Robin Andersson is an Associate Professor at the Department of Biology, University of Copenhagen , leading the Andersson Lab focused on modeling gene regulation to understand how enhancer and promoter dysregulation contribute to disease risk. His interdisciplinary research combines machine learning , statistical learning , genetics , and molecular biology to determine which noncoding sequences act as enhancers, predict regulatory activity from DNA sequences, and characterize mechanisms controlling gene expression variation. His research has produced significant insights into enhancer-promoter interactions , epigenetic inheritance , and transcriptional robustness . He has developed computational tools like ChromTransfer and hyperTRIBER for analyzing chromatin accessibility and RNA editing . His work bridges genomic mechanisms of disease with practical applications in noncoding variant interpretation and therapeutic target identification . Robin Andersson has received prestigious awards including the ERC Horizon 2020 Starting Grant , Sapere Aude Research Leader award , and Hallas-Møller Ascending Investigator award . He has supervised 17 MSc and 5 PhD students while contributing to academic service as PhD coordinator and strategic research board member. The lab maintains affiliations with the Novo Nordisk Foundation Center for Genomic Mechanisms of Disease and FANTOM consortium , with recent grants focusing on single-cell regulatory mapping and disease variant interpretation .
Pooya Hatami is an Associate Professor in the Department of Computer Science and Engineering at Ohio State University's College of Engineering. He joined the CSE department in 2019 after completing postdoctoral research at UT Austin (hosted by David Zuckerman) and spending two years as a postdoctoral researcher at the Institute for Advanced Study at Princeton and DIMACS at Rutgers University. He earned his Ph.D. from the University of Chicago in 2015 under the supervision of Alexander Razborov and Madhur Tulsiani. His research interests focus on Theoretical computer science , with particular emphasis on Randomness and Pseudorandomness, Communication Complexity, Analysis of Boolean Functions, Additive Combinatorics, and Learning Theory . His work often bridges theoretical computer science with mathematical concepts, developing rigorous frameworks for understanding computational complexity and designing efficient algorithms. His research has been supported by NSF grant CCF-1947546, demonstrating the significance and impact of his contributions to the field. An analysis of his recent publications reveals a strong focus on the intersection of learning theory and computational complexity, with particular attention to replicability in machine learning, communication complexity lower bounds, and the theoretical foundations of Boolean functions. His work on the Implicit Graph Conjecture and Borsuk-Ulam applications to learning theory demonstrates innovative approaches to longstanding problems in theoretical computer science. Scientific Awards: Best Paper Award at ICALP 2023 for "Online Learning and Disambiguations of Partial Concept Classes" Professor Hatami actively mentors graduate students, currently advising Pushen Wang and Yuting Fang in Computer Science and Engineering, and Chavdar Lalov and Sivan Tretiak in Mathematics. His involvement in program committees for major conferences like SODA 2024 and FOCS 2025 highlights his standing in the theoretical computer science community. His research has established important connections between pseudorandomness, communication complexity, and learning theory, contributing significantly to our understanding of fundamental computational limits.
