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Robert Nowak holds dual distinguished professorships as the Keith and Jane Morgan Nosbusch Professor in Electrical and Computer Engineering and the Grace Wahba Professor of Data Science at the University of Wisconsin–Madison. Based at the Discovery Building (330 N Orchard Street), he leads interdisciplinary research at the Wisconsin Institute for Discovery, bridging engineering with data science applications. His academic foundation includes: BS, MS, and PhD from the University of Wisconsin–Madison Post-doctoral Fellowship at Rice University Nowak's research program spans artificial intelligence, machine learning, and optimization with dual emphases on AI-driven health applications and systems optimization. His work integrates theoretical rigor with practical implementations, particularly in large language model fine-tuning, active learning frameworks, and neural network theory. Recent publications demonstrate strong focus on improving model efficiency, humor comprehension in AI systems, and theoretical bounds for retrieval-augmented generation. Analysis of his 15 most recent publications reveals dominant trends in large language model advancement (particularly humor understanding and task diversity), theoretical neural network analysis (including sparse architectures and multi-task learning), and novel active learning methodologies for open-world scenarios. His work consistently bridges theoretical machine learning with real-world applications in health and recommendation systems. While specific named awards aren't documented in the source material, his appointment to two endowed chairs (Nosbusch and Wahba professorships) represents exceptional institutional recognition of his scholarly impact. Nowak advises graduate students in the Electrical and Computer Engineering department and secures significant research funding, including NSF grants such as CIF: Small: Advanced Understanding and Applications of Deep Learning. His group operates within the collaborative ecosystem of the Wisconsin Institute for Discovery, fostering cross-disciplinary projects that integrate AI with health sciences and engineering systems. Current projects indicate strong momentum in human-AI collaboration frameworks and optimization of language model training pipelines.

• Artificial Intelligence
• Machine Learning
• Data Science
• +3 more

Emmanuel M. Gabriel, M.D., Ph.D., serves as Associate Professor of Surgery and Consultant in the Department of Surgery at Mayo Clinic in Jacksonville, Florida. He directs clinical and research activities within the Mayo Clinic Comprehensive Cancer Center, specializing in surgical oncology for breast cancer, melanoma, sarcoma, and gastrointestinal malignancies requiring advanced regional therapies like HIPEC. His dual MD/PhD training uniquely positions him at the intersection of immunology research and complex cancer surgery. Dr. Gabriel's educational trajectory includes: MD/PhD in Immunology, Robert Wood Johnson Medical School (2009), thesis on regulatory T cells and cancer vaccines BA in Biology/Economics with Chemistry/Mathematics minors, Drew University (2002), Summa Cum Laude Residency and Administrative Chief Residency, UT Health San Antonio Department of Surgery Fellowship in Complex General Surgical Oncology, Roswell Park Cancer Institute His research program integrates two critical cancer domains: pioneering tumor imaging techniques to visualize immune-tumor interactions during surgery, and identifying systemic barriers in cancer care delivery through health disparities research. These efforts aim to personalize immunotherapy selection and develop equitable care pathways for underserved populations. Dr. Gabriel's scientific contributions are recognized through: Faculty Teacher of the Year awards from Mayo Clinic Department of Surgery (2022) Multiple Young Surgeon Research Awards from American College of Surgeons (2016) E. Douglas Holyoke Award as Outstanding Surgical Oncology Fellow (2016) Ongoing service as grant reviewer for national cancer organizations As an educator, he mentors surgical trainees through Mayo's integrated residency programs while leading translational research in the David F. and Margaret T. Grohne Cancer Immunology Program. His clinical practice directly informs research priorities, maintaining a continuous bench-to-bedside-to-community feedback loop. Dr. Gabriel's laboratory operates within Mayo Clinic's NCI-designated cancer center infrastructure, utilizing advanced imaging core facilities and population health resources to advance both immunotherapy development and health equity initiatives.

