Find Academic Supervisors

• Retail Management
• Digital Marketing
• Consumer Behavior
• +6 more

Dr. Kirthi Kalyanam serves as Professor of Marketing at Santa Clara University's Leavey School of Business, where she holds dual leadership roles as Executive Director of the Retail Management Institute and Director of Internet Retailing. Her work bridges academic research with industry practice through Lucas Hall-based initiatives focused on retail innovation and digital transformation. Her research program centers on experimental investigations of digital marketing phenomena, with particular expertise in advertising effectiveness, multi-channel consumer behavior, and technology-driven retail disruptions. She employs advanced methodologies including field experiments, regression discontinuity designs, and machine learning to analyze consumer responses to advertising content, app crashes, subscription models, and business-to-business marketing scenarios. Her work consistently addresses practical retail challenges through data-driven insights. Analysis of her recent publications (2016-2025) reveals a methodological progression toward sophisticated experimental designs examining cross-channel effects, behavioral targeting, and technology failures. Her research demonstrates consistent focus on causal relationships in digital marketing, with increasing emphasis on business-to-business contexts and longitudinal advertising effects, while maintaining strong industry relevance through partnerships with major technology platforms. As Executive Director of the Retail Management Institute, she leads strategic initiatives connecting academic research with retail industry stakeholders through collaborative projects, executive education, and thought leadership programs focused on emerging retail technologies and consumer behavior trends.

• Arbovirology
• Emerging infectious diseases
• Livestock diseases
• +7 more

Professor Massimo Palmarini is a Professor of Virology at the MRC-University of Glasgow Centre for Virus Research, University of Glasgow. His research focuses on viral pathogenesis, particularly with arboviruses and emerging infectious diseases. Professor Palmarini's laboratory studies the biology and pathogenesis of livestock diseases induced by emerging arboviruses such as Bluetongue virus (BTV) and Schmallenberg virus (SBV). His research indicates that approximately 30 percent of all infectious diseases that emerged between 1990 and 2000 were caused by arthropod-borne viruses (arbovirus), likely resulting from increased travel and commerce, climate changes, ecological shifts, and intensified livestock production. His work has expanded significantly into coronavirus research, particularly SARS-CoV-2, examining viral evolution, host immune responses, and disease mechanisms. He employs advanced techniques including single-cell analysis, omics approaches, and machine learning frameworks to understand viral pathogenesis. Analysis of Professor Palmarini's recent publications (2023-2025) reveals a dual research focus: continued investigation of arboviruses (particularly Bluetongue virus) and extensive work on SARS-CoV-2 and related coronaviruses. His research on SARS-CoV-2 spans viral evolution, immune evasion mechanisms, host-pathogen interactions, and clinical manifestations of disease. His work on arboviruses examines transmission mechanisms, disease severity correlates, and viral determinants of host range. Professor Palmarini's research is funded by various sources including Wellcome, the Biotechnology and Biological Sciences Research Council (BBSRC), and the European Union. His laboratory has produced over 150 publications spanning more than three decades, demonstrating sustained contributions to virology research with particular emphasis on retroviruses, arboviruses, and coronaviruses.

Bilal MansoorView profile

Associate Professor

• Materials in Extreme Environments
• Microstructure-Mechanical Behavior Couplings
• Solid State Materials Processing
• +5 more

Bilal Mansoor serves as an Associate Professor in the Department of Materials Science & Engineering at Texas A&M University at Qatar, where he conducts research on materials behavior in extreme environments and advanced processing techniques. His educational foundation includes a Ph.D. and M.S. from the University of Michigan and a BSE from the University of Engineering and Technology, Pakistan. His academic journey began with a Bachelor of Science in Engineering in Mechanical Engineering from the University of Engineering and Technology, Pakistan in 2002, followed by a Master of Science in Mechanical Engineering from the University of Michigan in 2007, and culminated in a Ph.D. in Materials Science and Engineering from the University of Michigan in 2010. Dr. Mansoor's research program centers on two main thrusts: (1) understanding environment-microstructure-mechanical behavior couplings in materials exposed to extreme conditions, and (2) developing solid-state processing methods such as friction stir processing and additive manufacturing. His work extends to engineering education, where he designs courses that integrate hands-on learning with writing proficiency. Analysis of his recent publications (2023-2025) reveals a consistent emphasis on materials for harsh environments, including oxygen service compatibility, hydrogen embrittlement, and biodegradable metals for biomedical applications. He actively applies machine learning to materials characterization and leverages additive manufacturing for novel material systems. His excellence in teaching and research has been acknowledged through multiple awards: College-Level Teaching Award from The Association of Former Students at Texas A&M University at Qatar (2022) Faculty of the Year in Mechanical Engineering at Texas A&M University at Qatar (2020) Faculty Fellow at Qatar-Shell Research and Technology Center (2017-2019) Early Career Faculty Research Excellence Award at Texas A&M University at Qatar (2018) While specific details about his advised students and current grants are not publicly listed, Dr. Mansoor's collaborative work with industry partners like Qatar-Shell indicates active engagement in applied research projects.