Michel Kinsy is an Associate Professor at Arizona State University's School of Computing and Augmented Intelligence and Director of the Secure, Trusted, and Assured Microelectronics (STAM) Center. His work bridges hardware security, cryptographic systems, and efficient computing architectures. Education: PhD in Computer Science from Massachusetts Institute of Technology His research focuses on hardware security , including secure architectures, trusted execution environments, quantum-proof cryptography, polymorphous architectures, and zero-trust computing systems. Recent projects explore privacy-preserving machine learning, zero-knowledge proofs, and homomorphic encryption acceleration. Key publication trends include: Hardware security for post-quantum cryptography (2020-2025) Secure distributed systems (2021-2025) Privacy-preserving machine learning implementations (2018-2025) Root-of-trust mechanisms in edge devices (2019-2023) Cryptographic protocol acceleration (2020-2024) Scientific Recognition: MIT Presidential Fellow CRA-WP Inaugural Skip Ellis Career Award He teaches graduate-level courses in computer architecture, research methodology, and thesis/dissertation advising, with recent offerings including CSE 792 Research , EEE 599 Thesis , and CEN 799 Dissertation . As STAM Center director, Kinsy leads initiatives in secure microelectronics and collaborates with hardware/software co-design teams. His research website provides detailed project information: https://stamcenter.asu.edu
Namshik Han is a computational drug discovery scientist currently serving as Head of Computational Research & AI at the Milner Therapeutics Institute and Associate Faculty at the Cambridge Centre for AI in Medicine, both within the University of Cambridge. He also holds an Adjunct Professor position at Yonsei University College of Medicine. His work bridges academic research with industry applications through co-founding two startups: KURE.ai Therapeutics in the USA (focused on immune-oncology NK cell therapy) and CardiaTec Biosciences in the UK (dedicated to cardiovascular disease drugs), as well as contributing to the establishment of Storm Therapeutics. Dr. Han's research centers on developing and applying specialized Artificial Intelligence technologies to analyze complex multi-modal biomedical datasets. His lab at the Milner Therapeutics Institute focuses on enhancing AI technology for therapeutics research through machine learning, statistical analysis, and mathematical techniques applied to multi-omics and drug discovery. Key research areas include identifying novel therapeutic targets across diseases, drug repositioning, predicting drug efficacy and safety, and patient stratification for personalized medicine. His work leverages both publicly available big data and purposefully generated experimental data from academic collaborators and pharma/biotech partners. Analysis of Dr. Han's recent publications reveals a strong trend toward applying AI methodologies across diverse biomedical challenges. His work spans RNA methylation pathway prediction, drug-induced liver injury detection through NLP, cancer immunotherapy target identification using CRISPR screens, and SARS-CoV-2 pathway analysis for drug repurposing. These publications demonstrate his expertise in translating computational approaches to address specific therapeutic challenges across multiple disease areas. Dr. Han actively facilitates access to state-of-the-art AI technology for partner organizations within the Milner Consortium while developing novel computational methods. His entrepreneurial activities through startup companies indicate significant engagement with translational research and commercialization of academic discoveries. His laboratory utilizes interdisciplinary approaches combining computational methods with experimental validation across therapeutic areas. The lab has developed innovative approaches such as utilizing Artificial Neural Networks to predict the Mode of Action of drugs by simulating drugs on protein-protein interaction networks, as published in Science Advances (2021). This work exemplifies their strategy of bridging virtual simulations with real-world biological validation to advance therapeutic discovery.
Joo Won Park is an Associate Professor of Music Technology at Wayne State University, creating experimental electroacoustic compositions through electronics, toys, and everyday objects. His work has been featured at international festivals (ICMC, SEAMUS) and released across multiple labels (MIT Press, PARMA). He received the Kresge Arts Fellowship (2020) and Knight Arts Challenge Detroit (2019). Teaches courses like Theories of Electronic Music and Advanced Synthesis Director of Electronic Music Ensemble of Wayne State (EMEWS) which toured nationally Park's research focuses on making mundane sounds musical through creative coding and hardware manipulation. His 100 Strange Sounds YouTube series and Overundertone album archive his exploration of sonic possibilities in everyday environments. He emphasizes portability, affordability, and replicability in electronic instrument design. His electroacoustic works explore themes like human-machine interaction , game controller performance , and playful sound manipulation . The PS Quartet No.1 exemplifies his interest in video game muscle memory and controlled randomness in live performance. Scientific awards include: Knight Arts Challenge Detroit (2019, 2021) Kresge Artist Fellowship ($25,000, 2020) New Music USA Grant (2019) Active in the electroacoustic community as: Board member, Society for Electroacoustic Music in the United States Editorial member, Korean Electroacoustic Music Society Associate Director, Third Practice Electroacoustic Music Festival
