Lou is a Belgian student who graduated in Neuroscience and Cellular & Molecular Biology from Johns Hopkins University, Baltimore. During college, he studied rodent hippocampal place cells in Dr. Knierim’s lab. He then worked for two gap years on the genetics of psychiatric disorders at the Lieber Institute for Brain Development (Baltimore). He is now pursuing an MD-PhD at Emory, where he joined Drs. Willie and Singer’s labs. His research focuses on understanding circuits involved in memory and emotion, as well as non-invasive means of modulating such circuits. Specifically, he works with treatment-resistant epileptic patients who, for clinical reasons, temporarily undergo intracranial recordings, offering a unique opportunity to shed light on the workings of said circuits.
Kyle graduated from Brigham Young University in 2019 with a B.S. in bioinformatics, where he developed mutation mapping software under the direction of Dr. Jonathon Hill. As a biomedical engineering PhD student in Christopher Rozell’s lab, he is currently researching closed-loop, optogenetic control for studying and interfacing with the brain. He is broadly interested in the decoding and control algorithms behind neural interfaces—especially in the potential of spiking neural networks and neuromorphic computing to advance the field.
Sean O’Connell is working jointly as a graduate student in the labs of Chethan Pandarinath and Sam Sober. The main goal of his project is to uncover new insights into the neural mechanisms of skilled, dynamic motor control. Currently, he is developing a pipeline for collecting forelimb EMG recordings from rats during a skilled forelimb movement. He has also developed a new method for analyzing different muscle activation patterns during tasks with different rates of force development. Using this method, his goal is to identify any flexibility in population-level patterns of motor unit recruitment across these force conditions, which could shed some light on a long-standing dispute about flexible versus static recruitment patterns.
Matthew Williams graduated from Rochester Institute of Technology in 2019 with degrees in Mechanical Engineering and Biomedical Engineering. He previously worked in a research lab specializing in microfluidics and advanced cell culture techniques. Matthew Williams is now a member of the Sober Lab at Emory University and is developing implantable 3D microelectrode arrays for EMG recording.
Adriano graduated from Harvard College as a member of the Class of 2020 with a degree in Bioengineering. During college, he collaborated with the Global Health Initiative at Dana-Farber/Boston Children’s to prototype an early sepsis detection vital monitor meant for deployment in hospitals in low-income countries. For his senior project, he built the hardware and software elements of a wearable drowsiness monitor that used infrared radiation to detect eye blink features as a proxy for alertness. Currently, he is broadly interested in detecting and using brain signals to make real-time clinical decisions
Keren Zhang is a PhD student in Dr. Hang Lu’s lab in ChBE department. His research focuses on quantitatively characterizing the connectome of C. elegans, a nematode and model organism. He is currently working on developing microfluidics-based fluorescent microscopy imaging technique and computational pipeline to process large-scale connectome data.
Lisa graduated from the Georgia Institute of Technology in 2020 with a degree in Biomedical Engineering. As an undergrad, she worked under the direction of Dr. Bilal Haider characterizing excitatory and inhibitory responses in the mouse visual cortex. Now she is working jointly as a graduate student in the labs of Shella Keilholz and Dieter Jager at Emory University. Her work revolves around uncovering the dynamics of multimodal and multiscale brain activity. The main goal is to use fMRI and optical imaging to uncover trends in functional connectivity in Alzheimer’s disease.
Sihoon is a Chemical and Biomolecular Engineering Ph.D. student in Dr. Hang Lu’s lab. He is studying changes in functional connectivity associated with learning in the model organism, C. elegans. His work leverages microfluidic experimental setups and scalable data processing methods to generate novel, large-scale, and high content datasets. He graduated from the University of Minnesota in 2019, earning degrees in Chemical Engineering and Chemistry.
Sena is a Neuroscience PhD student working jointly in the labs of Drs. Robert Liu, Gordon Berman and Larry Young at Emory University. He is interested in understanding how the oxytocin system in the striatum influences the neurophysiological mechanisms in behaviors such as social attachment, which gradually emerge over long timescales and involve a trajectory of dynamic behavioral interactions. He uses computational and quantitative approaches to try to understand how social signals are translated into neural activity to modulate social behavioral responses. His work involves recording electrophysiological activities in freely moving socially monogamous rodents, prairie voles. He also applies machine learning and deep learning techniques to extract behavioral dynamics as the voles cohabitate and form social bonds.