Laura MillerView profile

Associate Professor

• Veterinary Virology
• Immunology
• Animal Genetics
• +3 more

Dr. Laura C. Miller is an Associate Professor in Veterinary Virology, Immunology & Genetics at Kansas State University's College of Veterinary Medicine. She joined K-State in 2023 after a 21-year USDA career focused on controlling swine viral diseases like PRRSV and Influenza A. Her research integrates 3D cell culture, spatial transcriptomics, and vaccine development to address economically critical livestock diseases. Ph.D. (2001) from University of Reading/Institute for Animal Health B.Sc. Hons. (1997) from University of Edinburgh Dr. Miller leads USDA-NIFA funded training programs and teaches DVM courses in Virology, Immunology, and Veterinary Public Health. Her work spans molecular virology (e.g., PRRSV N protein interactions) to global food security implications of animal health. Key collaborations include the National Bio and Agro-Defense Facility and editorial roles at Frontiers in Immunology , Frontiers in Genetics , and Frontiers in Veterinary Science . 2025 publications highlight advancements in AI diagnostics for African Swine Fever and interferon-expressing PRRSV vaccines. Her 2024 work explores SARS-CoV-2 responses in deer epithelial cells and GTPase-mediated viral inhibition. Awards include K-State's University Outstanding Scholar and leadership roles in swine immunology consortia. Scientific Awards: University Outstanding Scholar (Kansas State University) President, American Association of Veterinary Immunologists (2016 & 2023) Member-at-Large, NC-229 Swine Viral Diseases (2024-) She mentors graduate students like Sarlo Davila K.M. and Sang Y., and serves on university committees including Research Computing Advisory and Corporate Engagement. Her lab investigates genetic components of livestock disease expression and develops tools for global animal protein production efficiency.

• Biochemistry
• Computational Biology
• Enzyme Catalysis
• +4 more

Pratul Agarwal is a Professor in the Department of Physiological Sciences at Oklahoma State University (OSU), where he also serves as Associate Vice President for Research (Cyberinfrastructure) and Director of the High-Performance Computing Center since 2019. Previously, he held roles at Oak Ridge National Laboratory (2005-2018) and the University of Tennessee (2012-2019). With a Ph.D. in Computational Biochemistry from Pennsylvania State University (2002) and an MSc in Biochemical Engineering from IIT Delhi (1997), his work bridges biochemistry, computational biology, and high-performance computing (HPC). Agarwal’s research focuses on enzyme catalysis, genomic surveillance for pandemic prediction, and HPC infrastructure. His group develops hybrid computational-experimental methods to study protein structure-dynamics-function relationships, particularly in antibiotic resistance enzymes and redox regulators like BLVRB and APE1. He co-created the OSU Pandemic Prediction Dashboard for real-time SARS-CoV-2 surge forecasting. His 15 most recent publications (2019-2025) span enzyme dynamics (β-lactamases, Rev1, TERT), computational genomics (SARS-CoV-2 mutations), and metalloprotein mechanisms (LPMO, APE1). These leverage molecular dynamics , QM/MM simulations , and machine learning to dissect catalytic pathways and design inhibitors. Awards: Distinguished Contributor Award, ORNL (2011) Outstanding Paper Award (2010) Key Contributor Award (2010) Agarwal has secured grants from NASA , National Institutes of Health (NIH) , and National Science Foundation (NSF) for HPC infrastructure, multiscale modeling of enzymes, and pandemic prediction systems. He mentors interdisciplinary collaborations with structural biologists, enzymologists, and computational scientists globally.