F. Javier Arsuaga is a Professor in the Department of Molecular and Cellular Biology at the University of California, Davis, with affiliations in the Mathematics Department and multiple graduate groups including Biochemistry, Molecular, Cellular and Developmental Biology; Biostatistics and Statistics; and Mathematics. Position: Professor of Molecular and Cellular Biology Institution: University of California, Davis Office: Briggs Hall 0009 and MSB 2115 Email: jarsuaga@ucdavis.edu Graduate Group Affiliations: Biochemistry, Molecular, Cellular and Developmental Biology; Biostatistics, Statistics; Mathematics Dr. Arsuaga received his BS in Mathematics from Universidad de Zaragoza, Spain in 1993 and his PhD in Mathematics from Florida State University in 2000. His academic journey reflects a unique interdisciplinary path that bridges pure mathematics with molecular biology. His research focuses on developing mathematical and computational methods to address questions related to the 3D structure of chromosomes. The three-dimensional organization of the genome plays a critical role in cellular processes such as transcription, replication, and repair. His work has particular relevance to understanding DNA packaging in bacteriophages, mitochondrial DNA in trypanosomes (kDNA), and yeast. Dr. Arsuaga employs tools from low-dimensional topology, computational knot theory, random knotting, algebraic topology, persistence homology, combinatorics, statistics, and Monte Carlo methods. His laboratory, the Topological Molecular Biology Lab, is deeply committed to promoting diversity in mathematics and the sciences. An analysis of his recent publications reveals a consistent focus on applying topological methods to biological problems, particularly in three main areas: DNA topology in viral systems, kinetoplast DNA network analysis in trypanosomes, and cancer genomics. His work demonstrates how mathematical approaches can provide novel insights into genome organization, with applications ranging from understanding basic biological mechanisms to identifying patterns in cancer genomes. 2018 Plenary speaker: Abel Symposium, Geiranger, Norway 2018 Plenary speaker: Encuentros en Algebra Computacional y Aplicaciones (EACA), Zaragoza, Spain 2013-2014 Long Term Visitor of the Institute of Mathematics and Its Applications (IMA), Minneapolis, MN 2012 Plenary speaker: Conference in Computational Physics, Kobe, Japan 2011 Research selected by NSF for the NSF highlights As an advisor, Dr. Arsuaga has mentored numerous students including Maxime Pouokam and Rachael Phillips who completed Master's theses under his guidance. His laboratory has been supported by multiple National Science Foundation grants including DMS1519375, DMS1057284, and DMS0920887. He co-organizes the Biology and Mathematics in the Bay Area (BaMBA) conference, which encourages dialogue between researchers from different disciplines. His lab is known for being interdisciplinary and vertically integrated, bringing together mathematicians, biologists, and computational scientists to tackle complex biological problems. The Topological Molecular Biology Lab conducts research at the interface of mathematics and molecular biology, focusing on applications of topological methods to understand genome organization, study genome rearrangements in cancer, and model enzymatic actions such as those of recombinases and topoisomerases. The lab is known for developing innovative mathematical approaches to analyze complex biological structures and has made significant contributions to understanding DNA topology in various biological contexts.
Christian Scheideler is a Professor at the Institute for Computer Science (Theory of Distributed Systems) within the Faculty of Electrical Engineering, Computer Science, and Mathematics at the University of Paderborn. He serves as institute director, advisory committee member of SPAA, and associate editor for Journal of the ACM and Journal of Computer and System Sciences . His editorial and leadership roles extend to managing Journal of Interconnection Networks and steering committees for conferences like DISC, SIROCCO, and ALGOSENSORS. Director, Institute for Computer Science Advisory Committee, SPAA Associate Editor, Journal of the ACM and Journal of Computer and System Sciences Managing Editor, Journal of Interconnection Networks Steering Committee member for DISC, SIROCCO, ALGOSENSORS His research focuses on distributed algorithms, data structures, security in distributed systems, randomized algorithms, stochastic processes, network theory, and discrete mathematics . Notably, he investigates hybrid programmable matter systems, self-stabilizing overlay networks, and robust distributed protocols under adversarial conditions. Recent publications (2021-2025) highlight work on 3D programmable matter shape formation , low-diameter graph decompositions , reconfigurable circuits in amoebot models , and blockchain lightweight state replication . Topics span distributed computing, computational geometry, and network security. Scientific awards include the 2022 Edsger W. Dijkstra Prize in Distributed Computing for foundational work in self-stabilization and overlay networks. He has served as PC Chair (DISC 2022) and organized numerous conferences (SPAA, SSS, SIROCCO).
