Massachusetts Institute of TechnologyUnited States
Abhijit Banerjee is a Professor in the Department of Economics at the Massachusetts Institute of Technology (MIT). His research focuses on development economics, public health policy, and social protection programs, particularly addressing poverty and inequality in low- and middle-income countries. He has conducted large-scale experiments evaluating interventions such as conditional cash transfers, universal basic income, and healthcare policies. Key areas of interest include the design and implementation of anti-poverty programs, behavioral economics, and the long-term health impacts of infectious diseases like COVID-19. His work often integrates experimental methods to assess policy effectiveness, with contributions to global health studies and economic development strategies. Notably, his research on the RECOVERY trial evaluates treatments for hospitalized COVID-19 patients, while other studies explore financial spillover effects of electronic government transfers in Indonesia and savings behavior interventions in Chile. Banerjee has collaborated on projects analyzing post-COVID-19 health outcomes, labor market dynamics in India, and the role of trusted messengers in public health communication during crises. Despite the breadth of his contributions, specific details about his educational background, grants, or lab affiliations are not explicitly provided in the source text.
Maja J Matarić is the Chan Soon-Shiong Chaired and Distinguished Professor of Computer Science at the University of Southern California's Viterbi School of Engineering, with courtesy appointments in Neuroscience and Pediatrics. She serves as founding director of the USC Robotics and Autonomous Systems Center, co-director of the USC Robotics Research Lab, and Principal Scientist at Google DeepMind. Previously, she held leadership roles as USC's interim Vice President of Research (2020-2021) and Vice Dean for Research (2006-2019). Her educational background includes: PhD in Computer Science and Artificial Intelligence from MIT (1994) MS in Computer Science from MIT (1990) BS in Computer Science from University of Kansas (1987) Matarić pioneers Socially Assistive Robotics (SAR) , a field her lab named, focusing on human-robot interaction that provides assistance through social rather than physical support. Her research targets critical health and wellness challenges including post-stroke rehabilitation, autism spectrum disorder therapy, cognitive exercises for Alzheimer's patients, ADHD academic support, and mental health interventions. She develops systems modeling user engagement, personality, and motivation, with extensive real-world deployments in schools, rehabilitation centers, and homes. Analysis of her recent publications reveals dominant themes in cognitive health robotics (2025 CHI paper on LLM-powered elder care), pediatric assistive technology (2025 IDC speech therapy review), and adaptive preference modeling (2025 HRI contrastive learning work). Her research consistently bridges machine learning with human-centered design for vulnerable populations. Major scientific recognition includes: ACM Athena Lecturer Award (2024) ACM Eugene L. Lawler Humanitarian Award (2024) ACM Fellow (2020) Presidential Mentoring Award (2011) Multiple society fellowships (AAAS, IEEE, AAAI) As a dedicated mentor, Matarić has championed underrepresented groups through CRA-W, placing numerous women in faculty positions. She leads USC Viterbi's K-12 STEM Outreach Program serving low-income Los Angeles schools and authored The Robotics Prime for student education. Her research has secured significant funding enabling real-world technology transfer, with documented impact in rehabilitation centers and homes through deployable SAR systems. Her Robotics Research Lab at USC drives innovation in embodied AI, with current projects spanning LLM-integrated elder care robots, ADHD academic companions, and autism therapy systems. The lab emphasizes co-design with end-users and rigorous real-world validation across diverse populations.
Hilary Bernstein is an Assistant Professor at the Medical University of South Carolina (MUSC) within the College of Medicine , specifically affiliated with the Department of Psychiatry and Behavioral Sciences . Her academic profile emphasizes clinical practice and research in mental health disciplines. Degrees: MSW (Master of Social Work), DHA (Doctor of Health Administration) Research Focus: Her academic work spans individual and couples psychotherapy, with specialized expertise in Cognitive Behavioral Therapy (CBT) and Psychodynamic Psychotherapy. She investigates clinical research on mood disorders, depression, anxiety, relationship issues, and grief management.
