Find Academic Supervisors

• Medical Microbiology
• Malaria Molecular Surveillance
• Population Genetics
• +3 more

Dr. Robert Verity is an Assistant Professor in the School of Public Health at Imperial College London, affiliated with the Faculty of Medicine. His research focuses on malaria parasite genetics, particularly using molecular surveillance to understand transmission dynamics. He leads projects like the SIMPLEGEN pipeline funded by the Bill and Melinda Gates Foundation, aiming to optimize resource use in malaria research. His work integrates spatial data analysis, Bayesian methods, and population genetics to address global health challenges. During the pandemic, he contributed to early estimates of COVID-19 fatality rates as part of the Imperial College response team. Key affiliations: Imperial College Network of Excellence in Malaria, MRC Centre for Global Infectious Disease Analysis Current projects: Molecular inversion probes analysis in DRC, malaria drug resistance quantification Research interests include Plasmodium falciparum population structure, antimalarial resistance mechanisms, and spatial epidemiology. His work bridges field data collection with advanced computational methods to inform public health strategies.

• Mathematical modeling
• Optimization
• Systems engineering
• +12 more

Aurora Munguía-López is a Visiting Assistant Professor in the Department of Chemical and Biological Engineering at the University at Buffalo , where she leads the Sustainable Systems Engineering Laboratory . Her research focuses on developing computational tools to address sustainability challenges in plastics recycling, waste management, clean energy technologies, and manufacturing processes. PhD in Chemical Engineering (2021), University of Michoacán MSc in Chemical Engineering (2017), Technological Institute of Celaya BSc in Chemical Engineering (2014), Technological Institute of Celaya The laboratory specializes in multi-scale process design , technology pathway analysis , sustainable supply chains , and environmental/social justice , with applications spanning plastics recycling, clean energy systems, and food/pharmaceutical/textiles manufacturing. Recent work includes solvent-based recycling frameworks and techno-economic analyses for waste valorization. The Sustainable Systems Engineering Laboratory actively engages undergraduate researchers through programs like PRACTICE-REU , UB SURP , and NSF-funded projects. Prof. Munguía-López has presented at industry conferences such as Plastics In Composites and Lightweighting 2025 and FlexPackCon 2025 .

Craig A. ChinView profile

Associate Professor

• Digital Signal Processing
• Machine Learning
• Biomedical Signal/Image Processing
• +7 more

Craig A. Chin is an Associate Professor in the Department of Electrical Engineering at Kennesaw State University. He holds a Ph.D. and M.S. in Electrical Engineering from Florida International University (2006, 2001) and a B.S. in Electrical and Computer Engineering from the University of the West Indies (1995). Research Interests: Digital Signal Processing for Biomedical Applications Machine Learning in Biomedical Signal/Image Analysis Wireless Body Area Networks (WBANs) for Healthcare Network Security in Resource-Constrained Environments Biometric Authentication for Wireless Sensor Networks Innovations in Engineering Education (Cooperative/Active Learning, Humanities Integration) Article Trends: His publications (2001–2019) focus on Biomedical Signal Processing (EMG/Eye-Gaze Integration, Stress Detection), WBANs for mHealth , and Engineering Education Pedagogy . Recent work (2013–2019) emphasizes Cooperative Learning Strategies and Wireshark-based Network Security Labs . Academic Contributions: Craig has taught courses such as Biometrics, Data Communications, Biomedical Instrumentation, and Medical Electronics. He actively explores future research on biometric-driven security for Body Area Sensor Networks and active learning strategies in online education.

