Department of Biomedical Engineering. His research interests are in understanding how electromagnetic fields interact with the brain. He hopes to translate this knowledge into neuromodulation therapies for psychiatric and neurological disorders. He believes to make progress it is necessary to study the effect of brain stimulation on various levels using different modalities.
Harry Tran
Postdoctoral Associate
- PhD in Automation, Signal and Image Processing, and Computer Engineering, University of Lorraine, France
- Master of Science in Engineering, ENSEM, University of Lorraine, France
- Master in Complex Systems Engineering, University of Lorraine, France
Harry is a computational engineer investigating the effects of electric stimulation in single cells and large neuron populations (mainly transcranial alternating current stimulation tACS and transcranial magnetic stimulation TMS). He also performs invasive recordings in awake non-human primates to extract single unit activity (SUA) and multi unit activity (MUA).
Sangjun Lee
Postdoctoral Associate
- PhD in Electronic Engineering, Hanyang University, Republic of Korea
- MS in Biomedical Engineering, Hanyang University, Republic of Korea
- BS in Applied Physics, Hanyang University, Republic of Korea
Sangjun’s research interest is in investigating the effects of non-invasive brain stimulation (tDCS, tACS). He is specialized in computational simulation using finite element analysis to find ways to improve the stimulation efficacy. His goal is to validate the simulation through various experimental protocols.
Ghazaleh Soleimani
Postdoctoral Associate
- MS and PhD in Biomedical Engineering, Tehran Polytechnic, Iran
- BS in Electrical Engineering, Isfahan University of Technology, Iran
Ghazaleh’s research interest lies in the development of optimized brain stimulation protocols informed by brain mapping tools. She aims to understand how transcranial electrical/magnetic stimulation affects neural and behavioral outcomes. Utilizing MR neuroimaging, signal processing, and machine learning techniques, she investigates the relationship between stimulation-induced electric fields and changes in brain functions and behaviors. Her research is directed toward creating personalized brain stimulation protocols and refining stimulation parameters for individuals with neuropsychiatric diseases like substance use disorders, based on closed-loop systems that integrate brain function feedback into the stimulation parameters.
Malte Güth
Postdoctoral Fellow
- PhD in Neuroscience, Rutgers University, USA
- MS in Psychology, Philipps-Universität Marburg, Germany
- BS in Psychology, Philipps-Universität Marburg, Germany
Malte’s research is focused on developing novel methods for closed-loop EEG-TMS to individualize brain stimulation treatments and to study the functional relationships between neural oscillations and cognitive functions. To characterize the targeted oscillations and map out the connectivity of the targeted structures he is incorporating insights from simultaneous EEG-fMRI, MEG, and DWI.
Jimin Park
Postdoctoral Associate
- PhD in Electronic Engineering, Hanyang University, Republic of Korea
- BS in Electrical Engineering, Hanyang University, Republic of Korea
Jimin is focused on defining mechanisms of noninvaisve brain stimulation (tACS, TMS), using electrophysiological recordings in both humans and non-humans. His goal is to develop and validate stimulation protocols using signal processing, behavioral measures and computational simulation of Transcranial Electrical Stimulation.
Taylor Ann Berger
PhD Candidate in Biomedical Engineering
- BS in Biomedical Engineering, University of Tennessee, USA
Taylor's research interests are in expanding noninvasive neurostimulation for rehabilitation and treatment in neurological and psychiatric disorders. She strives to improve existing techniques and applications through dynamic computational modeling and the incorporation of artificial intelligence and deep learning.
Zachary Haigh
PhD Candidate in Biomedical Engineering
- BS in Biomedical Engineering, Colorado State University, USA
- BS in Chemical & Biological Engineering, Colorado State University, USA
Zach's research interest is in developing new tools to enhance the understanding and utility of noninvasive brain stimulation methods such as TMS. He is currently working to integrate tracking technologies and simulation programs for use with TMS. This technology would allow researchers and clinicians to compare electric field modeling to evoked potentials during stimulation.