Mattia graduated as an Electrical Engineer in 2018 from Pontificia Universidad Católica de Chile, with a BS in Electrical Engineering in 2016 and a MSc in Engineering in 2018. During his Master’s thesis and the years that followed, he worked in several projects in Chile developing control strategies and hardware for robotics. Additionally, he worked on implementing control algorithms for commercial FES devices for gait rehabilitation. Mattia joined Chethan Pandarinath’s lab as a Biomedical Engineering PhD student, and is interested in studying the systems relating neural activity and muscle activation during motor control, to uncover insights useful for developing brain machine interfaces to control FES and robotic devices for rehabilitation.
James graduate from University of Arizona in 2020 with a B.S in Biomedical Engineering. During his undergrad he worked in Dr. Philipp Gutruf’s lab where he helped developed wireless, battery-free, and subdermally implantable optogenetic tool with dopamine sensing capabilities. James is now a BME PhD student in Dr. Bilal Haider’s lab where he joined a project investigating optogenetic perturbations in PV and SST neurons in mice in relation to spatial attention.
Jorge received his B.S. in Electrical Engineering from the Pontifical Catholic University of Peru, focusing on image processing and optimization courses. He went on to pursue an M.Sc. in Digital Signal and Image Processing at the same institution, where he became interested in the cross-fertilization between the fields of computational neuroscience and machine learning. He’s excited about the study of machine learning methods that may help improve our understanding of the human brain, as well as drawing from current ideas in neuroscience to builld better machine learning techniques. His current work in Dr. Eva Dyer’s lab involves using augmented self-supervised learning methods to extract meaningful representations from brain images, in hopes of shedding light into the structure of different brain areas.
Jonathan graduated from the State University of New York at Geneseo in 2021 with degrees in Physics and Applied Mathematics. During his time as an undergraduate, Jonathan worked on developing and benchmarking computational methods from across the fields of derivative-free optimization, gravitational wave modeling and signal analysis, as well as fMRI and behavioral data analysis. Jonathan is now a Machine Learning PhD student at Georgia Tech working in the Systems Neural Engineering Lab of Dr. Chethan Pandarinath. Jonathan is interested in studying neural coding and working on machine learning methods capable of characterizing the dynamics of neural activity with the goal of improving brain-computer interface systems for motor rehabilitation.
Yenho graduated from The University of Texas at Dallas in 2019 with a B.A. in physics and a minor in biology. As an undergraduate, he conducted research with Dr. Albert Montillo at UT Southwestern Medical School developing deep learning models that identify neuroimage biomarkers. After graduating, he worked in the Machine Learning Team at the National Institute of Mental Health, where he built machine learning tools for a variety of neuroscience problems including spike sorting, fMRI denoising, and neural code interpretation. Currently, he is a graduate student in Georgia Tech’s Machine Learning program. As part of Dr. Christopher Rozell’s lab, he hopes to continue developing intelligent algorithms that can be integrated into the biomedical sciences and neurotechnology.
Lauren earned a B.S. in Biomedical Engineering from Florida State University, and conducted research at the National High Magnetic Field Laboratory with Dr. Sam Grant, researching functional connectivity patterns in ischemic rats. She is currently a graduate student in Dr. Shella Keilholz’s MIND Lab, investigating low acquisition time pulse sequences in fMRI and other neuroimaging modalities.
Yichao received his dual B.S degree in biology and biomedical engineering from Emory and Georgia Tech. During his undergraduate years at Emory, he conducted cancer genetics research at the Winship Cancer Institute for three years. After completing his curriculum at Emory, he continued to pursue his engineering degree at Georgia Tech. He worked at Dr. David Hu’s lab of Biolocomotion and studied the motion of elephant trunks to develop soft robotic arms. After completing his undergraduate degrees in 2018, he worked in an antibody-based testing kit development team at Raybiotech. As a flow cytometry specialist, he collaborated with several computational biologists in the company, and this experience inspired him to explore the application of computational methods in biomedical research. Currently, he is a BME PhD student in Dr. Ming-fai Fong’s lab. His research interest is to use electrophysiology, computational modeling, and control system engineering tools to understand the development of neuroplasticity in visual circuits.
Yasmine (she/her) is a Lebanese Neuroscience PhD student at Emory University, conducting graduate research in the Neural Plasticity Research Laboratory with Dr. Michael Borich. In the lab, she is interested in studying age-related changes in the connectivity and plasticity of human spatial navigation networks. Her work leverages neurostimulation and neuroimaging methods, such as TMS, fMRI, and concurrent TMS-fMRI. Previously, Yasmine graduated from the Georgia Institute of Technology in 2020 with a degree in Neuroscience and conducted undergraduate research with Dr. Shella Keilholz at Emory. Outside of research, Yasmine is interested in promoting inclusive science communication, contributing to science advocacy initiatives, and collaborative outreach opportunities with the Atlanta scientific research community.