• Cancer Immunology
• Immunotherapy
• Tumor Imaging
• +7 more

Kevin Kohl is an Associate Professor in the Department of Biological Sciences at the University of Pittsburgh, where he joined in 2017 after completing his Ph.D. at the University of Utah and postdoctoral research at Universidad Nacional de San Luis (Argentina) and Vanderbilt University. His work bridges microbial ecology, physiological adaptation, and evolutionary biology with a focus on vertebrate digestive systems. Education: Ph.D., University of Utah, 2015 (Advisor: Dr. Denise Dearing) Postdoctoral Research, Universidad Nacional de San Luis, Argentina (with Dr. Enrique Caviedes-Vidal) Postdoctoral Research, Vanderbilt University (with Dr. Seth Bordenstein) Dr. Kohl's research centers on how host ecology and evolutionary history shape digestive physiology and gut microbial communities, particularly in herbivorous mammals and lizards coping with low-protein, high-fiber, and toxin-rich diets. The Kohl Lab employs comparative, experimental, and computational approaches across fish, amphibians, reptiles, birds, and mammals to uncover functional implications and mechanistic bases of host-microbe relationships. Key research themes include phylosymbiosis, thermal physiology, nutritional ecology, and microbial dynamics in conservation contexts. His recent publications (2023-2025) reveal consistent exploration of diet-microbiome-physiology interactions, with emerging emphasis on methodological innovation (e.g., cryopreservation techniques, museum specimen analysis), climate change impacts on ectotherms, and accessibility in field research. Work spans fundamental mechanisms like gastric lysozyme evolution to applied conservation hologenomics initiatives. Dr. Kohl advises graduate students in biological sciences and leads the Kohl Lab, which maintains active international collaborations. The lab emphasizes rigorous experimental design while addressing real-world challenges like wildlife conservation microbiome applications and inclusive fieldwork practices. The Kohl Lab operates as a multidisciplinary hub investigating host-microbe interactions through projects including Integrative Nutritional Physiology, Landscape Variation in Pond Microbiomes, and Microbial Ecology of Animals Under Human Care. Current work increasingly integrates hologenomic perspectives to address conservation biology challenges and methodological limitations in microbiome research.

• Host-Microbe Interactions
• Gut Microbiome
• Physiological Ecology
• +5 more

Professor Pauleen Bennett is a leading scholar in Anthrozoology at La Trobe University's Bendigo campus, serving in the Department of Psychology, Counseling and Therapy within the College of Science, Health and Engineering since 2018. Her research program centers on human-companion animal relationships, particularly focusing on the psychological dimensions of human-dog bonds, veterinary wellbeing, and child-pet interactions. Her research interests span Anthrozoology , Human-Animal Relationships , and Companion Animal Psychology , with particular emphasis on dog behavior, veterinary burnout, and the therapeutic applications of human-animal bonds. Bennett leads the Anthrozoology Research Group (www.anthrozoologyresearchgroup.com) and has made significant contributions to understanding how animals impact human mental health across diverse contexts from farms to universities. Analysis of her recent publications reveals three dominant research trajectories: (1) human-animal relationship measurement tools development, (2) veterinary workplace wellbeing challenges, and (3) practical applications of human-animal bonds in agricultural, educational, and healthcare settings. Her work consistently bridges theoretical psychology with practical animal welfare applications. Bennett previously served as Associate Editor for Anthrozoos and on the board of the International Society for Anthrozoology. She co-supervises higher degree students across multiple Australian universities and maintains active community engagement through the Anthrozoology Research Group. Her funded research includes the Wildlife Victoria Inc Mental Health and Wellbeing Review (2021-2024), which developed recommended good practice guidelines for wildlife volunteer support programs. Bennett also serves as a consultant on human-animal interaction projects, translating academic research into practical community applications. Bennett maintains a productive research laboratory focused on human-animal interactions, with current projects examining puppy socialization practices, veterinary technician burnout, and the psychological benefits of animal-assisted interventions in university settings. Her Bendigo-based laboratory operates in close collaboration with Australian farms, veterinary clinics, and community organizations.

