Find Academic Supervisors

• Artificial Intelligence
• Cardiovascular Medicine
• Machine Learning
• +5 more

Dr. Evangelos (Evan) Oikonomou is an Assistant Professor in the Section of Cardiovascular Medicine at Yale School of Medicine. A physician-scientist specializing in AI applications for cardiovascular disease, he leads research at the intersection of computer vision, machine learning, and precision cardiology. His work focuses on developing scalable digital tools that can be integrated into clinical care pathways to improve cardiovascular diagnosis and risk assessment. Dr. Oikonomou's educational background includes: MD from the University of Athens Medical School (graduated as valedictorian) D.Phil. in Medical Sciences from the University of Oxford Internal Medicine Residency and Cardiology Fellowship at Yale School of Medicine His research spans multiple domains of AI in cardiovascular medicine, with particular focus on precision phenotyping and digital biomarkers. Key areas include developing perivascular adipose tissue imaging biomarkers for vascular inflammation assessment, designing deep learning algorithms for point-of-care echocardiography, and leading data-driven evaluations of treatment effect heterogeneity across clinical trials. His work aims to leverage multimodal AI to redefine diagnostic and prognostic frameworks in cardiovascular disease, emphasizing real-world implementation and equity in access to advanced diagnostics. Dr. Oikonomou's recent publications demonstrate a strong trend toward developing and validating AI algorithms that can be deployed in clinical settings for cardiovascular disease detection and risk stratification. His research increasingly focuses on multimodal approaches combining echocardiography, electrocardiography, and other data sources to create comprehensive cardiovascular assessment tools. His work has particular emphasis on making these tools accessible and applicable across diverse patient populations. Dr. Oikonomou has received numerous prestigious awards, including: NIH F32 Ruth L. Kirschstein National Research Service Award Young Investigator Awards from American Heart Association, American College of Cardiology, and European Society of Cardiology Heart Tank For the Cardiovascular Investigator - Imaging (Winner) from American College of Cardiology Trainee Poster Award Winner from CERSI Summit 2024 ASCI emerging generation (e-Gen) award from American Society of Clinical Investigation Elizabeth Barrett-Connor Research Award in Epidemiology and Prevention from American Heart Association Dr. Oikonomou leads the Cardiovascular Data Science Lab (CarDS) at Yale, where his team develops and implements AI-driven solutions for cardiovascular disease diagnosis and risk assessment. The lab focuses on creating practical, scalable tools that can be integrated into existing clinical workflows to enhance precision medicine approaches in cardiology.

• Neuroscience
• Neuroimaging
• Biomedical Engineering
• +3 more

Malika Datta is a Research Fellow in Neuroscience at Yale School of Medicine, Yale University. Her work focuses on advanced neuroimaging techniques and molecular mechanisms in neuroscience. She holds appointments in the Neuroscience department and contributes to interdisciplinary research in biomedical engineering and pharmacology. Her research interests include light-sheet microscopy innovation for large-scale biological imaging, dopaminergic system analysis under drug exposure, and genome editing via focused ultrasound. She has published extensively on topics such as Norrin-mediated astroglia-neuron interactions and optogenetic systems development. Recent publications highlight her contributions to scalable microscopy technologies and brain mapping methodologies. Her work bridges engineering and basic neuroscience, with applications in drug impact studies and neurotechnology. No scientific awards are explicitly mentioned in the provided information.

