Find Academic Supervisors

Ernabel DemilloView profile

Professor

• Journalism
• Broadcasting
• Asian American Studies
• +3 more

Ernabel Demillo is a tenured Professor of Journalism and faculty chair of the Department of Communication and Media Culture at Saint Peter's University, where she founded the journalism program in 2008 and established the Public Relations minor in 2022. An Emmy-award-winning broadcaster, she bridges academic leadership with Emmy-winning field reporting for CUNY-TV's 'Asian American Life' and formerly 'Good Day New York.' Her educational credentials include a Master of Science from Northwestern University's Medill School of Journalism and a Bachelor of Arts from the University of Southern California. These foundations underpin her career spanning broadcast journalism, ethical media practice, and program development in higher education. Professor Demillo's research and professional focus centers on Asian American studies, investigative journalism, and media representation. She has pioneered coverage of anti-Asian violence, AAPI political mobilization, and diversity gaps in Hollywood, theater, and children's literature. Her ethical approach to journalism—recognized by the Frank LoMonte Award—emphasizes community-centered storytelling and amplifying marginalized voices through documentary work and broadcast reporting. Her accolades include an Emmy win for a Philippines-based documentary, four Telly Awards (including the 2021 Anti-Asian Hate special), the New York Governor's Award for Community Service, and the George R.R. Martin Novel Writing Fellowship. Additional honors comprise a Folio Award for environmental reporting, Buzzfeed's '34 Epic Filipinos in the United States' recognition, and The Limited's New Look of Leadership Campaign feature. Demillo co-received a $240,000 New Jersey Civic Information Consortium grant with Slice of Culture (founded by her former students) to revitalize Hudson County local news. She mentors through board roles at AAJA (as Vice President of Broadcast), Apex for Youth, CACF (for 20 years), and ARK Solves. Her current projects include completing a historical novel about Japanese-occupied Philippines and expanding journalism program partnerships. Operating at the intersection of academia and broadcast media, she leads the 'Asian American Life' team at CUNY-TV while developing Saint Peter's curriculum. Her lab extends to community news initiatives like the Slice of Culture partnership, which trains students in real-world reporting to address local news deserts in New Jersey.

Liang DongView profile

Associate Professor

• Signal Processing
• Wireless Communications
• Cyber-Physical Systems
• +12 more

Dr. Liang (Leon) Dong is an Associate Professor in the Department of Electrical and Computer Engineering at Baylor University, where he conducts research and teaches in the areas of signal processing, wireless communications, and artificial intelligence. He leads the Laboratory of Signal Processing, Communications, and Artificial Intelligence, fostering innovation in next-generation communication systems, IoT, and AI-driven applications. PhD, Electrical & Computer Engineering, The University of Texas at Austin (2002) MS, Electrical & Computer Engineering, The University of Texas at Austin (1998) BS, Applied Physics with Minor in Computer Engineering, Shanghai Jiao Tong University (1996) Dr. Dong's research focuses on advancing digital signal processing and wireless communications, with strong emphasis on artificial intelligence applications. His work spans NextG wireless systems , IoT and smart cities , cyber-physical system security , and AI in healthcare and industrial automation . He applies deep learning to domains such as autonomous driving and drug discovery, and investigates energy-efficient, secure, and reliable communication protocols. The recent publications highlight a strong trend toward integrating AI into traditional signal processing and communications. Topics include mRNA vaccine stability prediction , smart city infrastructures , secure cyber-physical systems , and deep learning for biomedical and industrial applications . His work bridges theoretical innovation with real-world impact in defense, transportation, and public health. Dr. Dong has earned recognition as a Senior Member of IEEE and a Member of the American Physical Society. He has also served as Faculty Advisor for Baylor University's InterVarsity chapter. Senior Member, Institute of Electrical and Electronics Engineers (IEEE) Member, American Physical Society (APS) He has successfully advised numerous graduate and undergraduate students, many of whom now hold academic and industry positions at institutions like Stanford, Intel, NASA, L3Harris, and Cummins. His research is generously supported by Baylor's VP for Research, the National Science Foundation, NASA, the Department of Defense (TARDEC), the Michigan Department of Transportation, and industry leaders including Intel, L3Harris, ExxonMobil, and Denso. He actively mentors students through research assistantships and senior design projects. Dr. Dong leads the Laboratory of Signal Processing, Communications, and Artificial Intelligence, which provides a collaborative environment for advancing research in signal processing, communications, and AI. The lab supports graduate and post-doctoral researchers and offers opportunities for undergraduate involvement in AI programming, circuit design, and embedded systems.

