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Sunny JiangView profile

Professor

• Environmental microbiology
• Water treatment
• Antibiotic resistance
• +4 more

Sunny Jiang is a Professor in the Civil and Environmental Engineering Department at the University of California, Irvine, with a joint appointment in the Ecology and Evolutionary Biology Department . Her research integrates environmental microbiological and engineering principles to address critical challenges in water treatment, microbial ecology, and public health. Research projects in her Applied Environmental Microbiology Laboratory (AEML) focus on: Wastewater-based surveillance for pathogens like SARS-CoV-2 Antibiotic resistance dynamics in water systems Advanced biodegradation techniques for toxins Biofouling mitigation in desalination systems Microbial risk assessment under climate change Key scientific contributions include: NSF Graduate Research Fellowship (awarded to Katherine Brenner) Development of microfluidic portable pathogen analysis systems Leadership in climate change-microbial risk modeling Innovations in nanobubble technology for wastewater systems Notable students include Dr. Hunter Quon (PhD Environmental Engineering) and Katherine Brenner (NSF Fellow). Her lab actively engages in interdisciplinary work spanning water quality, biotechnology, and health risk assessment.

Marc David LudwigView profile

Lecturer

• Social Work
• Community Work
• Youth Work
• +9 more

Marc David Ludwig serves as a Lecturer at Alice Salomon University of Applied Sciences Berlin (ASH Berlin), teaching across multiple modules in the Bachelor's program in Social Work. His primary teaching responsibilities include Theories and Methods of Social Work (with focus on Action Methods), Propaedeutics, History and Theory of Social Work , and specialized courses on open child and youth work. He has held teaching assignments continuously from 2022 through 2025 across various semesters. Ludwig's research interests center on community work, youth participation, and socio-spatial contextualization of social services. His work emphasizes participatory approaches to social research, with particular attention to qualitative methods including grounded theory, ethnography, and mixed methods. He investigates social change impacts on young people and families, organization of citizen-led processes in marginalized communities, and cross-departmental integrated action in district development. His recent publications reflect these interests, with articles on crisis discourse, research-practice connections, and civic engagement. An upcoming anthology volume titled Social Work as a Place of Political Education (2025) demonstrates his ongoing scholarly contributions. Ludwig actively supervises numerous Bachelor's and Master's theses on topics ranging from youth participation to social inclusion challenges. Ludwig maintains significant professional engagement through memberships in multiple organizations including the German Professional Association for Social Work (DBSH), where he served on the Executive Board (2021-2024) and held editorial responsibility for FORUM sozial . He also serves on the Board of BAG Social Urban Development and Community Work and participates in working groups focused on doctoral funding and youth engagement.

• Biomedical Image Analysis
• Cryogenic Electron Microscopy (Cryo-EM)
• MRI and Ultrasound Image Segmentation
• +5 more

Dr. Hemant Tagare is a Professor at Yale School of Medicine with primary appointments in the Radiology & Biomedical Imaging department and secondary appointments in Biomedical Engineering and Statistics . He is affiliated with multiple research centers, including the Bioimaging Sciences , Center for Brain & Mind Health , and Yale Biomedical Imaging Institute . Research Interests Cryogenic Electron Microscopy (Cryo-EM) for protein structure reconstruction MRI/ultrasound image segmentation using machine learning Non-rigid registration and shape theory Mathematical foundations of image analysis Articles Trends : Recent publications focus on cryo-EM particle picking consensus algorithms, T2-weighted MRI standardization, and IVIM perfusion measurement in peripheral artery disease. Earlier works emphasize segmentation techniques, non-rigid registration, and phantom validation. Scientific Awards Best Poster Award (2003) for ultrasound segmentation algorithm Francois Erbsmann Award (1993) for medical image processing National Science Talent Search Scholarship (1977) from India

