Find Academic Supervisors

David HovemeyerView profile

Academic

• Static Analysis
• Systems Software
• Computer Science Education
• +3 more

David Hovemeyer is an Associate Teaching Professor at the Whiting School of Engineering, Johns Hopkins University . He holds a PhD (2005) and MS (2001) in Computer Science from the University of Maryland and a BA (1994) from Earlham College. Prior to joining JHU in 2019, he taught at Vassar College and York College of Pennsylvania. Education : PhD, MS, and BA in Computer Science Research : Focuses on static analysis , systems software , and computer science education Projects : FindBugs, CloudCoder, ProgSnap2, FunWithSound His recent work includes frameworks for declarative autograders , formats for programming process data , and tools for educational software development . He has been recognized with Excellence in Teaching Awards and contributes to open-source educational platforms like GitHub. Scientific Awards : 2024 Whiting School Teaching, Advising, and Mentoring Award Excellence in Teaching Award (multiple years) David maintains an active role in the academic community through peer instruction , programming contests, and recommendation letter advising . He also develops tools like FreePoll and Declarative Autograder Framework to enhance teaching efficiency.

• Electronic Structure Theory
• Machine Learning in Materials Science
• Data Driven Materials Science
• +6 more

Professor Patrick Rinke leads the Chair of AI-based Materials Science at the Technical University of Munich (TUM), within the TUM School of Natural Sciences and Department of Physics. His research group develops advanced electronic structure and machine learning methods to address critical challenges in materials science, surface science, physics, chemistry, and nanoscience. Professor Rinke's research spans multiple cutting-edge domains including electronic structure theory development, machine learning applications for materials science, data-driven materials discovery, biomaterials engineering, atmospheric science applications, clean energy materials, and hybrid materials systems. His work integrates advanced computational methods with practical applications across diverse scientific fields, particularly focusing on how artificial intelligence can transform traditional materials research. Analyzing his recent publications reveals strong trends in applying machine learning techniques to materials discovery, with particular emphasis on Bayesian optimization methods, active learning approaches for molecular data, and efficient dataset generation strategies. His research spans from fundamental electronic structure theory to practical applications in biomaterials, atmospheric science, and renewable energy technologies. Professor Rinke has received several prestigious awards including the August-Wilhelm Scheer visiting professorship (2017), a German Science Foundation research scholarship (2007), the Outstanding Postdoctoral Research Achievement Award from UC Santa Barbara (2009), recognition as an Outstanding Referee for Physical Review journals (2014), and the Institute of Physics Computational Physics Group Thesis Prize (2003). Professor Rinke actively contributes to the academic community through teaching and supervision. For the Winter term 2025/26, he is teaching courses including Academic Writing Skills, Introduction to Machine Learning for Materials Science, Current Topics in AI-Based Materials Science, and Machine Learning for Natural Sciences. His research group includes several team members working on diverse projects spanning the intersection of AI and materials science.

Brigitte PientkaView profile

Professor

• Programming Languages
• Verification
• Type Theory
• +6 more

Brigitte Pientka is a Professor at McGill University's School of Computer Science , where she leads the Computation and Logic group . She earned her PhD from Carnegie Mellon University in 2003 and previously studied at the University of Edinburgh and Technical University of Darmstadt. Education PhD in Computer Science, Carnegie Mellon University (2003) University of Edinburgh Technical University of Darmstadt Research Interests Her work focuses on the theoretical and practical foundations for building reliable software systems, combining logic, type theory, and verification with system-building. Key areas include: Type Theory and Dependent Types Logical Frameworks and Mechanized Metatheory Session-Typed Concurrency and Linear Logic Metaprogramming and Contextual Type Systems Theorem Proving and Formal Verification Functional Programming and Language-Based Security Professional Roles She has served as: PC Chair for ICFP'24 and CPP'24 General Chair for POPL'20 Executive Editor of Logical Methods in Computer Science Steering Committee Member for LICS, POPL, and ESOP Scientific Awards Dr. Pientka has received: Test of Time Award at PPDP'18 Humboldt Fellowship for research at MPI-SWS, Germany Labs & Teams She actively develops the Beluga programming language , a tool for mechanizing meta-theory proofs and type-driven program manipulation.