• Geometric Analysis
• Riemannian Geometry
• Metric Spaces
• +7 more

Christina Sormani is a Professor in the Department of Mathematics at Lehman College, City University of New York (CUNY), and a doctoral faculty member at the CUNY Graduate Center. She has been a key figure in geometric analysis since joining Lehman College in Spring 2000. Her research spans Riemannian geometry, metric spaces, and geometric measure theory, with a focus on the intrinsic flat distance, a concept she co-developed with Stefan Wenger. She has held visiting positions at prestigious institutions including the Institute for Advanced Study (IAS), Simons Center for Geometry and Physics (SCGP), and MSRI. Her education includes a PhD from the Courant Institute (1996), followed by postdoctoral positions at Johns Hopkins and Harvard University. She is deeply committed to mentoring and outreach, especially for underrepresented groups in mathematics. Sormani’s research interests center on convergence of Riemannian manifolds, particularly in contexts involving scalar curvature, Ricci curvature, and general relativity. She investigates the stability of geometric theorems such as the Positive Mass Theorem and scalar rigidity results using intrinsic flat convergence. Her work often involves constructing explicit examples, analyzing limit spaces, and proving compactness theorems. She has organized major workshops like VWRS and long programs at SCGP and Fields Institute. Her publications reveal a consistent focus on intrinsic flat convergence, its applications in general relativity, and its interplay with other notions like Gromov-Hausdorff and measured Gromov-Hausdorff convergence. The articles show a trend toward geometric stability, limit spaces with singularities, and the behavior of scalar curvature under weak convergence. She has received significant recognition for her work and service: Fellow of the American Mathematical Society (2015) Fellow of the Association for Women in Mathematics (2024) Sormani has advised numerous doctoral students and postdocs, including Dan Lee, Sajjad Lakzian, Raquel Perales, and Brian Allen. She has secured research funding from the NSF and PSC-CUNY. Her outreach includes organizing the "Inspiring Talks in Mathematics" lecture series and maintaining online resources for underrepresented mathematicians. She is actively involved in editorial boards and professional committees, contributing to the broader mathematical community. She is affiliated with research groups and teams focused on geometric analysis, scalar curvature, and convergence, including collaborations with Misha Gromov, Stefan Wenger, and others. Her recent work explores spacetime intrinsic flat convergence and null distances in Lorentzian geometry.

Catherine HurleyView profile

Professor

• Data visualization
• Data science
• Machine learning
• +4 more

Catherine Hurley is a Professor of Statistics at Maynooth University's Faculty of Science & Engineering, where she serves as Subject Head of Statistics in the Department of Mathematics and Statistics. She maintains strong affiliations with both the MU Hamilton Institute and the National Centre for Geocomputation, positioning her work at the intersection of statistics, data science, and computational methods. Dr. Hurley is a leading expert in data visualization with primary research interests in visualization techniques for data science and machine learning problems. Over her distinguished career, she has authored and contributed to numerous software packages, beginning with Data Viewer (1987), a predecessor to GGobi, Quail (1987-2000), and many R packages including condvis2, vivid (2021), and Bartvis (2022). Her work has significantly advanced the field of statistical graphics and model visualization. Her recent research has focused on conditional visualization for statistical models, with several publications on the condvis package and related tools that enable researchers to explore complex machine learning models through interactive visual interfaces. She has also made substantial contributions to dendrogram seriation, pairwise comparison visualization, and variable importance displays, creating numerous R packages that have become essential tools for statisticians and data scientists. Her 2023 publications include significant contributions to Bayesian additive regression trees and variable importance visualization for machine learning models. Dr. Hurley has held significant leadership roles in the statistical community, serving as Vice-President (2017-2019) and President (2019-2021) of the Irish Statistical Association. She also served as Editor-in-Chief and Editor of the R Journal from 2019 to 2023, playing a crucial role in advancing open-source statistical software development and dissemination. Her work demonstrates a consistent pattern of developing practical visualization tools that address real-world challenges in statistical analysis and machine learning interpretation. The progression from early work on statistical graphics infrastructure to recent innovations in model exploration reflects her sustained commitment to making complex statistical concepts accessible through visualization.