Candice M. DuncanView profile

Assistant Professor

• Environmental Science
• Environmental Chemistry
• Remediation
• +4 more

Dr. Candice M. Duncan is an Assistant Professor in the Department of Environmental Science & Technology at the University of Maryland's College of Agriculture and Natural Resources. Her office is located at 0206 H. J. Patterson Hall in College Park, MD. She specializes in environmental science, environmental chemistry, and contaminant transport, with a research focus on phytoremediation strategies for organic/inorganic pollutants and interdisciplinary soil chemistry-anthropology studies. Education: Ph.D. in Soil, Water, and Environmental Science (2014, University of Arizona) M.S. in Earth Science, Environmental Chemistry Minor (2008, North Carolina Central University) B.S. in Environmental Science, Environmental Chemistry Minor (2005, North Carolina Central University) B.S. in Biology, Chemistry Minor (2003, University of North Carolina at Greensboro) Research Interests: Dr. Duncan's work explores gas/liquid-phase transport of contaminants (e.g., TCE, PFAS, mercury), phytoremediation mechanisms, and anthropogenic trace metal analysis in historical contexts. She integrates geoscience, chemistry, and anthropology to address environmental justice and pollution mitigation. Publications: Her recent articles emphasize PFAS prioritization, phytoscreening efficacy, atmospheric pollution analysis, and STEM diversity initiatives. Trends show a strong focus on developing analytical methods for environmental contaminants and promoting inclusivity in geoscience education. Teaching: Courses taught include Introduction to Geoscience (AGNR 320), Soil Chemistry (ENST 421), and Senior Integrative Experience (ENST 472), where students investigate mercury phytoremediation in aquaponic systems.

Dario C. AltieriView profile

Professor

• Cancer Biology
• Tumor Metastasis
• Mitochondrial Function in Cancer
• +5 more

Dario C. Altieri, M.D. serves as President and Chief Executive Officer of The Wistar Institute, Director of the Ellen and Ronald Caplan Cancer Center (an NCI-designated facility), and Robert and Penny Fox Distinguished Professor leading the Genome Regulation and Cell Signaling Program. His leadership spans both administrative responsibilities and active cancer research. Born in Milan, Italy, Altieri was educated at the University of Milan School of Medicine, completed training in internal medicine, and holds a postgraduate degree in clinical and experimental hematology. His academic career includes positions at Scripps Clinic and Research Foundation (1987), Yale University School of Medicine (becoming professor with tenure in 1999), and founding chair of the Department of Cancer Biology at the University of Massachusetts Medical School (2002). He joined The Wistar Institute in 2010 as Cancer Center Director and Chief Scientific Officer, becoming President and CEO in 2015. Altieri's research focuses on cellular adaptation mechanisms or 'plasticity' exploited by cancer for disease progression. His laboratory investigates mitochondrial functions in cancer, including bioenergetics, reactive oxidative species buffering, inter-organelle communication with the endoplasmic reticulum, and retrograde gene expression. His work demonstrates that mitochondrial reprogramming is a universal cancer trait imparting unique plasticity to tumor responses across all disease stages. The lab has pioneered mitochondria-targeted cancer therapeutics, developing compounds like Gamitrinib that entered clinical trials (NCT04827810). Analysis of Altieri's recent publications (2020-2024) reveals a strategic evolution from foundational work on mitochondrial dynamics in tumor cell motility toward understanding Parkin protein's role in tumor immunity and metastasis suppression. His research spans molecular mechanisms to therapeutic applications, increasingly incorporating tumor microenvironment and immune system interactions, with direct translational impact. Altieri's laboratory team includes Research Assistant Professors Jagadish Ghosh, Ph.D. and Michela Perego, Ph.D., and Postdoctoral Fellow Minjeong Yeon, Ph.D. His research has received significant NIH funding including R35 CA220446 and R01 CA286080 grants. The laboratory employs multidisciplinary approaches spanning biochemical, cellular, and molecular techniques, xenograft and genetic animal models, and analysis of clinically-annotated patient samples. The Altieri Laboratory operates within The Wistar Institute's NCI-designated cancer center. His team discovered and characterized the survivin gene (with over 10,500 PubMed citations), establishing it as a fundamental cancer gene and therapeutic target. Recent work on Parkin's dual role in suppressing tumor traits while activating innate immunity opens new avenues for cancer immunotherapy development.

Jayur Madhusudan MehtaView profile

Associate Professor

• Environmental Archaeology
• Coastal Hazards
• Human-Environment Relationships
• +2 more

Jayur Madhusudan Mehta is an Associate Professor in the Department of Anthropology at Florida State University, where he also serves as Undergraduate Program Director. His research specializes in human-environment interactions, coastal archaeology, and Indigenous heritage preservation, with field projects spanning the Gulf Coast and Mississippi Delta. Mehta holds a Ph.D. in Anthropology from Tulane University (2015), an M.A. from the University of Alabama (2007), and a B.A. from the University of North Carolina (2004). His interdisciplinary work integrates geoarchaeology, ethnohistory, and environmental reconstruction to study how past societies responded to ecological challenges. Current initiatives include mediating coastal hazards for Indigenous communities, restoring ancient fisheries through paleoenvironmental analysis, and documenting plantation archaeology at Evergreen Plantation in Louisiana. Mehta's publications predominantly explore climate adaptation, cultural landscape resilience, and monumentality in Mississippian societies. His methodological approaches combine remote sensing, sedimentology, and spatial analysis to reconstruct historical ecologies and settlement patterns. He actively recruits graduate students for coastal archaeology projects and leads field schools focused on African Diaspora archaeology. As principal investigator for multiple research consortia, Mehta collaborates with Indigenous communities and federal agencies to develop culturally informed conservation strategies.