Yasemin J. ErdenView profile

Associate Professor

• Ethics
• Philosophy of Artificial Intelligence
• Health and Well-being
• +4 more

Yasemin J. Erden serves as an Associate Professor specializing in Philosophy with a pronounced focus on the ethical dimensions of artificial intelligence, health and well-being, and the societal implications of emerging technologies. Her interdisciplinary work bridges philosophical inquiry with neuroscience, biomedical engineering, and cognitive science to address critical questions at the intersection of human identity and technological augmentation. Her core research interests include: Ethics of Artificial Intelligence and Machine Autonomy Philosophy of Mind in Cognitive Prostheses Autonomy and Authenticity in Technology-Enhanced Selves Research Integrity and the Replication Crisis Ethical Assessment of Medical Robotics and Exoskeletons Memory, Identity, and Neural Enhancement Technologies Analysis of her recent publications (2024-2025) reveals a concentrated investigation into how cognitive and physical augmentation technologies reshape human experience. She critically examines hippocampal prostheses through functionalist philosophy, analyzes exoskeleton ethics across clinical/military contexts, and connects lying behaviors to foundational questions in philosophy of mind. Her work demonstrates consistent engagement with practical implementation challenges of ethical frameworks in real-world technological applications. Dr. Erden actively contributes to academic discourse through invited presentations on AI ethics, including "Ethics practice for science correction" (2023), "AI for psychiatry" (2023), and "Me, Myself, and AI" (2023). She extends her expertise to public audiences through media engagements such as commentary on tech sector trust dynamics (TikTok analysis, 2023) and human enhancement technologies (2022).

Francis MottaView profile

Associate Professor

• Topological Data Analysis
• Dynamical Systems
• Mathematical Biology
• +2 more

Francis Motta is Associate Professor in FAU's Department of Mathematics and Statistics. He obtained his Ph.D. from Colorado State University in 2014, specializing in computational topology and dynamical systems. Research integrates: Topological methods with machine learning Mathematical biology of infectious diseases Spatiotemporal analysis of complex systems Publications demonstrate novel applications of persistent homology to biological systems, particularly malaria pathogenesis and protein folding dynamics. Recent work establishes coupling between parasite replication cycles and host circadian rhythms. Active in interdisciplinary collaborations with biologists and computational scientists. Research supported by grants focused on developing topological algorithms for biological data analysis.

Jingyu LiuView profile

Professor

• Data Mining
• Multimodal Machine Learning
• Bioinformatics
• +6 more

Dr. Jingyu Liu is a Professor in the Department of Computer Science at Georgia State University (GSU), where she focuses on imaging genomics and the application of engineering advancements to biomedical research. She holds a PhD in Electrical and Computer Engineering from the University of New Mexico (2004), along with earlier degrees from Northern JiaoTong University. Prior to joining GSU in 2019, she conducted research at institutions such as the Mind Research Network and the Olin Neuropsychiatry Research Center. Her work bridges data science, neuroscience, and genetics, particularly in understanding brain anomalies linked to mental illnesses like schizophrenia, ADHD, and Alzheimer’s disease. Key research areas include multimodal machine learning, functional connectivity analysis, and the integration of genomic, epigenetic, and neuroimaging data. Dr. Liu’s research emphasizes the development of computational methods to analyze large-scale neuroimaging datasets, such as functional MRI and EEG, alongside genetic and epigenetic markers. Her projects include predicting disease progression, identifying biomarkers for mental health conditions, and studying developmental trajectories in children. Collaborations with global consortia like ENIGMA highlight her focus on cross-continental and collaborative research. She has pioneered frameworks like DSAM and aNy-way ICA, advancing the field of brain network analysis. Her work frequently explores the interplay between genetic factors and brain structure/function, aiming to improve diagnostic tools and treatments. Notable contributions include studies on the oral microbiome’s influence on brain connectivity in psychiatric disorders and the use of deep learning for mental health prediction. Dr. Liu’s methodologies, such as sparse parallel ICA and brain age modeling, demonstrate her expertise in both theoretical and applied computational neuroscience.

• Quantum Computing
• Data Science
• Social Network Analysis
• +4 more

George Km is a Professor of Computer Science at Oklahoma State University, affiliated with the Department of Computer Science since 1994. He holds a Ph.D. in Mathematics from Stony Brook University. His research focuses on quantum computing, big data analytics, social media analysis, and algorithm design. He has led numerous grants, including projects on quantum sensor data prediction, big data education, and Hadoop optimization. Notable contributions include work on quantum circuit algorithms, predictive analytics using Twitter data, and entropy-based veracity models. Teaching responsibilities include courses such as Formal Language Theory, Quantum Algorithms, and Numerical Methods. He has designed advanced special topics courses in quantum computing and big data. His work integrates theoretical concepts with practical applications in finance, healthcare, and social networks. Grants funded by the National Science Foundation (CISE) and industry partners demonstrate his impact in computational science and education. Publications span quantum automata, machine learning for financial modeling, and data reduction techniques. His research emphasizes interdisciplinary approaches, addressing challenges in algorithmic efficiency, data veracity, and computational infrastructure optimization. He advises on graduate courses and contributes to curriculum development in emerging technologies.