Paul FletcherView profile

Professor

• Neurobiological mechanisms of psychosis
• Computational psychiatry
• Clinical cognitive neuroscience
• +3 more

Professor Paul Fletcher serves as the Bernard Wolfe Professor of Health Neuroscience at the University of Cambridge Department of Psychiatry and Clinical Director of the Cambridge Neuroscience Interdisciplinary Research Centre. He holds concurrent appointments as a Wellcome Trust Investigator and Honorary Consultant Psychiatrist with the Cambridgeshire and Peterborough NHS Trust and Cambridge University Hospitals NHS Trust. His research centers on neurobiological mechanisms of psychosis , computational psychiatry , and appetite control in disordered eating . Fletcher pioneered influential theories linking prediction error signaling to psychotic symptoms, demonstrating how perturbations in frontal lobe responses explain hallucinations and delusions. His work integrates neuroimaging, psychopharmacology, and computational modeling to bridge clinical observations with neural mechanisms. Analysis of his recent publications reveals a dominant focus on prediction error computation in psychosis cortical structural changes in mental illness neurobiological correlates of eating disorders computational modeling of perceptual inference dopaminergic mechanisms in learning translational neuroscience approaches His work increasingly incorporates multimodal neuroimaging and real-world applications like the Hellblade: Senua's Sacrifice project. Key recognitions include: BAFTA Award for Games Beyond Entertainment (2017) James Bull Lectureship (2017) Election to Academy of Medical Sciences (2012) WFSP Research Award in Biological Psychiatry (2005) Fletcher maintains significant research funding through Wellcome Trust appointments spanning over two decades, including current status as a Wellcome Trust Investigator. His clinical neuroscience program bridges the Department of Psychiatry with NHS trusts, emphasizing translational pathways from basic mechanisms to clinical applications. The Fletcher Group operates within the Cambridge Neuroscience network, collaborating extensively across departments and healthcare systems.

• Neuroscience
• Stem Cell Therapy
• Parkinson's Disease
• +3 more

Professor Lachlan Thompson is a leading academic in neurogenesis and neural transplantation, affiliated with the School of Medical Sciences. His work focuses on advancing stem cell therapies for neurodegenerative diseases like Parkinson’s, particularly through engineered neural grafts and hydrogel-based delivery systems. He leads research on optimizing stem cell differentiation, immune evasion, and functional integration within host neural circuits. Current research students include Laura Ancellotti and Alex Johnson. Key grants include a 2024 NHMRC Ideas Grant for improving Parkinson’s cell therapies and 2023 startup funding for establishing his research programs. His lab collaborates with the Charles Perkins Centre, focusing on translational neuroregenerative strategies. Research interests span stem cell engineering, neural circuit reconstruction, and disease modeling using patient-derived iPSCs. Recent work emphasizes hydrogel oxygen reservoirs, suicide gene activation in grafts, and developmental timing of neural progenitors. Over 80 publications detail advancements in neural transplantation safety, gene therapy approaches, and rodent models of neurological disorders. Awards and recognitions are not explicitly mentioned, though his high-impact publications and NHMRC grants highlight his academic standing. His lab integrates biomaterials science, genetic engineering, and clinical translation to address unmet needs in neurodegenerative therapies.

• Cognitive Neuroscience
• Machine Learning
• Neuroimaging
• +7 more

Karim Jerbi is a Full Professor at the University of Montreal's Department of Psychology, within the Faculty of Arts and Sciences. He holds the Canada Research Chair (CRC) in Systems Neuroscience and Cognitive Neuroimaging (Junior 2) and leads interdisciplinary research programs. His affiliations include the CRM — Centre de recherches mathématiques, CERNEC — Centre de recherche en neuropsychologie et cognition, CRIUGM — Centre de recherche de l'Institut universitaire de gériatrie de Montréal, PhysNum — Laboratoire de physique numérique, BRAMS — Laboratoire international de recherche sur le Cerveau, la Musique et le Son, and CIRCA — Centre interdisciplinaire de recherche sur le cerveau et l'apprentissage. These affiliations emphasize his collaborative and interdisciplinary approach to neuroscience and neuroimaging. His research investigates cognitive functions and dysfunctions using advanced signal processing and machine learning applied to multimodal brain data. Key interests include neural oscillations, brain connectivity, and the interplay between cognitive processes and neuroimaging techniques like MEG and EEG. He explores topics such as sleep dynamics, decision-making, mindfulness meditation effects, and neurodegenerative disorders, bridging computational models with clinical applications. Jerbi's recent work highlights trends in AI-driven neuroimaging tools (e.g., MEEGNet, NeuroPycon), criticality in brain networks, and the impact of consciousness states on neural activity. His grants include leading the UNIQUE initiative (2019–2024) and co-directing projects like 'Partnership for Abundant Intelligences' (2024–2029), funded by organizations like FRQNT and SSHRC. These efforts aim to integrate AI, mathematics, and clinical research for transformative insights into brain function. Scientific Awards: Canada Research Chair (CRC) in Systems Neuroscience and Cognitive Neuroimaging (Junior 2). In advising, he has guided students in topics like AI-based biomarker identification, hypnosis dynamics, and motor intention decoding. His labs and teams, such as the CRM and CERNEC, focus on mathematical foundations of neural systems and neuropsychological cognition, respectively. Collaborations span diverse fields, including gériatrie, music cognition, and computational intelligence, reflecting his commitment to cross-disciplinary innovation.

