Find Academic Supervisors

• Infection Prevention
• Antimicrobial Resistance
• Epidemiology
• +3 more

Dr. Kerri Thom serves as Professor in the Department of Epidemiology and Public Health and Department of Medicine at the University of Maryland School of Medicine, holding the administrative role of Associate Dean for Student Affairs while directing the Office of Student Research and advising medical students through the Office of Student Affairs. Education: M.D. from University of Florida College of Medicine Internal Medicine Residency and Infectious Disease Fellowship at University of Maryland Medical Center and Baltimore VA Medical Center M.S. in Epidemiology and Clinical Research from University of Maryland School of Medicine Her research concentrates on infection prevention, antimicrobial resistance mechanisms, and transmission dynamics of multidrug-resistant pathogens—especially Acinetobacter baumannii —in healthcare environments. She develops evidence-based interventions for antimicrobial stewardship and infection control, addressing critical gaps in reducing healthcare-associated infections through clinical epidemiology and translational research. Analysis of Dr. Thom's publication record reveals sustained focus on healthcare epidemiology, with methodological diversity spanning clinical trials, observational studies, and mathematical modeling. Her work evaluates interventions across varied clinical contexts—from trauma resuscitation to transplant surgery—emphasizing practical strategies to combat multidrug-resistant organism transmission and antibiotic resistance. Dr. Thom actively mentors medical students through curriculum development and research supervision via the Office of Student Research. She has secured significant competitive funding from NIH, CDC, and AHRQ for projects targeting antibiotic resistance transmission and infection prevention. Selected Grants: CDC: "Transmission of Antibiotic Resistant Bacteria from Patient-to-Patient in Healthcare Setting and the Impact of Contact Precautions" (PI, 9/2018-9/2019) CDC: "Epicenters for the Prevention of Healthcare Associated Infections" (Co-Investigator, 9/2018-9/2020) AHRQ: "Removing barriers to hand hygiene and glove compliance: evaluation of two novel, time-efficient interventions" (PI, 8/2015-5/2019) CDC: "Epicenters for the Prevention of Healthcare Associated Infections (HAI) Cycle II" (Investigator, 9/2015-9/2018) ARLG: "ESBL-producing Enterobacteriaceae in solid organ transplant recipients" (Investigator, 7/2016-7/2018) CDC: "Impact of Post-antibiotic Prescription Review on Antibiotic Use and Resistance" (Co-PI, 9/2013-12/2016) NIH K23: "Epidemiology of Acinetobacter baumannii: An Emerging Nosocomial Pathogen" (9/2010-12/2016) As a key contributor to the CDC Epicenters program, Dr. Thom collaborates with national researchers on healthcare-associated infection prevention while leading student research initiatives that cultivate future clinician-scientists in infectious disease epidemiology.

Peter X. K. SongView profile

Professor

• data integration
• distributed inference
• high-dimensional data analysis
• +13 more