• Anthrozoology
• Human-Animal Relationships
• Companion Animal Psychology
• +4 more

Tej Chajed is an Assistant Professor in the Department of Computer Science at the University of Wisconsin-Madison, where he conducts research in formal verification of systems software. His work focuses on building and proving the correctness of critical systems, particularly file systems and concurrent software. Dr. Chajed earned his PhD from MIT in the PDOS group, followed by a one-year postdoc at VMware Research before joining UW-Madison. His academic journey reflects a strong commitment to bridging theoretical formal methods with practical systems implementation. Chajed's research centers on formal verification techniques for systems software, with particular emphasis on concurrent and crash-safe systems . His work aims to eliminate bugs in critical software through mathematical proofs of correctness. Key contributions include DaisyNFS (a verified concurrent file system), the Perennial framework for reasoning about crash safety, and Goose for connecting proofs to Go code. His research spans the intersection of programming languages, operating systems, and formal methods, developing practical tools that bring verification to real-world systems. His recent publications demonstrate a consistent trajectory toward more practical and scalable verification techniques for increasingly complex systems. The research shows progression from foundational verification frameworks to applied work on specific systems like file systems, journaling, and distributed protocols. A notable trend is the focus on making verification more accessible and practical for systems developers, bridging the gap between theoretical formal methods and real-world software engineering. Dr. Chajed serves on numerous program committees including OSDI 2025 PC, PLDI 2024 PC, SySDW 2023 PC, ECOOP 2023 ERC, CPP 2023 PC, POPL 2023 PC, PLDI 2022 PC, POPL 2022 AEC, EuroDW 2021 PC, POPL 2021 AEC, PLDI 2020 AEC, POPL 2020 AEC, and SOSP 2019 AEC, reflecting his standing in the systems and programming languages research community. In teaching, Chajed has developed and instructed courses on systems verification, operating systems, and protocol verification. He previously helped create MIT's 6.826 (Principles of Computer Systems) during his PhD. His passion for technical communication was cultivated during his time as a Communication Fellow in the EECS Communication Lab at MIT, where he continues to offer guidance to students on writing and presentation skills. His research group at UW-Madison focuses on advancing the state of the art in systems verification, with current projects centered around practical verification frameworks for concurrent and crash-safe systems.

• Formal verification of systems software
• Concurrent systems verification
• Crash-safe file systems
• +5 more

Femi Olan is a Senior Lecturer at the Strategy, Operations and Entrepreneurship department within Essex Business School at the University of Essex. His academic work bridges the intersection of digital entrepreneurship, knowledge management, and artificial intelligence in organisational contexts. Educational Background: PhD, University of Plymouth Research interests focus on digital entrepreneurship , artificial intelligence , and knowledge management , particularly examining how these technologies enhance organisational resilience and sustainability. His publications in journals like Information Systems Frontiers and Technological Forecasting & Social Change highlight applications of AI in supply chains, crisis information management, and sustainability. Recent editorial roles include Cogent Business & Management Journal (2024) and guest editorships for special issues on fake news, sustainable agriculture supply chains, and crisis information management. His 15 most recent articles (2022-2025) span topics such as explainable AI in B2B marketing, CSR implementation in African SMEs, and Industry 4.0 adoption in agriculture. He supervises PhD candidates in entrepreneurship and has secured funding from the UK Higher Education Academy and European Commission . As a coordinating board member of the Euro Working Group – Decision Support Systems , he contributes to international research networks and conferences.

• Digital Entrepreneurship
• Knowledge Management
• Performance Management
• +5 more

Haakon Sundbø is a Senior Lecturer at the Department of Information and Communication Technology, University of Agder. He teaches courses such as Computer Science (DAT100), Multimedia Design (DAT104), Web Publishing (DAT110), Visual Design (DAT222), Sound Engineering (DAT228), ICT and E-learning in Vocational Subjects (PED978), and Didactic Use of Digital Tools (MM903). His academic responsibilities also include guest lecturing and supervision in ICT Project (DAT215), Photography (DAT227), Video (DAT229), Bachelor's Project (DAT303), Web and Online Knowledge (MM901), Remote Operated Vehicles (MM202), Interaction Design (MM403), and Technology for Teachers (TEKPED60). Materials, Energy and Nanotechnology (BSc, University of Oslo) Multimedia Technology and Design (BSc, University of Agder) Multimedia and Educational Technology (MSc, University of Agder) Haakon's research focuses on lifelong learning, e-learning platforms, interaction design, user experience, artificial intelligence in education, augmented reality, virtual reality, and digital competence development. He has contributed to projects like Decentralized Competence Development (DEKOMP), UiA Consense, and drone technology research at University of Agder. His recent publications analyze AI integration in teaching, digital frameworks for schools, screen usage guidelines, and collaborative learning networks. He also leads a research group on Multimedia and E-learning, emphasizing flexible digital resources and practical technology adoption in educational contexts.

