Find Academic Supervisors

Andrea BajcsyView profile

Assistant Professor

• Robotics
• Artificial Intelligence
• Reinforcement Learning
• +7 more

Andrea Bajcsy serves as an Assistant Professor in the Robotics Institute and School of Computer Science at Carnegie Mellon University, leading the Interactive and Trustworthy Robotics Lab (Intent Lab). Her work focuses on enabling robots to safely interact with open-world environments through novel algorithms in control theory and machine learning. Her educational background includes a Ph.D. in Electrical Engineering & Computer Science from UC Berkeley under Anca Dragan and Claire Tomlin, followed by a postdoctoral position with Jitendra Malik and industry experience at NVIDIA's Autonomous Vehicle Research Group. Research centers on quantifying robot confidence, computing safe interaction policies for nuanced hazards (tearing, spilling, breaking), and aligning AI with human values. Key methodologies integrate optimal control, reinforcement learning, dynamic game theory, and deep learning, applied to robotic arms, quadrotors, quadrupeds, and autonomous vehicles. Core areas include safety for physical human-robot interaction, robot learning for manipulation, and world modeling. Recent publications (2024-2025) reveal a concentrated effort on uncertainty-aware safety mechanisms, out-of-distribution adaptation, and language-based safety specification. Her work increasingly bridges conformal prediction with interactive learning while leveraging vision-language models for real-time policy steering, as evidenced by multiple CoRL, RSS, ICRA, and ICLR acceptances. Scientific Awards: NSF CAREER Award (2025) Advises four active PhD students (Kensuke Nakamura, Ravi Pandya, Junwon Seo, Yilin Wu) and leads research funded by the NSF CAREER grant. Organizes community initiatives including the Northeast Systems and Control Workshop and ICRA workshops on Safely Leveraging VLMs in Robotics and Public Trust in Autonomy. Directs the Intent Robotics Lab, which develops theoretical frameworks and practical implementations for open-world robot safety. The lab maintains strong industry ties through NVIDIA collaborations and emphasizes real-world deployment across multiple robotic platforms.

Mohammad ZulkernineView profile

Professor

• Cyber-Physical System Security
• Software Reliability
• Security Engineering
• +6 more

Dr. Mohammad Zulkernine is a Full Professor and Canada Research Chair in Cyber-Physical System Security at Queen’s University’s School of Computing (Faculty of Arts and Science). He leads the Queen’s Reliable Software Technology (QRST) research group and directs the Queen’s Centre for Security & Privacy. His research focuses on secure software systems for cyber-physical systems, including autonomous vehicles, IoT, and cloud computing. Dr. Zulkernine holds a cross-appointment in Electrical and Computer Engineering and is a licensed Professional Engineer in Ontario. Education: BSc (Bangladesh BUET), MEng (Japan), PhD (University of Waterloo). He joined Queen’s in 2003 and has held sabbaticals at University of Trento, Italy and Irdeto Canada. He has published over 250 papers, led 35+ research projects, and supervised 120+ students. Awards include Canada Research Chairs (Tier I and II), Queen’s Excellence in Graduate Supervision Award, and Distinguished Supervision Award from the School of Computing. Research Interests: Cyber-Physical System Security, Software Reliability, IoT Security, Vehicle Networks, Secure Software Engineering, and Cybersecurity Risk Assessment. Active industry collaborations include EU-funded projects and Canada-Africa initiatives.

John P. O'DohertyView profile

Professor

• Decision Neuroscience
• Reward-related Learning
• Computational Modeling
• +3 more

John P. O'Doherty serves as the Fletcher Jones Professor of Decision Neuroscience within Caltech's Division of Humanities and Social Sciences, holding continuous faculty appointments since 2004 (Assistant Professor 2004-07, Associate Professor 2007-09, Professor 2009-present, Fletcher Jones Professor 2021-present). He previously directed the Caltech Brain Imaging Center (2013-17) and maintains affiliations with the T&C Chen Center for Social and Decision Neuroscience. His educational background includes a B.A. from University of Dublin, Trinity College (1996) and D.Phil. from University of Oxford (2000). His research focuses on computational and neural mechanisms of reward-based learning and decision-making , employing fMRI, intracranial recordings, and mathematical modeling to investigate how the brain solves complex decision problems through evolutionarily conserved algorithms. Key areas include Reinforcement learning systems (model-based/model-free arbitration) Observational and social learning mechanisms Neural representation of value, risk, and uncertainty Computational phenotyping of mental disorders Temporal dynamics of goal persistence Analysis of his 2023-2025 publications reveals dominant trends in computational psychiatry (problem gambling, autism traits), hierarchical decision-making, and neuroeconomic modeling of social behavior. His work consistently integrates cross-species computational frameworks with human neuroimaging to identify transdiagnostic mechanisms. While specific awards beyond his endowed professorship aren't detailed, his leadership as Brain Imaging Center Director and prolific high-impact publications demonstrate significant recognition. Current advising includes graduate researcher Sneha Aenugu on goal-persistence projects, with administrative support from Mary A. Martin (mmartin@caltech.edu). His active research program continues to pioneer computational approaches to understanding decision pathologies.