Ricardo Eiris is an Assistant Professor at Arizona State University's School of Sustainable Engineering and the Built Environment. His research integrates emerging technologies to enhance human performance in construction workforce training and education. Education Ph.D. in Design, Construction, and Planning, University of Florida (2020) M.S. in Digital Arts and Science, University of Florida (2020) M.S. in Construction Management, University of Florida (2016) M.S. in Civil Engineering, University of Florida (2016) B.S. in Civil Engineering, Universidad Metropolitana - Venezuela (2013) Research Focus His work spans three interconnected domains: (1) AI-Enabled Metaverse for workforce education transformation, (2) Extended Reality (AR/VR/MR) for hazard visualization, and (3) Drone Operations for inspection training. He develops immersive environments like iVisit and DroneSim to address safety and training gaps. Scientific Contributions 2024: 360-degree digital twins for task detection 2023: Social equity in PPE accessibility 2022: Multiuser VR site visit frameworks 2021: Drone flight visualization systems 2020: Comparative VR vs traditional safety methods Honors & Awards ASC VDC Faculty Boot Camp Fellowship (2024) ASC International Best Conference Paper Award (2023) ASC Mechanical & Electrical Faculty Fellowship (2022) ASCE ExCEEd Fellowship (2021) National Academies STEM Education Competition Winner (2020) Teaching & Leadership He teaches courses in construction technology and advanced research methods. Leads the Human-Centered Technology in Construction (HCTC) Research Group, focusing on technology-driven safety and workforce development.
Mårten Björkman is a Professor at the School of Electrical Engineering and Computer Science , Royal Institute of Technology (KTH) , specializing in Robotics, Perception and Learning . His research bridges 3D computer vision with multimodal sensor fusion, including force-torque sensing, to enhance human-robot interaction. Recent work focuses on modeling sequential data for robotic control, human movement prediction, and power systems. Key research areas include: Reinforcement learning for robotic systems Human movement analysis and prediction Implicit regularization in neural networks Online learning for dynamical systems Power system control with AI 3D perception through multi-view vision His recent publications span deep learning for assembly inspection , EEG-based brain-robot interfaces , safe reinforcement learning , and multimodal motion generation . The work intersects robotics, machine learning, and human-centric system design. The Robotics, Perception and Learning division at KTH hosts his research, equipped with state-of-the-art facilities for robotic vision and human interaction studies.
Brian Anthony Kelch is a Professor in the Department of Biochemistry and Molecular Biotechnology at UMass Chan Medical School, affiliated with the Morningside Graduate School of Biomedical Sciences. He holds additional roles in the Interdisciplinary Graduate Program and MD/PhD Program. Kelch earned his BS in Biochemistry & Molecular Biology from Pennsylvania State University and his PhD in Biochemistry & Molecular Biology from the University of California, San Francisco. His research focuses on structural and mechanistic studies of macromolecular machines , with emphasis on viral assembly mechanisms and DNA replication/repair complexes. The Kelch Lab employs cryo-EM, biochemical assays, and biophysical approaches to investigate clamp loaders, viral packaging motors, and DNA-protein interactions. Key areas include: Conformational dynamics in bacteriophage assembly Eukaryotic vs. prokaryotic clamp loader mechanisms Thermostable viral capsid engineering DNA damage signaling pathways Kelch's publications demonstrate consistent focus on structural virology (45%), DNA replication machinery (35%), and enzyme mechanisms (20%), with recent work exploring neurodevelopmental implications of viral proteins. His lab actively recruits postdoctoral researchers and collaborates with institutions like UCSF and the International Vaccine Institute.
