جست‌وجوی استاد و پژوهشگر

Paul Gölzمشاهده پروفایل

استادیار

• Social Choice Theory
• Algorithmic Fairness
• AI Ethics
• +۳ مورد دیگر

Paul Gölz is an Assistant Professor at Cornell University's School of Operations Research and Information Engineering (ORIE), with affiliations in Computer Science. His research focuses on computational social choice, algorithmic fairness, and AI ethics, addressing topics like democratic innovation, fair resource allocation, and AI systems for diverse users. Education: Undergraduate studies at Saarland University (Germany), PhD in Computer Science from Carnegie Mellon University, followed by postdoctoral research at Harvard University, UC Berkeley, and the Simons Laufer Mathematical Sciences Institute. His work has been recognized with awards including the JPMorgan Chase AI Research Fellowship (2021) and honorable mentions for prestigious dissertation awards (Dantzig and ACM SIGecom). Research Highlights : Developed Panelot, a tool for selecting citizens' assemblies using state-of-the-art algorithms. His work on fair refugee resettlement and apportionment methods has been featured in Operations Research and Nature . Recent projects include AI alignment distortion analysis and generative social choice mechanisms. Teaching : Teaches Optimized Democracy (Spring 2025) and Mathematical Programming (Fall 2024). Supervises PhD students in ORIE, focusing on interdisciplinary applications of optimization and social choice. Awards & Grants : Received a $40K Structural Democracy Fellowship (Crankstart) and an OpenAI grant for Democratic Inputs to AI. Active in policy briefs (e.g., mini-public selection strategies). Labs/Tools : Co-developed Panelot.org , a nonprofit platform for fair citizen assembly selection. Active in open-source tool development for social choice applications.

Steve Chaseمشاهده پروفایل

استاد

• Computational Neuroscience
• Neural Engineering and Technology
• Systems Neuroscience
• +۴ مورد دیگر

Steve Chase is a Professor at Carnegie Mellon University , affiliated with the Biomedical Engineering , Electrical and Computer Engineering , Neuroscience Institute , and Robotics Institute departments. His research spans Computational Neuroscience , Neural Engineering , and Systems Neuroscience , with a focus on neural circuits, motor control, and brain-computer interfaces (BCI). Research Areas: Sensation & Perception, Methods Development, Diseases & Disorders, Physiological & Anatomical Methods. Lab Highlights: Development of the RotaWheel, memory trace studies in the motor cortex, and investigations into BCI stabilization and learning dynamics. Scientific Contributions: His lab has published extensively in journals like Neuron , Nature Computational Science , eLife , and PNAS , with notable works on neural activity patterns, dimensionality reduction in calcium imaging, and sensory constraints on motor cortex modulation. Students and postdocs in his lab have received awards, including the CNBC best paper award.

Lawrence C. Washingtonمشاهده پروفایل

استاد

• Number theory
• Cyclotomic fields
• Elliptic curves
• +۵ مورد دیگر

Lawrence C. Washington is a Professor of Mathematics at the University of Maryland, College Park . His office is located in Mathematics Building 1105, and he can be reached at lcw@math.umd.edu . Teaching & Courses: In Spring 2023 he is teaching Cryptography 456 (TuTh 11:00–12:15) and co-organising the Algebra Seminar (MW 2–3). Office hours are held Tuesdays 1:30–2:30 and Thursdays 10:00–10:50. Research Interests: His work centres on number theory , with particular emphasis on cyclotomic fields , elliptic curves , cryptology , and Iwasawa theory . He has made extensive contributions to the study of p-adic L-functions , class groups , heuristics for class numbers , and the arithmetic of elliptic curves, often bridging deep theoretical questions with computational investigations. Textbooks & Scholarly Output: Washington is the author of several widely-used textbooks: Introduction to Cryptography with Coding Theory (3rd ed.) Introduction to Cyclotomic Fields Elliptic Curves: Number Theory and Cryptography An Introduction to Number Theory with Cryptography (2nd ed.) Elementary Number Theory Recent Publication Trends: Over the past five years his papers have focused on heuristics for Iwasawa invariants , anti-cyclotomic extensions , class groups of real cyclotomic fields , and analytic estimates for sums of prime powers . The work is characterised by a synthesis of algebraic, analytic, and computational techniques, frequently yielding explicit examples and numerical data that inform broader conjectures in algebraic number theory. Extracurricular Interests: Outside mathematics, Washington enjoys running and playing the bassoon , and he maintains a light-hearted page devoted to his favourite intersection in Chevy Chase, MD. Advising & Grants: While the provided text does not enumerate individual students or specific grants, his extensive publication record and long-standing professorship indicate ongoing supervision of graduate research and participation in funded projects in number theory and cryptography.