• Crystal structure determination
• Powder X-ray diffraction
• Solid-state NMR spectroscopy
• +6 more

Professor Kenneth Harris is a Distinguished Research Professor in the School of Chemistry at Cardiff University, specializing in the fundamental properties of solids and the development of advanced experimental techniques for materials characterization. His work bridges the gap between traditional crystallography and modern analytical methodologies, with a particular focus on overcoming limitations in structural analysis of complex materials. His research spans three primary interconnected themes: the development of techniques for determining crystal structures of organic solids directly from powder X-ray diffraction data; the advancement of in-situ solid-state NMR strategies for monitoring crystallization processes in real time; and the investigation of structural properties of anisotropic materials using polarized X-ray beam techniques, including the pioneering development of X-ray Birefringence Imaging (XBI). This work has significant implications for pharmaceutical development, materials science, and understanding biological crystallization processes. Analysis of his recent publications reveals a consistent trajectory toward increasingly sophisticated multi-technique approaches to materials characterization. His work increasingly integrates 3D electron diffraction, powder XRD, solid-state NMR, and computational methods like DFT calculations to solve previously intractable structural problems. A notable trend is the application of these methods to biologically relevant molecules (xanthine, riboflavin, L-tyrosine) and the development of techniques to monitor dynamic processes like crystallization and phase transitions in real time. His research demonstrates a shift from purely structural determination toward understanding the dynamic processes that govern material formation and transformation. Distinguished Research Professor title at Cardiff University Key contributor to the development of X-ray Birefringence Imaging Significant contributions to NMR crystallography methodologies Extensive publication record in top chemistry and materials science journals Professor Harris leads a research group focused on developing and applying cutting-edge techniques for materials characterization. His work has significant implications for pharmaceutical development, where understanding crystal structure and polymorphism is critical for drug efficacy and safety. His group has developed innovative approaches to monitor crystallization processes in real time, which has applications in both industrial manufacturing and understanding natural biomineralization processes. The group maintains strong collaborations with researchers across multiple disciplines, including physics, biology, and engineering, reflecting the interdisciplinary nature of modern materials science research.

• Intelligent Control Systems
• Fault and Anomaly Detection
• Virtual and Robust Sensors
• +5 more

Dr. José Luis Calvo Rolle serves as a Professor in the Department of Industrial Engineering at the School of Engineering, Universidade da Coruña (UDC), specializing in Systems Engineering and Automation. His research focuses on intelligent control systems, fault detection, and virtual instrumentation within the Cybernetic Science and Technology Research Group. Teaches across multiple programs including Master's in Industrial Computing and Robotics, Textile Technology, and Occupational Risk Prevention Coordinates thesis supervision across Industrial Engineering and related disciplines His research spans intelligent control systems and optimization, with significant contributions in virtual sensors, fault detection, and AI-driven modeling for industrial applications. Current projects integrate machine learning with industrial processes for naval construction, wastewater treatment, and precision livestock farming, demonstrating cross-disciplinary impact from energy systems to agricultural technology. Recent publications reveal strong trends in applying deep learning to industrial metaverse frameworks, wastewater optimization, and livestock monitoring systems. His work bridges theoretical control engineering with practical implementations in energy management, naval manufacturing, and sustainable agriculture, frequently utilizing dimensionality reduction and one-class classification techniques. Dr. Calvo Rolle actively mentors students through thesis supervision across multiple engineering disciplines and coordinates research projects with diverse funding sources including the European Commission, Spanish National Research Agency, and industrial partners like Navantia and Telefónica. His laboratory work centers on the Cybernetic Science and Technology Research Group, developing testbeds for industrial automation, virtual instrumentation, and AI-driven monitoring systems. Current initiatives include digital twin implementations for naval manufacturing and smart energy management systems.

Franco BasileView profile

Professor

• Analytical Chemistry
• Bioanalytical Mass Spectrometry
• Proteomics
• +5 more

Franco Basile is a Professor in the Department of Chemistry at the University of Wyoming, specializing in Analytical Chemistry and Bioanalytical Mass Spectrometry . His research focuses on developing rapid, non-enzymatic sample preparation techniques for proteomics and metabolomics of biological and environmental samples, including microorganisms, bees, plants, and coal deposits. Education: B.S. in Chemistry (University of Wisconsin-Eau Claire, 1985), Ph.D. in Analytical Chemistry (Purdue University, 1992) Research Interests include: Analytical Mass Spectrometry : Pioneering thermal/microwave digestion for on-tissue proteomics and imaging-MS Metabolomics and Lipidomics : Analyzing root exudates, invasive grasses, and insect cold tolerance Microbial Ecology : Investigating sterol synthesis in bacteria and soil metaproteomics Article Trends span from 2025 to 2012 , emphasizing MALDI- and ESI-MS applications in proteomics, metabolomics, and environmental analysis. Recent work includes non-intrusive laser techniques for protein denaturation monitoring and sterol gene studies in planctomycetes. Scientific Awards : NSF CAREER Award R&D 100 Award ACS Outstanding Professor Award Lindbergh Foundation Research Award Funding sources include NSF, NIH, USDA, and DTRA for projects on insect cryobiology , microbial methane production , and field-portable biodetection systems . The Biodetection and Mass Spectrometry Laboratory houses advanced instrumentation like Q-Exactive HF-X Orbitrap and MALDI-ToF/ToF-MS, supporting interdisciplinary collaborations across ecology, geology, and biomedical sciences.