Niels HenzeView profile

Professor

• Human-Computer Interaction
• Predictive Models in Interactive Systems
• Mobile Human-Computer Interaction
• +5 more

Niels Henze is a Professor at the Chair of Media Informatics within the Faculty of Languages, Literature and Cultural Studies at the University of Regensburg, where he has been serving since May 2018. His research centers on human-computer interaction, with a strong focus on predictive models in interactive systems, mobile interaction, augmented and virtual reality, and attention-aware computing. His research interests include: Human-Computer Interaction (HCI) Predictive modeling for runtime adaptation Mobile and wearable interaction Augmented and Virtual Reality (AR/VR) Attention-aware and context-sensitive systems Sociocognitive aspects of interactive technologies The analysis of his recent publications reveals a consistent focus on leveraging user behavior and contextual cues to build intelligent, adaptive interfaces. His work integrates machine learning with interaction design, emphasizing real-time model updates, implicit feedback, and cognitive load awareness to improve usability and user experience across mobile and immersive platforms. Scientific awards: No awards mentioned in the provided text. Niels Henze leads research in adaptive interactive systems and advises students in the field of media informatics. He has previously held a junior professorship at the University of Stuttgart and completed his doctorate at the University of Oldenburg under Susanne Boll. He is actively involved in advancing the theoretical and practical foundations of predictive and attention-aware computing. Grants and funding sources are not specified in the text. He is associated with the Institute for Information and Media, Language and Culture (I:IMSK) at the University of Regensburg, contributing to a multidisciplinary environment that bridges informatics with cultural and linguistic studies.

Grace LimView profile

Assistant Professor

• Organizational Behavior
• Diversity and Inclusion
• Social Class in Organizations
• +5 more

Grace Lim is an Assistant Professor in the Department of Management at the Nanyang Business School, Nanyang Technological University, Singapore. Her research focuses on inclusion, diversity, and the empowerment of disadvantaged employees in organizations, particularly those from lower social class backgrounds and women. Education: Ph.D. in Business (Organizational Behavior and Human Resources), Singapore Management University B.Sc. in Psychology, National University of Singapore Her research employs a range of methodologies, including field surveys, experiments, archival data, and qualitative methods, to ensure robust and generalizable findings. She investigates how individuals can exercise agency to overcome structural disadvantages in the workplace, contributing to the fields of organizational behavior, human resources, and social psychology. Her recent publications reflect a strong trend in studying diversity, inclusion, and equity, with a focus on social class, gender, leadership, and employee well-being. The research spans interdisciplinary themes, integrating insights from psychology, management, and sociology to understand workplace dynamics. Scientific Contributions: Published in top-tier journals such as Organizational Behavior and Human Decision Processes and Academy of Management Annals Research on social class, gender, inclusion, and leadership has been influential in shaping organizational practices Dr. Lim is actively involved in advancing knowledge in organizational behavior and human resources. She has not supervised any listed students yet but continues to contribute through impactful research and academic engagement. She is a member of the Centre for Leadership and Cultural Intelligence at NTU, collaborating on initiatives related to cultural intelligence and inclusive leadership.