Karen E. MockView profile

Professor

• Molecular Ecology
• Landscape Genetics
• Conservation Genetics
• +3 more

Karen E. Mock is a Professor in the Wildland Resources department at Utah State University’s Quinney College of Natural Resources. She holds a Ph.D. in Biology from Northern Arizona University (2000), an M.S. in Environmental Health from Colorado State University (1985), and a B.S. in Microbiology from the University of Texas at Austin (1980). With over 10 years of prior teaching at Yavapai Community College and extensive experience at USU, she teaches Genetics in Conservation and Management and graduate special topics in landscape genetics and Bayesian data analysis. Education: Ph.D., Biology, Northern Arizona University, 2000 M.S., Environmental Health, Colorado State University, 1985 B.S., Microbiology, University of Texas at Austin, 1980 Her research focuses on molecular ecology , examining landscape patterns of gene flow and genetic diversity in species such as aspen, freshwater mussels, frogs, mountain pine beetles, bears, Phragmites, and wild turkeys. She employs molecular markers to inform conservation strategies, habitat management, and population monitoring. Recent publications highlight her work on aspen clonality , freshwater mussel phylogeny , and invasive species genetics . Her research integrates landscape genetics , phylogenetics , and conservation genomics across terrestrial and aquatic ecosystems. Scientific Awards: Quinney College of Natural Resources Researcher of the Year, 2014 Quinney College of Natural Resources Undergraduate Advisor of the Year, 2010 College of Natural Resources Undergraduate Mentor of the Year, 2008 College of Natural Resources Teacher of the Year, 2007 Best Student Paper Award, Arizona-New Mexico Wildlife Society, 2000 Roger Hungerford Student Award, Arizona-New Mexico Wildlife Society, 2000 Mock has mentored numerous graduate students, including Ph.D. candidates in Wildland Resources and Watershed Sciences , with research spanning population genetics , conservation strategies , and molecular ecology . She contributes to journals such as Molecular Ecology , Conservation Genetics , and Forest Science .

• Evolutionary Biology
• Molecular Phylogenetics
• Comparative Evolutionary Studies
• +12 more

Rebecca Kimball is a Professor in the Department of Biology at the University of Florida , focusing on evolutionary biology through molecular techniques and field research. Her work spans three primary areas: phylogenetics for comparative studies, microevolutionary processes like mating systems and sexual selection, and linking genomic changes to organismal evolution. Education : Ph.D. (University of New Mexico, 1995) Research Themes : Phylogenetic reconstruction, genome-phenome mapping, sensory system evolution, and avian diversification. Her lab, the Braun-Kimball Lab , trains students in phylogenetics, computational biology, and population genetics. Current projects include galliform evolution, chemosensory systems in vultures, and hybridization studies in paradise flycatchers. She collaborates on NSF-funded phylogenomic initiatives and emphasizes rigorous lab practices, including long-term commitments for researchers and interdisciplinary training. Scientific Awards : No explicit awards listed, but her lab receives external grants (e.g., NSF, University Scholars Program). Advising & Grants : Mentors numerous graduate and undergraduate researchers. Lab members often co-author publications and pursue independent projects. Grants focus on phylogenomic tools and avian evolutionary questions. Labs & Teams : Leads the Braun-Kimball Lab, which engages in global collaborations (e.g., Field Museum, New York State Museum) and interdisciplinary work in genomics and ecology.

• Machine Learning
• Causal Inference
• Healthcare Analytics
• +3 more

Fredrik Johansson is an Associate Professor in the Department of Data Science and AI at Chalmers University of Technology. His research focuses on developing machine learning methods for healthcare applications, causal inference, and handling imperfect data. He leads multiple funded projects including WASP AI/MLX and research on causal machine learning for healthcare applications. Johansson's core research interests include: Machine learning for clinical decision support and healthcare analytics Causal inference methods for observational data Handling missing values and data quality issues Interpretable and robust ML models Domain adaptation and transfer learning Reinforcement learning for treatment policies His recent publications demonstrate strong focus on clinical ML applications (dermatology, rheumatology, Alzheimer's) and methodological work on causal inference. Frequent themes include handling missing data, model interpretability, and healthcare policy optimization. Collaborative work spans multiple medical domains using registry data, proteomics, and medical imaging. He leads significant research projects including: Kausalitet och sidoinformation för effektiv maskininlärning (VR-funded) Maskininlärning för kausal inferens från observationsdata (Wallenberg) Förutsättningar för inlärning av överförbara koncept (Wallenberg) Fattigdomsfällor i Afrika (Formas-funded)