Dr. Andrei A Korostelev is a Professor at UMass Chan Medical School, with primary appointments in the RNA Therapeutics Institute and the Department of Biochemistry and Molecular Biotechnology at the T.H. Chan School of Medicine. He also holds positions in multiple graduate programs at the Morningside Graduate School of Biomedical Sciences, including Biochemistry and Molecular Biotechnology, Biophysical Chemical and Computational Biology, Interdisciplinary Graduate Program, MD/PhD Program, and RNA Therapeutics and Biology Program. Dr. Korostelev received his BS and MS in Chemistry from Moscow State University, followed by a PhD in Chemistry & Biochemistry from Florida State University. His educational background provided the foundation for his current research in structural biology and molecular mechanisms of protein synthesis. Dr. Korostelev's research focuses on the structure and function of the ribosome, the cellular machine responsible for decoding genetic information and synthesizing proteins. His laboratory employs X-ray crystallography and cryo-electron microscopy to obtain high-resolution snapshots of different functional states of the ribosome during translation. Through biochemical approaches, his team tests hypotheses concerning the mechanisms and dynamics of the ribosome and translation factors. This research not only expands fundamental knowledge of this essential molecular machine but also aids in developing new drugs that target ribosomes, with potential applications in treating bacterial infections and other diseases. Dr. Korostelev's scientific contributions have been recognized with several prestigious awards, including the Soros Academic Fellowship from Moscow State University (1994-1995), the I.V. Berezin Young Scientist Award from Moscow State University (1996-1997), the RNA Society/Scaringe Young Scientist Award (runner-up, 2010), the Earl and Thressa Stadtman Scholar Award from ASBMB (2018), and the Early Career Award from the RNA Society (2018). As an active researcher and mentor, Dr. Korostelev supervises graduate students through rotation projects that apply X-ray crystallography and biochemical methods to understand ribosome mechanisms. His laboratory offers opportunities to investigate translation via mutagenesis/biochemical assays, crystallize and determine structures of translation factors and ribosome complexes, and improve computational methods for macromolecular structure determination. His extensive publication record demonstrates significant contributions to understanding translation termination, ribosome rescue mechanisms, frameshifting, and the structural dynamics of protein synthesis. Dr. Korostelev leads an active research laboratory focused on ribosome structure and function. His team combines structural biology techniques with biochemical approaches to investigate the molecular mechanisms of translation. Through collaborations with other researchers at UMass Chan Medical School and beyond, his laboratory continues to make significant contributions to our understanding of this fundamental biological process and its implications for human health and disease.
Lakshminarayanan Mahadevan, known as L. Mahadevan, is the Lola England de Valpine Professor of Applied Mathematics at Harvard University, with joint appointments as Professor of Organismic and Evolutionary Biology and Professor of Physics. He is a core faculty member of the School of Engineering and Applied Sciences (SEAS), where he leads interdisciplinary research spanning mathematics, physics, and biology through the Mahadevan group. His research explores the physics of living and non-living matter across scales, from molecular to planetary systems. Key interests include soft matter physics, biological morphogenesis, fluid dynamics, elasticity, and movement theory. Using experiments, theory, and computation—termed "Soft Math"—his work uncovers universal principles in complex systems, with recent focus on active matter, nematic systems, and tissue mechanics. Applications range from brain folding and snake locomotion to battery design and robotic systems. 2025 publications reveal intense activity in active matter physics, biological fluid dynamics, and applied mathematics. Dominant themes include nematic film instabilities, stochastic navigation in crowded environments, solid-state battery interfaces, and soft biological structures. Work consistently bridges theoretical modeling with experimental validation, drawing biological inspiration for engineering solutions while addressing challenges from cellular to planetary scales. The Mahadevan group at Harvard SEAS operates as a collaborative hub for mathematicians, physicists, biologists, and engineers. It maintains extensive cross-departmental collaborations within Harvard and international partnerships, emphasizing fundamental questions with tangible applications in biotechnology, materials science, and robotics. The group's culture prioritizes curiosity-driven exploration of everyday phenomena to reveal profound scientific principles.