Alexander J SundermannView profile

Assistant Professor

• Epidemiology
• Infection Prevention
• Pathogen Genomic Surveillance
• +3 more

Alexander J Sundermann serves as an Assistant Professor in the Department of Epidemiology at the University of Pittsburgh School of of Public Health. His research focuses on leveraging pathogen genomic surveillance and machine learning to revolutionize infection prevention practices in healthcare settings, with demonstrated impacts on outbreak detection accuracy and intervention speed. Education: 2013: BS in Microbiology, University of Rochester 2014: MPH in Infectious Diseases and Microbiology, University of Pittsburgh 2022: DrPH in Epidemiology, University of Pittsburgh Dr. Sundermann's work centers on whole-genome sequencing of pathogens to detect healthcare-associated transmission invisible to traditional methods. His research demonstrates how genomic surveillance reveals hidden outbreaks of vancomycin-resistant Enterococcus (VRE) and mucormycosis, directly linking colonization to clinical outcomes like ICU admission and mortality. He pioneers machine learning tools that analyze electronic health records to identify transmission routes, creating more efficient outbreak investigation frameworks across hospital networks. His publication portfolio (2019-2025) shows a clear trajectory toward integrated genomic-clinical surveillance systems, with recent work quantifying clinical and economic impacts while addressing implementation barriers. This interdisciplinary approach bridges epidemiology, genomics, and data science to transform infection prevention protocols. Scientific Awards: No awards listed in available information. Advising and Grants: While specific advisees and grant details aren't provided, his multi-institutional collaborations suggest active mentorship within genomic epidemiology research teams. His work with the National Healthcare Safety Network indicates engagement with major public health surveillance infrastructure. Labs and Teams: Dr. Sundermann leads cross-functional teams including microbiologists, data scientists, and clinicians across multiple healthcare systems. His UPMC outbreak investigations and national linen contamination studies demonstrate operational frameworks for real-time genomic surveillance implementation in complex hospital environments.

Joyoung LeeView profile

Associate Professor

• Connected Vehicle (CV) Systems
• Traffic Management
• Autonomous Vehicle Control
• +5 more

Dr. Joyoung Lee is an Associate Professor in the Department of Civil and Environmental Engineering at New Jersey Institute of Technology (NJIT). He previously served as Laboratory Manager at the Federal Highway Administration's Saxton Transportation Operations Laboratory. His research focuses on Connected Vehicle (CV) systems, including applications in traffic management, signal control optimization, and autonomous vehicle infrastructure integration. Dr. Lee holds a Ph.D. (2010) and M.S. (2007) in Transportation Engineering from the University of Virginia, and a B.S. (2000) in Transportation Engineering from Hanyang University. His work emphasizes CV-based solutions for real-time traffic systems, cooperative vehicle-infrastructure systems (CVIS), and autonomous vehicle integration. Notable achievements include the 2019 IEEE CAVS Best Paper Award and multiple best paper recognitions from PTV User Group Meetings. His research also addresses traffic safety through innovations like the Virtual Guide Dog system for visually impaired pedestrians and advanced traffic monitoring frameworks using LiDAR and computer vision. Education: Ph.D., Transportation Engineering, University of Virginia (2010) M.S., Transportation Engineering, University of Virginia (2007) B.S., Transportation Engineering, Hanyang University (2000) Dr. Lee's research interests span smart city infrastructure, edge computing for traffic systems, and sustainable transportation solutions. He has pioneered algorithms for cooperative intersection management, automated platooning systems, and federated learning-based traffic optimization. His work bridges theoretical models with real-world implementation through partnerships with FHWA and industry stakeholders. Key contributions include development of the Cumulative Travel-Time Responsive (CTR) traffic signal control system, smart arrival notification systems for paratransit services, and advanced microsimulation calibration techniques. His lab focuses on translating CV data into actionable strategies for safer, more efficient transportation networks. Awards: IEEE CAVS Best Paper Award (2019) ASCE Grand Challenge Innovation Contest Honorable Mention (2017) PTV VISSIM Best Paper Awards (2012, 2008) Excellence in Research Award (University of Virginia, 2011) Ongoing projects include semi-decentralized graph neural networks for traffic forecasting and low-cost LiDAR-based traffic monitoring systems. His work addresses critical challenges in autonomous vehicle integration, incident management, and infrastructure resilience through interdisciplinary collaborations.