• Multimedia Technology
• E-Learning
• Photography
• +16 more

Stuart Gordon is a Professor in Managing Humanitarianism and Programme Director for the International Development and Humanitarian Emergencies MSc at the London School of Economics and Political Science (LSE). His academic affiliations include the Department of International Development at LSE, where he also coordinates consultancy programs. He holds roles as an Associate Fellow at Chatham House and Senior Fellow of the Higher Education Academy. His research focuses on humanitarian governance, civil-military interaction, and the impact of counter-terrorist legislation on humanitarian operations. Prior to academia, he served as a senior adviser on UK Afghanistan strategies and held roles in the UK Armed Forces (RAF and Army), retiring as a Lieutenant Colonel. He has conducted fieldwork in conflict zones such as Afghanistan, Syria, and Somalia. Key areas of expertise include humanitarian accountability, risk management in crisis responses, and health emergencies like Ebola. He co-directs the LSE-ODI Senior Level Course on Conflict and Humanitarian Response with Sara Pantuliano and sits on the editorial board of the Disasters journal. His work bridges humanitarian principles, security policies, and practical challenges in conflict settings. Notable contributions include analyzing the unintended consequences of civil-military cooperation in peace operations and the impact of financial de-risking on Syrian humanitarian aid. His publications span over three decades, addressing themes from Afghanistan stabilization to medical ethics in conflict zones.

• Humanitarian Governance
• Counter-Terrorist Legislation
• Humanitarian-Military Interaction
• +3 more

Professor Saman Amarasinghe is a full Professor in the Department of Electrical Engineering and Computer Science (EECS) at the Massachusetts Institute of Technology (MIT), and Principal Investigator at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL). He leads the Commit compiler research group, which focuses on programming languages and compilers that maximize application performance on modern computing platforms. His work spans multiple academic departments and research centers, with strong affiliations to both MIT's School of Engineering and CSAIL. Professor Amarasinghe's research interests center around high-performance domain-specific languages and compiler technology . His work combines language design with sophisticated compilation techniques to deliver unprecedented performance for targeted application domains. His research spans multiple areas including image processing (Halide), sparse tensor algebra (TACO), graph analytics (GraphIt), stream computations (StreamIt), and bioinformatics (Seq). A significant thread throughout his work is the application of machine learning for compiler optimizations, from Meta optimization in 2003 to the OpenTuner autotuner framework. Analysis of Professor Amarasinghe's recent publications reveals a strong focus on sparse computing , compiler vectorization , and domain-specific language implementation . His work consistently bridges theoretical compiler concepts with practical performance gains across diverse application domains. The progression from earlier work on StreamIt and Halide to more recent projects like GraphIt and TACO shows an evolution toward more specialized, high-performance DSLs targeting specific computational patterns. His 2020-2025 publications particularly emphasize sparse tensor operations, GPU acceleration, and machine learning integration with compiler technology. ACM Fellow (2019) Professor Amarasinghe has made significant contributions to academic entrepreneurship and student development. He founded Determina, Inc. (acquired by VMware) based on security research from his MIT lab and co-founded Lanka Internet Services, Ltd., Sri Lanka's first ISP. As faculty director of MIT Global Startup Labs, his programs across 17 countries have helped create over 20 successful startups. His teaching includes the popular Performance Engineering of Software Systems (6.172) course with Professor Charles Leiserson, as well as innovative project-based courses like the Open Source Software Project Lab and Bring Your Own Software Project Lab. His educational approach emphasizes hands-on experience with compiler and language design concepts. Professor Amarasinghe leads the Commit compiler research group at MIT CSAIL, which has produced numerous influential domain-specific languages and compilers including Halide, TACO, Simit, StreamIt, and GraphIt. The lab maintains strong industry connections through projects like OpenTuner and Determina, and collaborates with researchers worldwide on compiler technology. The group's work spans both theoretical compiler research and practical implementation, with a consistent focus on bridging the performance gap between high-level programming abstractions and hardware capabilities.