Dr. Romy Lorenz is a Max Planck Research Group Leader at the Max Planck Institute for Biological Cybernetics in Tübingen, Germany, where she leads the Cognitive Neuroscience & Neurotechnology research group. She previously held postdoctoral positions at the University of Cambridge, Stanford University, and the Max Planck Institute for Human Cognitive & Brain Sciences from 2018 to 2023 as a Sir Henry Wellcome Postdoctoral Fellow. Dr. Lorenz's educational background includes: BSc in Psychology from Leuphana University (2009) MSc in Human-Machine Interaction from TU Berlin (2012) PhD in Neurotechnology from Imperial College London (2017) Her research focuses on understanding the frontoparietal brain network mechanisms that underpin high-level cognition and adaptive behavior. She employs an interdisciplinary approach combining subject-specific brain-computer interface technology, fMRI at standard and ultrahigh magnetic field strengths (3T, 7T, and 9.4T), EEG, non-invasive brain stimulation, computational modeling, and machine learning techniques. A key innovation in her work is the development of neuroadaptive Bayesian optimization methods that allow for real-time, closed-loop experimental design in cognitive neuroscience. Dr. Lorenz's recent publications demonstrate a clear trend toward investigating brain function at increasingly fine-grained spatial scales, particularly exploring layer-specific processing in the prefrontal cortex using ultrahigh-field fMRI. Her work bridges computational neuroscience, cognitive psychology, and neurotechnology, with applications ranging from basic cognitive science to clinical rehabilitation. A significant portion of her research focuses on closed-loop systems that integrate real-time brain imaging with adaptive experimental design and stimulation protocols. Her notable scientific achievements include: Outstanding Contributions in AI Innovation Award Sir Henry Wellcome Postdoctoral Fellowship Funding from the German Scholar Organisation Fellowships from the Wellcome Trust and Engineering and Physical Sciences Research Council Dr. Lorenz has secured significant research funding for her work, including support from the Wellcome Trust and German funding agencies. She has mentored several students, including Master's students like Pedro who has presented their collaborative work at conferences. Her research group actively recruits postdoctoral researchers and students interested in cognitive neuroscience and neurotechnology. Dr. Lorenz leads the Cognitive Neuroscience & Neurotechnology research group at the Max Planck Institute for Biological Cybernetics, which focuses on developing and applying advanced neuroimaging and computational methods to understand high-level cognitive functions. She has also co-initiated interest groups such as CoCoNUT (Computational Cognitive Neuroscience at the Max Planck Institute) to foster interdisciplinary collaboration. Her lab utilizes cutting-edge technologies including real-time fMRI at ultrahigh field strengths, EEG, and non-invasive brain stimulation to investigate frontoparietal network function.
Guilherme Dias de Melo is a Brazilian-French neurovirologist and Chargé de Recherche (Research Professor) at the Institut Pasteur in Paris, France, within the Unité Lyssavirus, épidémiologie et neuropathologie . Since 2022, he has led research on neurotropic viruses, focusing on SARS-CoV-2 and rabies virus , with a special emphasis on long COVID and viral persistence in the brain. Education: Habilitation à diriger des recherches (HDR), Université Paris Cité, 2025 Ph.D. in Medical and Surgical Pathophysiology, São Paulo State University (UNESP), Brazil, 2015 M.Sc. in Veterinary Medicine, UNESP, Brazil, 2012 D.V.M. (Doctor of Veterinary Medicine), UNESP, Brazil, 2010 Research Interests: Guilherme is deeply invested in understanding how neurotropic viruses such as SARS-CoV-2 and rabies virus invade the central nervous system, persist at low levels, and trigger long-term neurological symptoms like anxiety, memory loss, and depression. His work integrates cellular models , in vitro stem cell systems , and animal models to dissect the molecular mechanisms of viral neuroinvasion and neuroinflammation. His research spans: Neurotropic virus pathogenesis Long COVID and post-viral syndromes Viral persistence in brain tissue Neuroinflammation and immune responses in the CNS Rabies virus as a model for CNS infection Development of antiviral therapies and neutralizing antibodies Research Trends: His recent publications (2022–2025) reveal a strong focus on long COVID neurobiology , including transcriptomic profiling of brainstem changes in hamster models, the role of viral persistence in neurological symptoms, and the development of broad-spectrum neutralizing antibodies for both SARS-CoV-2 and rabies. He has also contributed to spatial transcriptomics , antiviral drug mechanisms , and immune imprinting in the context of viral variants. Scientific Awards & Recognition: While no formal awards are listed, his work has been recognized through high-impact publications and his role in the ANRS-MIE “Action coordonnée Covid long” group, a national initiative in France to address long COVID. Grants & Collaborations: Guilherme has worked across continents, including: Postdoctoral fellowships at Institut Pasteur (2015–2022) Visiting researcher at Institut Pasteur Korea (2018) Visiting scholar at Justus-Liebig University, Germany (2012) Active member of the ANRS-MIE long COVID initiative since 2022 Labs & Teams: He is part of the Lyssavirus, Epidemiology and Neuropathology Unit led by Hervé Bourhy at the Institut Pasteur Paris. The lab is equipped with state-of-the-art tools for studying viral neuroinvasion, including advanced microscopy, stem cell systems, and electrophysiology platforms.
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.
