Adam joined the lab in August of 2018 as a neuroscience PhD student, and quickly became an absoltuely essential member of the team.  His first paper in the lab examined the utility of multi-shell diffusion models (Pines et al., Developmental Cognitive Neuroscience 2020).  Pivoting from dMRI to fMRI, he next charachterized how coupling between person-specific, multi-scale functional networks re-organize in development  (Pines et al., Nature Communications 2022).  Finally, his last major project mapped how functional propagations align with the cortical heirarchy and evolve in youth (Pines et al., bioRxiv 2022).  Beyond these projects, Adam contributed to 6 additional published papers as a co-author, and receieved multiple awards including a NIMH F31 Fellowship.  Following graduation, he returned to Stanford to pursue his post-doc with Leanne Williams. 

Anna received her BSc in cognitive neuroscience in 2018 at Brown University where she undertook coursework and training in statistics and experimental psychology. She joined PennLINC 2018, where main work focused on meta-analyses of neuroimaging studies of pain, with the aim of finding brain regions and networks that are consistently involved in the central mechanisms of pain processing. During her time in the lab, she wrote two first author papers: one on brain responses to pain in healthy volunteers (Xu et al., Neuroscience and Biobehavioral Reviews 2020), and one examining pain responses in patients with chronic pain (Xu et al., JAMA Network Open 2020).   She left the lab in Summer 2020 for the neuroscience PhD program at Stanford.

After completing his PhD in bioengineering, Dr. Azeez Adebimpe joined the lab as a post-doctoral fellow in 2018 and quickly became an abolutely essential member of the neuroinformatics and data science team; he transitioned to a being PennLINC's Senior Data Engineer in 2020.  In that role, he became the primary developer of major software packages including the eXtensible Connectivity Pipelines as well as ASLPrep -- which was published in Nature Methods in 2022. Beyond these major efforts, his expertise was essential for the success of several generations of trainees,  resulting in over 15 collaborative papers.  In 2022, he transitioned to an exciting new role as the Lead Machine Learning Engineer at Johnson & Johnson, where he now leads a growing data science team. 

Diego joined the lab in Fall 2017 as a Clinical Research Coordinator, where he was involved in data acquisition and management for several neuroimaging studies. After successfully competing for a NIMH Research Supplement to Promote Diversity, Diego transitioned to a role as a data analyst.  He currently is using longitudinal multi-modal neuroimaging to explore the functional brain network features underlying irritability in youth and adolescence. While in the lab, he contributed to two papers.  He is also planning on completing a project he led examining how behavioral inhibition is linked to functional network abnormalities in youth.  In Summer 2020, he transitioned to the neuroscience PhD program at Penn.

Hamsi  grew up in Columbus, Ohio, and later in Bangalore, India, where she got her bachelor's degree in biotechnology engineering. Though this degree taught her really fun things like how to operate a lathe and how a fermenter works, she soon discovered that neuroscience excited her a lot more. So she moved to Irvine, California, to get her PhD under the guidance of Dr. Craig Stark. In grad school, her thesis focused on using diffusion MRI to study aging and disease-related microstructural changes in gray matter. In her post-doc at Penn LINC, Hamsi focused on the development of advanced compressed-sensing diffusion spectrum imaging (Radhakrishnan et al., bioRxiv 2023).  She subsequently returned to her interest in aging and joined the Penn Alzheimer's Disease Research Center & the Penn FTD Center as a senior scientist.

Kayla grew up in Ontario, California. She earned her Bachelor’s of Science  in Psychobiology at UCLA. She was a key member of the lab from 2017-2019, where she worked on a longitudinal study of brain development relabed to irritability in youth.  She contributed to two published papers as a co-author.  Kayla is now pursuing her medical training at Robert Wood Johnson Medical School.  

Lauren Beard began working in the lab during her first year as an undergraduate at Penn.  She continued to work with Ted for the next five years, including a year after graduation as a data analyst.  Lauren worked on many projects including the ENIGMA consortium projects, and contributed as a co-author five of these publications.  Lauren is now a Ph.D. student in Sociology at the University of Chicago.