Shixiang ZhuView profile

Assistant Professor

• Machine Learning
• Data Science
• Operations Research
• +7 more

Shixiang (Woody) Zhu is an Assistant Professor in Data Analytics at the Heinz College of Information Systems and Public Policy, Carnegie Mellon University. He holds a PhD in Machine Learning from Georgia Institute of Technology (2022) and B.S./M.S. in Computer Science from Beijing University of Posts and Telecommunications (2017). His research bridges machine learning, operations research, and statistics, focusing on sequential modeling, human-AI collaboration, and energy systems operations. He has received awards including the IEEE Power & Energy Society Best Paper Award (2025) and was a finalist for the INFORMS Wagner Prize (2021). Education : PhD in Machine Learning, Georgia Tech (2017–2022) B.S./M.S. in Computer Science, BUPT (2010–2017) His research emphasizes spatio-temporal data analysis , decision making under uncertainty , and applications to energy systems, healthcare, and public policy. Notable projects include optimizing police zone design (Wagner Prize finalist) and enhancing grid resilience through robust optimization. He actively collaborates with institutions like Argonne National Laboratory and NSF-funded projects. Awards : Best Paper Award, IEEE Power & Energy Society (2025) Gen-AI Fellows (2024) Finalist, INFORMS Wagner Prize (2021) Advising & Grants : Advises PhD students Zekai Fan, Wenbin Zhou, and others Recipient of Block Center Seed Grant (2024), NSF funding (2024) His work spans energy resilience, public policy optimization, and causal inference in social systems. He co-leads the INFORMS Data Mining Society and reviews for top journals like Operations Research and Management Science.

Gonzalo NápolesView profile

Assistant Professor

• Artificial Intelligence
• Machine Learning
• Cognitive Science
• +5 more

Gonzalo Nápoles is an Assistant Professor at Tilburg University's School of Humanities and Digital Sciences, Department of Cognitive Science and AI. He holds a Doctoral Degree in Computer Science from Rough Cognitive Networks (2014–2017). His research focuses on AI applications in cognitive modeling, pattern classification, and neural networks with interdisciplinary applications in healthcare, finance, and social sciences. Key research areas include Fuzzy Cognitive Maps, data augmentation techniques for neuroimaging, and interpretable machine learning systems. He actively contributes to UN Sustainable Development Goals related to education and innovation. Recent work explores AI ethics, financial risk assessment using dynamic networks, and sensory processing disorder analysis through neural networks. Education: Doctoral Degree in Computer Science, 2017 (Thesis: Rough Cognitive Networks) Prize-winning research includes Best Paper Awards at CIARP 2021 and IWAIPR 2023. He collaborates internationally, hosting academic visitors and serving on multiple PhD committees. Current projects involve stock prediction using graph neural networks and fMRI data augmentation methodologies. Awards: Best Paper Award - CIARP 2021 Best Paper Award - IWAIPR 2023 Nápoles advises on PhD theses in cognitive science and AI applications. His work bridges theoretical advancements with practical implementations in healthcare, finance, and urban systems.

Shuva PaulView profile

Researcher

• Machine Learning
• Deep Learning
• Game Theory
• +11 more

Shuva Paul is a Researcher at NREL's Energy Security and Resilience Center , specializing in power systems cybersecurity . His work focuses on collaborative autonomy, computational intelligence, reinforcement learning, game theory, smart grid security , and critical infrastructure protection . Research Interests: Machine learning and deep learning for critical infrastructure systems Event and anomaly detection in power grids Supply chain cybersecurity Cyber-physical energy systems security and resilience Professional Experience: Postdoctoral Fellow, Georgia Institute of Technology (Feb 2021–May 2022) Postdoctoral Research Associate, Washington State University (Jun 2020–Jan 2021) Graduate Intern, NREL (May 2019–May 2020) Graduate Research Assistant, South Dakota State University (2016–2019) Education: PhD, Electrical Engineering, South Dakota State University Master of Electrical and Electronics Engineering, American International University - Bangladesh Bachelor of Electrical and Electronics Engineering, American International University - Bangladesh Advisory and Editorial Contributions: Paul has served as a session chair at IEEE EnergyTech (2013) and IEEE Electro Information Technology (2019) conferences, and as a reviewer for journals like IEEE Transactions on Smart Grid and Neurocomputing . He also acted as a guest editor for the Journal of Sensor and Actuator Networks .