Tim Althoff is an Associate Professor at the Paul G. Allen School of Computer Science & Engineering, University of Washington, specializing in Artificial Intelligence and Human-Centered Computing. His research focuses on behavioral data science, combining Data Science Natural Language Processing Social Computing Human-Centered AI Ethics & Fairness to extract insights about health and well-being. Recent publications highlight advancements in: Mental health support through AI Wearable sensor health monitoring Online community analysis Reproducibility in data science Public health interventions with notable papers in ACL, Nature Machine Intelligence, and NeurIPS. Scientific recognition includes: ACL 2023 Outstanding Paper Award WWW 2021 Best Paper Award Double ICWSM 2021 Best Paper Awards SIGKDD Dissertation Award 2019 Fulbright Scholarship German National Merit Foundation Actively mentoring postdoctoral researchers and seeking PhD students in areas like neural representation learning, NLP applications to psychology, and mobile health technologies through his Behavioral Data Science Group .
Dr. Sudie E. Back is a Professor in the Department of Psychiatry and Behavioral Sciences at the Medical University of South Carolina (MUSC), College of Medicine. She also serves as Director of the NIH-sponsored Drug Abuse Research Training (DART) program and is a Staff Psychologist at the Ralph H. Johnson VA's STAR program. Her expertise lies in treating substance use disorders and PTSD, particularly among veterans and civilians. She leads both behavioral and pharmacological clinical trials, as well as neuroimaging studies. Education: PhD in Clinical Psychology from the University of Georgia (2004), clinical internship at Yale University School of Medicine (2002–2003), and postdoctoral training at MUSC (2004–2005). Research Interests: Co-occurring substance use and PTSD, trauma-focused therapies, veterans' mental health. Funding: NIH, Department of Defense, and VA grants, including K23, R01, K02, and a Fulbright award. Dr. Back has pioneered integrated treatment approaches, such as combining oxytocin with exposure therapy for AUD and PTSD. She also developed COPEWeb , a web-based training program for providers treating PTSD and SUD. Her trials include randomized clinical trials on cognitive processing therapy and relapse prevention. Awards: Career Development Award (K23) R01 grants Independent Scientist Award (K02) Fulbright Scholar Award (Australia) Labs/Teams: Director of DART program at MUSC and STAR program at the VA, focusing on translational research and clinical training.
Jeff Huang is an Associate Professor and Associate Chair of Computer Science at Brown University. His research focuses on Human-Computer Interaction (HCI), with emphases on personalized systems using behavioral data, health informatics, and user interfaces. Huang holds a PhD from the University of Washington and degrees from the University of Illinois at Urbana-Champaign. His work is funded by NSF, NIH, and ARO, and he has received awards including the NSF CAREER Award and ARO Young Investigator Award. Education: PhD in Information Science, University of Washington (2013) MS in Computer Science, University of Washington (2013) BS and MS in Computer Science, University of Illinois at Urbana-Champaign (2007) Research Interests: His work spans health informatics (e.g., sleep tracking systems like Self-E and SleepCoacher), user interface design, and leveraging behavioral data for personalized systems. Notable projects include WebGazer (webcam eye tracking), filtered.ink (creative illustration tools), and Sochiatrist (mental health analytics). Teaching: He teaches courses on user interfaces, HCI, and research methods, including CSCI 0130/1300 (User Interfaces), CSCI 2300 (HCI Seminar), and CSCI 2000 (Research Methods). Awards: NSF CAREER Award Facebook Fellowship ARO Young Investigator Award Grants & Advising: Huang leads a research group advising over 50 students, many of whom have pursued academic and industry roles. His grants support projects in HCI, health tech, and collaborative systems.