Marieta Pehlivanova received her Ph.D. in Psychology at Penn and was co-mentored by Ted and close collaborator Joseph Kable.   Among her other work, Marieta demonstrated that impulsive choice in adolescents is associated with thinner cortex, especially in regions important for reward-based decision making (Pehlivanova et al., JNeurosci 2018).  Marieta is now a Senior Research Scientist at the Division of Perceptual Studies at the University of Virginia School of Medicine.

Natalie was a clinical research coordinator for Ted and Dan Wolf for four years. During her time in the lab, she was responsible for a series of NIH-funded studies on how abnormalities in the brain's reward system are associated with mental illnesses such as schizophrenia, bipolar disorder, and depression. Through her hard work on these studies, she contributed to four publications.  Following her time in the lab, she completed the joint MD / MBA program at KCU. She is now a psychiatry resident at the Einstein Healthcare Network.  

Rastko Ciric was a data analyst in the lab for three years, where he was the primary person responsible for processing the multi-modal imaging data of the Philadelphia Neurodevelopmental Cohort. To accomplish this huge task, Rastko designed and built a new image processing pipeline system – the eXtensible Connectivity Pipelines. Rastko used this system to conduct a rigorous benchmarking analysis of 14 different denoising strategies to mitigate motion artifact in studies of functional connectivity; this paper was one of the top 3 most-cited papers in Neuroimage in 2017. Subsequently, he provided further details for these procedures in a dedicated protocol paper (Ciric et al., Nature Protocols 2018). In addition to these major projects which he lead, Rastko supported (and was co-author) on an additional 13 papers. He is now a Ph.D. candidate in Bioengineering at Stanford University, where he works with Russ Poldrack.

Shi Gu completed his Ph.D. in the lab of close collaborator Dani Bassett.  As a graduate student, he was incredibly productive, including the first application of network control theory to neuroimaging data (Gu et al., Nature Communications, 2015).  As he transitioned to a post-doc position in Ted's lab, he completed a study defining normative network development (Gu et al., PNAS, 2015).  Later, Shi used functional hypergraphs to examine development of brain connectivity (Gu et al., Human Brain Mapping, 2017).   Dr. Gu's post-doc ended when he was the youngest recipient ever of the won the hyper-competitive "1000 Talent's" mechanism in China, which allowed him to start his laboratory as a Professor in the University of Electronic Science and Technology of China in Chengdu.  Subsequently, he was recognized as one of Forbes China "30 Under 30".

Sophia jonied the lab from Wesleyan University, where she excelled in research and was capitan of the soccer team.  She spent three years in the lab, leading a longitudinal imaging study of executive dysfunction in youth. Additionally, she led a independent systematic review integarting evidence from fMRI studies of psychedelics; this was presented as a first author poster at the Society of Biological Psychiatry and is being prepared for publication.  She now pursuing her longstanding dreams of being a physician as a medical student at Jefferson.  

Dr. Zaixu Cui joined the lab in October 2017 as a postdoctoral fellow. Prior to joining the lab, he received his bachelor’s degree in computer science from Anhui University, and then received his Ph.D. degree in Cognitive Neuroscience from Beijing Normal University in China. During his time in the lab, he published two major first-author papers. First, using techniques from network control theory, he demonstrated that white matter networks mature to facilitate the activation of fronto-parietal regions critical for executive function (Cui et al., 2020, eLife). Furthermore, he demonstrated that person-specific functional networks are refined in development in youth and impact cognition (Cui et al., 2020, Neuron). Additionally, he contributed to another 10 collaborative papers in the lab. Following the successful completion of his postdoc training in 2021, Zaixu was recruited to start his own laboratory as faculty at the Chinese Institute for Brain Research in Beijing, China.

Angel Garcia de La Garza completed his undergraduate training in statistics at Penn, and was a data analyst in the lab for two years. He quickly grew to be an in-house statistical expert, developing particular expertise in analysis of longitudinal data with mixed models, and nonlinear developmental data with general additive models. To facilitate the application of these complex models to high-dimensional neuroimaging data, he developed an R package-- `voxel` -- which is available in CRAN. In addition to this, Angel contributed to and was co-author on an additional five papers from the lab. Angel graduated to join the Biostatistics program at Columbia University, where he earned his PhD.  He is now an Assistant Professor of Biostatistics at Albert Einstein College of Medicine.