Min ChenView profile

Professor

• Statistical Genomics
• Bioinformatics
• Bayesian Methods
• +5 more

Dr. Min Chen is a Professor in the Department of Mathematical Sciences at the University of Texas at Dallas (UTD), affiliated with the School of Natural Sciences and Mathematics. He holds an adjunct professorship at the University of Texas Southwestern Medical Center. His expertise spans statistical genomics, bioinformatics, Bayesian methods, and sampling techniques. He completed his Ph.D. in Statistics and Decision Science at the University of Texas at Austin and a postdoctoral fellowship in statistical genomics at Yale University. Education: B.S. in Computer Science (University of Science & Technology of China, 1994); M.A. in Statistics (University of Pittsburgh, 1999); Ph.D. in Statistics (UT Austin, 2006); Postdoc in Statistical Genomics (Yale University, 2008–2010). Research focuses on statistical methodologies in genomics, including genome-wide association studies, network-based modeling, and Bayesian integrative analysis. He also explores spatial modeling and ranked set sampling. His work addresses challenges in cancer genetics, epigenetics, and single-cell gene regulation. Notable awards include the NIH Career Development Award (2013), David Bruton Fellowship (2006), and R.L. Anderson Student Paper Award (2006). He is a member of the American Statistical Association and International Chinese Statistical Association. He advises graduate students in Data Science, Statistics, and Bioinformatics & Computational Biology (BCBM) programs. His teaching includes courses on advanced statistical methods and data science. Research contributions span over 40 peer-reviewed articles, with recent work in tumor pathology imaging, antibiotic resistance, and Alzheimer’s disease mechanisms.

Biniam KebedeView profile

Assistant Professor

• Food Bioprocessing
• Data Science
• Fermentation Technology
• +9 more

Dr. Biniam Kebede is an Assistant Professor in the Department of Food Science at the University of Guelph. His research focuses on integrating bioprocessing, food analytics, and data science to enhance food functionality and sustainability. He leads the Food Bioprocessing and Data Science Research Group, which explores fermentation, enzymatic treatments, and machine learning for food innovation. Academic History: B.Sc. in Food and Biochemical Technology, Bahir Dar University (Ethiopia) M.Sc. in Food Technology, Ghent University (Belgium) Ph.D. in Bioscience Engineering, KU Leuven (Belgium) Research Interests: Dr. Kebede's work addresses sustainable food systems through: Optimizing fermentation to unlock bioactive compounds from plant-based sources Mitigating off-flavors in pulses via value-chain analysis Engineering food structures to improve nutrient bioaccessibility Developing portable machine learning tools for food authenticity Valuing indigenous food ingredients and traditional processing methods His approach combines multi-omics, imaging, and AI to create predictive models for food innovation. Awards & Affiliations: 2022 IUFoST Young Scientist Award 2014 EFFoST PhD Student of the Year Award Member of IFT, CIFST, and IUFoST Honorary affiliation with University of Otago (New Zealand) Training Philosophy: Dr. Kebede emphasizes personalized mentoring through Individual Development Plans (IDPs), biweekly lab meetings, and interdisciplinary collaboration. Students engage in all research phases, including conference presentations and industry partnerships to build technical and professional skills.