• Radiation Oncology
• Medical Physics
• Treatment Planning Techniques
• +۵ مورد دیگر

Dr. Sotirios Stathakis is Chief of Physics at the Mary Bird Perkins Cancer Center (2023–Present) and Associate Director of the Medical Physics Division at the University of Texas Health Science Center San Antonio (2017–2022). He holds an Adjunct Professor position at Louisiana State University's Department of Physics and Astronomy (2023–Present). His expertise lies in radiation oncology and medical physics, with a focus on patient-specific quality assurance, dose verification, and advanced treatment techniques like adaptive radiation therapy and SBRT. Education: Ph.D., Medical Physics, University of Patras (2005) M.S., Medical Physics, University of Aberdeen (1997) B.S., Physics (minor in Mathematics and Computer Science), University of Waterloo (1995) Research Interests: Patient-specific quality assurance Daily dose verification Treatment planning techniques Adaptive radiation therapy Stereotactic body radiation therapy (SBRT) Automation and workflow optimization in radiation oncology Publications: Over 20 peer-reviewed articles since 2020, focusing on topics like Monte Carlo simulations, AI-driven beam analysis, and AAPM task group recommendations for IMRT verification. Key themes include improving dose accuracy, equipment validation, and clinical implementation of advanced radiation technologies. Grants & Awards: Not explicitly listed in provided text. Labs/Teams: Collaborates with institutions like Fox Chase Cancer Center, South Texas Veterans Health Administration, and LSU on medical physics research and clinical applications.

Brandon M. Stewartمشاهده پروفایل

دانشیار

• Quantitative Methods
• Statistical Methods
• Text Analysis
• +۵ مورد دیگر

Brandon M. Stewart is an Associate Professor of Sociology at Princeton University with extensive interdisciplinary affiliations. He serves as Director of the Statistics Core at the Office of Population Research and maintains formal connections with the Politics Department, Princeton Institute for Computational Science and Engineering, Center for Information Technology Policy, and Center for the Digital Humanities. Stewart holds editorial leadership as Co-Editor-in-Chief of Political Analysis and Associate Editor at Sociological Methods & Research . His educational background includes: Ph.D. in Government from Harvard University (2015) Master's degree in Statistics from Harvard University (2014) Stewart's research pioneers innovative quantitative methods for social science applications, specializing in automated text analysis and modeling complex heterogeneity in regression. His methodological frameworks enable researchers to uncover hidden structures in large datasets that were previously too costly or impossible to analyze. While his recent work has focused on using newspaper archives to study propaganda mechanisms in contemporary China, his tools are deliberately designed for broad applicability across diverse domains including education, human trafficking, forced migration, international relations, constitutional law, and psychology. His publication record demonstrates consistent innovation at the intersection of statistics, machine learning, and social inquiry. Stewart's work shows a clear trajectory from foundational methodological development to practical implementation across numerous substantive areas, with recurring themes of enhancing causal inference with textual data, developing robust topic modeling techniques, and creating accessible computational tools for social scientists. Stewart's scholarly excellence has been recognized through multiple prestigious awards: 2024 Leo Goodman (Early Career) Award from the Methodology Section of the American Sociological Association 2023 Emerging Scholar Award from the Political Methodology Society Edward R Chase Dissertation Prize Gosnell Prize for Excellence in Political Methodology Political Analysis Editor's Choice Award Recognition for Excellence in Mentoring Graduate Students As a mentor, Stewart has guided several successful graduate students to faculty positions at institutions including UCLA and Georgetown. His collaborative approach is evident in numerous multi-author projects spanning disciplines from political science to computational linguistics. His leadership extends to the Sociology Statistics Reading Group, which he founded to foster interdisciplinary methodological exchange, and his summer methods camp that trains social scientists in advanced quantitative techniques.