Dr. Antonia Kaczkurkin completed her postdoctoral fellowship in the lab from 2015-2019. Prior to joining the lab, she received her Bachelor of Science degree in psychology from the University of Arizona, summa cum laude. She received her Master of Arts and Ph.D. degrees in clinical psychology from the University of Minnesota, where she was a National Science Foundation (NSF) Graduate Research Fellow.  Her research in the lab focused on using multi-modal neuroimaging and machine learning tools to understand dimensions of psychopathology across discrete categorical diagnoses.  She was incredibly productive, with three first-author papers in Biological Psychiatry, as well as first author papers in The American Journal of Psychiatry, Molecular Psychiatry, and Cerebral Cortex. While in the lab, she successfully competed for a NIMH Research Supplement to Promote Diversity, NARSAD Young Investigator Award, and a NIMH K99/R00 Pathway to Independence Award. She is now an Assistant Professor of Psychology at Vanderbilt University.

After undergraduate work at Washington University in St. Louis, Cedric embarked on the joint M.D.-Ph.D. program at Penn with the Neuroscience Graduate Group. His thesis work, co-advised by Dani Bassett, broadly focused on understanding heterogeneity of psychiatric disorders and brain connectivity by marrying big data in neuroimaging (Xia et al., 2018, Nature Communications) with machine learning tools (Xia et al., 2020, Human Brain Mapping). Most recently, his third first-author paper with the lab ventured into delineating individual differences using smartphone based digital phenotyping (Xia et al., 2021, under review). With a passion for breaking down complex stories with data visualization, Cedric closely collaborated on more than fifteen other projects in the lab as a co-author and contributed art work to the covers of Biological Psychiatry twice. His work was recognized by the Blavatnik Fellowship as well as multiple merit travel awards, including those from the American College of Neuropsychopharmacology, Society of Biological Psychiatry, and Organization on Human Brain Mapping. During his time at the lab, he also furthered international collaborations with exchanges at academic institutions in France and Germany (and met his future husband while at it.) Earning an M.D. and a Ph.D. in 2021, Dr. Xia is pressing ahead with his career adventure combining medicine, tech, and business. 

After undergraduate work at Cornell and a two year stint as an NIMH IRTA, Graham completed his PhD through the Neuroscience Graduate Group. Co-mentored by Dani Bassett, Graham's work sought to use techniques from network science to understand the developing brain. He was phenomenally successful. While in the lab, he wrote three first author papers. He demonstrated that during development structural brain networks become increasingly segregated (Baum et al., Current Biology 2017). Furthermore, in a methodological paper, he showed that motion artifact can systematically bias estimates of structural brain network connectivity (Baum et al., Neuoimage 2018). Finally, he delineated that coupling between structural and functional brain networks remodels in a hierarchy-dependent manner throughout adolescence (Baum et al., PNAS 2019). In addition to these important papers, he contributed to 12 other papers in the lab, and received an NIMH F31 award. 

Jake grew up r in Philadelphia, though his neuroscience trek took him elsewhere for the last ten years. Jake studied at Hampshire College, where he took a bunch of psychology, biology and statistics classes and called it "Neuroscience". After graduating, Jake worked for three years as a lab manager for Bill Jagust at University of California, Berkeley. The Jagust Lab used PET and other imaging techniques to study aging and Alzheimer's disease, and it was in Berkeley that that Jake began learning neuroimaging and python. Jake continued this work as a PhD student at McGill with Alan Evans, where his thesis focused on tau-PET imaging and disease progression modeling in Alzheimer's disease. Here, Jake also began perfecting his craft in in machine learning and multi-omics analyses. During his PhD, Jake developed many international collaborators and spent six months in Amsterdam, as well as time in London, Paris and Sweden. Jake joined the PennLINC in an effort to link development to vulnerability to neurodegenerative diseases in aging.  While in the lab he was incredibly productive and was awarded a NIA K99/R00, which he declined in order to take a tenure-track faculty position at the University of Lund in Sweden.