• Infrastructure Economics
• Construction Finance
• Climate Change Economics
• +4 more

D'Maris Coffman is a Professor in Economics and Finance of the Built Environment at the Bartlett School of Sustainable Construction, University College London (UCL). She serves as Vice Dean for Innovation & Enterprise and has held leadership roles including Director (Head of Department) of BSSC from 2017-2023. She is Editor-in-Chief of Structural Change and Economic Dynamics , contributes to editorial boards of journals like The Journal of Cleaner Production , and holds visiting appointments at Tsinghua University, the University of Milan, and Beijing Institute of Technology. PhD in Economics (University of Pennsylvania, 2008) MA in Economics (University of Pennsylvania, 2004) MA in History (University of Cambridge, 2011) BSc in Economics (University of Pennsylvania, 1999) Her research bridges economic history, infrastructure economics, and climate change mitigation, with a focus on: Measuring welfare impacts of infrastructure investment Financial tools for decarbonization (carbon trading, CDR futures) Regional carbon emissions in China and Zambia Supply chain dynamics during crises (e.g., Great Fire of London, COVID-19) Construction industry challenges (trade credit reliance, rare earth supply) Urban sustainability through bike-sharing systems Recent publications analyze historical financial systems, urban carbon patterns in China, and climate-resilient infrastructure. Her work has been cited over 1,000 times, with notable impact on Nature Sustainability (378 citations) and Nature Human Behaviour (683 citations). Scientific distinctions include Fellowships with the Royal Geographical Society (2022), Academy of Social Sciences (2023), and Accademia Nazionale dei Lincei (2023). She has held editorial leadership roles since 2016. As a mentor, she has guided PhD students in topics ranging from colonial Indian railways to energy policy in Zambia. Graduates now hold roles at Oxford, LSE, UCL, and the Tony Blair Institute. She currently supervises four research students and an incoming scholar on Kenyan public sector capabilities.

Gian-Gabriel GarciaView profile

Assistant Professor

• Health Policy
• Personalized Medicine
• Medical Decision-Making
• +5 more

Gian-Gabriel Garcia is an Assistant Professor and Harold E. Smalley Early Career Professor at the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Institute of Technology, with a dual role as Pillar 1 Co-lead in Data Science, Machine Learning, and Artificial Intelligence at the Children's Healthcare of Atlanta Pediatric Technology Center. His work bridges predictive analytics and decision-making frameworks in healthcare contexts. Education : PhD and MS in Industrial and Operations Engineering (University of Michigan), BS in Industrial Engineering (University of Pittsburgh) Research focuses on responsible AI for healthcare, emphasizing health equity , stochastic optimization , and machine learning applied to concussion management, opioids, maternal health, and cardiovascular disease. His methodologies integrate dynamic programming and simulation to address stakeholder acceptability. Key article themes include concussion diagnostics , responsible AI in diabetes care, and interpretable policies for chronic disease management. His work frequently leverages Markov decision processes and stochastic modeling . Scientific Awards National Science Foundation Graduate Research Fellowship INFORMS Bonder Scholarship for Applied Operations Research in Health Services SMDM Lee B. Lusted Prize INFORMS Minority Issues Forum Paper Competition First Prize INFORMS Minority Issues Forum Poster Competition First Prize Garcia also contributes to undergraduate mentorship and serves as Vice President of Communications (co-chair) for the INFORMS Minority Issues Forum, alongside council membership in the INFORMS Health Applications Society.