• Programming Languages
• Compilers
• Domain-Specific Languages
• +7 more

Asaf Cohen is an Associate Professor in the Department of Mathematics at the University of Michigan, Ann Arbor, affiliated with the College of Literature, Science, and the Arts. He holds a B.Sc., M.Sc., and Ph.D. from Tel-Aviv University (2005–2013). His research focuses on applied probability, stochastic processes, and control theory, with emphasis on mean-field games, mathematical finance, actuarial science, diffusion and large deviation analysis, machine learning, and risk-sensitive control. His work also addresses applications in stochastic networks, energy markets, epidemiology, and economics. Key research areas include diffusion approximations, large deviations, queueing theory, and partial differential equations. Dr. Cohen has contributed to the analysis of multiclass queueing systems, optimal dividend strategies, and strategic server behavior in heavy traffic regimes. His methods often involve advanced stochastic control techniques and game-theoretic models. He has published extensively on topics such as mean-field games, SIR models for epidemics, and Bayesian sequential testing. His academic contributions span theoretical advancements and practical applications in finance, insurance, and operations research.

• Applied Probability
• Stochastic Processes
• Control Theory
• +12 more

Dr. George Karakostas is an Associate Professor in the Department of Computing and Software at McMaster University. His research focuses on Scientific Computing, Optimization, and Theoretical Computer Science, with a particular emphasis on algorithms, scheduling, and resource management in data centers and mobile networks. He is actively involved in advising graduate students and contributes to cutting-edge research in digital twins, edge computing, and approximation algorithms. Dr. Karakostas holds a PhD (implied by title) and has authored numerous publications addressing challenges in workload distribution, thermal management, and task scheduling under deadline constraints. His work often intersects with practical applications in IoT, wireless networks, and energy-efficient infrastructure. Key research trends include optimizing resource allocation in distributed systems, developing efficient offloading strategies for mobile devices, and leveraging digital twins for system performance enhancement. Despite the volume of his publications, the focus consistently revolves around theoretical rigor paired with real-world applicability. Dr. Karakostas is affiliated with the Digital & Smart Systems research cluster and teaches advanced courses such as CAS 744: Advanced Topics in Design of Algorithms (Theory). His contact information includes karakos@mcmaster.ca and a faculty profile page at www.cas.mcmaster.ca/~gk.

• Scientific Computing
• Optimization
• Theoretical Computer Science
• +3 more

Irith Pomeranz is the Cadence Professor of Electrical and Computer Engineering at Purdue University's College of Engineering. Her research focuses on advanced testing methodologies for VLSI circuits, including functional test compaction, fault diagnosis, and built-in self-test (BIST) techniques. She is affiliated with the Department of Electrical and Computer Engineering and has contributed extensively to improving test efficiency and fault coverage in digital circuits. Her work addresses challenges such as aging effects, transition faults, and path delay faults, with a particular emphasis on practical implementations for industrial applications. Key areas of interest include modular test sequences, configuration-based compaction, and dynamic testing strategies for in-field environments. She has developed algorithms for dual-target diagnostic testing and synchronization mechanisms for online fault detection in logic blocks. Research Trends in her publications emphasize innovations like storage-based BIST schemes, adaptive test scheduling, and shared test data architectures. These advancements aim to reduce test data volume, improve fault coverage, and enhance reliability in modern integrated circuits. Her work often bridges theoretical foundations and practical hardware implementations. Grants & Advising : While specific grants or student advisees are not listed, her prolific publication record indicates active involvement in research projects and graduate supervision within Purdue's ECE department. Labs & Teams : Her contributions are likely tied to Purdue's VLSI and testing research groups, though specific lab affiliations are not detailed in the provided text.