Ryan P. HuangView profile

Associate Professor

• Computer Systems
• Operating Systems
• Distributed Systems
• +7 more

Ryan P. Huang is an Associate Professor in the Computer Science & Engineering department at the University of Michigan, College of Engineering, where he leads the Order Lab. Previously, he was an Assistant Professor at Johns Hopkins CS department from 2017 to 2022. His research focuses on computer systems, particularly operating systems and distributed systems, with emphasis on reliability, efficiency, and defensibility across cloud data centers and mobile devices. Dr. Huang's research interests center on pushing the boundaries of cloud systems availability and observability. His work addresses critical challenges such as gray failures and partial failures in distributed systems, developing principled techniques for failure detection and localization. His research spans multiple thrusts including Panorama for enhanced observability, Watchdog for runtime checking, OmegaGen for partial failure localization, and Narya for predictive failure mitigation. He also investigates energy-efficient mobile systems and system misconfiguration prevention. His recent publications demonstrate a strong trend toward addressing silent failures in distributed systems, with multiple papers accepted to top-tier conferences including SOSP and OSDI in 2025. His work bridges theoretical principles with practical system implementations, focusing on real-world challenges in cloud infrastructure and distributed computing environments. NSF CAREER award recipient Multiple Best Paper Awards (OmegaGen, Argus, LeaseOS) CRA Outstanding Undergraduate Researcher Award honorable mentions for advisees Dennis Ritchie doctoral dissertation award honorable mention Dr. Huang actively mentors PhD students including Yuzhuo Jing, Wanning He, Yuxuan Jiang, and others. His lab has produced graduates who have gone on to faculty positions at institutions like University of Virginia and Boston University. He serves on program committees for major systems conferences including SOSP, OSDI, and NSDI, contributing significantly to the academic community. The Order Lab maintains active research collaborations and regularly publishes in top-tier venues, with multiple papers accepted to SOSP and OSDI in 2025.

• Inflammatory Bowel Disease
• Crohn's Disease
• Ulcerative Colitis
• +5 more

Waqqas Afif, MD, M.Sc., FRCPC, is an Investigator at the RI-MUHC (Montreal General Hospital site) within the Infectious Diseases and Immunity in Global Health Program . He holds the position of Associate Professor in the Department of Medicine at McGill University , and is affiliated with the Division of Gastroenterology at the MUHC . His research focuses on the safety and efficacy of biologic medications in treating Inflammatory Bowel Disease (IBD) , with a specific emphasis on Therapeutic Drug Monitoring (TDM) to optimize patient outcomes. Key areas include Biologic therapy optimization Endoscopic and histologic remission Drug concentration analysis Mucosal healing Predictive biomarkers Real-world treatment patterns Scientific Contributions : His recent work explores histologic activity in UC relapse proactive TDM strategies ustekinumab dose escalation in Crohn's guselkumab efficacy in UC metabolic comorbidities in IBD personalized infliximab dosing and other topics published in journals like Inflamm Bowel Dis , Gastroenterology , and Am J Gastroenterol . For contact, email waqqas.afif@mcgill.ca .

Zhiqing ZhouView profile

Associate Professor

• Workplace Mental Health
• Workplace Mistreatment
• Work-Nonwork Interface
• +4 more

Zhiqing Zhou is an Associate Professor in the Department of Mental Health at Johns Hopkins Bloomberg School of Public Health. He holds affiliations with the Hopkins Business of Health Initiative and the Johns Hopkins P.O.E. Total Worker Health® Center. His research examines organizational impacts on employee mental health, workplace mistreatment, work-nonwork balance, and health behaviors. Education: PhD, University of South Florida (2014) MA, University of South Florida (2012) BA, Peking University Health Science Center (2009) Research Interests: Dr. Zhou investigates how workplace practices influence employee well-being, focusing on: Workplace violence/bullying prevention Cross-domain spillover between work and family life Behavioral interventions for health/safety promotion Impact of illegitimate tasks and incivility on mental health Publication Trends: Recent articles (2021-2025) emphasize remote work challenges, cyber incivility, moral identity in organizations, and dyadic family-work dynamics, using longitudinal and diary methodologies. Awards: Summer Faculty Research Fellowship, Office of Naval Research (2021, 2022) Academy of Management OB Division Best Reviewer Award (2015) SIOP LGBT Research Award (2012) Leadership: Associate Editor for Journal of Occupational Health Psychology , Group & Organization Management , and Stress & Health . Collaborates with global researchers and graduate students.