Iva TolicView profile

Professor

• Mitotic spindle
• Mitosis
• Biophysics
• +7 more

Iva Tolic is a Full Professor and Senior Research Group Leader at the Ruđer Bošković Institute in Zagreb, Croatia, with tenure since 2019. She is an elected associate member of the Croatian Academy of Sciences and Arts (2020) and an EMBO member (2018). Her work bridges molecular biology and biophysics to study mitotic spindle mechanics. Education: PhD in Biology (2002, University of Zagreb); Diploma in Molecular Biology (1996, University of Zagreb) Her research focuses on mitotic spindle dynamics, including microtubule sliding, kinetochore forces, and spindle chirality. She employs optogenetics, theoretical modeling, and advanced microscopy to uncover mechanisms preventing aneuploidy in human cells. Recent publications highlight her contributions to understanding spindle mechanics, including microtubule-sliding modules and biomechanics of chromosome alignment. She has secured major grants like the ERC Synergy Grant (2020) and ERC Consolidator Grant (2014). Scientific awards: ERC Synergy Grant (2020), Ignaz L. Lieben Award (2017), National Science Award of Croatia (2015), etc. With over 91 peer-reviewed papers and a Google Scholar h-index of 36, Tolic has delivered more than 150 invited talks globally. She leads interdisciplinary projects integrating microscopy protocols for biomedical research and investigates molecular origins of aneuploidies.

• Cell Biology
• Developmental Biology
• Meiosis
• +3 more

Ricardo Benavente is an Extraordinary Professor and Academic Director in the Department of Cell and Developmental Biology at the University of Würzburg's Biocenter. He leads the Benavente Lab, focusing on meiotic processes and synaptonemal complex (SC) structure. His career includes a Dr. med. from the University of Heidelberg, a habilitation (Dr. rer. nat. habil.), and postdoctoral work as an Alexander von Humboldt Fellow at the German Cancer Research Center. Research interests center on the functional organization of the cell nucleus during meiosis, particularly the synaptonemal complex and telomere dynamics. Techniques used include super-resolution microscopy and electron tomography, applied to mouse models and comparative studies across metazoans. Key findings include insights into SC protein conservation and meiotic chromosome behavior. Publications highlight structural studies of SC components (e.g., SYCP proteins), telomere-nuclear envelope interactions, and evolutionary aspects of meiosis. He contributed to the Latin-American Academy of Sciences since 2001 and collaborates with institutions like Uruguay's Clemente Estable Institute. His work bridges molecular mechanisms of meiosis with evolutionary biology, emphasizing structural and functional insights into genetic variability.

Kate SpencerView profile

Professor

• Environmental Geochemistry
• Sediment Contamination
• Estuarine and Coastal Systems
• +15 more

