Affiliates

Mike addresses the influences of managerial and stakeholder cognition on corporate social performance, reputation, and financial performance. 

Joanne Ciulla studies the ethics of leaders and leadership, and she also writes on business ethics and the philosophy of work.

The Institute for Ethical Leadership

Patrick works at the intersection of machine learning and human learning, using probabilistic models and tools from pure mathematics.

Why deviance arises in business settings, how to evaluate it, and how to deter destructive deviance while promoting constructive deviance.

Trying to understand the cellular and synaptic substrates underlying innocuous touch perception by elucidating the functional organization of sensory neurons in mouse hairy skin and uncovering the neural codes of touch perception in the spinal cord dorsal horn.

Molecular mechanisms underlying sensory and cognitive function in mouse models of human diseases. The lab is interested in understanding how mutations in chromatin remodeling proteins results in hyperactivity and circling behavior in mutant mice. Identifying transcriptome changes in affected neurons by deep sequencing will help us understand how the activity and development of these neurons have been altered. Our goal is to bridge the molecular changes in neurons to the abnormal behavior observed in these mouse models.

Sensory processing, decision-making, and neural plasticity in mice. Record and manipulate specific neurons and neural circuits as mice perform learned tactile behaviors to understand sensory-guided decision-making from the synaptic to the network levels. We are also interested in how brain injury and neurological disorders impact neuronal activity and behavior.

Our lab models human neurodevelopmental disorders in mouse with a particular focus on Tourette Syndrome (TS). Despite the prevalence of TS in the general population (~1/100 individuals), the underlying pathophysiology is poorly understood. We are currently using CRISPR-based approaches to generate mouse models that harbor recently discovered human point mutations found in sporadic forms of TS. With these disease mouse models, we are investigating how circuit development and function in the brain are perturbed by the human mutations using a combination of mouse genetics, circuit labeling techniques, optogenetics, electrophysiology, and mouse behavior. Additionally, the mouse models will provide powerful tools for drug screening approaches that can inform complementary studies with human iPSC lines.

Our lab is interested in the molecular mechanisms regulating dendritic spine morphogenesis and synaptic plasticity. Dendritic spines are small, actin-rich protrusions that receive most of the excitatory synaptic inputs in the brain.

Machine learning, robotics, planning and learning in partially observable domains, reinforcement learning.

Aims to develop agent-centric models for simulating crowd dynamics that challenge foundational assumptions in crowd modeling, while providing solutions that are validated using comparisons to real data, and virtual reality experiments. These solutions can be used to optimize the behavioral dynamics of real crowds and model the relationships between crowd flow and environment features, with applications in predictive analytics and crowd management, and environment layout design. His other research interests include real-time multi-agent planning, character animation for autonomous virtual humans, and digital storytelling.

Image interpretation using planning and learning techniques; methods of theory formation for classification, configuration, planning and design problems with biomedical applications.

American Sign Language and Gesture recognition from video, human identification and intent recognition from video, human computer interaction, shape and motion representation for recognition.

I develop computational models to learn generalizable and human-readable representations from unlabeled data, with a focus on natural language processing. To this end, I rely on mathematical frameworks such as Information theory: a representation is good if it transmits most information. Linear algebra: a representation is good if it lies in an optimal subspace. I am also interested in applications of learned representations to practical problems such as entity linking. I am not a theoretician by trade, but I enjoy working with theoreticians to study topics relevant to representation learning such as estimating mutual information.

Joel Finkelstein is a Post-Doctoral Fellow at the Madison Program for Ideas and Institutions at Princeton University and the director of the Network Contagion Research Institute, which deploys machine learning tools to expose the growing tide of hate and extremism on social media

Interested in Decision Theory, Game Theory and Neuroeconomics.

Experimental Economics, Decision and Game Theory, Uncertainty and Information Economics

Lauren is a specialist in interdisciplinary approaches to literature and culture, especially the long nineteenth century. As chair of the MLA's History and Literature forum she has organized a panel devoted to "Literatures of Artificial Intelligence". Her current research describes the advent of data-driven machine learning in the invention of Sherlock Holmes.

Behavior neuroscience and genetics: with a focus on the 'nature-nurture' theme of genetics and cognitive behavior. Research areas include the genetics of compulsive behaviors (such as alcoholism and drug addiction) and neuro-sensory disorders (such as diabetic neuropathy and neuropathic pain). Techniques utilized include molecular genetics, animal behavior models, and machine learning algorithms with statistics/bioinformatics models for neuro-behavior pattern analysis.

Philosophy and psychopathology (especially disorders of self); phenomenological philosophy; Wittgenstein; philosophical aspects of psychoanalysis.

Clinical Counseling Psychology

Word sense disambiguation and lexical semantics; morphology; multiword expressions; applications of natural language processing to education and information retrieval.

Theoretical and comparative syntax of natural languages focusing on models of parameterization for deriving grammars from universal principles.

My research focuses on thoughts and utterances that don’t fit standard propositional models. I am especially interested in metaphor and other forms of figurative speech; in slurs and other forms of ‘loaded’ language; in cognitive perspectives and emotions; and in non-sentential representational systems such as maps and diagrams.