Lianne LefsrudView profile

Associate Professor

• Risk Management
• Sustainability
• Organizational Theory
• +5 more

Lianne Lefsrud serves as Associate Professor and Risk, Innovation, and Sustainability Chair (RISC) in the Department of Chemical and Materials Engineering at the University of Alberta's Faculty of Engineering. Her interdisciplinary research bridges engineering, social sciences, and policy to transform risk management practices across energy, mining, construction, and railroading industries, directly influencing regulations, building codes, and industry operations for sustainable development. Her academic credentials include: BSc in Civil Engineering (Cooperative Program), University of Alberta (1994) MSc in Interdisciplinary Civil & Environmental Engineering and Sociology, University of Alberta (1996) PhD in Strategic Management and Organization, Alberta School of Business (2014) Dr. Lefsrud's research centers on risk management frameworks for sustainability challenges. She examines hazard identification, social license to operate, and technology adoption drivers in high-hazard industries, with emphasis on prospective risk assessment (e.g., hydrogen infrastructure design) and retrospective analysis (e.g., microplastic pollution impacts). Her work integrates circular economy principles into energy systems while addressing unintended consequences across UN Sustainable Development Goals. Recent publications (2024-2025) demonstrate heavy focus on machine learning applications for rail and construction safety, hydrogen infrastructure risk analysis, and science denial mitigation. Key patterns show cross-industry adaptation of AI for incident prediction, regulatory gap analysis for emerging energy systems, and socio-technical approaches to reconcile sustainability goals with operational realities. Scientific recognition includes: Erb Post-Doctoral Fellowship (University of Michigan) Dow Sustainability Research Fellowship (Ross School of Business) Dr. Lefsrud mentors graduate students through industry-integrated projects like her Sustainable Design course where teams generated patents and city solutions. Her research secures Alberta Innovates funding with 1:4 industrial-to-federal matching, collaborating with Suncor, Transport Canada, and Canadian Standards Association. Grants target practical implementations including railcar inspection systems and hydrogen safety protocols. She co-founded Insight Risk Systems and leads the Lefsrud Lab, prioritizing inclusive teams with under-represented groups (women, Indigenous, LGBTQ2S+, neurodiverse) to tackle 'wicked problems' in sustainability. The lab leverages interdisciplinary partnerships across engineering, computer science, psychology, and environmental sociology for real-world risk management solutions.

• Structural Health Monitoring
• Civil Infrastructure
• Machine Learning for Engineering
• +7 more

Dr. Andy Nguyen is a Senior Lecturer in Structural Engineering at the University of Southern Queensland, within the School of Engineering. He is an active researcher and educator, specializing in the Structural Health Monitoring (SHM) of critical civil infrastructure such as bridges, buildings, and transport tunnels. Bachelor of Engineering (BEng), NUCE, 1999 Master of Engineering (MEng), NUCE, 2003 Doctor of Philosophy (PhD), Queensland University of Technology (QUT), 2014 Dr. Nguyen's research is at the forefront of integrating advanced technologies into civil engineering. His primary focus is on developing and deploying sophisticated SHM systems that utilize sensors, data analytics, and machine learning to provide real-time insights into the structural integrity of ageing infrastructure. His work aims to enable proactive maintenance, extend the lifespan of structures, and enhance public safety. He has successfully implemented monitoring systems on major bridges and high-rise buildings in Queensland and New South Wales, with systems capable of even detecting distant earthquake events. His research interests span Structural Health Monitoring, Machine Learning for Engineering, Damage Detection, Finite Element Model Updating, Sustainable Building Materials like bamboo, and the application of AI for automated condition assessment of transport infrastructure. The analysis of his recent publications reveals a strong and consistent research trajectory centered on the application of data-driven and AI methods to solve practical problems in civil infrastructure. His work frequently combines signal processing techniques (like Stockwell Transform) with deep learning models for tasks such as crack detection in concrete and pavement. He also conducts significant research on model updating for complex structures like cable-stayed and arch bridges, using vibration data and optimization algorithms. The integration of machine learning for overload classification and the development of cost-effective, automated monitoring systems are key trends in his recent output. Advanced Queensland Fellow (2024-2027) Dr. Nguyen is actively involved in research supervision and collaboration. He is currently supervising several postgraduate students on projects related to AI-powered condition assessment, bamboo as a sustainable building material, and railway track design. He receives research funding from the Queensland Government through his Advanced Queensland Fellowship. His research has direct practical applications, as evidenced by his public engagement, such as writing for The Conversation on safeguarding ageing bridges, and his work with the Australian Network of Structural Health Monitoring. Dr. Nguyen's work embodies the development of a next-generation 'Living' Laboratory for engineering education, where research, teaching, and real-world infrastructure monitoring are integrated. His current projects involve creating smart, automated fault detection systems and advancing 'digital twin'-based monitoring platforms for infrastructure.