Peter X. K. Song is a Professor in the Department of Biostatistics at the University of Michigan School of Public Health. With expertise spanning statistical methodology development and interdisciplinary applications, Dr. Song maintains active collaborations across Nutritional Sciences, Environmental Health Sciences, Chronic Disease research, and Nephrology. His work bridges theoretical statistics with practical healthcare solutions, focusing on innovative approaches to complex data challenges in public health and medicine. Based at the M4140 SPH II building in Ann Arbor, he leads the Song Lab and contributes significantly to the academic community through teaching, research mentorship, and scholarly publications. PhD, University of British Columbia, Vancouver, 1996 BS, Jilin University, Changchun, 1985 Dr. Song's research focuses on the statistical foundation of big data analytics, with particular emphasis on data integration, distributed inference, high-dimensional data analysis, longitudinal data analysis, mediation analysis, and spatiotemporal modeling. His methodological innovations address critical challenges in smart health applications, including organ exchange programs, children's health, chronic disease management, environmental health assessment, and nutritional sciences. His approach combines statistical theory, integer optimization, and algorithm development to create practical tools that help researchers understand complex relationships between environmental exposures and health outcomes. Dr. Song's publication record demonstrates a consistent trajectory of methodological innovation applied to pressing health challenges. His recent work shows increasing focus on sleep classification using AI techniques, personalized treatment effect analysis, distributed statistical methods for high-dimensional data, and epigenetic applications in adolescent health. The interdisciplinary nature of his research is evident in publications spanning biostatistics journals, computer science venues, and domain-specific medical publications. His work increasingly addresses the challenges of integrating diverse data sources while maintaining statistical rigor in the era of big data. IMS Fellow ASA Fellow Elected Member of the International Statistical Institute 2017 ENAR John Van Ryzin Award Dr. Song has mentored an impressive 22 PhD students and 6 postdoctoral trainees throughout his career, with many now holding faculty positions at prestigious institutions or working as data scientists in leading technology companies. His lab, the Song Lab, currently supports two postdoctoral research fellows and eight doctoral students working on cutting-edge statistical methodology development. His collaborative research extends across numerous grants that support interdisciplinary projects in kidney paired donation programs, environmental health studies, nutritional sciences, and chronic disease research, demonstrating his commitment to translating statistical innovation into practical health solutions. The Song Lab serves as a hub for interdisciplinary statistical research at the University of Michigan, bringing together experts from statistics, operations research, and machine learning to address complex challenges in medical and public health sciences. Current lab members include eight doctoral students and three postdoctoral fellows working on projects related to optimal organ matching strategies, causal mediation pathways of omics biomarkers, and statistical methods for big data integration. The lab maintains strong connections with clinical researchers across nephrology, pediatrics, environmental health sciences, and nutritional sciences, ensuring that methodological developments remain grounded in real-world applications.

Sithik AliyarView profile

Researcher

• Wind Energy
• Computational Fluid Dynamics
• Offshore Engineering
• +3 more

Sithik Aliyar is a Postdoctoral Researcher at the Department of Wind and Energy Systems, Flows Wind Turbine Design Division, at the Technical University of Denmark (DTU). He specializes in computational fluid dynamics (CFD) and offshore wind turbine dynamics, focusing on wave interactions with floating structures. Institution: Technical University of Denmark (DTU) Department: Flows Wind Turbine Design Division, Wind and Energy Systems Research Focus: Floating wind turbines, extreme sea states, harmonic separation, and numerical algorithms His work combines advanced CFD simulations with experimental validation to analyze floating wind turbine stability under directional waves. Recent contributions include the FloatStepper algorithm for robust wave response modeling and studies on SPAR platform upending risks. Publications highlight collaborations with experts like H. Bredmose and J. Roenby, with research outputs spanning Renewable Energy , Royal Society Open Science , and international conferences on ocean engineering. Key metrics include open-access citations, computational fluid dynamics, and floating wind turbine dynamics.

Jennifer SpindelView profile

Assistant Professor

• International Security
• Arms Trade
• Civil-Military Relations
• +4 more

Jennifer Spindel is an Assistant Professor in the Political Science Department at the University of New Hampshire , where she directs the International Affairs Program . Her research focuses on international security , arms trade dynamics , and civil-military relations , analyzing how weapons transfers function as strategic signals and shape global power structures. She contributes policy analysis to Foreign Affairs , War on the Rocks , and Defense One , and holds a non-resident fellowship at the Institute for Future Conflict (US Air Force Academy, 2024–2025). Education: Ph.D. in Political Science (University of Minnesota), BA in Peace and Conflict Studies (Colgate University) Research Themes: Arms trade as political signaling, diffuse power structures, public attitudes toward military diversity, civil-military relationship dynamics Policy Engagement: Regularly contributes to national/international media, addressing defense strategy and arms trade implications. 2025 work explores mid-tier weapons’ strategic importance through Ukraine’s conflict experience. Collaborates with Stanton Foundation , Lyndon B. Johnson Foundation , and Global Racial and Social Inequality Lab . Scientific Awards: 2019 Kenneth Waltz Prize (Best Dissertation in International Security) Course Development Grant (Stanton Foundation, 2021–2022) Advocacy: Breast cancer survivor and volunteer Patient Advocate with Dana Farber/Harvard Cancer Center