Professor Kate Spencer is a leading environmental geochemist at Queen Mary University of London, serving as Professor of Environmental Geochemistry and Deputy Dean for Research Impact in the School of Geography. Her research bridges geomorphology, hydrology, and ecology to address critical issues in estuarine and coastal sediment management. She is actively involved in teaching across undergraduate and postgraduate programs, emphasizing experiential and consultancy-style learning. Her research focuses on sediment-bound contaminants, cohesive sediment dynamics, flocculation, saltmarsh restoration, and the environmental impacts of historical coastal landfills and dredging. She employs advanced techniques such as X-ray computed tomography and 3D imaging to study floc structure and microplastic transport. Her work is supported by major funders including NERC, Defra, and the Environment Agency, and she collaborates with institutions like the Environment Canada and the Natural History Museum. Kate Spencer’s recent publications highlight a trend toward interdisciplinary environmental science, combining traditional geochemistry with cutting-edge imaging and modeling. Key themes include climate change impacts on coastal landfills, microplastic sedimentation, and 3D quantification of floc porosity. Her work has significant policy relevance, particularly in pollution risk assessment and coastal management. President elect of the Estuarine and Coastal Science Association (2012–present) Invited keynote speaker at international conferences in Venice and Germany International visiting fellowships at National Water Research Institute (Canada) and University of Xiamen (China) She has successfully supervised over ten PhD students and is actively recruiting new researchers through programs like the EU Erasmus Mundus SMART and the London NERC DTP. Her supervision focuses on hydrology, sediment structure, biogeochemistry in saltmarshes, and environmental impacts of flooding and landfills. She has led major projects on mine water pollution, coastal waste, and hydrodynamic dredging. Her research group utilizes advanced laboratories and field methods, including in-situ XRF and 3D imaging, to support both fundamental science and applied environmental solutions.

Susan L. UstinView profile

Professor

• Remote Sensing
• Imaging Spectroscopy
• Ecosystem Ecology
• +9 more

Susan L. Ustin is a Professor in the Department of Land, Air, and Water Resources at the University of California Davis, where she has been a faculty member since 1999. She is also the Associate Director of the John Muir Institute of the Environment and Head of the Center for Spatial Technologies and Remote Sensing (CSTARS). Her academic journey began with a Ph.D. in Botany from UC Davis in 1983, followed by a postdoctoral fellowship working with NASA's Jet Propulsion Laboratory on imaging spectroscopy. Ph.D. in Botany, University of California Davis, 1983 M.A. in Biology, California State University, Hayward, 1978 B.S. in Biology, California State University, Hayward, 1974 Dr. Ustin is a leading expert in remote sensing, with over 30 years of experience applying imaging spectroscopy, LiDAR, thermal, and multispectral data to ecological and environmental problems. Her research spans landscape and ecosystem ecology, focusing on vegetation mapping, invasive species detection, canopy water content estimation, wildfire risk modeling, and climate change impacts. She has developed novel methods for quantifying biophysical and biochemical properties of vegetation using remote sensing technologies. Her recent publications demonstrate a strong trend in integrating multiple remote sensing platforms (LiDAR, hyperspectral, thermal, satellite) to study complex ecological systems. Key research areas include fuel type and canopy structure mapping for wildfire risk, biochemical analysis of plant species, and monitoring environmental disturbances such as oil spills and hurricanes. She has been a key member of NASA's MODIS Science Team and the HyspIRI Preparatory Science Team, contributing to major Earth observation missions. Elected Fellow, American Geophysical Union (AGU), 2017 Honorary Doctorate, University of Zurich, Switzerland, 2010 Outstanding Service Award, American Society of Photogrammetry and Remote Sensing, 2004 Elected Senior Member, IEEE, 2004 SERDP Conservation Project of the Year Award, 2004 Elected Fellow, The Remote Sensing and Photogrammetry Society, 2002 Dr. Ustin has advised numerous graduate students and postdoctoral scholars and has led major research initiatives including the Center for Spatial Technologies and Remote Sensing. She has secured significant research funding from NASA, DOE, and other agencies to support her work on global environmental change and remote sensing applications. Her collaborations span across institutions and disciplines, including work with the National Research Council and Battelle on NEON. She leads the Center for Spatial Technologies and Remote Sensing (CSTARS), which focuses on developing and applying advanced remote sensing technologies for environmental monitoring. The center works on projects ranging from agricultural productivity to wildfire risk assessment and ecosystem health monitoring using airborne and satellite platforms.