Zhihe Zhao
PhD Candidate in Biomedical Engineering
- MS in Biomedical Engineering, Duke University, USA
- BS in Biomedical Engineering, University of Houston, USA
Zhihe is fascinated by how the brain works and by the interactions between neurons and electromagnetic fields. His eagerness to improve people's quality of life motivates him to study brain stimulation to treat neurological disorders. Zhihe's interested in multiscale computational modeling of neural responses to non-invasive neuromodulation, such as TMS and tACS, to better understand their mechanisms. His goal is to improve the efficacy of neuromodulation-based treatment modalities.
Da Som Choi
PhD Candidate in Biomedical Engineering
- MS in Electronic Engineering, Hanyang University, Republic of Korea
- BS in Mechanical & Biomedical Engineering, Kangwon National University, Republic of Korea
Da Som is interested in finding better ways to deliver electrical currents directly to the target and investigating the effect of tES on neuronal activities. Her primary research goals are directed toward understanding brain function by engaging in experimental and theoretical inquiries with the hopes of treating a malfunction of the brain using non-invasive transcranial stimulation. During pursuit of her master’s degree, she performed both theoretical and experimental studies on non-invasive transcranial electric stimulation (tES), and she mainly focused on computational simulation for intersectional short pulse (ISP) stimulation.
Michelle Ma
PhD Student in Biomedical Engineering
- BSA in Neuroscience, University of Texas at Austin, USA
Michelle is interested in optimizing real-time closed-loop TMS-EEG treatments for neuropsychiatric disorders. She aims to study how oscillation dynamics in the brain are related to disease states and how these dynamics are modulated by noninvasive stimulation. She also hopes to take advantage of the unique opportunity presented by TMS-EEG to study networks of effective, or casual, brain connectivity.
Makaha Harmon
PhD Student in Biomedical Engineering
BS Bioengineering, University of Washington, USA
Makaha's research interest is in enhancing the clinical translation of closed-loop TMS systems to improve their usability and accessibility in clinical settings. She aims to develop user-friendly, hardware-integrated systems capable of delivering optimized closed-loop TMS treatments for neuropsychiatric disorders. Her goal is to create technology that lowers the barrier to adoption in clinics while ensuring consistent stimulation delivery and reducing variability in treatment outcomes.
Zijia Jin
Master's Student in Biomedical Engineering
BS in Biomedical Engineering, Tiangong University, China
Zijia is working on the analysis of brain activities after non-invasive stimulation such as TMS. Her research interests revolve around using both computational and electrophysiological methods to optimize the treatment for neurological disorders. Her goal is to gain assessment and research experience in graduate study that will involve understanding the mechanism of different neuromodulation techniques.
Stephanie Bai
Master's Student in Biomedical Engineering
BS in Biomedical Engineering, University of Minnesota, USA
Stephanie's interests revolve around understanding the mechanisms of non-invasive brain stimulation techniques, specifically TMS, and their potential applications in neurological disorders. Previous projects have explored the impact of TMS on motor responses and the use of TMS combined with diffusion-weighted imaging (DWI) to predict patient response to stroke. Currently, she is investigating the optimization of phase angle stimulation during TMS using machine learning algorithms.
Yona Ketema
Undergraduate Research Assistant, Biomedical Engineering
Aneka Blenker
Undergraduate Research Assistant, Biomedical Engineering
Lab Alumni
Kathleen Mantell - PhD in Biomedical Engineering, University of Minnesota
Jonna Rotteveel - Lab Manager
Estefania Cruz Casillo - Undergraduate Research Assistant
Miles Wischnewski - Postdoctoral Associate
Sina Shirinpour - Research Scientist
Rebecca Kazinka - Postdoctoral Associate
Ivan Alekseichuk - Research Scientist
Nipun Perera - PhD in Biomedical Engineering, University of Minnesota
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