Rocio Lilen SeguraView profile

Assistant Professor

• Civil Engineering
• Infrastructure Resilience
• Climate Change Adaptation
• +5 more

Rocio Lilen Segura is an Assistant Professor in the Department of Civil, Environmental and Sustainable Engineering at Santa Clara University's School of Engineering. She holds a Ph.D. in Civil Engineering from Sherbrooke University (2019) and a B.Sc. in Civil Engineering from Del Comahue National University (2013). Dr. Segura specializes in infrastructure resilience against extreme events and climate change, focusing on probabilistic risk assessment of critical infrastructure systems like dams and levees. Her work bridges civil engineering with machine learning and climate justice, integrating built, natural, and social systems to address environmental challenges. 2023 Severo Ochoa Mobility Programme grant 2019-2022 MITACS Accelerate industrial postdoc scholarship 2019 Léonard de Vinci medal and Scholarship Her research spans seismic risk reduction, surrogate modeling, and uncertainty quantification in dam engineering, with over 10 publications in journals like Advances in Civil Engineering and Water Journal. She previously collaborated with Hydro-Quebec during her postdoctoral research.

Ahmed Bin ZamanView profile

Assistant Professor

• computational biology
• evolutionary computation
• artificial intelligence
• +1 more

Ahmed Bin Zaman serves as an Assistant Professor in the Department of Computer Science at George Mason University, where his research bridges computational methods with biological discovery. His academic profile emphasizes innovative approaches to protein structure prediction and optimization challenges. His educational foundation includes: PhD in Computer Science, George Mason University (2021) Master of Science in Computer Science, George Mason University (2020) Zaman's research program centers on computational biology, with specialized expertise in evolutionary computation and artificial intelligence applied to protein conformation analysis. He develops stochastic optimization frameworks to enhance protein structure prediction accuracy, focusing on conformational space mapping and decoy ensemble generation. His methodology integrates evolutionary algorithms with multi-objective optimization to navigate complex molecular landscapes, contributing significantly to template-free protein structure determination. His publication trajectory from 2017-2022 reveals distinct research phases: initial work in cybersecurity threat detection evolved into a concentrated focus on computational structural biology. Thirteen protein-related publications demonstrate consistent innovation in conformational sampling techniques, while maintaining methodological rigor through evolutionary computation and machine learning integration. Key contributions include conformation space mapping frameworks and adaptive stochastic optimization systems that address decoy diversity challenges. Professional development shows progression from industry experience at Technext Limited (as team leader/researcher) and lecturing at Metropolitan University to his current academic role. His teaching philosophy emphasizes cultivating independent problem-solving capabilities in students through cognitive tool development.

Mayank GoelView profile

Assistant Professor

• Mobile Computing
• Sensing
• Signal Processing
• +7 more

Mayank Goel serves as an Assistant Professor in the Software and Societal Systems Department (S3D) at Carnegie Mellon University's School of Computer Science. His research bridges computer science and societal impact through practical sensing systems that leverage existing environmental devices for health monitoring and human-computer interaction without requiring hardware modifications. Dr. Goel specializes in mobile computing, signal processing, and machine learning to develop unobtrusive health technologies applicable to real-world scenarios. His core research areas include passive activity recognition for chronic disease management (particularly multiple sclerosis), privacy-preserving acoustic sensing, smartwatch-based clinical interventions for post-operative care, and equitable healthcare systems for global development contexts. He emphasizes end-to-end solutions through close collaboration with medical professionals and designers to ensure immediate deployability outside laboratory environments. Analysis of his 2024-2025 publications reveals a strong interdisciplinary focus spanning computer science, biomedical engineering, and clinical practice. Key trends include longitudinal digital phenotyping for neurological conditions, on-device privacy preservation in activity recognition, and multimodal procedural assistance systems. His work consistently addresses real-world challenges in sensor placement flexibility, user adoption barriers, and equitable access to medical technologies. No scientific awards were mentioned in the available documentation. Information regarding student advising, research grants, or laboratory affiliations was not specified in the provided materials, though his publication record indicates active collaboration with medical professionals and bio-engineers for clinical validation of health technologies.