• Wireless Communications
• Mobile Communication Systems
• mm-wave/sub-THz Communication
• +۶ مورد دیگر

Tommy Svensson is a Professor of Communication Systems at Chalmers University of Technology, where he leads research on wireless systems on air interface and wireless backhaul network technologies. He received his Ph.D. in information theory from Chalmers in 2003 and has extensive industry experience from Ericsson AB, working with core, radio access and microwave networks. His primary research interests include: Design and analysis of mobile communication systems Physical storage algorithms Multi-user access and resource allocation Cooperative/context-aware/secure communication mm-wave/sub-THz communication C-V2X and JCAS Satellite networks Sustainable design and comprehensive architecture Professor Svensson has been actively involved in numerous European research projects including WINNER I/II/+, ARTIST4G (contributing to 3GPP LTE standards), METIS, mmMAGIC, and 5GCar (towards 5G), and Hexa-X, RISE-6G, SEMANTIC, ROBUST-6G, and ECO-eNET (towards 6G). He also contributes to the Chase/ChaseOn and WiTECH antenna systems center of excellence at Chalmers, focusing on mm-wave and (sub)-THz solutions for various wireless scenarios. His publication record is extensive, with 6 books, 111 journal papers, 151 conference papers, and 80 public EU project deliverables to his name. Professionally, he serves as: Founding member/editor of the IEEE JSAC Series on Machine Learning in Communications and Networks Chair of the award-winning IEEE Sweden Vehicular Technology/Communications/Information Theory Societies chapter Editor of IEEE Transactions on Wireless Communications and IEEE Wireless Communications Letters Lead local organizer of EuCNC & 6G Summit 2023 Coordinator of the Communication Engineering Master's Program at Chalmers

Andreas Peter Burgمشاهده پروفایل

دانشیار

• Circuits and systems for telecommunications
• Silicon implementation of communication technologies
• Communication algorithms optimization
• +۵ مورد دیگر

Andreas Peter Burg is a Tenured Associate Professor at the École Polytechnique Fédérale de Lausanne (EPFL), where he leads the Telecommunications Circuits Laboratory (TCL) within the School of Engineering. He holds multiple academic and administrative roles at EPFL including Associate Professor in Teaching (SEL, EDMI, EDEE), Director of SEL Management, and Member of the Doctoral Program Committee for Electrical Engineering. Dr. Burg received his Dipl.-Ing. degree in 2000 and Dr. sc. techn. degree in 2006 from ETH Zurich. His academic career includes positions as SNF Assistant Professor at ETH Zurich (2009-2011) before joining EPFL in January 2011 as a Tenure Track Assistant Professor, where he was promoted to Tenured Associate Professor in June 2018. His research focuses on circuits and systems for telecommunications , with particular expertise in silicon implementation of communication technologies, communication algorithms optimization for hardware, low-power VLSI signal processing, and digital integrated circuits. His work bridges theoretical communication concepts with practical circuit implementations, addressing challenges in wireless and wired communication systems. His recent publications (2024-2025) demonstrate a strong focus on next-generation communication technologies including 6G systems, advanced error correction coding, wireless sensing applications, and ultra-low power circuit design. These works span multiple subfields from LDPC and polar code decoding to RF signal processing and machine learning applications in wireless systems. Willi Studer Award (2000) ETH Medal for diploma thesis (2000) ETH Medal for Ph.D. dissertation (2006) Swiss National Science Foundation Assistant Professorship grant (2008) Dr. Burg has been involved in the development of more than 25 ASICs throughout his career and co-founded Celestrius, an ETH spinoff in MIMO wireless communication. His laboratory work focuses on practical implementations of communication algorithms with emphasis on power efficiency and hardware optimization. Current research directions include 6G technologies, wireless sensing applications, and novel error correction techniques for next-generation communication systems.

Prabhanjan Ananthمشاهده پروفایل

استادیار

• Cryptography
• Theoretical Computer Science
• Post-Quantum Cryptography
• +۳ مورد دیگر

Prabhanjan Ananth is an Assistant Professor in the Department of Computer Science at the University of California, Santa Barbara (UCSB), holding the Glen and Susanne Culler Endowed Chair in Computer Science. He earned his Ph.D. from UCLA in 2017, followed by a postdoctoral fellowship at MIT's CSAIL. His research focuses on cryptography, particularly in classical and post-quantum cryptography, with emphasis on unclonable primitives, pseudorandomness, and cryptographic protocols. Education: Ph.D. in Computer Science from UCLA (2013–2017), postdoctoral research at MIT (2017–2019). Research Interests: His work spans theoretical computer science and cryptography, including post-quantum security, quantum-resistant systems, and unclonable cryptographic primitives. He explores topics like pseudorandomness in quantum models, revocable encryption, and cryptographic protocols for multi-user environments. Recent Publications: His 2025 work advances revocable encryption and pseudorandom unitaries in quantum models. He also contributes to unclonable secret sharing and modular cryptographic design. His research often bridges theoretical foundations with practical applications in quantum-safe systems. Awards: Glen and Susanne Culler Endowed Chair in Computer Science (UCSB). Advising: Current Ph.D. advisees include Aditya Gulati, Yao-Ting Lin, and Divyanshu Bhardwaj. Past students have secured roles at institutions like JPMorgan Chase and EPFL. Teaching: Teaches courses on automata theory (CS 138) and cryptography (CS 178), emphasizing rigorous mathematical proofs and foundational concepts.

