Find Academic Supervisors

• Mechanism Design
• Auction Theory
• Voting Institutions
• +5 more

Benny Moldovanu serves as Professor of Economics at the University of Bonn, where he concurrently holds leadership positions as Director of the Graduate School and founding Co-Director of the Hausdorff Center for Mathematics. His academic influence extends internationally through visiting professorships at the University of Michigan, Northwestern University, Yale University, and University College London. His research program centers on mechanism design, with pioneering applications to auction theory, dynamic pricing systems, competitive contests, and voting institutions. This work bridges theoretical economics with real-world policy challenges, particularly in industrial organization and political economy contexts where strategic decision-making is critical. His methodological approach combines rigorous game-theoretic modeling with practical institutional design. Recent publications demonstrate consistent application of mechanism design principles to contemporary political-economic challenges including Brexit negotiations, two-sided market dynamics, and historical legislative analysis, while maintaining foundational contributions to auction theory and social choice mechanisms. Moldovanu's scientific contributions have earned significant recognition: Fellow of the Econometric Society Max Planck Prize Gossen Prize His professional impact extends beyond academia through advisory roles for major corporations and government entities on auction design and strategy implementation. Editorial leadership includes associate editorships at premier journals such as Econometrica, Journal of Economic Theory, Games and Economic Behavior, and Journal of the European Economic Association. As founding Co-Director of the Hausdorff Center for Mathematics, Moldovanu cultivates interdisciplinary research at the intersection of mathematical theory and economic applications, fostering collaborative projects that address complex institutional design problems through advanced quantitative methods.

Nuri OvücView profile

Professor

• Intermedial Design
• Digital Media
• Information and Communication Design
• +4 more

Nuri Ovüc serves as a Professor at the University of the Arts Bremen (HfK Bremen) within the Faculty of Art and Design's Department of Digital Media. He has been instrumental in the institution since 1993, notably as the initiator and co-founder of the Digital Media degree program (1998–present) and Institute syn (2004), following his 2001 appointment procedure confirming suitability for professorship. His career spans industry roles including System Consultant at Apple Center Hamburg/Bremen (1987–1989) and co-founding ventures like idc atelier gmbh (1991–1993) and development group Coinn (1996–2002). His research centers on Intermedial Design as the critical link between digital media and traditional visual/aesthetic disciplines, emphasizing formal rules of information and communication design within complex media contexts. He investigates design-related aesthetic couplings and discontinuities, framing media as interconnected systems rather than isolated artifacts—a philosophy foundational to Bremen's Digital Media curriculum where students develop visual expression through cross-disciplinary media interactions. Professor Ovüc's innovative work has earned 15 major awards: 2002: Golden City Gate, ITB Berlin (2nd place) 2000: Europrix 2000 Europe's best in multimedia (1st place) 2000: Electronic Administration, Accenture (1st place) 2000: Municipal Internet Offers, Focus (1st Place) 1998: Multimedia Transfer '98, Baden Württemberg (1st place) 1997: Municipalities in Webtest, Speyer University (1st place) 1995: Design Competition NRW Communication Design Award 1990: Typography Germany Design Award 1989: BDG Graphic Design BRD award His research projects include the EU-funded RITTS infrastructure initiative (1997–1998), virtual museum development (1998), Domshof in Bremen cultural project (2000), 'We are building a city' (2000–2001), 'The Fantasy to Power' collaboration (2006–2007), and 'learning by moving' with HsB Bremen (2007). He co-founded design group Know (2010) and maintains active teaching in courses like 'Mishap ... slip-up' and 'From Hölderlin to Nibelungen'.

• International Finance
• Monetary Policy
• EU Economic Architecture
• +2 more

Agnès Bénassy-Quéré serves as Professor of Economics at Paris 1 Panthéon-Sorbonne University and Paris School of Economics, currently on leave to fulfill her role as Deputy-Governor at Banque de France. Her distinguished public service portfolio includes: Chief Economist at the French Treasury (2020-2023) Chair of the French Council of Economic Analysis (2012-2017) Director of CEPII (2006-2012) She additionally contributes to the French macro-prudential authority, tax advisory council, productivity council, and Franco-German council of economic experts. Her research concentrates on International Finance, Monetary Policy, and EU Economic Architecture, with specific expertise in international monetary systems, European fiscal frameworks, and crisis impact analysis. She investigates policy coordination mechanisms and economic governance challenges within the European Union through both theoretical modeling and empirical firm-level studies. Recent publications (2020-2025) reveal consistent analytical focus on euro area reform, fiscal-monetary policy synergies during crises, and equitable international monetary structures. Her work demonstrates methodological rigor through integration of firm-level data analysis with macroeconomic policy evaluation, particularly regarding pandemic impacts and investment frameworks.