Spiridon Ivanov PenevView profile

Professor

• Wavelet Methods in nonparametric curve estimation
• Edgeworth expansions and Saddlepoint Approximation Methods
• Structural Equation Models
• +8 more

Professor Spiridon Ivanov Penev is a leading academic in the School of Mathematics and Statistics at the University of New South Wales. He holds a PhD in Mathematical Statistics from Humboldt University (Berlin, Germany) and has been affiliated with UNSW since 1992, progressing from Lecturer to Professor in 2019. His research spans wavelet methods, saddlepoint approximations, structural equation models, and stochastic risk analysis. Education: PhD in Mathematical Statistics, Humboldt University Current Affiliation: Department of Statistics, School of Mathematics and Statistics, UNSW His work focuses on advanced nonparametric techniques, including wavelet-based signal recovery with adaptive sampling rates, and robust inference in structural equation models. He has developed bias-corrected reliability measures for psychometric applications and contributed to stochastic optimization problems in finance and engineering. Recent publications highlight his expertise in semiparametric regression, robust portfolio optimization, and marine engineering applications using machine learning. Key trends include the use of Bregman divergence for shape-preserving estimation and Markov chain methods for climate model weighting. Scientific Awards: DAAD award Elected member of the International Statistical Institute (ISI) He has supervised numerous grants as Chief Investigator, including Australian Research Council projects and industry collaborations. Administrative roles include membership in the School of Mathematics and Statistics Executive Committee. Teaching duties span advanced statistical inference, multivariate analysis, and data science applications.

Ulrich W. ThonemannView profile

Professor

• Supply Chain Management
• Optimization
• Information Systems
• +5 more

Prof. Ulrich W. Thonemann is a Full Professor and Director of the Department of Supply Chain Management & Management Science at the University of Cologne's Faculty of Management, Economics and Social Science. Since 2019, he has served as Dean of the Faculty and President of the University of Cologne Executive School since 2018. His research spans Supply Chain Management Optimization Behavioral Operations Information Systems . His recent work focuses on Incentive systems for forecast sharing Behavioral inventory metrics Contract design for newsvendor problems Demand information sharing Capacity rationing . He has served on the scientific advisory board of Bundesvereinigung Logistik and as Associate Editor for Production and Operations Management . Scientific Awards: Terman Fellow (1999-2000) Anderson Faculty Scholar (1998-2000) Outstanding Academic Achievements at Stanford (1992) Contact: ulrich.thonemann@uni-koeln.de | Research Group Website

• Industrial and Manufacturing Engineering
• Logistics
• Supply Chain Management
• +4 more

Anna Corinna Cagliano is a Full Professor at the Department of Management and Production Engineering (DIGEP) , Polytechnic University of Turin . She is a member of the CARS@PoliTO Interdepartmental Center for Automotive Research and Sustainable Mobility, and serves as Deputy Coordinator of the Doctoral College in Management and Production Engineering . Research Interests: Industrial and manufacturing engineering, logistics, supply chain management, project risk analysis, healthcare logistics, and ICT applications in logistics. Scientific Affiliation: AIDI Italian Association of Industrial Plant Teachers since 2016. Research Trends: Her publications focus on the intersection of Industry 4.0 , lean manufacturing , and sustainability in logistics. Key areas include automated storage systems , digital twins in intra-logistics , and COVID-19 impacts on supply chains . She emphasizes ICT tools and risk management across industrial and healthcare contexts. Teaching Roles: She lectures on Industry 4.0 for Production Systems and Plants and Manufacturing Systems at the Master’s and Bachelor’s levels in Automotive and Management Engineering. She also supervises PhD students in Management and Production Engineering . PhD Students: Simone Preziosa (2024–ongoing) Abror Hoshimov (2019–2023) Mahsa Mahdavisharif (2019–2023)

Zhenyu YangView profile

Lecturer

• Urban Transportation Network Modeling
• Travel Demand Management
• Transport Economics
• +5 more