Shuangquan Wangمشاهده پروفایل

استادیار

• Mobile & Wearable Computing
• Activity Recognition
• Smart Health
• +۳ مورد دیگر

Shuangquan (Peter) Wang is an Assistant Professor of Computer Science at Salisbury University. He holds a PhD in Computer Science from the College of William & Mary (2020) and a PhD in Pattern Recognition and Intelligent Systems from Shanghai Jiao Tong University (2008), along with earlier degrees from Wuhan University of Technology and Wuhan Institute of Technology. His research focuses on mobile/wearable computing, activity recognition, smart health, and machine learning. He has over 10 years of experience in academia and industry, including roles at Philips Research East Asia and Nokia Research Center (Beijing). His work emphasizes wearable sensor-based health monitoring, such as fall detection, mastication analysis, and Parkinson’s disease monitoring. He leads the WISH Research Lab and serves as an Associate Editor for Elsevier's Smart Health Journal. Recent contributions include papers on salinity anomaly detection (2024), LLM-based user requirement analysis (2024), and socially acceptable food recognition (2022). His research trends emphasize interdisciplinary applications of machine learning in healthcare and sensor-driven human activity analysis. Professional service roles include coordinating Salisbury University’s Center for Applied Mathematics and Science (2021–2024) and chairing ACM/IEEE CHASE conferences. He has delivered invited talks on artificial intelligence and its societal impacts to diverse audiences, including the Institute of Retired Persons at Salisbury University. His lab, WISH Research Lab, explores innovative solutions in smart health and mobile computing, integrating wearable technologies with machine learning for real-world health applications.

Keith Deckerمشاهده پروفایل

دانشیار

• Multi-Agent Systems
• Artificial Intelligence
• Distributed Artificial Intelligence
• +۹ مورد دیگر

Keith Decker is an Associate Professor and JPMorgan Chase Fellow in the Department of Computer and Information Sciences at the University of Delaware's College of Engineering. He holds multiple affiliated faculty positions at the Artificial Intelligence Center of Excellence, Data Science Institute, Center for Bioinformatics and Computational Biology, and Institute for Financial Service Analytics. His research spans several key areas of computer science with a focus on Multi-Agent Systems , Distributed Artificial Intelligence , Computational Organization Design , and Bioinformatics . His work bridges theoretical foundations with practical applications in finance, healthcare, and information systems. Dr. Decker's publications reflect trends in distributed AI with emphasis on coordination technologies, agent communication, and information gathering systems. His work has evolved from foundational multi-agent coordination theory to applications in bioinformatics, financial services, and health informatics. DARPA special recognition award for foundational research in coordination technologies Dr. Decker has advised numerous graduate students and led significant research projects including automated genetic annotation, coalition management for electric vehicle-to-grid power systems, and machine learning for automated health coaching. His interdisciplinary work demonstrates strong connections between theoretical AI research and practical applications across multiple domains. He maintains active leadership roles in the academic community, having served as program co-chair for the International Conference on Autonomous Agents and Multi-Agent Systems and other major AI workshops.

• Databases
• Web Data Management
• Logical Methods in Computer Science
• +۴ مورد دیگر

Michael Benedikt is a Professor of Computer Science at the University of Oxford and a Governing Body Fellow of University College. He holds the role of Director of the Advanced MSc in Computer Science program. His research focuses on databases, Web data management, logical methods in computer science, and theoretical computer science. Benedikt's work intersects with artificial intelligence, machine learning, and algorithms, with contributions to query languages, data integration, and formal methods. Education: Ph.D. in Mathematics, University of Wisconsin, 1993 Prior roles: Distinguished Member of Technical Staff at Bell Laboratories (1994–2006), visiting researcher at Yahoo! Labs Research Interests: Databases and information exchange Web and Web 2.0 data management Logical methods in computer science Formal verification and query optimization Applications in AI and machine learning Key Projects: FOX : Query-driven data acquisition from web-based sources PDQ : Proof-driven query answering over web-based data TRANCE : Transforming nested collections efficiently Awards: Best Paper Award at ICALP 2017 (Track B) EPSRC Established Career Fellowship (2015–2020) Advising & Grants: Directed the MSc in Advanced Computer Science program Supervised PhD students including Chia-Hsuan Lu and past advisees such as Luying Chen and Ben Spencer Received funding for projects like the ERC DIADEM initiative Labs & Teams: Active in the Department of Computer Science’s research groups, including the Algorithms At Large and Databases teams.