Yuhong NanView profile

Associate Professor

• Software Security
• Privacy Leakage Analysis
• IoT Security
• +3 more

Yuhong Nan is an Associate Professor in the School of Software Engineering at Sun Yat-sen University, China, specializing in software security and privacy leakage analysis for emerging platforms including IoT, mobile systems, and blockchain. Previously a Post-doctoral Research Associate at Purdue University under Prof. Dongyan Xu, she builds practical security tools to detect and mitigate vulnerabilities in real-world systems. Dr. Nan earned her PhD from Fudan University in 2018 supervised by Prof. Min Yang. Her academic journey spans rigorous research in security engineering with emphasis on empirical validation and tool development for complex platform ecosystems. Her research program focuses on uncovering systemic security flaws through innovative analysis techniques. Key contributions include vulnerability detection in smart contracts (e.g., state dependencies, reentrancy), privacy leakage analysis in mobile/IoT ecosystems, and countermeasures against deceptive UI patterns. She employs hybrid approaches combining static/dynamic analysis, machine learning, and large-scale empirical studies to develop deployable security solutions. Analysis of her 15 most recent publications (2023-2025) reveals dominant themes in blockchain security (60%), particularly smart contract/DApp vulnerabilities, with significant work in mobile privacy (30%) and cross-platform threats (10%). Her methodology consistently leverages fine-grained static analysis, semantic enrichment, and feedback-driven fuzzing, yielding tools like SmartAxe and Midas that have influenced industry practices. Dr. Nan actively mentors graduate researchers with 17 advisees including Tencent-employed graduates, and serves as a trusted reviewer for premier journals (IEEE TDSC, TMC, TOPS) and conference committees (ASIACCS, ICICS). Her leadership in security communities bridges academic research with practical defense mechanisms. At Sun Yat-sen University, she directs a high-output research group that collaborates with industry partners to address evolving threats in decentralized systems, maintaining her position among top publishing authors in USENIX Security, CCS, and NDSS venues through rigorous technical innovation.

Claire Le GouesView profile

Professor

• Software Engineering
• Program Analysis
• Defect Repair
• +5 more

Claire Le Goues is a Professor of Computer Science at Carnegie Mellon University, primarily affiliated with the Software and Societal Systems Department (S3D) within the School of Computer Science (SCS). She serves as the Associate Department Head for Faculty within S3D and leads the squaresLab research group. Le Goues also co-directs the REUSE@CMU summer program and teaches software engineering and program analysis at undergraduate, master's, and PhD levels. Her research spans software engineering and programming languages, with a particular focus on how to construct, maintain, evolve, improve/debug, and assure high-quality software systems. Le Goues has made significant contributions to automated program repair, program analysis, and defect detection. Her work often bridges theoretical foundations with practical applications, addressing real-world challenges in software development and maintenance. Le Goues' recent publications demonstrate a clear trend toward integrating large language models and generative AI with traditional software engineering techniques. Her research examines how these technologies can enhance program repair (BatFix, AdverIntent-Agent), vulnerability detection (Interpretable Vulnerability Detection Reports), and testing (LWDIFF for WebAssembly). This represents an evolution from her earlier foundational work in program repair (GenProg) toward leveraging contemporary AI advancements. She has mentored numerous students through her squaresLab research group and has been instrumental in developing educational programs that prepare the next generation of software engineers. Le Goues is also known for her advocacy for double-blind review processes in academic conferences, having implemented this approach when co-chairing the Symposium for Search-Based Software Engineering in 2014.