Zhenyu Yang is a Lecturer and Postdoctoral Researcher at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the College of Engineering through the Department of Civil Engineering and the Urban Transport Systems Laboratory (LUTS) . He holds a PhD in Industrial System Engineering from the National University of Singapore (2022), an M.Eng from Beijing Jiaotong University, and a Diploma in Transportation Engineering from Huazhong University of Science and Technology. PhD, Industrial System Engineering, National University of Singapore (2022) M.Eng, Beijing Jiaotong University Diploma, Transportation Engineering, Huazhong University of Science and Technology His research focuses on urban transportation network modeling , travel demand management , and traffic information provision , with a strong emphasis on handling uncertainty and optimizing shared mobility systems. Recent work explores reinforcement learning applications, vehicle-drone cooperative delivery , and dynamic incident-responsive traffic systems . His publications highlight advancements in ridesourcing algorithms , congestion pricing , and multi-modal transport regulation . As a lecturer, he teaches Transportation Economics , covering demand-supply dynamics, welfare analysis, and environmental policy in transport systems. He is affiliated with EPFL's Urban Transport Systems Laboratory (LUTS) and contributes to the SGC-ENS teaching unit.

Katherine MilkmanView profile

Professor

• Behavioral Economics
• Judgment and Decision Making
• Behavior Change
• +3 more

Katherine L. Milkman (Katy) is the James G. Dinan Professor at the Wharton School of the University of Pennsylvania, with secondary appointments in Penn's Perelman School of Medicine and School of Arts & Sciences. She co-founded and co-directs the Behavior Change for Good Initiative, a research center dedicated to advancing the science of lasting behavior change. Her work integrates economics and psychology to address challenges like savings, exercise adherence, vaccination rates, and discrimination through large-scale field experiments. Education: PhD in Computer Science and Business from Harvard University; Bachelor's degree (summa cum laude) in Operations Research and Financial Engineering from Princeton University. Research Focus: Milkman's research leverages big data and behavioral science to understand decision-making failures (e.g., self-control, discrimination) and design scalable interventions. Her recent work emphasizes: Nudge-based strategies for education, health, and finance Diversity enhancement in organizational settings Habit formation through incentive structures Publication Trends: Her 15 most recent articles (2022-2025) primarily involve megastudies testing behavioral interventions. Key themes include: leveraging email/reminders to improve math education and vaccination rates; addressing loan delinquency through nudges; and using stereotyping dynamics to increase diversity in hiring. Over 80% employ field experiments across healthcare, finance, and education sectors. Awards & Honors: Thinkers50 Top Management Thinker (2021, 2023) Schmidt Futures Innovation Fellow (2022) Fellow, Association for Psychological Science (2020) Multiple teaching awards from Wharton (2015, 2016) William F. O’Dell Award for impactful research (2017) Advisory & Grants: Milkman has advised major organizations including The White House, Google, Walmart, and the U.S. Department of Defense. Her Behavior Change for Good Initiative secures funding for large-scale social impact research. She hosts Schwab's behavioral economics podcast Choiceology and contributes to policy through op-eds in The New York Times and Scientific American . Labs & Teams: Co-directs the Behavior Change for Good Initiative, collaborating with interdisciplinary researchers (e.g., Angela Duckworth, Sendhil Mullainathan) on longitudinal studies. The initiative designs and tests interventions across health, education, and savings domains.

Qian ZhangView profile

Assistant Professor

• Climate Change Mitigation
• Sustainable Mining
• Life Cycle Assessment
• +7 more