Rahul Jainمشاهده پروفایل

استاد

• Quantum Computation
• Information Theory
• Complexity Theory
• +۳ مورد دیگر

Rahul Jain is a Professor in the Department of Computer Science at the National University of Singapore (NUS), School of Computing. He was promoted to full Professor from January 2020, having previously served as Associate Professor (July 2013-July 2013) and Assistant Professor (November 2008-July 2013). He is also a Principal Investigator at the Centre for Quantum Technologies (CQT), Singapore since November 2008. Dr. Jain earned his Ph.D. in Computer Science from Tata Institute of Fundamental Research, Mumbai (2003) and B.Tech. in Electrical & Electronics Engineering from Indian Institute of Technology, Mumbai (1997). Prior to joining NUS, he conducted postdoctoral research at UC Berkeley (2004-2006) and at the Institute for Quantum Computing, University of Waterloo, Canada (2006-2008). His research spans quantum computation, information theory, complexity theory, communication complexity, and cryptography. Dr. Jain has made significant contributions to quantum information theory, particularly in quantum communication complexity, quantum key distribution, and quantum algorithms. His work bridges theoretical computer science with quantum information processing, exploring fundamental limits of quantum computation and communication. His research demonstrates strong expertise in both theoretical proofs and practical applications of quantum information principles. Analysis of Dr. Jain's recent publications (2022-2025) reveals a consistent focus on quantum cryptography foundations, quantum communication protocols, and quantum information theory. His work frequently appears in top theoretical computer science venues including FOCS, STOC, and QIP, as well as leading journals like IEEE Transactions on Information Theory. Key themes include non-malleable quantum codes, quantum state redistribution, quantum communication complexity, and quantum cryptographic protocols with rigorous security proofs. Award under the VISITING ADVANCED JOINT RESEARCH FACULTY SCHEME (VAJRA) 2017-18 by Department of Science and Technology, Government of India BEST of 2016 by ACM Computing Reviews Young Researcher Award, National University of Singapore, 2012 Best paper award at STOC 2010 IBM Distinguished Dissertation Award, 2005 TAA-Sasken Best Thesis Award, 2005-2006 Dr. Jain has supervised numerous graduate students who have secured positions at Harvard University, IBM, JPMorgan Chase, University of Waterloo, and other prestigious institutions. His research is supported by significant grants including the VAJRA Faculty Scheme award. He serves as Associate Editor for the Journal of Computer and System Sciences and on program committees for major conferences including ITCS 2025, FOCS 2022, and QIP 2022-2014. At CQT, he leads research in quantum information theory and quantum algorithms, contributing to Singapore's position as a regional hub for quantum computing research.

Mostafa Milaniمشاهده پروفایل

استادیار

• Data Management
• Databases
• Data Cleaning
• +۷ مورد دیگر

Mostafa Milani is an Assistant Professor in the Department of Computer Science at Western University. His research focuses on data management, databases, and their applications in data cleaning, privacy, provenance, and fairness. Before joining Western, he held postdoctoral positions at the University of British Columbia and McMaster University, and earned his Ph.D. from Carleton University under Dr. Leopoldo Bertossi. Education: Ph.D. in Computer Science from Carleton University (supervised by Leopoldo Bertossi), Postdoctoral Fellowships at University of British Columbia and McMaster University. Research Interests: Data Quality, Privacy, Provenance, Fairness, Entity Matching, Query Optimization, and Database Systems. His work emphasizes ethical data practices and integrates machine learning for improved database interactions. He has contributed to projects like Building Trust in Data (privacy/fairness integration) and Unified Data Exploration (provenance and query recommendations). Courses taught include Databases I/II, Applied Logic, and Web Systems. Current advisees include 7 MSc and 1 PhD student. Former students have graduated across MSc and undergraduate programs. His research is supported by grants and collaborations, and he actively participates in program committees for top conferences like SIGMOD and VLDB.