Zhiyuan LiView profile

Professor

• Program Analysis
• Compiler Design
• Parallel Computing
• +6 more

Zhiyuan Li is a Professor in the Department of Computer Sciences at Purdue University's College of Engineering. His primary research and teaching focus on program analysis, transformation, and run-time management for high-performance computing and multicore systems, as well as reliable software for networked embedded systems. Professor Li teaches graduate-level courses including CS502: Compiling and Programming Systems and CS591RS1: Research Seminar for First-year Graduate Students. Office: LWSN 3154H Contact: li@cs.purdue.edu Phone: +1 765-494-7822 Professor Li's research spans multiple areas within computer science, with particular emphasis on compiler design, program analysis, and parallel computing. His work addresses fundamental challenges in enabling efficient execution of applications on modern parallel architectures, including multicore processors and large-scale distributed systems. He has made significant contributions to techniques for data dependence analysis, loop parallelization, array privatization, and memory optimization in compilers. His research also extends to reliable software development for embedded and sensor network systems, where resource constraints and reliability requirements present unique challenges. Professor Li's publication record demonstrates consistent contributions to top-tier conferences and journals in computer science, particularly in the areas of parallel computing, compiler optimization, and high-performance numerical methods. His work shows a progression from foundational compiler techniques to applications in scientific computing domains such as computational fluid dynamics for jet engine noise simulation. This interdisciplinary approach connects low-level program analysis with real-world engineering applications requiring petascale computing resources. Principal Investigator for NSF/PetaApps project on jet engine noise simulation Principal Investigator for Intel-sponsored research on data dependence profiling Extensive service on program committees for major conferences including ICS, PPoPP, and LCTES Professor Li has been actively involved in mentoring graduate students through research projects and course instruction. His jet engine noise simulation project specifically mentions training three Ph.D. graduate students and involving undergraduate research assistants. As coordinator for the first-year graduate research seminar, he plays a significant role in guiding new students through the transition to graduate research work in computer science. His laboratory work focuses on developing compiler techniques and runtime systems for parallel and high-performance computing. The research infrastructure includes implementations in GCC for fast data dependence profiling and support for SIMD/SSE instructions, demonstrating practical applications of theoretical compiler techniques.

• Interstitial Lung Disease
• Pulmonary Fibrosis
• Lung Injury Mechanisms
• +3 more

Martin Rainer Kolb is a Professor of Medicine at McMaster University's Faculty of Health Sciences, specializing in Interstitial Lung Diseases (ILD) and General Respirology at St. Joseph's Healthcare Hamilton. He serves as Section Editor for ILD in the European Respiratory Journal, one of the top journals in respiratory medicine with an impact factor of 24.9, having previously served as Chief Editor. Dr. Kolb's research focuses on mechanisms of lung injury, repair and fibrosis, particularly in Idiopathic Pulmonary Fibrosis (IPF). His work spans pre-clinical studies of disease mechanisms, efficacy of novel drugs, and biomarker development for lung fibrosis. He actively leads international and national ILD clinical trials as Principal Investigator and Steering Committee member. His scholarly output shows a strong focus on progressive pulmonary fibrosis, with recent publications examining CT patterns, biomarkers, macrophage polarization, drug treatments like nintedanib, and patient pathways in ILD. His work demonstrates a consistent trajectory from basic mechanisms to clinical applications in fibrotic lung diseases. Dr. Kolb has received significant recognition including election to the Canadian Academy of Health Sciences and awards from the Parker B. Francis Families Foundation, Canadian Institute for Health Research, and the National Institute for Health. Parker B. Francis Families Foundation Award Canadian Institute for Health Research Award National Institute for Health Award Fellow of the Canadian Academy of Health Sciences With over 300 peer-reviewed publications, Dr. Kolb maintains an active research program that bridges basic science and clinical applications in pulmonary fibrosis. His leadership extends to journal editorial roles and multicenter clinical trials, significantly influencing the field of interstitial lung disease research and treatment.