Divya MahajanView profile

Assistant Professor

• Computer Architecture
• Distributed Systems
• Machine Learning Systems
• +2 more

Divya Mahajan is an Assistant Professor holding dual appointments in the College of Computing and College of Engineering at Georgia Institute of Technology. She directs the Systems Infrastructure and Architecture Research Lab, focusing on sustainable computing platforms for large-scale AI, machine learning, and data storage systems. Her research integrates computer architecture, distributed systems, and database technologies to optimize end-to-end data pipelines. Mahajan earned her PhD from Georgia Tech and Bachelor's from IIT Ropar (President's Gold Medal). Prior to academia, she was a Senior Researcher at Microsoft Azure, leading communication collective designs for distributed DNN training. Awards include NCWIT Collegiate Award (2017) and HPCA Distinguished Paper Award (2016). Research spans hardware-software co-design for ML systems, efficient recommendation architectures, federated learning optimization, and PIM/NPU acceleration. Recent projects address challenges in large-scale model serving, edge-cloud integration, and sustainable computing. Student advisees include PhD and MS researchers in systems and architecture. Publications demonstrate consistent innovation in accelerating ML workloads through novel hardware/software techniques, with work appearing in ISCA, MICRO, ASPLOS, NeurIPS, and VLDB. Current projects explore energy-efficient AI infrastructure and domain-specialized systems for emerging economies.

Richie GouldingView profile

Assistant Professor

• Exercise Physiology
• Musculoskeletal Health
• Diabetes Research
• +3 more

Richie Goulding is an Assistant Professor at Vrije Universiteit Amsterdam, affiliated with both the Faculty of Behavioural and Movement Sciences (Physiology Department) and the AMS - Musculoskeletal Health. He holds a post-Doctoral Fellow position in the Laboratory for Myology. His research focuses on physiological determinants of exercise tolerance, mitochondrial dysfunction in type 1 diabetes, and exercise bioenergetics. Goulding completed his PhD at Liverpool Hope University and conducted postdoctoral research in Kobe, Japan, under the Japan Society for the Promotion of Sciences. Key research areas include the role of exercise training in mitigating mitochondrial dysfunction, oxidative metabolism regulation, and age-related declines in physical capacity. He has published extensively on topics such as skeletal muscle adaptations, post-exertional malaise in Long COVID, and critical power thresholds in exercise physiology. Goulding teaches courses on applied exercise physiology and training aging/disuse-related issues. His work integrates experimental physiology, clinical studies, and machine learning to explore exercise performance and health outcomes. Recent studies emphasize mitochondrial health in diabetes, muscle abnormalities in chronic conditions, and predictive modeling of exercise responses.

Akshay KrishnamurthyView profile

Adjunct Assistant Professor

• Machine Learning
• Statistics
• Reinforcement Learning
• +4 more

Akshay Krishnamurthy is an Adjunct Assistant Professor at the University of Massachusetts Amherst and a Senior Principal Research Manager at Microsoft Research NYC. His research focuses on machine learning and statistics, particularly interactive learning frameworks, reinforcement learning, and generative AI. He holds a PhD from Carnegie Mellon University and a B.Sc. from UC Berkeley. Education: PhD in Computer Science, Carnegie Mellon University (2015) B.Sc. in Electrical Engineering and Computer Science, UC Berkeley (2010) Research Interests: His work emphasizes feedback-driven data collection in machine learning, including contextual bandits, reinforcement learning, and their applications to language models and generative AI. Recent focus areas include sample-efficient exploration and decision-making under limited feedback. Awards: National Science Foundation Graduate Research Fellowship (2010) Best Student Paper Award at Asilomar Conference (2013) Grants & Collaborations: Active in interdisciplinary collaborations, including organizing workshops on foundations of post-training in generative AI. His research bridges theoretical guarantees with practical applications in reinforcement learning and decision-making systems. Labs/Teams: Leads research initiatives at Microsoft on generative AI, reinforcement learning, and scalable machine learning systems.