Maria Gorlatova is an Associate Professor of Electrical and Computer Engineering at Duke University's Pratt School of Engineering, where she leads the Intelligent Interactive Internet of Things (I3T) Lab. She also holds a secondary affiliation as Faculty Network Member of the Duke Institute for Brain Sciences and has previously served as Assistant Professor of Computer Science. Dr. Gorlatova earned her Ph.D. in Electrical Engineering from Columbia University (2013), following M.Sc. and B.Sc. (Summa Cum Laude) degrees in Electrical Engineering from University of Ottawa, Canada. Prior to joining Duke, she was an Associate Research Scholar in the Electrical Engineering Department and Associate Director of the Princeton EDGE Lab at Princeton University (2016-2018). She also has industry experience with Telcordia Technologies, IBM, and D. E. Shaw Research. Her research focuses on advancing intelligent behavior in Internet of Things systems and applications, particularly in mobile pervasive systems and the Internet of Things. Her work crosses traditional discipline boundaries, requiring thinking across multiple layers of system and protocol stacks. Current research themes include breaking barriers for technologies that enable fundamentally new deployments and experiences, such as energy harvesting, artificial intelligence adapted to IoT constraints, and augmented reality. Her lab specifically develops edge- and IoT-enabled intelligent augmented reality platforms, with applications in healthcare and human-robot collaboration. Analyzing her recent publications reveals a strong focus on augmented reality systems, particularly for medical applications. Her work spans computer vision for AR, spatial tracking, SLAM systems, vision-language models for AR security, and VR/AR applications in neurosurgery and rehabilitation. A significant portion of her recent work addresses challenges in mixed reality for medical procedures, demonstrating the translational impact of her research. Google Anita Borg USA Fellowship Canadian Graduate Scholar CGS NSERC Fellowships Columbia University Presidential Fellowship Columbia University Jury Award for Outstanding Achievement in Communications ACM SenSys Best Student Demonstration Award IEEE Communications Society Young Author Best Paper Award IEEE Communications Society Award for Advances in Communications Best Research Artifact Award, IEEE IPSN (2020) N2 Women Rising Star, Networking Networking Women (N2Women) (2019) Dr. Gorlatova's research has been supported by various funding sources that enable her work on edge computing for augmented reality, IoT systems, and medical applications. She actively mentors graduate students who frequently appear as first authors on her publications, indicating strong student involvement in her research. Her I3T Lab at Duke focuses on creating human-facing pervasive mobile computing platforms that enable transformative applications, with recent emphasis on creating advanced augmented reality platforms that integrate edge computing and IoT technologies. The I3T Lab is developing next-generation AR systems with capabilities in edge AI, collaborative spatial awareness, AR user cognitive context sensing, and AR QoS/QoE evaluation. Current projects include applications in healthcare (particularly neurosurgery guidance and rehabilitation) and human-robot collaboration scenarios, demonstrating the lab's focus on real-world impact of pervasive computing technologies.
Professor Rebecca Lawson is a Professor of Neuroscience and Computational Psychiatry at the University of Cambridge, affiliated with the Department of Psychology and Bye-Fellow at Peterhouse College. Her research focuses on understanding how humans learn to make predictions under uncertainty, with applications to mental health conditions such as anxiety and depression. She leads the Prediction and Learning (PaL) Lab, which combines computational modeling, neuroimaging (e.g., 7T MRI), and behavioral experiments to study cognitive processes in typical and atypical populations. Key research interests include computational psychiatry, autism spectrum disorders, neuroimaging techniques, and the neurochemical basis of learning mechanisms. She has received significant funding, including a £4.3m Wellcome Mental Health Award and the Sir Henry Dale Fellowship. Notable contributions include advancing theories of neural gain and sensory expectations in autism, as well as studies on uncertainty processing in anxiety and depression. Professor Lawson holds academic awards such as the BNPA Lishmann Prize and the BAP Psychopharmacology Award. She actively contributes to public engagement, including initiatives like Knit-a-Neuron and involvement with PrideinSTEM. Her lab collaborates internationally, with projects like the CamRAA study investigating autism-anxiety overlaps and the Chemical and Brain Basis of Uncertainty (CBBU) study exploring pharmacological interventions. Education: PhD in Cognitive Neuroscience (University of Cambridge), BA (Hons) Psychology & Philosophy (University of Glasgow). Grants: £4.3m Wellcome Award, Parke-Davis Fellowship, Lister Institute Prize. Labs/Teams: Principal Investigator of the PaL Lab; collaborations with MRC Cognition and Brain Sciences Unit, Yale University, and Brown University.