Alvin CheungView profile

Associate Professor

• Data Management
• Programming Languages
• Software Systems
• +4 more

Alvin Cheung is an Associate Professor in the Computer Science Division at UC Berkeley's EECS department. He is affiliated with the Data Systems and Foundations group, Programming Systems group, Sky Lab, and SLICE Lab, and serves as a faculty affiliate at the Berkeley Institute for Data Science. He advises the Data Science Discovery Program and provides technical guidance to industry partners. His research spans data management, programming languages, and scalable software systems, with emphasis on helping users process large datasets efficiently. Key innovations include verified lifting (applying formal methods and ML to infer program properties) and systems for optimizing database-backed applications and geospatial analytics. Recent work explores LLM-driven code optimization and transpilation techniques. His publications (2023-2025) show strong trends in ML-enhanced systems, verified compilation, and data management tools. Articles frequently integrate formal methods, program synthesis, and hardware-aware optimizations across domains like databases, distributed computing, and HCI. Scientific Awards: ACSIC Rock Star Award (2025) Dahl-Nygaard Junior Prize (2024) VLDB Early Career Research Contribution Award (2023) IEEE TCDE Rising Star Award (2020) Sloan Fellowship (2019) NSF CAREER Award (2017) 20+ additional honors Advising & Grants: He mentors PhD/MS students (e.g., Lily Liu at OpenAI, Chenglong Wang at Microsoft Research). Research is funded by: NSF DOE ONR ARO Intel Notable grants include ONR Young Investigator Award and ARO Early Career Program Award. Labs & Teams: Leads projects in Berkeley's Data Systems/Programming Systems groups and collaborates with Sky Lab/SLICE Lab. Manages labs focused on verified compilation (e.g., Tenspiler) and data infrastructure (e.g., Spatialyze).

Miryung KimView profile

Professor

• Software Engineering
• Software Engineering for Data Intensive Computing
• Automated Testing
• +7 more

Miryung Kim is a Professor and Vice Chair of Graduate Studies in UCLA's Computer Science Department, where she directs the Software Engineering and Analysis Laboratory. She is renowned for her pioneering work in software evolution, code clone management, and establishing the emerging field of Software Engineering for Data Intensive Computing (SE4DA and SE4ML). Her research focuses on automated testing and debugging for Apache Spark, developer tools for heterogeneous computing, and conducting systematic studies of refactoring practices in industry. She led the first large-scale study of data scientists in industry and developed JDebloat, a Java bytecode debloating tool that made significant tech transfer impact to the Navy. Her recent publications demonstrate strong trends in fuzz testing for big data analytics and heterogeneous computing, with a focus on natural input generation, co-dependence awareness, and leveraging hardware probes for acceleration. Her work bridges software engineering with data-intensive and heterogeneous computing paradigms. ACM SIGSOFT Influential Educator Award (2022) ICSME Most Influential Paper Award (2023 and 2020) NSF CAREER award Google Faculty Research Award Okawa Foundation Research Award Humboldt Fellow ACM Distinguished Member As an academic advisor, she has produced eight tenure-track faculty members at institutions including Columbia, Purdue, and Virginia Tech. Her research has been supported by National Science Foundation, Air Force Research Laboratory, Google, IBM, Intel, Okawa Foundation, Samsung, and Office of Naval Research. She previously served as Program Co-Chair of ESEC/FSE 2022 and has delivered keynotes at ASE 2019 and ISSTA 2022. She maintains active industry collaborations, serving as an Amazon Scholar at Amazon Web Services and having spent time as a visiting researcher at Microsoft Research.