Weiwei DangView profile

Associate Professor

• Epigenetics
• Aging Research
• Cancer Biology
• +3 more

Weiwei Dang is an Associate Professor at Baylor College of Medicine, affiliated with the Huffington Center On Aging and the Department of Molecular and Human Genetics. He also serves as a Member of the Dan L Duncan Comprehensive Cancer Center and a Basic Science Representative in the Faculty Senate. His research focuses on epigenetic mechanisms regulating aging and age-related cancers, using yeast replicative aging models and mammalian stem cells. Key areas include histone modifications, chromatin architecture, and stress response pathways. Education: PhD from Southern Illinois University (2006), Post-Doctoral Fellowship at the University of Pennsylvania (2011). His lab has received grants from the National Institute on Aging (NIA) for projects such as 'Regulation of longevity through maintenance of transcription fidelity' (R01AG052507) and 'Molecular mechanisms of cellular response to age-associated chromatin changes' (R01AG081347). Research highlights include discoveries of cryptic transcription in aging cells and the CAD response mechanism, which promotes longevity by addressing chromatin defects. Collaborative efforts with postdocs (e.g., Brenna McCauley, Qinghao Zhang) and graduate students (e.g., Nic Nikoloutsos) advance understanding of epigenetic pathways in aging and oncogenesis.

Ioanna FampiouView profile

Assistant Professor

• Computational Materials Science
• Catalysis
• Nanomaterials
• +3 more

Ioanna Fampiou is a Continuing Track Assistant Professor at the University of Delaware's Department of Materials Science and Engineering, part of the College of Engineering. She holds a B.Sc. and M.Eng. in Electrical and Computer Engineering from the National Technical University of Athens (Greece) and a Ph.D. in Mechanical Engineering from the University of Massachusetts Amherst (2014). Prior to her current role, she served as a Visiting Assistant Professor at Villanova University's Department of Mechanical Engineering. Education: B.Sc., Electrical and Computer Engineering, National Technical University of Athens M.Eng., Electrical and Computer Engineering, National Technical University of Athens Ph.D., Mechanical Engineering, University of Massachusetts Amherst (2014) Research Interests: Her work focuses on computational materials science, catalysis, and engineering education. Her studies explore surface chemistry, nanomaterials, and energy materials, with a particular emphasis on catalyst design, reaction mechanisms, and computational modeling of 2D materials like graphene and transition-metal dichalcogenides (TMDs). She also contributes to curriculum development in materials science education. Research Trends: Her publications highlight advancements in understanding catalytic processes (e.g., methanol oxidation on gold surfaces), lithium intercalation in graphene-MoS 2 heterostructures, and machine learning applications in predicting adsorption energies. Recent work (2023) investigates strain effects on TMDs' electronic properties, reflecting her expanding focus on nanotechnology and energy materials. Awards: Certificate of Distinction in Teaching, Harvard University (2018) Advising & Grants: While no formal advisees are listed, her teaching and curriculum development roles emphasize educational innovation. No specific grants are mentioned in the provided texts. Labs/Teams: Not explicitly stated, but her research likely aligns with computational materials science groups within the Department of Materials Science and Engineering.

• Radiation Oncology
• Stereotactic Radiosurgery
• Tumor Control
• +2 more

Dr. Cheng Yu is Professor of Clinical Neurological Surgery and Radiation Safety Officer at Keck Medical Center of USC. He earned his PhD in solid state physics from Michigan Technological University and completed post-doctoral training in radiation oncology at the University of Chicago. With expertise spanning stereotactic radiosurgery systems, machine calibration, and treatment planning, he has managed thousands of cases involving tumors and vascular malformations. Research focuses on comparative dosimetry across radiosurgery modalities (linac, Gamma Knife, CyberKnife), treatment optimization, and precision targeting. Authored over 100 peer-reviewed papers and contributed to AAPM Task Group 135 on robotic radiosurgery QA. Clinical innovations include developing protocols for hypofractionated brain treatments and automatic metastasis detection algorithms. Recent publications explore mitochondrial mechanisms in bone metabolism and viral oncology pathways. Maintains active research in radiation physics advancements and neuro-oncology applications.