Christopher M EARLS is a Professor in the Department of Psychology at Université de Montréal's Faculty of Arts and Sciences. He specializes in forensic psychology, psychopathology, and behavioral studies with a focus on sexual delinquency and juvenile prostitution. His research explores the intersections of psychopathy, criminal behavior, and mental health comorbidities. He teaches courses including Psychopathology: Introduction across undergraduate programs in psychology, social sciences, and cognitive neuroscience. His academic contributions span over two decades, with notable work on psychopathy assessment, parenting practices in non-criminal populations, and sexual behavior conditioning. Education Affiliations: Université de Montréal (primary) Teaching Programs: Baccalauréat en psychologie, Neuroscience cognitive, Social Work programs Dr. EARLS has directed 10+ theses and mémoires since 1998, focusing on forensic psychology topics like sexual delinquency correlates and psychopathy measurement validity. His work bridges clinical psychology with sociocultural factors, particularly in marginalized populations like sex workers and juvenile offenders. Research Highlights: Clinical assessment tools comparison (paper vs. digital psychopathy scales) Gender differences in psychopathy expression Impact of childhood trauma on sexual interest development Though no formal awards are listed, his extensive publication record reflects sustained contributions to forensic and clinical psychology research.
Adriana Tapus is a Full Professor at ENSTA Paris, affiliated with Institut Polytechnique de Paris, leading the Autonomous Systems and Robotics Laboratory (SAR) within the Computer Science and Systems Engineering Unit (U2IS). She holds an HDR (Habilitation) and a PhD from EPFL, Switzerland, with postdoctoral experience at USC. Her research focuses on socially assistive robotics, human-robot interaction (HRI), and personalized therapy for individuals with physical/cognitive impairments. She directs the IP Paris Doctoral School and coordinates national/international projects like the EU-funded ENRICHME and SWEET. Education: PhD in Mobile Robotics, EPFL (2005) Habilitation (HDR), ENSTA Paris (2011) M.S. Computer Science, University Joseph Fourier Engineer, Politehnica University of Bucharest Research Interests: Tapus pioneers socially assistive robotics, integrating machine learning, human modeling, and multimodal communication (verbal/non-verbal/para-verbal). Her work addresses adaptive therapies for vulnerable populations using robotics, physiological data interpretation, and context-aware interaction. Key themes include: Human-robot cooperation and trust Emotion recognition and expression Personalized rehabilitation systems AI ethics and human-centered design Publications: Over 150 articles, with recent work exploring humor in HRI, teleoperation trust models, and cross-cultural intelligent vehicles. Notable 2025 contributions include studies on robot laughter efficacy and multimodal facial expression frameworks. Awards: 2025: 4 IROS papers accepted 2016: 25 Women in Robotics recognition 2010: Romanian Academy Award Multiple conference best paper awards (RO-MAN, ICRA, etc.) Advising & Grants: Supervised over 20 PhD students and led projects like EU Horizon 2020 ENRICHME. Current students focus on teleoperation dynamics, robot humor, and haptic interfaces. Active in editorial roles (IJSR, THRI) and conference organization (HRI General Chair 2019). Labs/Teams: Founder of RoboticsByDesign lab and co-initiator of the Hi! Paris interdisciplinary AI center. The SAR lab develops systems for healthcare, education, and human-robot collaboration.