Jinqiu YangView profile

Associate Professor

• software reliability
• quality assurance of machine learning systems
• autonomous vehicles
• +5 more

Jinqiu Yang is an Associate Professor in the Department of Computer Science and Software Engineering at Concordia University in Montreal, Canada. Her research focuses on improving software reliability and quality assurance, particularly in the context of machine learning systems and autonomous vehicles. She leads active research projects in software testing, automated program repair, and mining software repositories, with strong connections to both academic and industrial applications. Her research interests span software reliability, quality assurance of machine learning systems including autonomous vehicles, software testing, automated program repair, text analytics of software artifacts, and mining software repositories. She has developed novel approaches for testing deep learning libraries, evaluating robustness in autonomous driving systems, and tracking the evolution of static code warnings. Her work bridges traditional software engineering with emerging challenges in AI systems, addressing critical issues of reliability and safety in complex software environments. Yang's recent publications (2021-2025) demonstrate a clear trajectory toward AI/ML system reliability, with increasing focus on autonomous vehicles, concept drift detection, and security aspects of large language models. Her work spans both theoretical foundations and practical applications, often involving empirical studies of real-world systems and development of practical tools to address identified challenges. ACM SIGSOFT Distinguished Paper Award Dr. Yang actively mentors graduate students and is currently recruiting Master's and PhD candidates. She has secured significant research funding including NSERC Discovery Grants (2019-2025), Gina Cody Research and Innovation Fellowship (2024-2026), and participation in the NSERC CREATE Program SE4AI (2021-2026). Her research is supported by multiple grants including NOVA – FRQNT-NSERC PROGRAM (2024-2027) and Volt-Age Seed Grant (2024-2026). She leads research in the O-RISA Lab at Concordia University, focusing on reliability and security aspects of intelligent software systems. Her team collaborates with industry partners including IBM, where she previously worked at IBM Watson Research Lab and IBM CAS, bringing practical experience to her academic research.

Michaela NoreikView profile

Professor

• Obesity Research
• Geriatric Nutrition
• Dietetics
• +3 more

Prof. Dr. Michaela Noreik serves as Professor in the Department of Nutritional Science at Niederrhein University of Applied Sciences, Mönchengladbach, where she teaches Interdisciplinary Casework, Planetary Health Diet, and Special Seminar in Nutrition Research. She directs the Laboratory for Nutritional Status and maintains active consultation hours for student engagement. Her educational foundation includes a Dr. rer. medic. in nutritional therapy evaluation from Universität zu Köln (2009-2012) and dual degrees in Oecotrophology (Fachhochschule Münster) and Nutrition and Dietetics (Fachhochschule Nimwegen, NL) completed between 2004-2008. Noreik's research centers on obesity interventions, geriatric nutrition, and sustainable dietary systems. She leads projects including OWL (Online Weight Loss programmes), CReDDI (dietary intervention metabolism studies), and SwapSHOP (digital grocery interventions). Her work bridges clinical practice with academic rigor, emphasizing evidence-based approaches to nutritional assessment and therapy standardization. Recent publications (2013-2021) reveal strong focus on digital health interventions for weight management, dietary approaches to type 2 diabetes, and nutritional implications in neurodegenerative conditions. Her methodology frequently employs randomized controlled trials and systematic reviews, with growing emphasis on planetary health frameworks and sustainable food systems. Her scientific recognition includes: 2019 Award of Excellence for Consistent Outstanding Performance (Oxford University) Noreik has secured significant third-party funding for clinical studies in obesity and oncology during her Oxford tenure. Current student projects involve developing nutrition assessment databases and implementing mobee®360 digital platforms. She actively supervises interdisciplinary casework modules with healthcare disciplines. She established the Laboratory for Nutritional Status at Niederrhein University and previously built nutrition teams at St. Marien-Hospital Köln. Her international collaborations include Hogeschool van Arnhem en Nijmegen and Umeå University for planetary health initiatives, reflecting her commitment to transnational research networks.

Antonio MastropaoloView profile

Assistant Professor

• Artificial Intelligence
• Natural Language Processing
• Software Engineering
• +6 more