Kristin joined the lab as a clinical research coordinator in June 2018 after graduating from the University of Virginia.  In her four years at PennLINC, she quickly became totally indespensible, being promoted several times and ultimately leading all prospective brain imaging studies, including a large-scale longitudinal neuroimaging study mapping network development underlying executive dysfunction in adolescence. Additionally, she also led a project that deliniated robust links between activation of the executive system and neighborhood-level socioeconomic status (Murtha et al., Cerebral Cortex 2022).  Beyond this , she contributed as co-author to an additional six papers in the lab.  In summer 2022, she graduated from the lab and is now pursuing her Ph.D. in Clinical Psychology at Penn under the mentorship of Becky Waller.  

Ted was very lucky that his first clinical research coordinator was Lillie Vandekar.  Starting in 2011, she helped him get his lab started, and ran an imaging study examining reward system deficits across psychiatric disorders.  She contributed and was a co-author on three papers during her three years in the lab.  She left the lab to pursue doctoral training in clinical psychology; she is now the founder and owner of Nashville Psychotherapy, LLC.

Max spent two years in the lab as a Senior Research Scientist after completing his post-doc with our close collaborator Dani Bassett. While in the lab, Max made huge contributions to the neuroinformatics team, including critical work on XCP-D, ASLPrep, and developing PennLINC Kit. Beyond informatics, he was central to many analytic projects including  work on BPD-spectrum symptoms.  Moreover he was central to many collaborations and mentored nearly every member of the team.  In total, he contributed to 5 papers (with more in process).  

Nick completed a research rotation in the lab while he was the Chief Resident at the Center for Addiction and Mental Health in Toronto, where he is mentored by Aristotle Voineskos.  He started a new collaboration between the labs, applying machine learning techniques to a clinical trial that integrated neuroimaging. This work was published in Neuropsychopharmacology (Neufeld et al., 2020).  Following this aextremely succesful rotation, he returned to Toronto, and was promoted to a faculty position. In 2020, he was awarded a NARSAD Young Investigator award.

Robert earned a bachelor’s degree in Psychology at the University of Colorado Denver, where he graduated summa cum laude before joining the lab through the Post-Baccalaureate Research Education Program. Despite coming into the lab with limited technical abilities, he quickly learned to manage, process, and analyze the data from a longitudinal multimodal study. Through his quick learning and hard-work, he lead a first-author project that revealed accelerated cortical thinning within affective brain networks is associated with symptoms of irritability in youth (Jirsaraie et al., Neuropsychopharmacology 2019). He is currently a PhD student in computational and data science at Washington University in St. Louis, where he is mentored by Deanna Barch and Aris Sotiras.

After Simon Vandekar completed his undergraduate work at Penn State, he joined the lab as a data analyst. While also teaching himself advanced statistics on the side, he became an incredibly productive member of the lab. By the time he left three years later to join the lab of close collaborator Taki Shinohara as a graduate student, he had contributed to seven publications. Notably, he lead a study that described how cortical thinning is governed in part by the sulcal topology of the cortex (Vandekar et al., J Neurosci 2015). Simon graduated with his Ph.D. in Biostatistics in 2018, and is now an Assistant Professor in Biostatistics at Vanderbilt University where he leads a highly-producive, NIH-funded imaging statistics lab.

Tinashe joined the lab after completing his bachelors and masters degree at Drexel University, and immediately became an indepensible member of the neuroinformatics team.  He worked on a myriad of projects in his four years at the lab, including the massive Reproducible Brain Charts Project, the Flywheel imaging database,  a cross-disorder project on abnormalities in reward system responses, and a new study on mobile phenomics.  In addition to being a total R guru, he was the primary developer of FlywheelTools, which was published as a first-author manuscript in Frontiers in Neuroinformatics; he also contributed to six additional published papers as a co-author.   He left PennLINC to pursue his PhD in personalized health informatics at Northeastern University.