Craig KnoblockView profile

Research Professor

• Knowledge Graphs
• Semantic Web
• Data Integration
• +7 more

Craig Knoblock serves as the Keston Executive Director of the Information Sciences Institute (ISI) at the University of Southern California, Vice Dean of Engineering for the Viterbi School of Engineering, and Research Professor of both Computer Science and Spatial Sciences. He also directs USC's Data Science Program and leads the Center on Knowledge Graphs as Research Director. Dr. Knoblock's research focuses on techniques for describing, acquiring, and exploiting the semantics of data. His extensive work spans source modeling, schema and ontology alignment, entity and record linkage, data cleaning and normalization, extracting data from the Web, and building comprehensive knowledge graphs. With over 300 published works in these areas, his research has significantly advanced the field of semantic data integration. His work demonstrates strong trends toward practical applications of knowledge graphs across diverse domains including cultural heritage, geospatial information systems, human trafficking detection, and sensor networks. The evolution of his publications shows a progression from foundational ontology alignment techniques to sophisticated knowledge graph applications addressing real-world challenges. Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) Fellow of the Association of Computing Machinery (ACM) Past President and Trustee of the International Joint Conference on Artificial Intelligence (IJCAI) Recipient of the 2014 Robert S. Engelmore Award Seven best paper awards for his research contributions As Executive Director of USC's Information Sciences Institute, Dr. Knoblock leads one of the world's premier research centers in computer science and information technology. His leadership extends to directing the Center on Knowledge Graphs and serving as Associate Director of the Informatics Program at USC. His educational background includes a Bachelor of Science from Syracuse University and Master's and Ph.D. degrees in Computer Science from Carnegie Mellon University.

Leonardo TonettoView profile

Researcher

• Mobile User Modeling
• Deep Learning
• Data Analysis
• +6 more

Leonardo Tonetto is a researcher at Technical University of Munich (TUM) within the Chair of Connected Mobility, working under Prof. Jörg Ott. His office is located in FMI 01.05.038 and he maintains an active presence in both academic research and open-source development with significant GitHub contributions (19 repositories, 73 stars). His work bridges theoretical research and practical implementation in mobility systems. Dr. Tonetto's research spans Mobile User Modeling , Deep Learning & Data Analysis , Signal Processing , and Complex Networks . His work demonstrates particular expertise in extracting meaningful patterns from human mobility data while addressing critical privacy concerns. Recent publications show increasing focus on ethical implications of location-based data and energy-efficient computing for augmented reality applications. Analysis of his publication record from 2014-2025 reveals a consistent research trajectory evolving from fundamental mobility pattern analysis toward more complex systems integrating privacy considerations and energy efficiency. His work increasingly intersects computer science with social implications, particularly in location-based services and epidemic modeling. The research shows strong methodological diversity, employing machine learning, network analysis, and signal processing techniques across various application domains. Through his GitHub profile and open-source contributions, Tonetto demonstrates commitment to reproducible research and community engagement. His technical skills span multiple programming languages and systems, supporting both theoretical research and practical implementation of mobility-aware systems. While specific grant information isn't publicly available, his consistent publication output suggests successful research funding.

Kahadawala CoorayView profile

Professor

• Modeling continuous statistical distributions
• Statistical inferences
• Actuarial science
• +1 more

Kahadawala Cooray is a Professor at the Department of Statistics, Actuarial and Data Sciences within the College of Science and Engineering at the University of Nevada at Las Vegas. He holds a Ph.D. from the same institution (2008) and a B.Sc. from the University of Colombo, Sri Lanka (1994). Education : Ph.D. (2008, University of Nevada at Las Vegas), B.Sc. (1994, University of Colombo, Sri Lanka) Cooray specializes in modeling continuous statistical distributions and applying them to actuarial science and medical research. His work includes parametric analysis of renal failure data, Bayesian estimation of composite distributions, and extensions of the Weibull and Gumbel distributions for complex datasets. His research trends focus on creating flexible statistical models for heavy-tailed data, multivariate dependence structures, and applications in insurance risk analysis. Key contributions include generalized copulas, folded logistic distributions, and hybrid Weibull-Pareto models for survival analysis. Scientific Awards : First Ph.D. graduate in mathematical sciences in Nevada (2008) Wolzinger Family Research Scholarship (2008) Cooray teaches courses in statistics and actuarial science, and he is affiliated with the American Statistical Association and its Mid-Michigan Chapter. His collaborations include researchers like M. M. A. Ananda and S. Gunasekera.

Padraig MacCarronView profile

Associate Professor

• Complex Networks
• Social Network Analysis
• Big Data Applications
• +3 more

Padraig MacCarron is an Associate Professor in the Department of Mathematics and Statistics at the University of Limerick, specializing in complex networks. He is affiliated with the Centre for Research Training in Foundations of Data Science and the Mathematics Applications Consortium for Science and Industry (MACSI). Education: BSc in Astrophysics from University College Cork; PhD from Coventry University on social networks in narratives. His research focuses on interdisciplinary applications of complex networks, including social polarization, criminal networks, and trust dynamics in health research. He collaborates with Psychology, Law, and Health departments to model social phenomena like community formation and fragmentation. Recent work explores structural properties of social networks through diverse domains such as Twitter analysis for political polarization, participatory health research partnerships, and arts-based methods for migration health co-production. This spans network theory, social media analytics, and data-driven policy modeling. He is a member of MACSI and the Centre for Research Training, emphasizing computational methodologies and team-based collaborations. Padraig actively accepts PhD students for projects involving network science and social systems modeling.