Dr. Antonio Mastropaolo is an Assistant Professor of Computer Science at William & Mary, USA. His research lies at the intersection of Artificial Intelligence, Natural Language Processing, and Software Engineering, with a strong emphasis on the automation of SE-related practices. He promotes explainability, efficiency, and optimization from both model-centric and output-centric perspectives. His research interests focus on the reliability and efficiency of AI systems for software engineering. He investigates robustness and adaptability of foundation models like GitHub Copilot, as well as documentation and summarization of code components. His work addresses critical challenges in AI-driven software development including transparency, scalability, and developer productivity. His publication portfolio shows a strong trend toward neurosymbolic approaches that combine neural learning with symbolic reasoning. Recent articles explore quantization of large code models, code summarization optimization, and resource-efficient AI for software engineering. His work spans both theoretical foundations and practical applications, with emphasis on empirical validation of AI techniques in real-world SE contexts. Distinguished Reviewer Award for service on FSE'25 program committees Distinguished Reviewer Award at ASE 2024 Distinguished Paper Award for 'Unveiling ChatGPT's Usage in Open Source Projects' at MSR'24 Distinguished Paper Award for 'How do Hugging Face Models Document Datasets, Bias, and Licenses?' at ICPC'24 Dr. Mastropaolo advises PhD students, with Saima recently starting her PhD journey with a publication in FORGE 2025. He received an NSF Grant (#2451058) in April 2025 for research on efficient and responsible AI for software engineering. His service includes committee membership for major conferences including ASE, ICSE, ICSME, and FSE across multiple tracks including Research Papers, NIER, and Tool Demonstrations.

Dongdong SheView profile

Assistant Professor

• Security
• Machine Learning
• Fuzzing
• +3 more

Dongdong She is an Assistant Professor in the Department of Computer Science and Engineering at The Hong Kong University of Science and Technology (HKUST). His research focuses on the intersection of security and machine learning, applying data-driven approaches to solve security problems. He has established himself as a prominent researcher in software security and fuzzing techniques with publications in top conferences including IEEE S&P, CCS, and USENIX Security. Dr. She received his Ph.D. from Columbia University's Department of Computer Science, where he worked with Professors Suman Jana and Baishakhi Ray. Prior to Columbia, he conducted research with Zhiyun Qian on Android Security at the University of California, Riverside. He completed his undergraduate studies at Huazhong University of Science and Technology. His research spans two main areas: LLM Security, which investigates the security of large language models and LLM-powered systems, and LLM for Traditional Security, which leverages LLMs to solve traditional security problems such as program analysis and vulnerability discovery. His work often combines machine learning techniques with traditional security approaches to develop innovative solutions for software security challenges. Dr. She's publication record shows a consistent evolution from foundational work in neural network-assisted fuzzing (NEUZZ) toward more advanced applications in LLM security and program analysis, demonstrating both theoretical rigor and practical impact with techniques adopted by the security community. Among his notable achievements: Distinguished Paper Award at ISSTA 2025 Distinguished Paper Award at IEEE S&P 2025 Best Paper Award Runner-Up at CCS 2022 Second Place in SBFT 2024 Fuzzing Competition Finalist in 2019 NYU CSAW Applied Research Competition Dr. She currently advises several Ph.D. students including Yuchong Xie, Shuangjie Yao, and Qiao Zhang, who began their studies in Fall 2024. He serves on program committees for major conferences including ASE 2025, where he is a PC Member for the Research Papers track. His research is supported by grants enabling his team to pursue innovative approaches at the intersection of machine learning and security. His research group maintains active collaborations with institutions worldwide and contributes to open-source security tools that are widely used in both academia and industry, with a particular focus on developing advanced techniques for software security analysis through the application of machine learning.

