Lili Zheng is an Assistant Professor in the Department of Statistics at the University of Illinois. Her research focuses on statistical methodology, machine learning, and high-dimensional data analysis with applications in neuroscience and network science. Key areas of expertise include graphical models, stochastic processes, and algorithmic optimization. She collaborates extensively on projects involving functional connectivity analysis, neuronal data imputation, and interpretable machine learning frameworks. Her work bridges statistical theory and computational practice, addressing challenges in model inference, feature importance assessment, and low-rank tensor completion. Notable contributions include techniques for distribution-free inference, spectral clustering in patchwork learning, and Gaussian process parameter estimation using mini-batch stochastic gradient descent. Dr. Zheng's research emphasizes interdisciplinary applications, particularly in neuroimaging (calcium imaging, functional connectivity) and multi-modal data integration. She actively explores statistical challenges in big data contexts, emphasizing robust methodologies for real-world datasets.
Dr. Merry Mani is an Associate Professor in Radiology and Imaging Sciences and Biomedical Engineering, specializing in biomedical imaging and signal processing. Her work focuses on advancing MRI-based imaging technologies to study neurological disorders such as Alzheimer's, Autism, and Epilepsy. She holds a Ph.D. in Electrical and Computer Engineering from the University of Rochester (2014) and completed a postdoctoral fellowship at the University of Iowa School of Medicine (2018). Her research combines biophysical modeling with machine learning to explore brain microstructures. Key achievements include the NNARSAD Young Investigator Grant and NIH-funded projects like 'Fast Multi-dimensional Diffusion MRI with Sparse Sampling'. Her lab develops cutting-edge reconstruction methods like qModeL and MUSSELS, prioritizing high spatio-temporal resolution imaging. Major contributions span diffusion MRI acquisition, model-based deep learning, and clinical applications in neurodegenerative diseases. Notable grants include NIH R01EB031169 for Alzheimer’s neurodegeneration studies and projects on rTMS for depression. Her work bridges imaging innovation with clinical impact, aiming to improve diagnosis and treatment through advanced imaging biomarkers.
Istvan Mody is a Professor at the University of California, Los Angeles (UCLA) with appointments in the Department of Neurology and Department of Physiology . His research focuses on synaptic signaling in health and disease, including mechanisms of GABAergic transmission, calcium homeostasis, and their roles in neurological disorders such as epilepsy, Alzheimer's disease, Huntington's disease, stress, alcoholism, and postpartum depression. He utilizes advanced techniques like patch-clamp electrophysiology, neuroanatomical and immunohistochemical methods, and molecular biology in animal models and human brain tissue . Research Interests: Dr. Mody investigates the physiology, pharmacology, and pathology of synaptic transmission and extrasynaptic receptor activation , with a particular emphasis on GABA(A) receptors and their subunit-specific modulation. His work explores how disruptions in excitation-inhibition balance contribute to neurological diseases, including mechanisms of tonic inhibition , calcium signaling , and neurosteroid interactions . He also studies the effects of chronic stress and hormonal fluctuations on neural excitability and behavior. Publications Trends: Recent studies highlight his work on gamma oscillations in Alzheimer's models, microglial dynamics , and rehabilitation strategies for stroke. His lab develops optical tools like dqGEVI for neuronal activity monitoring and investigates human brain organoids to model network dysfunction in epilepsy and intellectual disability. Laboratory Location: 635 Charles Young Dr S, Los Angeles, CA 90095, United States.
John Serences is a Professor in the Department of Psychology at the University of California, San Diego (UCSD). He leads the Perception and Cognition Lab, which participates in the Neuroscience Graduate Program. His research focuses on how behavioral goals and attention influence perception, memory, and decision-making, employing techniques like psychophysics, computational modeling, EEG, and fMRI. Key projects explore serial dependence, neural adaptation in visual cortex, and the interplay between sensory processing and mnemonic storage. Recent work highlights mechanisms reconciling repulsive neuronal adaptation with attractive behavioral biases. Affiliations: Department of Psychology, UCSD; Neuroscience Graduate Program. Research Themes: Visual perception, working memory, decision-making, neuroimaging. His lab investigates neural dynamics underlying cognitive processes, with particular emphasis on how attentional modulations and stimulus history shape neural representations. Notable contributions include studies on adaptive sensory coding and the role of top-down signals in perceptual stability.