Behnam TaebiView profile

Professor

• Energy & Climate Ethics
• Engineering Ethics
• Nuclear Energy
• +4 more

Behnam Taebi is Full Professor of Energy & Climate Ethics and Scientific Director of the Safety & Security Institute at Delft University of Technology. He leads TU Delft | The Hague, a university-wide initiative connecting engineering knowledge with public policy. His work bridges technology, ethics, and policy through roles at Harvard University’s Belfer Center (2014–2020) and The Young Academy of the Royal Netherlands Academy of Arts and Sciences (2016–2021). As co-Editor-in-Chief of Science and Engineering Ethics , he contributes to shaping ethical discourse in engineering. BSc in Material Science and Engineering (2006) PhD in Philosophy of Technology (2010) Taebi's research focuses on the ethical dimensions of energy systems, nuclear technology, and climate engineering. He explores intergenerational justice, distributive equity, and responsible innovation frameworks. His work integrates value-sensitive design and moral emotions to address uncertainties in technological risk governance, particularly for nuclear energy and carbon capture. Recent publications highlight ethics in nuclear waste repositories, climate policy metaphors, and synthesizing justice frameworks. His VENI-grant from NWO supports innovative research on technological risks. Collaborations span the OECD Expert Panel on transdisciplinary research and co-editorship of influential volumes like The Ethics of Nuclear Energy (Cambridge, 2015) and Ethics and Engineering: An Introduction (Cambridge, 2021). As Scientific Director of the Safety & Security Institute , he leads interdisciplinary efforts to address societal challenges through engineering ethics. His initiatives emphasize inclusive energy transitions, equitable climate strategies, and bridging technical and social sciences in policy-making.

Leila Moslemi NaeniView profile

Senior Lecturer

• Project Management
• Fuzzy Methods
• Mathematical Modelling
• +5 more

Dr. Leila Moslemi Naeni is a Senior Lecturer at the University of Technology Sydney (UTS), School of Built Environment, with a dual appointment in the Faculty of Design, Architecture and Building. She previously served as a Lecturer at UTS (2016-2018) and Sessional Lecturer at Curtin University (2015-2016). PhD in Computer Science (University of Newcastle, 2017) MSc in Industrial Engineering (Sharif University of Technology, 2007) BSc in Industrial Engineering (Iran University of Science and Technology, 2004) Her research focuses on project management under uncertainty, integrating fuzzy systems and mathematical modeling with applications in construction, ESG reporting, and disruptive technologies. She developed innovative methods for statistical control charts in project monitoring and leads research on leveraging blockchain and digital tools for sustainable infrastructure. Recent publications highlight her work on resource-constrained scheduling algorithms, ESG integration in megaprojects, and gamification in project management education. She serves as Review Editor for Frontiers in Environmental Science and on the Editorial Board of Smart and Sustainable Built Environment . 2016 PMI NSW Research Award 2022 Walt Lipke Award 2013 FEBE Postgraduate Research Prize As an active research mentor, she supervises PhD students in machine learning applications, disaster management technologies, and social infrastructure investments. Her teaching emphasizes simulation-based learning, collaborating with Oulo University (Finland) to quantify educational value.

• Pediatric Critical Care Medicine
• Quality Improvement in Healthcare
• Sepsis Management
• +4 more

Sarah Kandil, MD, is an Associate Professor of Pediatrics (Critical Care) at Yale School of Medicine and a pediatric intensivist at Yale New Haven Children’s Hospital (YNHCH). She specializes in pediatric critical care medicine, sedation services, and quality improvement initiatives. Dr. Kandil holds leadership roles as Deputy Quality and Safety Officer at YNHCH and has spearheaded collaborative projects to improve outcomes in pediatric sepsis, reduce CLABSI rates, and optimize antibiotic timing in critically ill children. Education: MD from McGill University (2004), residency at Baystate Children’s Hospital (2008), fellowship at Yale SOM (2011). Her research focuses on systematic methods for quality improvement, sepsis care protocols, and metabolic changes during critical illness. Notable contributions include the Transport Risk Assessment in Pediatrics (TRAP) score for transport triage and studies on glucose control in PICU patients. Key Awards: 2011 Travel Award (Eastern Society of Pediatric Research), 2010 Best Research Abstract (AAP Transport Medicine Section). Leads the IPSO Collaborative to reduce pediatric sepsis mortality. Developed the CLABSI Rapid Response Team to proactively address infection risks. Published extensively on pediatric sepsis, antibiotic timing, and quality improvement strategies. Labs/Teams: Active in the Pediatric Critical Care Transport Program and the Quality and Safety Division at YNHCH.