Faculty Mentors

The Training in Research Undergraduate Experience through the Rutgers Addiction Research Center (TRUE RARC) Scholar Program offers undergraduate students the opportunity to engage in research experiences within participating Rutgers faculty labs. Please find a list of participating Principal Investigators (PIs) and descriptions of their research and opportunities within their labs below.

The Barker Lab applies cutting edge technologies to interrogate neural circuits involved in psychiatric disorders. Our goal is to better understand the maladaptive processes that affect the brains of individuals afflicted with drug addiction and co-morbid mental disorders with the hope of advancing more effective treatment strategies. The lab applies anatomical techniques to define the types of neurons that comprise specific brain pathways, calcium imaging and electrophysiological techniques to record the types of information encoded by these circuits, and optogenetic or chemogenetic technologies to manipulate circuit-level activity. Students will learn research from every angle, including the project background, understanding and performing key methods such as animal behavior, learning to organize, analyze and graph data, and finally learning to think critically about their results.

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The REACH Alliance research lab is comprised of a diverse group of researchers, students, community members, mental health service providers, and individuals with lived experiences who are dedicated to understanding and addressing mental health inequities, particularly for racial and ethnic minoritized populations. Students will be able to contribute to ongoing research studies in the following ways: Contacting/responding to participants; Distributing compensation; Attending data collection events; Entering survey data; Assisting with IRB proposals/updates; Designing and distributing recruitment materials; Participating in weekly lab meetings; Co-authoring presentations and publications and developing independent projects; and Developing content for the lab’s social media and website.

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Dr. Bhanji is a faculty member within the Delgado Lab whose research uses neuroimaging, behavioral decision–making, and emotional assessment methods to understand neural systems underlying decision making and emotional experience in humans with a history of substance use. Students will have an opportunity to apply machine learning classification techniques to neuroimaging data collected from a sample of individuals recovering from opioid use disorder, as well as a sample of tobacco cigarette smokers. Students will learn to plan, carry out, validate, and document analyses. Training will include fundamentals of fMRI to measure brain responses, use of python and R libraries for time series classification, and literature review of research on brain systems for incentive processing that are relevant to addiction. Additionally students will learn to present their work to a scientific audience. 

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Our lab studies the tremendous experience-dependent neuroplasticity of the adult brain in normative (learning experiences) and pathological (addiction-related experiences) that explain changes in behavior that reflect memory. As a “memory lab”, we consider the addiction process in the view of an aberrant memory process that takes the rein of behavior to lead individuals into bouts of craving, withdrawal and relapse. We investigate molecules and genes in the wet lab, neurophysiology in our electrophysiology lab, and behavior using conditioned tasks in rats to model and design ways to intervene in what we hope would apply to human addiction and related behaviors. Students will have the opportunity to learn experimental (wet lab) procedures, behavioral training in rats, some neuropharmacology, and data analysis; couched in literature review.

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We use mouse models to understand the neural circuitry underlying appetitive behaviors including drug use and compulsive food intake. Students will be responsible for conducting behavioral, physiological, and molecular experiments with mice, collect and analyze data, present data. Students must be comfortable with handling and experimentation with mice.

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My research focuses on determining biological mechanisms that contribute to the expression and development of externalizing behavior in adolescence. I am particularly interested in understanding the biological, environmental, and developmental influences on the emergence, persistence, and desistance of antisocial behavior and substance use in adolescence and early adulthood. Towards this end, I incorporate a broad range of methods to better understand this phenotypic expression. I am also trained as a clinical psychologist and am interested in translating these mechanistic findings into clinically relevant measures or interventions for at-risk youth. Students will contribute to data collection, data cleaning, basic data analysis, and literature reviews.

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Research projects use digital health methods (e.g., data collected using smartphone, wearable device like Fitibit) to understand how “in the moment” feelings and behaviors captured by daily phone surveys and wearables (e.g., activity level, sleep) can be used to predict and better manage mental and physical health. A student has the opportunity to be involved in literature review; after training and with on-going supervision: participant recruitment (e.g., describing the study to people who express initial interest in the project prior to consent), updating screening and recruitment numbers using R-script, assisting with data collection (e.g., monitoring participant completion of daily data), participating in preliminary analyses (depending on skill level in data analyses). Student with interest and experience / familiarity with smartphones (Android, iOS), apps, and wearables preferred.

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My work focuses on the design, implementation and evaluation of novel interventions in the Emergency Department. Specifically, our group conducts biomedical clinical trials in the Emergency Department and other settings with a focus on pharmacotherapies. The selected student will have the opportunity to assist our project managers and research associates with screening and data collection for ongoing clinical trials in the Emergency Department.

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The Translational Psychiatric Genomics (TPG) Lab researches how genetic and environmental influences contribute to the development of patterns of substance use and related behaviors, such as childhood conduct problems and depression, and how we can use that information to inform prevention and intervention. Lab members are involved in a wide variety of research projects including gene identification efforts, twins studies, longitudinal studies, and randomized controlled trials. Undergraduate students will have the opportunity to contribute to a variety of projects assisting with activities such as conducting literature reviews, data cleaning and analysis, and contributing to manuscripts and presentations.