Matthew W. Buczynski is an Assistant Professor at the School of Neuroscience , part of the College of Science at Virginia Tech . Holding a Ph.D. in Biochemistry from the University of California San Diego (2008) and postdoctoral training at The Scripps Research Institute (2009-2016), he joined Virginia Tech in August 2016 after completing his postdoctoral fellowship. Education: B.S. in Chemistry, University of Michigan , 2001 Ph.D. in Biochemistry, University of California San Diego , 2008 Postdoctoral Training, The Scripps Research Institute , 2009-2016 Dr. Buczynski’s research program focuses on identifying novel druggable targets for addiction and neurological disorders through mass spectrometry and behavioral pharmacology . His work integrates chemical biology , molecular pharmacology , and in vivo microdialysis to study molecular changes in the brain during chronic drug exposure. Key areas include nicotine dependence , ethanol withdrawal , and cross-talk between pain and addiction mechanisms. His recent publications highlight endocannabinoid system modulation , TRPV1/TRPA1 receptor activation in pain, and diacylglycerol lipase (DAGL) mechanisms in nicotine withdrawal. He employs both self-administration and forced exposure models to validate therapeutic targets. Prospective students can contact him directly through his lab’s website .
Jerome Engel, M.D., Ph.D. is a Professor at the Jane and Terry Semel Institute for Neuroscience and Human Behavior , University of California, Los Angeles (UCLA). He serves as Director of the Epilepsy Telemetry Unit within the Seizure Disorder Center and is a member of the Brain Research Institute and the Neuroscience GPB Home Area. His work spans neurology, psychiatry, and biomedical research. Research Focus: Epilepsy, epileptogenesis, high-frequency oscillations (HFOs), neuroimaging, surgical interventions, and biomarker development. Key Contributions: Pioneering studies on fast ripples as biomarkers, network-based surgical outcome prediction, and advanced HFO detection algorithms. Publications (15 most recent) address topics such as kainic acid models of epileptogenesis, thalamic sleep spindles in pediatric epilepsy, self-supervised HFO analysis, and graph theoretical measures for surgical planning. His work frequently employs medRxiv and Epilepsia as platforms for translational findings. Contact: engel@ucla.edu
Hang Lu is an Associate Professor in the Department of Communication and Media at the University of Michigan's College of Literature, Science, and the Arts. He specializes in science, health, environmental, and risk communication (ComSHER), with a focus on media psychology. His research explores audience responses to media messages about sensitive topics and strategies to enhance message effectiveness. Lu holds a Ph.D. in Communication from Cornell University (2018), along with advanced degrees from Cornell, Marquette University, and Central South University in China. He directs the Media and Risk (MaR) Lab and previously served as a postdoctoral fellow at the Annenberg Public Policy Center. His research spans four main areas: 1) emotion dynamics in media responses, 2) predictors of information behaviors, 3) media effects on stigmatization, and 4) AI applications in sensitive domains. He has published in journals like Journal of Communication , Risk Analysis , and Public Understanding of Science , earning multiple top paper awards. As Vice Chair of the Environmental Communication Division at the International Communication Association, Lu contributes to interdisciplinary dialogue. His work addresses critical societal issues such as climate change communication, vaccination hesitancy, and emerging technology ethics.
Robert E. (Rob) Kass is the Maurice Falk University Professor of Statistics and Computational Neuroscience at Carnegie Mellon University, holding joint appointments in the Department of Statistics & Data Science, Machine Learning Department, and Neuroscience Institute. His research spans Bayesian statistics, neural data analysis, and computational neuroscience. Kass earned a B.A. in Mathematics from Antioch College, a Ph.D. in Statistics from the University of Chicago, and has been at CMU since 1981. He has served as Department Head of Statistics (1995–2004) and Interim Co-Director of the CNBC (2015–2018). His work focuses on statistical methods for neuroscience, particularly analyzing spike train data and identifying cross-brain interactions. Notable contributions include co-authoring Analysis of Neural Data and foundational articles on Bayesian inference. Kass has received prestigious awards such as the National Academy of Sciences membership and COPSS Distinguished Achievement Award. Research interests include computational neuroscience, statistical modeling of neural systems, and interdisciplinary education. He has advised numerous students and co-organized major workshops like the Statistical Analysis of Neuronal Data series. Kass’s work emphasizes the interplay between statistical rigor and scientific insight, bridging theoretical and applied domains. Education: B.A. in Mathematics, Antioch College Ph.D. in Statistics, University of Chicago Postdoctoral Fellow, Princeton University Scientific contributions include advancements in spike train analysis, Bayesian model assessment, and statistical methods for brain connectivity. His work on neural synchrony and population coding has influenced both theoretical and applied neuroscience.