I’m interested in intentionality in thought and language and how they’re related. I do work in philosophy of mind, philosophy of language, metaphysics, epistemology and rational decision theory. 

Philosophical problems concerning intentionality and consciousness; issues of non-monotonic reasoning.

Philosophy of science, especially philosophy of psychology

Dept. of Neurology 

Dr. Michelle Chen is a neuropsychologist, with a PhD in Clinical Psychology (with neuropsychology concentration and health emphasis) from Yeshiva University and postdoctoral training at Kessler Foundation. Her research involves the study of neurodegeneration and brain-behavior relationships in neurologic populations, such as older adults with cognitive impairment and persons with multiple sclerosis (MS). She has an interest in utilizing digital and sensor technology in the assessment and treatment of cognitive dysfunction.

Dept. of Psychiatry

Clinical translational neuroscience of addiction, brain imaging, decision neuroscience, computational psychiatry

 Dept. of Neuroscience and Cell Biology

The main goal of Dr. Manzini’s research is to bridge the genetics and mechanisms of disease to identify genes that are essential for human cognition and to define the molecular mechanisms underlying neurodevelopmental disorders focusing on autism and neuromuscular disorders. The Manzini lab combines human genetics with molecular, cellular, and behavioral approaches in murine and zebrafish models to link human genetics to neuronal cell biology, intracellular signaling, and behavior. Her recent work aims to identify molecular mechanisms that could underlie sex bias in autism and to develop novel precision medicine approaches for congenital neuromuscular disease.

Dept. of Pharmacology & Medicine

Dr. McClenaghan is interested in how ion channels work, what happens when they break, and how can we fix them? Ion channels are proteins, found in cell membranes, which open and close to allow the movement of charged atoms (ions) into and out of cells. This movement of ions underlies the electrical currents critical for a vast range of biological processes. Your heartbeat, muscles, brain, and the regular function of all your other cells, rely on the precise activities of these ion channels.

Our research 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 comorbid disorders such as anxiety disorders, depression, or chronic pain with the hope of advancing more effective treatment strategies.

Social cognitive and perceptual processes involved in successful goal pursuit; self-regulation and self-control.

Psychosocial and emotional factors involved in the development and course of chronic physical diseases. A focus of some of his current work concerns the role of mental representations (beliefs) in accounting for patients’ failure to undertake health-promoting behaviors for managing chronic medical conditions such as coronary disease.

The unifying themes in my action-research, clinical work, and policy/advocacy are the development of positive, constructive life paths for children and youth and the organization of opportunities to allow this to happen in equitable ways. This has brought me into areas such as social-emotional learning (SEL), its more recent variation, social-emotional and character development (SECD), emotional intelligence, social competence promotion, character education, primary prevention, school-based, evidence-based intervention, and socialization of identity.

Computer models of syntactic parsing and language comprehension.

Cognitive development; autobiographic memory and development of planning skills.

Social perception, stereotypes and prejudice, science reform, applied philosophy of science.

Blog Website

Behavioral and Systems Neuroscience and Health Concentration. His main questions relate to how central and peripheral immune events influence the cognitive and emotional state of animals, and through what mechanisms this might occur.

Obesity is a complex state characterized by behaviors including enhanced food motivation leading to chronic weight gain, and associated with neuronal adaptations in brain circuits that mediate food-seeking behaviors.

Application of natural language processing and facial recognition models to the study of social cognition (stereotypes, psychological intersectionality, first impressions); social biases in machine learning.

Our research focuses on understanding how chronic stress exposure alters behavior in both sexes and whether neural circuits can be leveraged to reverse maladaptive effects of stress exposure.

Dr. Persaud investigates the underlying processes that govern how we encode, store, and retrieve information from memory and how these processes change/differ as a function of development, culture, and expertise.

Mark Aakhus investigates the relationship between communication and design, especially the uses of technological and organizational design, to augment human interaction and reasoning for decision-making and conflict-management. He uses multiple methods from discourse analysis and computational social science to examine language, argumentation, and social interaction in professional practice, organizational processes, and information infrastructures.

Human interaction with information, particularly in information retrieval.

Human-Computer Interaction, interaction design, mobile and ubiquitous computing, healthcare, everyday wellbeing, environmental sustainability, behavior change

I direct the Behavioral Informatics Lab at Rutgers University. Our lab looks at multiple problems at the intersection of Big Data Analytics, Computational Social Science, and Multimedia Information Systems. The research group focuses on using mobile phones, sensors, and social media for understanding and influencing human behavior. We develop new algorithms and design interfaces that support understanding human behavior while actively responding to issues like algorithmic bias and privacy concerns.

Psycholinguistics: linguistic and cognitive factors modulating morphosyntactic processing in adult learners (e.g., executive control, cognitive load, language experience), using behavioral (eye tracking, self-paced reading) and electrophysiological (ERPs) techniques.

Philosophy of Mind, Cognitive Science, Philosophy of Mathematics and Logic, Philosophy of Physics.