• Neuroscience
• Physiology
• Neurophysiology
• +3 more

Nick A. Ritucci, Ph.D., serves as a Senior Lecturer in the Department of Neuroscience, Cell Biology, and Physiology within the College of Science and Mathematics at Wright State University. He directs multiple core physiology courses including Human Anatomy & Physiology I/II and Human Structure & Function I/II, demonstrating extensive pedagogical leadership through course coordination roles since earning his doctorate from Wright State in 1997. Education: B.S. in Natural Sciences, Xavier University (1989) M.S. in Physiology & Biophysics, Wright State University (1992) Ph.D. in Biomedical Sciences, Wright State University (1997) Dr. Ritucci's research centers on respiratory neurophysiology , specifically investigating neuronal and astrocytic responses to hypercapnia and intracellular pH regulation in brainstem chemosensitive regions. His work employs advanced techniques like fluorescence pH imaging in brainstem slices to elucidate mechanisms in areas including the retrotrapezoid nucleus and locus coeruleus, with implications for sleep apnea and respiratory disorders. His publication record (1995-2005) reveals consistent focus on chemoreception mechanisms, particularly how medullary neurons regulate acid-base balance during hypercapnia. These studies, primarily in the American Journal of Physiology , established foundational knowledge in respiratory control neurobiology through innovative single-cell pH measurement methodologies. Scientific Awards: Boonshoft School of Medicine Excellence in Undergraduate Edcuation (2025) College of Science and Mathematics Undergraduate Students' Choice Award (2015) Wright State University Teaching Excellence Award (2010) Research Training Fellowship, American Lung Association (2000-2002) Comroe-Forster-Lambertsen Young Investigator Award (1999) Dr. Ritucci secured significant research funding including the American Lung Association Fellowship (2000-2002), while his course co-director roles across six physiology programs demonstrate sustained educational leadership. His dual focus on rigorous laboratory research and curriculum development has shaped neuroscience education at Wright State for over two decades.

Laurens BliekView profile

Assistant Professor

• Artificial Intelligence
• Optimization
• Sustainable Logistics
• +5 more

Laurens Bliek is an Assistant Professor at the Department of Industrial Engineering & Innovation Sciences, Eindhoven University of Technology (TU/e). He specializes in combining artificial intelligence (AI) with optimization techniques for computationally intensive problems, focusing on sustainable applications such as public transport, electric vehicles, and CO 2 reduction. Education: MSc in Applied Mathematics (2014), PhD in Systems & Control (2019) from Delft University of Technology. Prior Role: Postdoctoral researcher at the Algorithmics group, Delft University of Technology. Research Interests: His work addresses AI-driven optimization of expensive cost functions, particularly in logistics, communications, and healthcare. He develops methods to handle computationally intensive simulators and digital twins, emphasizing real-time decision-making and sustainability. Recent Publications: His research spans predictive maintenance using Fourier graph neural networks, real-time container yard allocation, and 5G network optimization. Articles appear in journals like IEEE Transactions on Neural Networks and Learning Systems and Computer Networks . Collaborations: Laurens collaborates with industry partners (LioniX, Dutch Railways) and organizations (European Supply Chain Forum, Logistics Community Brabant). He co-leads the 12-PhD program AI Planner of the Future and participates in AI sustainability working groups. Supervision: Co-promotor of PhD students Ya Song and Abdo Abouelrous, focusing on AI applications in routing and maintenance logistics.