• VLSI Testing
• Circuit Design
• Test Compaction
• +7 more

Tim Leung is the Boeing Endowed Chair Professor of Applied Mathematics and Director of the Computational Finance & Risk Management (CFRM) Program at the University of Washington. He also serves as core faculty in the Quantitative Ecology and Resource Management (QERM) Program and is affiliated with the Center for Quantitative Science. His research focuses on Financial Mathematics, Optimal Stochastic Control, and Algorithmic Trading, with over 70 publications and multiple books. He has held professorships at Johns Hopkins University (2008-2011) and Columbia University (2011-2016). Education: Ph.D. in Operations Research & Financial Engineering from Princeton University (2008), B.S. in Operations Research & Industrial Engineering from Cornell University (2003). His work has been funded by the National Science Foundation and recognized by the Emerald Literati Network Award (2016). He leads the CFRM program, which trains professionals in computational finance, and co-edits the Modern Trends in Financial Engineering book series. He serves on editorial boards of journals like Applied Mathematical Finance and SIAM Journal on Financial Mathematics . Research interests include derivatives pricing, ETF dynamics, and risk management strategies. He has pioneered frameworks for mean reversion trading, futures portfolio optimization, and statistical arbitrage. His recent work explores regime-switching models, multiscale volatility analysis, and applications of machine learning in financial signal processing. Awards: Emerald Literati Network Award (2016) Leadership Roles: Chair of INFORMS Finance Section, Vice Chair of SIAM Activity Group on Financial Mathematics & Engineering Advisory Roles: AI for Finance Institute His research spans theoretical advancements and practical applications, with a focus on bridging stochastic control theory and real-world financial markets.

• Financial Mathematics
• Optimal Stochastic Control
• Algorithmic Trading
• +5 more

Kim Everett is an Instructor in the Higher Education Administration and Policy department at Northwestern University's School of Education and Social Policy (SESP). As a founder of Unfragmented LLC, she operates a private practice focusing on coaching, consulting, and healing-centered approaches. Holding a PhD in Educational Leadership from Iowa State University, her career spans over two decades in student affairs, emphasizing support for historically marginalized students through identity-conscious practices. Education: PhD, Educational Leadership and Policy Studies, Iowa State University MEd, Educational Leadership and Policy Studies, Iowa State University BS, Elementary Education, Iowa State University Her research and practice integrate contemplative practices, anti-racist frameworks, and policy advocacy to foster inclusive environments. She specializes in organizational development, leadership coaching, and community-building initiatives across higher education and nonprofit sectors. Kim’s work bridges academia and community through projects addressing systemic inequities, particularly for first-generation and BIPOC students. Her consulting focuses on helping individuals and institutions align goals with ethical values and actionable strategies.

• Contemplative Education
• Anti-Racism in Education
• Anti-Oppressive Policies
• +3 more

Martin Henz is an Associate Professor at the National University of Singapore , affiliated with the School of Computing and its Department of Computer Science . His academic journey includes an M.Sc. in Computer Science from Stony Brook University (1993) and a Dr.rer.nat. in Computer Science from Saarland University (1997). He has also worked as a Research Scientist at the German Research Centre for Artificial Intelligence. Research Focus : Scalable Experiential Learning, Systems for Teaching/Learning, AI in Education, Programming Languages, Algorithms, and Constraint Programming. Key Projects : Source Academy (immersive programming environment), Deep Teaching (LMS enhancements), and NUS Seafarers (maritime experiential learning). Publications span education technology, programming languages, and sustainable engineering, with recent works focusing on JavaScript-based pedagogy, automated question generation, and electric vehicle conversions. He supervised Rahul Singhal 's PhD, leading to the educational startup Cerebry, and co-founded Workforce Optimizer Pte Ltd with Alan Sevugan. Awards : NUS Annual Digital Education Award (2021) NUS Annual Teaching Excellence Award (2016/17) Fulbright Scholarship (1990) Startup @ Singapore Champion (2001)

• Programming Languages
• Software Engineering
• Artificial Intelligence
• +8 more