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The Holly Lab studies the neural basis of decision making, and how these neural circuits and behaviors are disrupted by prior stress and models of psychiatric diseases (including substance use disorders) in mice. We use a range of cutting-edge systems neuroscience approaches to record from and manipulate the brain while mice are engaged in decision-making tasks (such as fiber photometry, in vivo electrophysiology, and optogenetics), as well wet-lab work with brain tissue (such as recording dopamine in brain slices, staining and imaging specific cell-types) and computational modeling of behavior. Students will contribute to projects working with mice doing behavioral experiments, as well as other projects with no live mouse work, including immunohistochemical analysis of brain tissue and computational modeling of decision-making behavior.

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Projects in the Addiction & Decision Neuroscience Lab use brain imaging, computational modeling, and dense longitudinal phenotyping methods to understand how people make decisions, how decision-making is shaped by our motivational states and context, and the mechanisms that drive addictive behavior at the person level. Ongoing studies focus on these questions in the specific context of opioid and alcohol use disorders. Dr. Konova also co-directs the Rutgers-Princeton Center for Cognitive Computational Neuro-Psychiatry, a center dedicated to applying similar methods transdiagnostically, across substance use and other psychiatric disorders. Students can contribute to our research in multiple ways: participant recruitment, assisting with participant assessment and conducting experimental procedures, literature review, data organization, and data analysis and presentation.

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We focus on daily diary and sleep watch measurement to better understand daily experiences of social interactions, discrimination, mental health, physical health, and sleep. Our studies use sleep watches (actigraphy) and online daily diary surveys (i.e., “ecological momentary assessment” or EMA), and our statistical modeling includes multilevel modeling in SPSS and/or MPlus. Our current studies focus on sexual and gender minority (LGBTQ+) populations, with a focus on minority stress and coping. Students will contribute to data analysis, data cleaning, and literature reviews.

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We have a large range of projects, from GIS mapping and informatics to AI/Machine learning models and big data analysis, to developing and testing clinical tools, to reducing gambling-related harm among college athletics. The Center for Gambling Studies provides a “boutique” opportunity to students to work across a range of projects, focusing on skill acquisition that begins with learning how to find and synthesize literature to data table construction and basic measurement and report review. Students will begin with a generalist exposure and then be mentored by faculty and staff across areas based on their interests and level of skill-development.

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My research explores how digital technology tools can be used to improve assessment and treatment for substance use problems and co-occurring mental health distress. Ongoing projects include 1) a randomized clinical trial examining a data-driven approach to counseling for co-occurring anxiety, traumatic stress, and problematic drinking, 2) an observational study examining daily processes that facilitate treatment and recovery in a residential treatment center, and 3) meta-science projects examining the utility of experience sampling methods for clinical research and practice. Students will contribute to data cleaning and analysis, survey/materials design and programming, qualitative interviewing and coding, and literature review and extraction.

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The mission of the GENA program is to understand how genetic and environmental factors contribute to the onset, persistence, and remission of alcohol and other substance use disorders. Our primary area of focus is on how alcohol and other substance use affects and is affected by close relationships with parents, peers, and romantic partners across the lifespan. We take a genetically informed perspective in our work, with a particular interest in understanding the social/environmental mechanisms through which genetic risk for alcohol use disorder and related problems are transmitted in families, as well as gene-environment interplay that may render some individuals more susceptible to social/environmental risks. Undergraduate research assistants in the GENA program will have the opportunity to be involved in a variety of potential research activities such as literature reviews, data analysis, and the preparation of manuscripts and scientific presentations.

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My lab is broadly interested in motivation and reward learning, and how these processes become disordered in addiction. We are particularly interested in what drives sensation seeking and how it contributes to behavioral addictions. My lab investigates mouse behavior using a variety of approaches, including operant conditioning and home cage video analysis. I am seeking a student who can assist with data analysis of mouse movement behavior using pose-estimation models (e.g., DeepLabCut). This task would require strong computational skills.

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Dr. Sizemore’s research focuses on the development of digital health interventions to address mental health and substance use in marginalized populations, with a focus on sexual and gender minorities. Specifically, her NIH-funded research takes an integrative health approach to intervention development, using positive psychology and mindfulness research to inform the development of evidence-based interventions. Current projects include (1) a study seeking to adapt and test an app-based positive psychological program, which uses a just-in-time adaptive intervention (JITAI) design, and (2) a secondary data analysis of a large nationwide cohort study that aimed to track HIV seroconversion over several years. Students may be involved in transcription of qualitative interviews, qualitative coding of interview/focus group data, quantitative data analysis, and literature review for manuscript development. Students will also have the opportunity to use secondary data to prepare and submit abstracts for conference presentation.

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My lab employs frameworks of behavioral economics and applied behavioral science to understand patterns of decision making in addiction. Current research in the lab involves behavioral assessments of alcohol reward and the impact of alternatives on the rewarding value of alcohol, understanding substance use patterns in neurodiverse populations, and methodological refinement of behavioral economic frameworks of substance use. Research in the lab is conducted with participants both virtually and in-person in our laboratory in Piscataway via behavioral surveys and tasks. Students will be expected to complete literature reviews, assist in data collection during in-person research studies in the lab, and analyze data where applicable. Students will have the opportunity to collaborate on posters and presentations that are developed from lab research, if interested.

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We are interested in the transdiagnostic features of psychopathology. We use a combination of experience sampling, and neuroimaging. Current studies focus on relations between the structure of psychopathology and the ability to resist temptations, and brain changes in chronic alcohol use disorder. Student tasks will range from data management and quality control, running subjects through study procedures, to data analysis, with roles depending upon student interest and existing computer skills. Students with some computer programming experience are preferred.

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