Darryl D HolmView profile

Professor

• Geometric Mechanics
• Nonlinear Science
• Fluid Dynamics
• +6 more

Roles & Affiliations : Darryl D. Holm is a Professor of Applied Mathematics at Imperial College London and a Lab Fellow at Los Alamos National Laboratory. His primary affiliation is with the Department of Mathematics within the Faculty of Natural Sciences. He holds the Chair in Applied Mathematics and is affiliated with the CNRS-Imperial Abraham de Moivre UMI, Dynamical Systems, Fluid Dynamics, and other research groups. Research Interests : Holm’s work focuses on Geometric Mechanics and its applications to nonlinear science, including integrable systems, turbulence, and shape analysis. His research emphasizes Lie symmetry reduction , particularly in fluid dynamics, and explores emergent singular phenomena. Key areas include: Integrable systems and solitons Nonlinear dynamics in fluid dynamics and plasma physics Geometric approaches to turbulence and climate modeling Mathematical foundations of ocean plastic solutions Publications & Grants : Holm has authored over 150 papers (see arXiv and MathSciNet ). His work includes foundational contributions to the Camassa-Holm equation and turbulence modeling (LANS-α). He has collaborated widely, including with the Simons Foundation and Los Alamos National Lab. Labs & Teams : Holm contributes to Imperial’s Mathematics of Planet Earth initiative and leads research groups in geometric mechanics and fluid dynamics.

Emmanuel StamatakisView profile

Research Fellow

• Neuroscience
• Neuroimaging
• Cognitive Neuroscience
• +5 more

Dr. Emmanuel Stamatakis is a Senior Research Associate at the University of Cambridge, affiliated with the School of Clinical Medicine and the Division of Anaesthesia. He maintains research ties with the Centre for Speech, Language, and the Brain (CSLB) while focusing on neuroimaging, consciousness studies, and traumatic brain injury (TBI) mechanisms. Institution: University of Cambridge Primary Affiliation: School of Clinical Medicine, Division of Anaesthesia Research Affiliation: Centre for Speech, Language, and the Brain (CSLB) Academic Rank: Research Fellow His research spans neuroscience, neuroimaging, and anaesthesia, with particular emphasis on: Consciousness dynamics under pharmacological and pathological conditions Functional and structural brain connectivity in TBI and delirium Neural mechanisms of anaesthetic agents Evolutionary and comparative neuroscience of brain states Long-term outcomes after neurological trauma Neurotechnology applications in clinical settings Recent publications reveal trends in: Quantifying consciousness through functional gradients and harmonic decomposition Linking anaesthesia-induced neural changes to clinical outcomes Exploring genetic and inflammatory factors in TBI recovery Multi-modal imaging approaches to neurological disorders Translational studies bridging animal models and human conditions Methodological advancements in brain network analysis

Jonas KloecknerView profile

Researcher

• Geostatistics
• Petroleum Engineering
• Mining Engineering
• +7 more

Jonas Kloeckner is a PhD Candidate at the Federal University of Rio Grande do Sul (UFRGS) in the Mineral & Environmental Technology and Extractive Metallurgy Program, focusing on Geostatistics, and concurrently serves as a Visiting Research Scholar at Stanford University under Professor Jef Caers. His academic journey includes a MSc in Engineering and Mining Engineering from UFRGS, a Bac +5 degree from Ecole des Mines d'Alès (France), and a Visiting Student stint at Columbia University (USA). His research interests span geostatistical modeling of carbonate facies, Bayesian approaches for uncertainty quantification, and applications of machine learning in geological and medical domains. Key technical areas include Markov Chain Random Fields, seismic data integration, and spatial continuity analysis, with a focus on improving sustainability in mining operations and reservoir characterization. Notable contributions include advancements in covariance table methodologies for automated spatial analysis and risk assessment frameworks for bauxite mining. His work bridges geological data interpretation, stochastic simulation techniques, and computational tools for resource optimization. Currently affiliated with Stanford's energy geoscience initiatives, his research emphasizes interdisciplinary applications of geostatistical models.