Rayid GhaniView profile

Professor

• Machine Learning
• Artificial Intelligence
• Data Science
• +5 more

Rayid Ghani is a Professor at Carnegie Mellon University (CMU), affiliated with both the Machine Learning Department (School of Computer Science) and the Heinz College of Information Systems and Public Policy. He co-leads CMU’s Responsible AI Initiative and leads the Data Science and Public Policy Group and the Data Science for Social Good Program. His work focuses on applying machine learning, AI, and data science to address social and policy challenges in health, criminal justice, education, public safety, workforce development, and sustainability, with an emphasis on fairness, equity, and transparency in AI systems. Education: PhD in Software Engineering PhD in Societal Computing Rayid’s research spans three pillars: (1) building AI systems for human collaboration to improve decision-making, (2) embedding fairness and equity in AI design, and (3) ensuring reliability and resilience of AI systems in dynamic environments. He emphasizes application-grounded experimental design and stakeholder engagement. His recent publications include frameworks for fair ML experimentation, analyses of fairness-accuracy trade-offs, and AI applications in child welfare, public health, and housing policy. He has also contributed to policy discussions, including congressional testimonies on responsible AI procurement. Advising & Grants: Rayid collaborates with governments, NGOs, and academic institutions on projects like eviction prevention, HIV care retention, and bias mitigation in public policy. He advises non-profits and startups on data science strategy and ethics. Labs & Teams: He leads the Data Science and Public Policy Group and the Data Science for Social Good Program at CMU, fostering interdisciplinary collaborations between computer scientists, social scientists, and policymakers.

• K-12 Computing Education
• Social Justice in Computing
• Physical Computing
• +3 more

Gayithri Jayathirtha is an Assistant Professor in the College of Education at the University of Illinois at Urbana-Champaign, specializing in Curriculum & Instruction. Her research focuses on integrating social justice into K-12 computing education through electronic textiles and pedagogical frameworks. She holds a Ph.D. and Master's in Learning Sciences from the University of Pennsylvania, along with a B.S. in Computer Science Engineering from Bangalore University, India. Research Interests: Jayathirtha explores how electronic textiles can bridge technical and societal dimensions in computing education. Her work emphasizes critical engagement, equity, and teacher roles in reshaping curricula to include sociopolitical implications of technology. Key areas include computational thinking assessment, collaborative debugging, and justice-centered learning. Publications: Since 2017, she has published extensively in ACM and IEEE conferences, focusing on topics like teacher identity in social justice, student problem-solving with e-textiles, and portfolio assessments for computational thinking. Notable works include redesigning introductory computing programs to address colonialism and bias, as well as frameworks for politicized trust in classrooms. Scientific Contributions: Jayathirtha has co-authored studies on bugs as catalysts for peer collaboration, the invisibility of everyday computing systems, and strategies for equitable K-12 computing education. Her research often involves partnerships with educators to develop and test innovative teaching methods. Professional Impact: Through her publications and presentations at RESPECT, SIGCSE, and ICLS conferences, Jayathirtha advocates for expanding computing education beyond technical skills to include societal implications. Her work provides practical tools for teachers to integrate critical perspectives into curricula.

Leonid GoubergritsView profile

Professor

• Cardiovascular Modeling
• Computational Fluid Dynamics (CFD) in Medicine
• Hemodynamics
• +10 more

Leonid Goubergrits is a Professor of Cardiovascular Modeling and Simulation at the Einstein Center Digital Future and Charité – Universitätsmedizin Berlin . With a background in applied mathematics and physics from the Moscow Institute of Physics and Technology, he has dedicated his career to applying computational fluid dynamics (CFD) to cardiovascular medicine since immigrating to Germany in 1995. His work bridges fundamental research and clinical applications, aiming to integrate numerical models into everyday medical practice to enhance diagnostics and reduce invasiveness. Doctorate at Technische Universität Berlin (2000) Habilitation at Technische Universität Berlin (2016) His research spans blood flow modeling in coronary vessels, cerebral aneurysms, heart valves, and the aorta, alongside artificial organ development and blood damage modeling . He leads a research group at Charité and the German Heart Center Berlin, focusing on patient-specific simulations and their translation to clinical settings. Recent publications highlight his work on deep learning integration for hemodynamic analysis, 4D Flow MRI validation , and medical device optimization using computational models. His team’s research includes virtual therapy planning for aortic valve replacements, hemolysis modeling , and pulmonary artery pressure sensors . Leonid actively contributes to education, redesigning TU Berlin’s Fluid Mechanics in Medicine curriculum and fostering interdisciplinary collaboration between engineers, physicians, and computer scientists. His vision emphasizes the digital transformation of medicine through computational modeling and simulation.