• Theoretical Computer Science
• Design and Analysis of Algorithms
• Discrete Optimization
• +۷ مورد دیگر

Nikhil Bansal holds the prestigious Patrick C. Fischer Professorship of Theoretical Computer Science in the Department of Computer Science & Engineering at the University of Michigan's College of Engineering. His research program has established him as a leading figure in theoretical computer science, with significant contributions to algorithm design and analysis, particularly in discrete optimization problems. Bansal's research focuses on theoretical computer science with emphasis on design and analysis of algorithms for discrete optimization problems. His work spans multiple areas including discrepancy theory, approximation algorithms, randomized algorithms, combinatorial optimization, complexity theory, machine learning theory, and probability. He has made significant contributions to understanding the limits of approximation algorithms and developing novel techniques for combinatorial optimization problems. Analysis of Bansal's recent publications reveals a strong focus on discrepancy theory, online algorithms, and combinatorial optimization. His work often bridges theoretical computer science with discrete mathematics and probability theory. A recurring theme across his publications is the development of novel algorithmic techniques for solving NP-hard problems with provable guarantees. His research has evolved from foundational work in approximation algorithms to more recent contributions in quantum computing complexity and stochastic optimization. Patrick C. Fischer Professor of Theoretical Computer Science Bansal has advised numerous PhD students including Marek Elias, Shashwat Garg, and Greg Koumoutsous, as well as mentoring several postdoctoral researchers. He has served on editorial boards for top journals including Journal of the ACM, Theory of Computing, and Stochastic Models, and has been active on program committees for major conferences such as STOC, FOCS, SODA, and ICALP, including serving as chair for ICALP 2021. Bansal has organized multiple academic workshops including the STOC 2020 Workshop on Recent Advances in Discrepancy and Applications, several SDP Days at CWI Amsterdam, and the Semester on Bridging Continuous and Discrete Optimization at UC Berkeley in Fall 2017.

Brian Wells Penceمشاهده پروفایل

استاد

• Global Mental Health
• HIV Epidemiology
• Opioid Epidemic Research
• +۶ مورد دیگر

Brian Wells Pence is a Professor in the Department of Epidemiology at the Gillings School of Global Public Health, University of North Carolina at Chapel Hill. He concurrently serves as Associate Director of the Division of Global Mental Health in the Department of Psychiatry, Member of the Institute for Global Health and Infectious Diseases, and Affiliate Faculty of the Injury Prevention Research Center at UNC. Dr. Pence's academic credentials include: PhD in Epidemiology from the University of North Carolina at Chapel Hill (2005) MPH in Epidemiology from Columbia University (2000) BA in Economics from Yale University (1996) His research program centers on three interconnected domains: global mental health interventions for vulnerable populations, intersections between mental illness and health crises (HIV/opioid epidemics), and suicide prevention. Methodologically, he integrates implementation science, advanced epidemiologic methods for observational data, and large administrative datasets to address critical gaps in mental health service delivery. Current NIH-funded projects include SHARP (NIMH U19) scaling depression treatment in Malawian primary care, TRACE (NIMH R34) addressing mental health in HIV care across the southern US, and INSPIRE (NIMH R01) establishing North Carolina's suicide surveillance system. Analysis of Dr. Pence's key publications (2005-2014) reveals consistent focus on trauma-mental health-HIV syndemics across diverse settings (US, Malawi, Tanzania, Cameroon). His work demonstrates how depression and trauma undermine HIV treatment adherence while pioneering implementation strategies to integrate mental health services into infectious disease care. Recurring methodological themes include validation of screening tools in resource-limited contexts and causal pathway analysis of mental health comorbidities. Dr. Pence directs the NIAID T32 pre- and postdoctoral training program in infectious diseases epidemiology and serves as associate director for research of the NIMH D43 mental health training program for Malawian scientists. His grant portfolio comprises multiple NIH mechanisms including R01, R34, R21, U19, and T32 awards supporting implementation research across the mental health-HIV-opioid continuum. His research infrastructure spans the Institute for Global Health and Infectious Diseases, Injury Prevention Research Center, and Gillings Innovation Labs. Key collaborations include the Sub-Saharan Africa Regional Partnership (SHARP) with Malawian institutions and the Coping with HIV/AIDS in the Southeast (CHASE) cohort study across the southeastern US, reflecting his transnational approach to mental health implementation science.