Dr. Qian Zhang serves as Assistant Professor in the Robert M. Buchan Department of Mining at Queen's University's Smith Engineering, leading the Green Mining Value Chain (GreeMVC) Lab. His research develops strategic frameworks for sustainability and resilience throughout mining value chains, with emphasis on climate change mitigation and resource efficiency in global mineral systems. His academic foundation includes a Ph.D. in Urban Engineering from the University of Tokyo (awarded Japanese Government MEXT Scholarship), complemented by MSc and BSc degrees in Environmental Science plus a Minor in Economics from Peking University. Prior to his current role, he conducted postdoctoral research at the University of Victoria and University of Tokyo while consulting for the World Resources Institute on climate-energy initiatives. Dr. Zhang's expertise spans carbon footprint analysis , life-cycle assessment , and industrial ecology applied to mining systems. He employs advanced methodologies including input-output analysis and material flow accounting to model environmental pressures across urban infrastructure and mineral supply chains. His work specifically addresses greenhouse gas accounting, water-energy nexus challenges, and circular economy implementation in resource-intensive sectors. Recent publications reveal strong methodological convergence between artificial intelligence and environmental assessment, particularly in optimizing mining operations through reinforcement learning and geospatial analysis. Key thematic clusters include carbon accounting standardization, critical mineral sustainability, and policy-oriented modeling of environmental pressures throughout mineral value chains. His research program is supported by major competitive grants: NSERC Discovery Grant (2022-2027) SSHRC Institutional Grant (2023, 2025) NSERC Alliance Missions Grant (2023, 2024) Mitacs Accelerate Grant (2023, 2025) NFRF Exploration Grant (2025-2027) NRCan Energy Innovation Program (2025) Dr. Zhang actively mentors a dynamic research group comprising 10+ graduate students and postdocs, securing collaborative funding through institutional and federal channels. His GreeMVC Lab maintains active partnerships with industry leaders and government agencies to translate research into practical sustainability solutions for the mining sector, with current projects focusing on AI-driven fleet management and life-cycle assessment of mineral supply chains. The GreeMVC Lab operates as a multidisciplinary hub with structured mentorship programs, regular industry engagement events, and international collaborations including the COM symposium on sustainable circularity. The lab's physical space in Goodwin Hall supports advanced computational analysis of mining value chains while fostering innovation in green mining technologies through student-led research initiatives.

• Pneumonia
• Clinical Decision-Making
• Medical Informatics
• +3 more

Dr. Barbara E. Jones serves as an Associate Professor in the Department of Internal Medicine at the University of Utah School of Medicine, with dual appointments in Pulmonary and Critical Care Medicine. Her clinical practice spans diverse healthcare settings within the Veterans Affairs system and academic medical centers, focusing on evidence-based adaptation of care to varied patient populations. Her educational background includes: M.D. from University of Washington School of Medicine B.A. in Philosophy from Dartmouth College Master of Science in Clinical Investigation (M.S.C.I) from University of Utah Postdoctoral Fellowship in Pulmonary and Critical Care Medicine at University of Utah Residency in Internal Medicine at University of Utah Dr. Jones' research centers on decision-making processes in pneumonia diagnosis and treatment, employing a tripartite informatics approach combining population analytics, cognitive behavior analysis, and clinical decision support systems. Her work specifically targets reducing diagnostic uncertainty and treatment variation across healthcare systems, with emphasis on equitable care delivery for diverse patient populations. Current projects investigate diagnostic discordance in community-acquired pneumonia, electronic surveillance for hospital-acquired infections, and machine learning applications for diagnostic error detection. Analysis of her 15 most recent publications reveals consistent focus on pneumonia management systems, with emerging emphasis on pandemic impacts on diagnostic practices and AI-driven quality improvement. Her work predominantly utilizes large VA healthcare datasets spanning 100+ medical centers, featuring mixed-methods approaches that integrate quantitative analytics with qualitative clinician experience assessment. Dr. Jones actively contributes to clinical guideline development and medical education through editorial work in major journals including Chest and Annals of Internal Medicine , where she frequently addresses controversies in pneumonia diagnosis and antibiotic stewardship. Her research program operates at the intersection of the University of Utah Health system and the Veterans Affairs national healthcare network, leveraging electronic clinical decision support implementations across diverse hospital settings including rural and critical access facilities. Current initiatives focus on real-time feedback systems for diagnostic performance improvement and automated surveillance for healthcare-associated infections.

• Corporate Finance
• Incentives
• International Business
• +8 more

Edward B. Berk is a Senior Lecturer of Business Administration at Harvard Business School, affiliated with the Finance Unit. He is also the Barry and Teri Volpert Fellow, focusing on corporate finance, private equity, and international business. Education: Harvard Business School (Baker Scholar, Siebel Scholar), Harvard College (BA, magna cum laude), and Ecole Polytechnique (Jean Monnet Fellow). Berk’s research spans private equity investments, operational turnarounds, capital structure, and strategic leadership in consumer-facing industries across Europe and global markets. His work addresses high-growth ventures and cross-border acquisitions. His publications analyze private equity case studies involving turnarounds, mergers and acquisitions, and capital structure optimization, reflecting his expertise in corporate finance and strategic management. Scientific Awards: HBS Student Association Faculty Teaching Award (2018, 2019), Robert F. Greenhill Award (2020). Berk teaches Private Equity Finance (elective curriculum) and Finance I & II (required curriculum). His career includes leadership roles at Bain Capital, where he coordinated European investment committees and drove private equity initiatives.