Federica SandroneView profile

Lecturer

• Rock Mechanics
• Tunnel Engineering
• Underground Construction
• +4 more

Federica Sandrone is a Lecturer at the School of Architecture, Civil and Environmental Engineering (ENAC) at École Polytechnique Fédérale de Lausanne (EPFL), where she also serves as a Scientist at the Laboratory of Experimental Rock Mechanics (LEMR) within the Institute of Civil Engineering. Her academic career spans over 15 years with continuous contributions to tunnel engineering and rock mechanics research. Her research focuses on the intersection of rock mechanics and tunnel engineering, with particular expertise in tunnel pathology analysis, TBM performance in challenging geological conditions, and long-term tunnel behavior. Sandrone's work bridges theoretical analysis with practical engineering applications, addressing real-world problems in tunnel infrastructure management and maintenance. Her research methodology combines field investigations, laboratory testing, and numerical modeling to understand complex geomechanical behaviors. Analysis of her recent publications reveals a consistent focus on tunnel inspection methodologies, TBM performance prediction in difficult ground conditions, and the long-term behavior of tunnel structures. Her work has evolved from fundamental tunnel pathology studies to more advanced applications involving GIS integration, probabilistic modeling, and modern inspection techniques including laser scanning and image analysis. Engineer at SBB-Infrastructure (2008-present) responsible for Tunnels Management and Maintenance Assistant for Tunnel Engineering courses (2007-present) PhD supervision including Erika Paltrinieri's 2015 thesis on TBM performance Development of tunnel inspection methodologies and condition assessment procedures Her teaching activities include courses in Rock Mechanics and Underground Construction, where students learn about the mechanical behavior of rock materials, tunnel excavation and support design, planning and management of underground works, and risk assessment in tunnel construction.

Enrico OpriView profile

Assistant Professor

• Neuromodulation
• Deep Brain Stimulation (DBS)
• Neurological Disorders
• +4 more

Dr. Enrico Opri is an Assistant Professor in the Department of Biomedical Engineering at the University of Michigan , where he directs the Opri Lab. His research focuses on engineering novel methodologies to automate and enhance clinical procedures in neuromodulation for neurological disorders such as Parkinson’s, Tourette syndrome, essential tremor, and epilepsy. Research Focus Neurophysiological activity in basal ganglia-thalamocortical circuits Therapeutic effects of neuromodulation (e.g., Deep Brain Stimulation, cortical stimulation mapping) Identification of neurological biomarkers for improved clinical procedures Advancements in closed-loop neurostimulation systems Article Trends Dr. Opri's recent publications emphasize closed-loop deep brain stimulation (DBS) systems, computational modeling of neural activity, and the identification of biomarkers for neurological disorders. Key subfields include Parkinson’s disease motor dynamics, Tourette syndrome tic detection, essential tremor treatment, and cortico-thalamic coupling mechanisms. His work bridges biomedical engineering and clinical neuroscience, focusing on translating technological innovations into therapeutic applications.

Mohit SinghalView profile

Teaching Professor

• Cybersecurity
• Privacy
• Social Media Analysis
• +3 more

Mohit Singhal is an Assistant Teaching Professor at Northeastern University in Boston specializing in Cybersecurity and Privacy within the Teaching Faculty. His work bridges computational systems and social dynamics in digital environments. His primary research interests include: Cybersecurity Privacy Social Media Analysis Content Moderation Fairness in AI Malware Analysis He investigates algorithmic fairness in business ranking systems, censorship circumvention technologies, causal effects of content moderation policies, and cybersecurity misinformation propagation across platforms like Yelp, Parler, and Twitter. Publication trends from 2019-2025 reveal an evolution from malware analysis toward social-media-centric research, with increasing focus on fairness evaluation frameworks, toxicity measurement in online conversations, and adversarial robustness of privacy tools. Recent work integrates causal inference methods with computational social science approaches. No scientific awards were mentioned in available sources. As a Teaching Professor, Singhal focuses on pedagogy and curriculum development in cybersecurity education. While specific grant details and student mentorship information are not publicly documented in the provided materials, his role involves training students in emerging challenges at the intersection of technology and society.