Shana StoddardView profile

Associate Professor

• Autoimmune disorders
• Protein engineering
• Computational chemistry
• +6 more

Dr. Shana Stoddard is an Associate Professor of Chemistry at Rhodes College, where she leads the Molecular Immunotherapeutics Research (MIR) lab. Her research program focuses on improving patient outcomes with autoimmune disorders, cancer, neurological disorders, and coronaviruses through protein engineering, computational chemistry, and rational drug design. Dr. Stoddard received her educational training from: Postdoctoral Researcher at St. Jude Children's Research Hospital (Diagnostic Imaging) Ph.D. in Chemistry and Biochemistry from University of Mississippi M.Ed. in Curriculum and Instruction (emphasis Special Education) from Freed-Hardeman University B.S. in Chemistry from Prairie View A&M University Dr. Stoddard's research interests span multiple areas of biomedical science with a focus on therapeutic development. Her work in autoimmune disorders centers on primary membranous nephritis (PMN), where she develops auto-antibody-specific inhibitors and antigen-specific therapies. In cancer research , she focuses on designing selective histone deacetylase (HDAC) inhibitors for various cancer types, particularly targeting HDAC8 for neuroblastoma treatment. Her lab also works on neurological disorders , developing HDAC4 inhibitors for Huntington's disease and glioblastoma. During the COVID-19 pandemic, her lab pivoted to coronavirus antiviral development , creating peptide-based fusion inhibitors and protease inhibitors. Additionally, Dr. Stoddard is deeply committed to diversity and equity in STEM education , developing pedagogical approaches to create more inclusive classrooms. Analysis of Dr. Stoddard's recent publications reveals a consistent focus on structure-based drug design across multiple therapeutic areas. Her work employs computational chemistry approaches to model protein structures and design inhibitors with improved selectivity. A significant portion of her research targets histone deacetylases (HDACs), with emphasis on achieving isozyme selectivity among the 18 different HDAC enzymes. Her lab has made contributions to understanding protein structures involved in autoimmune kidney diseases and developed computational models of previously uncharacterized proteins. Dr. Stoddard has received numerous prestigious awards recognizing both her research and mentorship: 2025 – LMI Mellon Fellow 2024 – Lloyd N Ferguson Young Scientist Award from NOBCChE 2024 – Sigma Xi, The Scientific Research Honor Society inductee 2024 – Ruth Kirschstein Diversity in Science Award from ASBMB 2023 – Tyrone Mitchell Mentor-on-the-Map Award from NOBCChE 2023 – Silvia Ronco Innovative Mentor Award from CUR Chemistry 2022 – Henry C. McBay Outstanding Teaching Award from NOBCChE 2021 – Outstanding Mentor of the year Award CUR Health Sciences (Early Career Stage) 2021 – Accessibility and Inclusivity Advocate of the Year: Campus Life Award (Rhodes College) Dr. Stoddard is renowned for her exceptional mentorship of undergraduate researchers, particularly from underrepresented groups in STEM. She established the STEM Cohort Mentoring program at Rhodes in 2017 to support diverse students pursuing STEM careers. Her lab has produced numerous undergraduate co-authors on peer-reviewed publications across multiple disciplines. She has successfully guided many students into medical schools and graduate programs. Dr. Stoddard has secured competitive funding for her research, including participation in the Project Kaleidoscope STEM Leadership Institute held by the American Association of Colleges & Universities. The Molecular Immunotherapeutics Research (MIR) lab at Rhodes College is a vibrant research environment where undergraduate students work alongside Dr. Stoddard on cutting-edge biomedical research. The lab currently pursues four major research projects: 1) Protein Engineering and Development of Antigen Specific Therapeutics for Autoimmune Disorders; 2) Modeling and Investigation of Structure and Function Relationships of Unsolved Protein Structures; 3) Design, Synthesis, and Biological Testing of Novel Therapeutic Compounds for Cancer, Autoimmune, and Neurological Disorders; and 4) Development of Broad-Spectrum Coronavirus Antivirals. The MIR lab collaborates with researchers at institutions including Boston University Medical College, University of Mississippi, and St. Jude Children's Research Hospital.