Kathryn JohnsonView profile

Professor

• Wind Energy Control Systems
• Engineering Education
• Floating Offshore Wind Turbines
• +3 more

Kathryn Johnson is a Professor in the Department of Electrical Engineering at Colorado School of Mines with a joint appointment at the National Renewable Energy Laboratory (NREL). She holds the Ben Fryrear Chair for Innovation and Excellence and earned her B.S. from Clarkson University (2000), and M.S./Ph.D. from University of Colorado Boulder (2002/2004). Her research spans wind energy control systems (floating offshore turbines, ultra-scale rotors, wind farm optimization) and sociotechnical engineering education (macroethics, social justice integration). Research Focus: Dr. Johnson leads pioneering work in aerodynamic control of floating offshore wind turbines, developing morphing rotor technologies for 50-MW systems, and optimizing wind-hydrogen integration. Her education research examines how sociotechnical thinking develops in engineering students, with fieldwork validated through international collaborations. Publication Trends: Recent works (2021-2023) demonstrate dual emphasis on: 1) Advanced wind turbine control (aerodynamic load mitigation, floating platform stabilization, grid integration) and 2) Engineering pedagogy (sociotechnical identity formation, ethics frameworks, justice-oriented curriculum design). Over 75% of recent publications involve experimental validation through NREL field tests. Awards & Honors: Fulbright Canada Research Chair in STEM Education (2021) Clare Boothe Luce Endowed Professorship (2005) IEEE Senior Member recognition Educational Leadership: Teaches core courses including Feedback Control Systems, Modern Control Design, and Wind Energy Systems. Developed Mines' first sociotechnical integration modules for control engineering curricula. Supervised 15+ graduate students in wind energy and education research. Facilities & Collaboration: Leads experimental work at NREL's National Wind Technology Center, directing the SUMR (Segmented Ultralight Morphing Rotor) consortium. Collaborates with 10+ institutions on DOE-funded projects including USFLOWT floating turbine initiative.

• Digital Inequality
• Health Information Technology
• Older Adults
• +7 more

Timothy Hale is a Teaching Assistant Professor in the Department of Kinesiology and Community Health at the University of Illinois. His research focuses on digital inequality , health information technology , and technology usability for older adults . Collaborations with institutions like Taylor and Francis, Frontiers in Public Health, and the International Symposium on Human Factors and Ergonomics in Health Care Research areas include: Social media regulation in healthcare LGBTQ+ virtual outreach Usability testing for mobile health apps Legacy and emergent digital inequalities Key research trends from 2014-2024 show interdisciplinary work at the intersection of public health , gerontechnology , and digital equity . His work spans user-centered design , telemedicine , and health behavior analysis across diverse populations.

Sorin TulucaView profile

Professor

• Global Financial Crises
• Financial Valuation
• Derivatives
• +6 more

Sorin Tuluca serves as Professor of Finance at Fairleigh Dickinson University's Silberman College of Business within the Department of Finance, Decision Sciences, Economics, and International Business. With over 25 years in academia following a 12-year engineering career in aircraft construction, he integrates technical rigor with financial expertise across graduate and undergraduate programs. His educational foundation includes: MSAE in Aerospace Engineering from Polytechnic University of Bucharest MBA and DBA from Cleveland State University Research centers on global financial crises , derivative valuation , and real options theory applied to strategic decisions. Recent work explores NFT project valuation, ESG integration in S&P 500 firms, and capital budgeting conflicts using Bloomberg Terminal data. His publications span top journals like The Financial Review and practitioner outlets including The Journal of Wealth Management. Current scholarship reveals three dominant trends: (1) Real options frameworks for emerging assets like NFTs, (2) Liquidity-profitability-ESG interrelationships in corporate performance, and (3) Educational innovation through financial data platforms. This bridges theoretical finance with actionable industry applications. Key recognitions include: Bright Idea Award from NJPRO (2017, 2019) for business faculty research Bartlett Professor of Teaching Innovation (2016-2018) for Bloomberg Terminal integration He mentors students through courses like Corporate Finance and Derivatives while leveraging institutional resources including Wharton Research Data Services. Media commentary in The Wall Street Journal and Bloomberg Business Week demonstrates policy-relevant economic analysis. His teaching innovations receive dedicated university funding for technology-enhanced finance education. Active engagement with Bloomberg Terminals defines his data-driven approach, supporting both research on market volatility and hands-on student training. Editorial board service for finance journals and conference program chair roles reflect ongoing scholarly leadership within the finance community.