Martin T. Wells is the Charles A. Alexander Professor of Statistical Sciences at Cornell University, with joint appointments in the Department of Statistical Science, Department of Biological Statistics and Computational Biology, Department of Social Statistics, and as Professor of Clinical Epidemiology and Health Services Research at Weill Medical School. He serves as Editor-in-Chief of the ASA-SIAM Book Series and Co-Editor of the Journal of Empirical Legal Studies. Cornell University, Ithaca, NY Weill Cornell Medical College Research Interests span applied and theoretical statistics, Bayesian methods, biostatistics, clinical epidemiology, and computational biology. His work bridges disciplines like finance, legal studies, and health services research. Article Trends highlight advancements in Bayesian modeling, quantum cognition machine learning, tensor analysis, and misclassification correction, with applications in genomics, finance, and public health. Fellow of the American Statistical Association Fellow of the Royal Statistical Society Contributions include developing statistical software (e.g., rTensor), methodological innovations in clinical trials, and empirical legal studies on civil rights and the death penalty.
University of Illinois Urbana-ChampaignUnited States
Pasquale Bottalico serves as Associate Professor in the Department of Speech and Hearing Science at the University of Illinois, with dual appointments as Associate Professor at the Center for Latin American and Caribbean Studies and Affiliate Faculty in the School of Music. His unique interdisciplinary profile bridges engineering, music performance, and speech science, reflecting his dual academic training and professional artistry. His educational foundation includes: Bachelor's in Telecommunications Engineering from Univeristà Mediterranea di Reggio Calabria, Italy Concurrent Opera Singing degree from F. Cilea Music Academy, Reggio Calabria Master's in Telecommunications Engineering from Politecnico di Torino, Italy Ph.D. in Metrology specializing in acoustics measurement uncertainty and classroom acoustics Dr. Bottalico's research centers on vocal load quantification and professional voice techniques , with significant contributions to understanding vocal fatigue in teachers and singers. His work spans Speech Intelligibility in educational environments, Room Acoustics for performance and learning spaces, and Musical Acoustics of historical vocal styles. A distinctive thread throughout his research examines how acoustic conditions modulate voice production and perception, increasingly incorporating virtual reality and bone conduction technologies for innovative assessment and intervention approaches. His Colombian vocal health study demonstrates cross-cultural applications of his work. Analysis of his 2023-2025 publications reveals three dominant research trajectories: (1) The impact of noise and dysphonia on children's speech processing in educational settings, using multimodal assessment including EEG; (2) Virtual reality applications for voice production research and therapeutic intervention; (3) Cross-cultural validation of vocal fatigue metrics and development of biofeedback systems. His work consistently bridges engineering precision with clinical applicability, particularly for professional voice users in challenging acoustic environments. No scientific awards were documented in the available information. While specific advising relationships aren't detailed, his research collaborations span international institutions including Colombian and Italian universities, suggesting graduate mentorship in interdisciplinary projects. No grant information was provided, though his systematic reviews and cross-cultural studies imply externally funded research activities. Though no dedicated laboratory is specified, his virtual reality voice studies and acoustic parameter assessments suggest affiliations with audio engineering facilities and voice clinics, likely through the Speech and Hearing Science department's research infrastructure.