Boris LandaView profile

Assistant Professor

• Statistical Signal Processing
• Geometric Data Analysis
• Manifold Learning
• +5 more

Boris Landa is an Assistant Professor in the Department of Electrical & Computer Engineering at Yale University. His research focuses on statistical signal processing and geometric data analysis, developing theoretical and computational tools for analyzing large, complex datasets. He holds a Ph.D. and M.S. from Tel Aviv University, Israel, and a B.S. from the Technion - Israel Institute of Technology. His work bridges computational methods with applications in molecular biology, cryo-electron microscopy, and high-dimensional data analysis. Notable contributions include robust inference of manifold geometry, doubly stochastic scaling techniques, and multi-reference factor analysis for alignment problems. Recent research explores optimal transport metrics for single-cell data and noise stabilization in signal recovery. Landa's publications span prestigious journals such as SIAM Journal on Mathematics of Data Science and Information and Inference. His methodologies address challenges in manifold learning, graph Laplacian normalization, and biological dataset integration. Active areas include developing adaptive algorithms for low-rank signal detection and robust statistical techniques for heterogeneous data. His educational background includes advanced studies in applied mathematics and engineering, with a strong emphasis on interdisciplinary applications. Ongoing projects involve geometric approaches to omics data analysis and scalable solutions for large scientific imaging datasets.

Nadia FigueroaView profile

Assistant Professor

• Robotics
• Human-Robot Interaction
• Machine Learning
• +4 more

Nadia Figueroa is the Shalini and Rajeev Misra Presidential Assistant Professor in the Mechanical Engineering and Applied Mechanics (MEAM) Department at the University of Pennsylvania . She holds secondary appointments in Computer and Information Science (CIS) and Electrical and Systems Engineering (ESE) , and is a core faculty member at the General Robotics, Automation, Sensing & Perception (GRASP) Laboratory . Before joining Penn, she was a Postdoctoral Associate at MIT's CSAIL under Prof. Julie A. Shah and earned her Ph.D. at EPFL with Prof. Aude Billard. Her academic journey includes research roles at DLR and NYU Abu Dhabi , along with degrees from Monterrey Tech (B.Sc.) and TU Dortmund (M.Sc.) . Education: Ph.D. in Robotics, Control and Intelligent Systems, EPFL (2019) M.Sc. in Automation and Robotics, TU Dortmund B.Sc. in Mechatronics, Monterrey Tech Her research focuses on adaptive intelligence for robots to learn from and interact with humans, emphasizing fluid collaboration in safety-critical applications. Key areas include reactive control algorithms , human-robot co-manipulation , and real-time navigation . Techniques integrate machine learning , control theory , and perception to ensure stability, safety, and robustness in dynamic environments. Recent work trends highlight reactive motion policies for imitation learning, dynamical systems modulation with non-convex obstacles, and EEG-based intent detection for assistive robotics. She also explores soft robotics with MORF systems and SE(3) control for end-effector precision. Her publications reflect interdisciplinary approaches at the intersection of robotics, AI, and human biomechanics . She has taught MEAM-520 Introduction to Robotics at Penn and served as Head Teaching Assistant at EPFL for courses like MICRO-401 Machine Learning Programming . Her Figueroa (Human-Centered) Robotics Lab , established in 2022, collaborates with institutions like MIT and EPFL to advance fluid human-robot autonomy.

Yifan SunView profile

Assistant Professor

• GPU Architecture
• Computer Architecture Simulation
• Multi-GPU Systems
• +5 more

Yifan Sun is an Assistant Professor in the Department of Computer Science at William & Mary, leading the Scalable Architecture Lab. He holds a Ph.D. in Electrical and Computer Engineering from Northeastern University (2020). His research focuses on GPU architecture, simulation tools, and multi-GPU system design. Recent work includes TrioSim (a lightweight DNN workload simulator) and NetCrafter (optimizing multi-GPU network traffic). He has published extensively at top venues like ISCA, MICRO, and IEEE Vis. Educations: Ph.D. in Electrical and Computer Engineering, Northeastern University (2020); M.S. and B.S. not explicitly stated but implied through academic progression. Research Interests: Developing explainable architecture tools, improving simulation frameworks (Akita/MGPUSim), and addressing challenges in wafer-scale GPU design. His work bridges hardware-software co-design with visualization techniques to enhance human understanding of complex architectures. Grants: Awarded NSF CCRI and CRII grants for simulation-as-a-service and explainable architecture projects. Collaborations include UVA, NUS, and Northeastern University. Labs/Teams: Scalable Architecture Lab (SARCHLAB), focusing on GPU systems, simulation, and visualization. Active in organizing workshops and GitHub repositories (e.g., https://github.com/sarchlab).