Lakshmi BalasubramanyanView profile

Associate Professor

• Credit Risk Management
• Operational Risk Modeling
• Fintech
• +4 more

Lakshmi Balasubramanyan is an Associate Professor in the Department of Banking & Finance at Case Western Reserve University's Weatherhead School of Management, joining in 2017. She holds a PhD and MS from Penn State University in quantitative banking analytics, alongside BA/MA degrees from the National University of Singapore. Specializes in AI integration in commercial banking Focuses on credit/operational risk modeling Expert in regulatory frameworks (Dodd-Frank Act) Active media commentator on financial trends Her research bridges traditional banking practices with emerging technologies, particularly through RegTech and FinTech innovations. Key contributions include analyzing bank balance sheet dynamics under liquidity regulations and developing entropy-based approaches to risk heterogeneity. Recent publications explore causal relationships between risk oversight and bank stability, syndicated loan market information asymmetry, and credit market feedback mechanisms. Current projects involve NSF-funded AI-enabled financial ecosystems. Recipient of two CSWEP Research Fellowships Multiple teaching award nominations (2020-2023) 2021 Weatherhead Intramural Grant recipient 2019 UCITE NORD Grant awardee Active in institutional service as Faculty Senate Committee member and Women in Finance advisor. Collaborates with Federal Reserve institutions on banking supervision research.

Gerrit RemaneView profile

Professor

• Digital Transformation
• IT Management
• Business Intelligence
• +7 more

Prof. Dr. Gerrit Remane is a full-time professor at Wedel University of Applied Sciences since 2018, leading the Bachelor's program in IT Management, Consulting, and Auditing (IMCA) and the Master's program in Business Information Systems / IT Management (WIM). He specializes in IT management, business intelligence, and digital transformation, integrating his industry experience from Roland Berger and academic research on digital business models and innovation. Education: Dr. rer. pol (Digital Business Models in the Mobility Sector), Georg-August-University Göttingen (2014–2017) M.Sc. Business Information Systems, Technical University of Munich (2008–2011) B.Sc. Business Information Systems, Wedel University of Applied Sciences (2005–2008) Research Interests: Digital transformation and business model innovation Agile methodologies in enterprise IT Strategic data acquisition and analytics Sustainable IT practices and Green Technology DevOps, BizDevOps, and hybrid project management His recent publications focus on digital business models, agile transformations, and sustainability in IT. He has supervised numerous student seminars on topics like ITIL maturity assessments, data privacy, generative AI use cases, and metaverse applications. While no specific scientific awards are documented, his work has been presented at conferences including AMCIS, ECIS, and WI. Gerrit Remane collaborates with scholars such as S. Schneider, A. Hanelt, and L.M. Kolbe, and his research underscores the integration of IT with organizational strategy.

• Distributed Energy Resources
• Smart Grids
• Distribution Network Automation
• +5 more

Sami Repo is a Professor in Electrical Engineering, focusing on power distribution systems and smart energy technologies. His work spans distribution network automation, flexibility services, and integration of distributed energy resources. Doctor of Science (Technology) in Electrical Engineering (2001) Master of Science (Technology) in Electrical Engineering (1996) His research interests include smart grids, congestion management, and cyber-physical energy systems. Recent publications address challenges in electric vehicle charging, green hydrogen regulation, and photovoltaic revenue optimization. He serves as an examiner and doctoral dissertation opponent, contributing to academic evaluation in electrical engineering programs. Key subtopics include EV charging control, EU energy policy, and renewable energy integration. Examiner for Wenlong Liao (2023): Modelling and optimization of active distribution networks Opponent for Etherden Nicholas (2012): Distributed energy resource hosting capacity