Jingling XueView profile

Professor

• Programming Languages
• Compilers
• Program Analysis
• +5 more

Jingling Xue is a Scientia Professor at the School of Computer Science and Engineering at the University of New South Wales (UNSW) in Sydney, Australia. As an IEEE Fellow of the Computer Society, he leads the Programming Languages and Compilers research group, focusing on practical applications of compiler optimization and program analysis techniques. His work bridges theoretical foundations with real-world software systems, particularly in developing open-source tools for large-scale program analysis. Professor Xue received his B.Eng and M.Eng degrees from Tsinghua University in 1984 and 1987, respectively, followed by a PhD from the University of Edinburgh in 1992. His academic journey has established him as a leading figure in programming languages and compiler technology. Xue's research spans programming languages, compiler technology, and program analysis with emphasis on practical relevance. His current projects include compiler techniques for improving parallelism and locality, pointer/alias analysis for million-line-scale programs, and static/dynamic analysis for detecting bugs and security vulnerabilities in real-world applications like web browsers and Android apps. His group actively develops open-source tools to support scientific replicability and reproducibility in these areas. His recent publications demonstrate a strong focus on applying program analysis techniques to modern challenges including AI compilers, homomorphic encryption, security vulnerability detection, and graph processing systems. The work shows evolution from traditional compiler optimization to addressing emerging domains like privacy-preserving computation and deep learning systems while maintaining rigorous theoretical foundations. Scientific Awards: Best Paper Award at CGO'13 Best Paper Award at CGO'16 Distinguished Paper Award at ECOOP'16 Distinguished Paper Award at ICSE'18 Distinguished Paper Award at ISSTA'19 Distinguished Paper Award at ASE'19 Distinguished Artifact Award at ISSTA'23 Best Artifact Award at FSE'23 Distinguished Paper Award at ASE'23 Test-of-Time Award at CGO'21 Professor Xue has successfully supervised 30 PhD students to completion, many of whom now work as professors or researchers in academia and industry. He has served as Program Chair for major conferences including LCTES'13, CC'18, CGO'20, and General Chair for LCTES'20. His group currently focuses on memory safety in Rust, smart contract analysis, AI compilers, compilation for privacy-preserving computation, and adversarial attacks in deep learning. The Programming Languages and Compilers group maintains strong connections with industry partners, translating theoretical advances into practical tools for real-world software development challenges. Their work on pointer analysis, memory safety, and compiler optimizations continues to influence both academic research and industrial practice.

Shaohua LiView profile

Assistant Professor

• Software Engineering
• Programming Languages
• Security
• +3 more

Shaohua Li is an Assistant Professor at The Chinese University of Hong Kong (CUHK), specializing in the correctness and security of critical software systems with emphasis on compilers. His research spans Software Engineering , Programming Languages , and Security , focusing on innovative compiler testing methodologies. Key areas include leveraging large language models for test generation, optimizing fuzzing techniques through prefix-guided execution, and decoupling sanitization mechanisms to reduce overhead in vulnerability detection. His work addresses fundamental challenges in ensuring reliability of systems programming infrastructure. Recent publications demonstrate a cohesive trajectory toward practical compiler validation: from empirical rustc bug analysis to SAND's low-overhead sanitization framework. The research consistently bridges theoretical formal methods with real-world implementation challenges in security-critical systems, showing particular strength in adapting AI techniques for traditional software testing problems.

Daye NamView profile

Assistant Professor

• Software Engineering
• Artificial Intelligence
• Human-Computer Interaction
• +3 more

Daye Nam is an Assistant Professor in the Department of Informatics at the University of California, Irvine, where they design, build, and evaluate AI tools for developers using natural language processing techniques. Their work sits at the intersection of software engineering, artificial intelligence, and human-computer interaction, with a strong focus on creating useful and usable tools that make software development more accessible, efficient, and enjoyable. Education PhD in Software Engineering, Carnegie Mellon University (2018-2024) MS in Computer Science, University of Southern California (2016-2018) BS in Computer Science, Yonsei University (2012-2016) Research Interests Dr. Nam's research focuses on designing, building, and evaluating AI tools for programmers at all levels, with an emphasis on making these tools both useful and usable. Their work spans several key areas including machine learning for software engineering (ML4SE), developer experience, and human-AI interaction. They employ a user-centered approach that involves conducting empirical studies to understand programmers' needs, building and training machine learning models based on those insights, creating tools for programmers, and evaluating them using human-computer interaction methods. Their research has particular relevance to AI-powered developer tools, API documentation and discovery, and educational applications of AI for programming students. Publications and Research Trends Dr. Nam's recent publications demonstrate a clear trajectory toward understanding and improving how developers interact with AI systems. Their work increasingly focuses on empirical studies of developer-AI interaction, particularly with large language models for code generation and understanding. There's a strong emphasis on understanding trust in AI systems among developers, measuring the actual impact of AI on development speed, and designing tools that balance automation with user control. Their research methodology often combines log analysis, user studies, and the development of novel AI-powered tools that address specific developer pain points. Scientific Awards and Honors Best Tool Paper Award at ASE ACM Student Research Competition 2nd Place SIGSOFT CAPS Student Travel Award for FSE ACM SIGSOFT NSF Travel Award NSF Travel Award for ICSE SIGSOFT Best Research Award from University of Southern California Teaching and Service Dr. Nam teaches SWE 233: Intelligent User Interfaces at UC Irvine, guiding students through the design and evaluation of AI-powered interfaces for software development. They have previously served as a Teaching Assistant and Co-Instructor for Foundations of Software Engineering at Carnegie Mellon University. In terms of service, they've been on program committees for major software engineering conferences including ICSE, ASE, and FSE, and have reviewed papers for journals like TOSEM and Empirical Software Engineering. They've also been active in student support programs, organizing and mentoring for graduate applicant support initiatives.