Allison Ross Eckard, MD is Professor in the Departments of Pediatrics and Medicine at the Medical University of South Carolina (MUSC) College of Medicine, serving as Division Chief for Pediatric Infectious Diseases and Director of MUSC's Ryan White Pediatric HIV Clinic and HIV Transition Clinic. She maintains an adjunct faculty position at Emory University and holds board certification in Pediatrics and Pediatric Infectious Diseases. Her primary research focuses on metabolic, cardiovascular, and nutritional complications of chronic HIV and antiretroviral therapy across age groups, with emphasis on inflammation's role in comorbidities like cardiovascular disease and bone disorders. Current investigations include NIH R01-funded research on interventions for weight gain and abdominal fat in HIV, vitamin D supplementation, and statin therapy. She has published nearly 60 peer-reviewed papers on HIV pathogenesis and treatment optimization. Dr. Eckard co-chairs the DHHS panel for Guidelines for the Prevention and Treatment of Opportunistic Infections in HIV-Exposed and HIV-Infected Children and serves on the DHHS panel for Guidelines for the Use of Antiretroviral Agents in Adults and Adolescents with HIV . Her clinical work specializes in comprehensive HIV care for children through young adults, with particular focus on adolescent/young adult transition issues and global health initiatives through Lespwa Timoun in Haiti. Recent efforts include developing COVID-19 treatment guidelines for children and school safety protocols. HIV Specialist certification (American Academy of HIV Medicine) Fellow, Infectious Diseases Society of America Fellow, Pediatric Infectious Diseases Society Fellow, HIV Medical Association Member, HIV Medical Association's 'Ending the HIV Epidemic' working group She leads MUSC's HIV education initiatives and serves as inpatient consultant for pediatric infectious diseases, with advanced training in tropical medicine. Her NIH-funded research examines targeted interventions to minimize comorbidity development in HIV, while her clinical leadership spans the Ryan White HIV program, transition clinics, and global health partnerships.
Kristin Bernard, Ph.D. (University of Delaware, 2013), is an Associate Professor of Clinical Psychology at Stony Brook University’s Department of Psychology. Her research focuses on the neurobiological consequences of early adversity, parent-child relationships, and the efficacy of early parenting interventions such as Attachment and Biobehavioral Catch-up (ABC). She collaborates with Power of Two, a NYC-based nonprofit, and leads the Developmental Stress and Prevention Lab. Current grants include studies on epigenomics, maternal attachment representation, and community-based ABC interventions. Dr. Bernard’s work bridges clinical and developmental psychology, emphasizing prevention science and translational research. Education: Ph.D. in Clinical Psychology, University of Delaware, 2013. Research Interests: Child maltreatment, neurobiological impacts of early adversity, parenting interventions, psychobiology of attachment, and intervention efficacy. Her lab investigates mechanisms linking caregiving quality to child outcomes, including cortisol regulation, brain development, and behavioral compliance. Lab & Partnerships: Directs the Developmental Stress and Prevention Lab, focusing on high-risk populations. Collaborations include Power of Two for ABC implementation and NYC agencies like the Administration for Children’s Services. Current projects explore neighborhood influences on parenting (Geography of Parenting Study) and neural correlates of parenting behavior (SNAP study). Grants & Funding: Principal Investigator on NIH-funded projects (R03 HD099372, R01 MH119310) and co-PI on Stony Brook’s seed grants. Projects examine accelerated aging biomarkers and intervention effectiveness in community settings. Publications: Over 50 peer-reviewed articles and a co-authored book on ABC interventions. High-impact journals include Psychoneuroendocrinology , Development and Psychopathology , and Child Development .
Christopher Weidlich is an Assistant Professor of Clinical in the School of Nursing and Health Studies at the University of Miami. His academic focus includes psychiatric nursing, mental health education, and healthcare provider well-being. He is involved in research addressing simulation-based education, mental health disorders in occupational groups such as fire investigators, and interventions to improve resilience among healthcare providers. His research interests span simulation modalities in psychiatric nursing education, organizational stigma's impact on mental health service utilization, and substance abuse trends like xylazine adulteration. He has also contributed to studies on military healthcare, including resilience programs for providers and PEMF therapy for chronic pain. Dr. Weidlich’s work is supported by his affiliation with the University of Miami’s School of Nursing and Health Studies, leveraging resources such as the Simulation Hospital Advancing Research and Education (S.H.A.R.E.®) facility. His research emphasizes practical applications in clinical settings and improving patient outcomes through innovative educational and therapeutic approaches.