Wenjun XieView profile

Assistant Professor

• Enzymology
• Enzyme Engineering
• Computational Chemistry
• +3 more

Wenjun Xie is an Assistant Professor of Medicinal Chemistry at the University of Florida's College of Pharmacy. He holds a B.S. in Chemistry and Statistics and a Ph.D. in Physical Chemistry from Peking University. His postdoctoral training included work at MIT and the University of Southern California under Nobel Laureate Dr. Arieh Warshel. His research focuses on enzymology, enzyme engineering, computational chemistry, AI-driven drug discovery, gene editing, and natural product biosynthesis. Xie's work integrates experimental and computational approaches to advance biocatalyst design and pharmaceutical innovation. Education Peking University – B.S. in Chemistry and Statistics (2012, 2017) Massachusetts Institute of Technology – Ph.D. in Physical Chemistry (2020) Postdoctoral Associate at MIT (2017–2020) and University of Southern California (2020–2023) Research Interests : Dr. Xie’s lab explores enzyme catalysis mechanisms, computational modeling of biological systems, and AI-driven solutions for drug discovery. Key projects include engineering haloalkane dehalogenases, optimizing luciferase proteins for bioluminescence, and studying chromatin dynamics using deep learning. His work bridges fundamental biochemistry with translational applications in medicine and materials science. Publications : Recent work highlights AI-driven enzyme design, supramolecular assemblies in antiviral systems, and computational studies of ion channels. His articles reflect a focus on interdisciplinary approaches to solve complex biological problems. Grants and Collaborations : Active collaborations with institutions like USC and MIT, leveraging Nobel laureate expertise in computational chemistry. Research is funded through grants focused on AI in drug discovery and enzyme engineering.

Arthur SugdenView profile

Adjunct Professor

• Machine Learning
• Data Science
• Neuroscience
• +6 more

Arthur Sugden is an Adjunct Professor at the Integrated Innovation Institute in Pittsburgh, PA, and the Founder and CEO of Allref Inc., with a career spanning academia and industry in highly interdisciplinary domains. His academic credentials include: BA in Physics and Astronomy from Wesleyan University PhD in Molecular Biology, Cellular Biology, and Biochemistry from Brown University (2015) Postdoctoral research at Harvard University's Beth Israel Deaconess Medical Center Dr. Sugden's research integrates data science, machine learning, and neuroscience with applications in wearable technology. His work spans viral oncology (Epstein-Barr/Kaposi's sarcoma viruses), neural mechanisms of memory consolidation, physiological state estimation, and supernova astronomy, reflecting exceptional breadth across natural sciences and computational methods. Analysis of his 9 key publications (2007-2021) reveals an evolution from virology and astronomy toward neuroscience and machine learning, with recent high-impact work in Neuron and Nature Neuroscience exploring how association cortex links sensory cues to outcomes and how insular cortex tracks physiological states. No scientific awards are documented in the provided materials. While his industry role as CTO of Behaivior (developing opioid craving detection via wearables) demonstrates applied research translation, no student advising or grant funding details are specified.

Deepak NagrathView profile

Professor

• Cancer Metabolism
• Tumor Microenvironment
• Systems Biology
• +4 more

Deepak Nagrath is a Professor of Biomedical Engineering at the University of Michigan's College of Engineering, affiliated with the Biointerfaces Institute. His lab focuses on systems biology approaches to understand cancer metabolism and tumor microenvironment interactions. Key research areas include metabolic flux analysis, collateral lethal target identification (CLIM platform), and developing precision therapies using circulating tumor cell organoids. The lab integrates machine learning with genomic data to model metabolic dependencies in cancers like pancreatic, lung, and brain tumors. Education details are not explicitly stated in the provided text, but Dr. Nagrath's work emphasizes interdisciplinary training at the intersection of engineering, biology, and computational science. His lab's research highlights include: Metabolic systems biology of human diseases Extracellular vesicle-mediated metabolic crosstalk Microfluidic platforms for tumor organoid generation Machine learning-driven metabolic flux analysis Research interests center on dissecting how tumor microenvironments modulate cancer cell metabolism, with a focus on developing therapies targeting metabolic vulnerabilities. Recent advancements include metabolic modeling of brain cancers and digital twin technology for personalized therapy. Notable projects include the CLIM platform for identifying collaterally lethal genes in ovarian cancer and the development of the ExoSponge device for exosome isolation. The lab collaborates with clinical teams to translate findings into therapies for metastatic cancers and liver diseases. Grant activities involve NSF funding (e.g., Ajay Shankaran's Graduate Research Fellowship) and partnerships with industry for device commercialization. The lab is part of the Biointerfaces Institute, fostering collaborations in biomaterials and regenerative medicine.