Kristina Schoonjans is an Associate Professor at EPFL’s School of Life Sciences, where she leads the Laboratory of Metabolic Signaling (UPSCHOONJANS). Her research focuses on the molecular mechanisms of bile acid signaling, nutrient sensing, and intermediary metabolism, particularly in the context of metabolic disorders such as obesity, fatty liver disease, and cancer. She investigates how the liver-gut-brain axis integrates metabolic signals through nuclear receptors and mitochondrial dynamics. Her research interests include: Bile acid signaling and its role as a hormonal regulator Nutrient and metabolite sensing in energy homeostasis Intermediary metabolism and metabolic disorders Role of nuclear receptors (e.g., TGR5, LRH-1) in liver, gut, and adipose tissue Mitochondrial dynamics and fission in metabolic regulation Organoid models for studying liver and intestinal metabolism Systems genetics using BXD mouse populations The most recent articles highlight a strong focus on bile acid signaling, particularly through TGR5 and LRH-1, in regulating metabolic health. Themes include the conversion of white fat to beige fat (beiging), hepatic tumorigenesis, mitochondrial fission, and the use of organoid and genetically engineered mouse models. There is a consistent emphasis on translational applications for obesity, fatty liver disease, and cancer. Scientific honors include: Windaus Prize from the Dr. Falk Foundation (2010, shared with Johan Auwerx) for the discovery of the signaling/endocrine function of bile acids Prof. Schoonjans actively supervises PhD students and has advised numerous doctoral candidates who have since completed their theses. Her lab is supported by multiple grants from Swiss and international funding agencies, including the Swiss National Science Foundation, EPFL, CONACYT, and the Foundation for Health and Education. She teaches in several doctoral programs at EPFL, including Life Sciences Engineering, and contributes to education through the SSV and EDBB/EDCB/EDMS-ENS programs. The Schoonjans Lab brings together scientists, doctoral assistants, and technicians working on projects related to metabolic signaling. The team uses advanced techniques such as genetically modified mouse models, organoid cultures, and multi-omics (metabolomics, proteomics, transcriptomics) to study the liver-gut and brain-liver axes. The lab has a strong track record of high-impact publications and collaborations with institutions worldwide.
Markus Heilig is a Professor of Psychiatry and Head of the Department of Biomedical and Clinical Sciences (BKV) at Linköping University. He serves as Director of the Center for Social and Affective Neuroscience (CSAN), integrating basic and clinical neuroscience to address addictive and affective disorders. His work bridges neuropharmacology, molecular psychiatry, and clinical trials. Linköping University (Current) Center for Social and Affective Neuroscience (CSAN) (Director) Wallenberg Center for Molecular Medicine (Collaborator) His research focuses on alcohol dependence mechanisms, stress-neurotransmitter interactions (e.g., CRF, substance P, endocannabinoids), and personalized medicine approaches. Using animal models and human neuroimaging (fMRI), his lab explores epigenetic changes in frontal lobe and amygdala neurons that drive compulsive alcohol use. Recent publications highlight his work on endocannabinoid modulation for PTSD treatment, neural correlates of reward choices, and pharmacological interventions targeting GABA and opioid receptors. His studies often combine brain imaging, behavioral analysis, and pharmacology. Scientific awards include the 2019 Wallenberg Clinical Scholar grant and 2017 CAN/Nordic Drugs prizes. Heilig's research is supported by Vetenskapsrådet (SEK 57 million center funding) and international donations like the Andrew J. Bock Memorial Fund.
Prof. Ilse Dewachter is the head of the Biomed Neuroscience research group at Hasselt University (UHasselt), specializing in Alzheimer’s therapy and prevention for over 25 years. Her work focuses on multi-targeted therapies targeting tau, inflammation, and ApoE, alongside pioneering research into disease prevention via blood-based biomarkers. Recent studies explore a protective APOE3ch mutation that halted Alzheimer’s progression in a patient, offering hope for new treatments. Research Interests: - Alzheimer’s disease mechanisms (Abeta, tau, inflammation) - Multi-target therapies and biomarker development - Neurodegenerative disease prevention strategies - Genetic mutations impacting disease progression Articles Overview: Her most recent work (2025-2022) addresses neuroinflammation, tau propagation models, and AI-driven neuroimaging. Key themes include APOE genetics, blood-brain barrier dynamics, and exercise impacts on cognition. Funding & Grants: Current projects require significant investment for advanced biomarker equipment and clinical trials. A notable €300,000 grant funded research on brain lipid metabolism’s role in Alzheimer’s. Labs & Teams: Leads the BIOMED Neuroscience group at UHasselt, collaborating internationally on preclinical models and drug development.
Aaditya Rangan is an Associate Professor of Mathematics at the Courant Institute of Mathematical Sciences, New York University. He holds a Ph.D. from UC Berkeley (2003) and a B.A. from Dartmouth College (1999). His research focuses on applying numerical analysis and scientific computing to biological systems, including neuronal network dynamics in the insect olfactory system and mammalian visual cortex. He also develops computational tools for genomic data analysis, particularly biclustering methods for gene expression and SNP datasets. Rangan currently directs NYU's master's program in mathematics. Key contributions include models of synaptic depression in neural systems and algorithms for cryo-EM data processing. His work is published in journals like the Journal of Computational Neuroscience and PLoS Computational Biology , and his software tools are available on GitHub.