Tanja PenterView profile

Professor

• History of Ukraine, Russia, and the Soviet Union
• Dictatorship comparison (Stalinism vs. National Socialism)
• Holocaust and civilian victims
• +4 more

Prof. Dr. Tanja Penter is a Professor of Eastern European History at Ruprecht-Karls-University Heidelberg since 2013. Her research focuses on 19th-20th century Ukraine/Russia/Soviet Union, Stalinism vs. National Socialism, Holocaust studies, transitional justice, and memory politics. She leads the DFG-GRK 2840 'Ambivalent Enmity' and directs the Research Centre on Antiziganism. Education/Positions: PhD (1999, Cologne), Habilitation (2008, Bochum), prior roles at Hamburg University and Humboldt University Berlin. Awards include the 2011 René Kuczynski Prize for her book Coal for Stalin and Hitler . Publications span over 70 works, including monographs on Odessa 1917 and Donbas labor history. Key areas include Nazi/Soviet collaboration trials, Holodomor legacy, and post-Soviet victim compensation. She advises on historical commissions (e.g., German-Ukrainian, German-Russian) and contributes to encyclopedic projects on Nazi genocide. Teaching: Exam authority across all history programs at Heidelberg. Consultation hours during lectures: Wednesdays 11:00-12:30.

• Sociology of Gender
• Sociology of Human Differentiation
• Sociology of the Body
• +4 more

Marion Müller is a Full Professor (W3) of Sociology with focus on Gender Studies at the University of Tübingen, affiliated with the Faculty of Economics and Social Sciences and the Department of Sociology. She has held this position since 2016 after serving as Junior Professor at the University of Trier (2013-2016). Her academic background includes a dissertation from Bielefeld University (2008) and sociology degree from Johannes Gutenberg University Mainz (2002), with studies spanning sociology, political science, and cultural anthropology. Her research program examines complex social differentiation mechanisms through multiple lenses: Theoretical frameworks: General sociology, interaction theory, globalization studies Human differentiation: Gender, ethnicity, disability, and categorical boundary formation Embodied practices: Sociology of the body, sports sociology, pregnancy/childbirth Global systems: World society theory, institutional categorization, human rights Publication analysis reveals consistent focus on deconstructing social categorization in bodily practices—particularly in sports contexts—with evolving attention to global governance mechanisms. Recent works examine institutional categorization of indigenous peoples and disability, building on earlier sports-related gender/ethnicity research. Major recognitions include: Fritz Thyssen Foundation Prize (2014) for racial category analysis German Sociological Association dissertation award (2010) Bielefeld University dissertation prize (2009) DGS qualification thesis award (2002) Teaching responsibilities span bachelor/master programs in sociological theory, gender studies, and qualitative methods. Student advising occurs through scheduled office hours and thesis colloquia, though no specific grant or lab information is documented.

Volker StefanskiView profile

Professor

• Animal Physiology
• Immunology
• Stress Biology
• +3 more

Prof. Dr. Volker Stefanski is a University Professor (W3) at the University of Hohenheim's Faculty of Agricultural Sciences, leading the Department of Behavioral Physiology of Livestock. He holds a Dr. rer. nat. from Bielefeld University (1991) and has held roles including Postdoc at UCLA (1993-1995), Research Associate and Privatdozent at the University of Bayreuth (1995-2005), and Head of Immunology at the Leibniz Institute for Zoo and Wildlife Research (2006-2009). His research focuses on stress biology, immunology, and animal physiology, particularly in livestock like pigs and laboratory models. Key areas include hormonal stress responses, immune system dynamics, and the interplay between social stress and health outcomes in animals. His work spans from molecular mechanisms (e.g., catecholamine effects on Salmonella) to applied studies on housing conditions and immunological practices in agriculture. Selected projects explore diurnal rhythms in pig immunity, microbiome shifts due to diets, and maternal stress impacts on offspring. His research emphasizes translational applications for improving animal welfare and disease resistance in farming systems. He contributes to interdisciplinary collaborations, integrating physiology, immunology, and behavioral studies.