Ana LucicView profile

Assistant Professor

• Interpretable Machine Learning
• Artificial Intelligence
• Earth System Science
• +3 more

Ana Lucic is an Assistant Professor in Artificial Intelligence at the University of Amsterdam , with a joint appointment between the Institute for Logic, Language and Computation and the Informatics Institute . Her research focuses on interpretable machine learning applications for scientific discovery and societal impact. Formerly at Microsoft Research AI for Science and Partnership on AI PhD in Explainable Machine Learning from University of Amsterdam (2022) BSc/MSc in Mathematics from McMaster University Research Highlights: Develops mechanistic interpretability methods for deep learning architectures. Created Aurora , a foundation model for Earth system forecasting outperforming traditional operational models in air quality prediction and tropical cyclone tracking. Pioneers Clifford-Steerable CNNs for geophysical data analysis. Actively hiring PhD students for AI transparency research . Collaborative Networks: Contributions to ELLIS Summer School and ICML workshops . Collaborates with Microsoft Research AI for Science team on climate-related ML projects. Involved in organizing TerraBytes workshop at ICML 2025. Recent Advancements: Key role in publishing Aurora model in Nature (2025), demonstrating superior performance in Earth system forecasting. Supervises Ege Erdogan , new PhD student focused on mechanistic interpretability. Actively contributes to open-source AI development through GitHub repositories and technical discussions.

• Software Engineering
• Software Testing
• Program Analysis
• +4 more

Alessandro (Alex) Orso is the Dean and Professor at the University of Georgia College of Engineering , starting in 2025. Previously, he spent 25 years at Georgia Institute of Technology , where he served as a Professor in the College of Computing , Director of the Scientific Software Engineering Center , and Associate Dean for Off-Campus and Special Initiatives . Education: Ph.D. in Computer Science – Politecnico di Milano, Italy M.S. in Electrical Engineering – Politecnico di Milano, Italy B.S. in Electrical Engineering – Politecnico di Milano, Italy Research Focus: Alex Orso is a leading expert in software engineering , with a focus on software testing , program analysis , and debugging . His work aims to improve software reliability, security, and trustworthiness , and has been validated on real-world systems. He has led initiatives to integrate AI and large language models into testing workflows, particularly for REST APIs and mobile applications . Scientific Recognition: Distinguished Member of the Association for Computing Machinery (ACM) Fellow of the Institute of Electrical and Electronics Engineers (IEEE) ISSTA Impact Paper Award (2021) Research Funding & Leadership: Orso has secured major funding from Google, IBM, Microsoft , and government agencies. In 2021, he led the acquisition of $11 million from Schmidt Futures to establish the Scientific Software Engineering Center at Georgia Tech, where he served as inaugural director. Teaching & Innovation: He was an early advocate of Georgia Tech’s Online Master of Science in Computer Science (OMSCS) and has taught a virtual software engineering course since its launch in 2014.

Scott F. MidkiffView profile

Professor

• Networking
• Telecommunications
• Computer Engineering
• +4 more

Scott F. Midkiff is a Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech. His research focuses on networking, telecommunications, and cybersecurity, with particular emphasis on 5G, O-RAN, edge cloud computing, and interference management in wireless networks. He holds a Ph.D. from Duke University (1985), an M.S.E.E. from Stanford University (1980), and a B.S.E. from Duke University (1979). Midkiff’s work spans theoretical and applied domains, including stochastic optimization for RAN intelligent controllers, network slicing, and wireless control plane design. He has contributed to advancements in interference alignment, MIMO systems, and secure spectrum sharing. His awards include the ORBIE Award and Capital CIO of the Year. Awards: ORBIE Award, Capital CIO of the Year Service: Member at Large, IEEE Committee on Engineering Accreditation Activities; ABET Program Evaluator His research group explores cutting-edge topics like software-defined cellular networks, distributed scheduling in underwater networks, and energy-efficient routing in sensor networks. Midkiff is affiliated with Virginia Tech’s research initiatives in pervasive computing and sustainable wireless systems.