Bérénice Benayoun, PhD is an Associate Professor at the USC Leonard Davis School of Gerontology , with secondary appointments in the Department of Molecular and Computational Biology (USC Dornsife College of Letters, Arts and Sciences) and the USC Norris Comprehensive Cancer Center . Her research bridges aging biology , epigenetics , and sex differences using vertebrate models like the African turquoise killifish and machine learning . Education : École Normale Supérieure (BSc, MSc), Paris Diderot-Paris 7 University (PhD in Genetics and Cell Biology) Her lab investigates epigenome and transcriptome remodeling during aging , focusing on how biological sex influences these processes. Key themes include inflamm-aging , genomic instability , and immune senescence , with applications in neurodegeneration and reproductive longevity . Recent publications highlight sex-dimorphic gene regulation in neutrophils , macrophages , and brain aging , alongside novel insights into transposable elements and MOTS-c mitochondrial signaling . She pioneers the use of single-cell transcriptomics and multi-omics in aging research. Scientific awards include: 2024 Vincent Cristofalo Rising Star in Aging Research Award 2023 AGHE Rising Star Early Career Faculty Award 2023 USC Mentoring Award 2023 Rising Star in Reproductive Biology 2021 Nathan Shock New Investigator Award 2019 Rosalind Franklin Young Investigator Award Her editorial roles include Geroscience , Translational Medicine of Aging , and eLife . She mentors students across PhD programs in Biology of Aging , Neuroscience , and Molecular Medicine , as well as Master's and undergraduate trainees.
Dr. Rodolfo J. Flores serves as an Assistant Professor in the Department of Psychology within the College of Liberal Arts at the University of Texas at El Paso (UTEP). His primary research investigates neuromodulator function in the prefrontal cortex, with emphasis on acetylcholine and dynorphin systems during motivational conflict, stress responses, and addiction pathways. He employs advanced optogenetic and biosensor technologies to dissect neural circuitry underlying psychiatric conditions. Dr. Flores earned his Ph.D. in Social Cognitive and Neuroscience from UTEP in 2019, followed by postdoctoral training at the National Institute of Mental Health (NIMH). His work bridges molecular neuroscience with behavioral outcomes, focusing on how stress and substance exposure alter prefrontal cortical function. His research portfolio demonstrates consistent high-impact publication in top neuroscience journals including Nature Neuroscience , Neuron , and Psychoneuroendocrinology . Current work examines opioid neuropeptide dynamics, nicotine-alcohol interactions, and sex-specific hormonal influences on addiction behaviors. Methodologically, he specializes in genetically encoded biosensors and circuit-level manipulations to study threat processing and reward pathways. Dr. Flores teaches graduate and undergraduate courses including PSYC 4341 (Motivation & Emotion), thesis/dissertation supervision (PSYC 5395/6395), and research applications courses. His lab actively trains students through undergraduate research (RSRC 4033) and independent study opportunities (PSYC 4352).
Chen Ran, PhD, is an Assistant Professor in the Department of Neuroscience at Scripps Research in San Diego. His laboratory focuses on understanding how the brain processes internal sensory signals from visceral organs, such as hunger, satiety, nausea, and visceral pain. Using advanced techniques like in vivo two-photon calcium imaging, optogenetics, and circuit tracing, his team maps the functional architecture of brainstem circuits responsible for interoceptive processing. Key contributions include the discovery of a 'visceral homunculus' in the brainstem and the development of novel calcium indicators for high-resolution neuronal activity tracking. Education : PhD in Biology, Stanford University (2017) Bachelor of Science in Biology, Peking University (2011) Research Interests : Dr. Ran’s work integrates experimental and analytical approaches to decode how visceral stimuli are transduced into conscious sensations. Current projects investigate the coding logic of mechanical, chemical, and thermal signals from internal organs, with implications for developing therapies for obesity, diabetes, visceral pain, and eating disorders. The lab employs cutting-edge tools to visualize and manipulate neural circuits in awake behaving mice, linking circuit-level activity to physiological states. Awards & Honors : NARSAD Young Investigator Award (2022) NIH K01 Career Development Award (2023) Simons Collaboration on the Global Brain Award (2022) Harvard Brain Science Initiative Award (2021) Grants & Funding : Supported by NIH, Simons Foundation, and private philanthropy, his research bridges basic science and translational medicine. Current grants focus on brainstem circuit mapping and developing therapeutic targets for interoceptive disorders. Labs & Affiliations : Dr. Ran leads an interdisciplinary team at Scripps Research’s Neuroscience Department, collaborating with engineers, geneticists, and clinicians to advance interoceptive neuroscience.