KC graduated from the Georgia Institute of Technology in 2020 with a BS in Chemical and Biomolecular Engineering and a minor in Biomedical Engineering. While in undergrad, she explored how monomers available on prebiotic earth self-assemble and evolve into present-day proteins and RNA. She returned to Georgia Tech to pursue a PhD in BioEngineering, with the overall goal of applying her biochemistry experience to medical application and disease models. Currently, she works in Dr. Bilal Haider’s lab researching how cross-cortical neural circuit activity generates sensory perception and action. Her current project focuses on elucidating the neural mechanisms of impaired sensory processing in a human-relevant mouse model of autism spectrum disorder.
Zach earned a B.S. in physics in 2019 and an M.S. in biomathematics in 2021, both from Illinois State University. During his undergraduate research, he studied the Hodgkin-Huxley model in the context of astrocyte-mediated synaptic interactions. His senior research project culminated in the creation of an electronic circuit that qualitatively captures the main features of the Hodgkin-Huxley single neuron model. For his master’s thesis, he used mathematical models to study the biophysical mechanisms of the single neuron underlying thermotaxis in Caenorhabditis elegans. At Georgia Tech, he currently works in Hannah Choi’s mathematical neuroscience group. He is broadly interested in how convergent-divergent network structures combine and interact with the nonlinear dynamics of their units to optimize information processing, especially in the context of vision.
Eloy graduated with a double Master’s degree in Biomedical Engineering and Embedded Systems from the Delft University of Technology in the summer of 2021. While pursuing an Industrial Design Engineering undergrad at the TU Delft in the Netherlands, he minored in medicine at the Erasmus Medical Center Rotterdam and started researching neurodevelopmental disorders under the supervision of Dr. Tonya White. At Georgia Tech, Prof. Dr. Vince Calhoun supervises his Ph.D., where he focuses on understanding the multimodal macro-scale dynamics of the human brain using deep learning. Through his research, he hopes to empower psychiatric clinicians with quantitative measures to complement and inform therapy sessions.
Xinhui is a PhD student in Georgia Tech’s Electrical and Computer Engineering program. Working with Dr. Vince Calhoun at TReNDS Center, she is developing analysis frameworks to identify and predict linked cross-modal biomarkers from multimodal neuroimaging datasets. Her research goals include understanding the principles of information processing in the nervous system from multimodal neuroimaging, in the hope of developing human-like intelligent algorithms and building energy-efficient neuromorphic machines. Previously, she received a M.S. in Biomedical Engineering from Columbia University and a M.S. in Computer and Information Technology from the University of Pennsylvania. She also worked as a research engineer at Child Mind Institute where she developed a software pipeline for fMRI preprocessing and analysis.
Hymavathy Balasubramanian is a first year graduate student in the neuroscience program at Emory. She is the recipent of the George W Woodruff Fellowship from the Laney graduate school and a Simon-Emory Fellowship in Computational Neuroscience from the neuroscience graduate program at Emory.
Hyma has an undergraduate degree is biomedical engineering from India, and a master’s in Computational Neuroscience from the Bernstein Centre of Computational Neuroscience, Berlin, Germany. Her research interests are aligned towards understanding the neural computations underlying sensory behaviour, and how communication is mediated between different cortical and subcortical representations of the sensory stimuli in the brain.
Currently, Hyma is exploring labs across Emory and Georgia tech working on wide array of research topics to find her dissertation thesis lab.
Outside of research, she is keen on participating in endeavours encouraging international students in the US and is motivated to support them in their transition to the US graduate school experience.
Jacob is a second year BME Student in Dr. Svjetlana Miocinovic’s Lab studying the effects of deep brain stimulation (DBS) on behavioral task response times in patients with Parkinson’s Disease in the OR. He graduated with a BS in Biomedical Engineering from Case Western Reserve University and a MS in Neurobiology from Northwestern University.
Vaibhavi is an Indian student who graduated with Bachelor’s and Master’s from Indian Institute of Technology, Chennai (India). Her Master’s thesis was jointly advised by Dr. Markus Barth (University of Queensland, Australia) and Dr. Ganapathy Krishnamurthi (IIT Chennai). She is currently pursuing her PhD at Emory University in Neuroscience under the guidance of Dr. Vince Calhoun. Her research interests majorly lie along using different modalities from neuroimaging datasets (sMRI, fMRI), by using deep learning, computational neuroscience and data fusion approaches. She is passionate about solving problems related to the neuropsychiatric and neurodevelopmental disorders to hopefully have computational tools and models which would be clinically relevant.