Scott Richard FloydView profile

Associate Professor

• Radiation Oncology
• Brain Tumor Research
• DNA Damage Response
• +7 more

Scott Richard Floyd is the Gary Hock and Lyn Proctor Associate Professor of Radiation Oncology at Duke University School of Medicine, with secondary appointments as Associate Professor of Radiation Oncology and Assistant Research Professor in Pharmacology and Cancer Biology. He is also a Member of the Duke Cancer Institute and serves as Associate Radiation Director of the Duke Center for Brain and Spine Metastasis and Associate Program Director of the Duke Radiation Oncology Residency Program. Dr. Floyd received his M.D. and Ph.D. from Yale University in 2002. His professional training includes: Internship in Internal Medicine at Hospital of Saint Raphael (2002-2003) Residency in Radiation Oncology at Harvard Medical School, Harvard Radiation Oncology Program (2003-2007) Clinical Investigator position at MIT Koch Institute for Integrative Cancer Research (2012-) Dr. Floyd's research focuses on DNA damage signaling and repair in brain tumor cells, particularly investigating how chromatin changes mediated by epigenetic modifiers affect the DNA damage response (DDR). His lab develops small animal irradiation techniques and mouse models of glioblastoma to test the effects of epigenetic writers and readers on DDR in clinically relevant model systems. He aims to identify strategies to enhance tumor cell killing while protecting normal brain tissues from radiation damage. His work on brain slice models provides a platform for studying stroke, Alzheimer's disease, Huntington's disease, and brain tumors while reducing animal use. Analysis of Dr. Floyd's recent publications reveals a strong focus on brain metastases, radiation necrosis, and the application of artificial intelligence in radiation oncology. His work increasingly integrates radiogenomics, machine learning, and novel radiation techniques to improve outcomes for patients with brain tumors. There's a clear trend toward interdisciplinary collaboration, particularly in combining radiation therapy with immunotherapy and targeted agents, as evidenced by his leadership in the Consortium for Intracranial Metastasis Academic Research (CIMARa). Dr. Floyd has secured significant research funding, including: NEUROD1 function in SCLC fate and plasticity (NIH, 2024-2029) Synthetic lethality with BET bromodomain inhibition (American Cancer Society, 2025-2026) ASPET SURF Institutional Award (2018-2028) Multiple NIH R01 grants supporting his research on DNA damage response and brain tumor biology Dr. Floyd leads the Floyd Lab, which focuses on studying mechanisms of DNA damage signaling and repair in brain tumor and other mammalian cells. His lab utilizes advanced techniques including small animal irradiation, mouse models of glioblastoma, and organotypic brain slice culture platforms. He is also involved in Project Brainslice, which develops experimental model systems using brain slices to research new treatments for brain diseases. His clinical expertise centers on the treatment of benign, primary, and metastatic tumors of the brain and spine, making him a key figure in Duke's brain and spine metastasis program.

Leah Chase-WallarView profile

Professor

• Neuroscience
• Biochemistry
• Neurochemistry
• +3 more

Dr. Leah Chase-Wallar serves as Professor of Biology & Chemistry at Hope College since 2000, maintaining active research in the A. Paul Schaap Science Center with dual departmental affiliations in Chemistry and Biology. Her work bridges neurochemistry and molecular biology through investigations of oxidative stress mechanisms in neurodegenerative disorders. She earned her B.S. from the University of Michigan – Flint (1993) followed by a Ph.D. from the University of Minnesota (1999), establishing her foundation in biochemical neuroscience. Her research program centers on system x c - regulation, specifically examining how hydrogen peroxide modulates cystine/glutamate exchange to protect dopaminergic neurons in Parkinson's disease models. This involves advanced techniques including mammalian cell culture, immunocytochemical analysis, western blotting, and enzymatic assays for glutathione/peroxide measurement. Her publication trajectory (1994-2007) reveals evolving specialization: early comparative physiology work on reindeer nutrition transitioned into focused neuroscience research on glutamate transport systems, metabotropic receptor pharmacology, and neurotoxin mechanisms. The most recent publications demonstrate increasing emphasis on oxidative stress pathways relevant to Parkinson's disease. Dr. Chase-Wallar has secured substantial research funding including multiple Campbell Foundation grants (2001-2007), a Towsley Research Scholar award (2003-2006), and NSF support (2002-2003) for neuroscience laboratory development. Her Chase-Wallar Research Group actively involves undergraduate students in project design and execution within Hope College's Chemistry Department framework, with facilities in the A. Paul Schaap Science Center enabling cellular and molecular investigations of dopaminergic systems.