Find Academic Supervisors

Huang LinView profile

Assistant Professor

• Biostatistics
• Bioinformatics
• Machine Learning
• +3 more

Huang Lin is an Assistant Professor of Biostatistics at the University of Maryland's Department of Epidemiology and Biostatistics, School of Public Health. His research focuses on statistical methodologies, machine learning, and causal inference applied to high-dimensional omics data in microbiome and metabolomics studies, with applications in cancer, HIV/AIDS, maternal and child health, and clinical trials. He holds a BS in Statistics and Chemistry from Xiamen University (China), a PhD in Biostatistics from the University of Pittsburgh, and completed a postdoc at NIH. His academic work bridges bioinformatics and statistical innovation, addressing challenges in biomedical data analysis. Notably, he explores causal inference frameworks for infectious disease studies and develops machine learning tools for omics data integration. Recent collaborations include improving clinical trial methodologies in maternal health and HIV treatment efficacy. While his listed publications emphasize materials science for solid oxide fuel cells, this may reflect a dual academic focus or potential data overlap. His academic profile highlights biostatistics expertise, with research trends in interdisciplinary applications of statistical models to biomedical problems. No awards are explicitly listed, though his work demonstrates impactful contributions to methodological advancements.

Zachary UlissiView profile

Adjunct Professor

• Catalysis
• Surface Science
• Energy Science
• +3 more

Zachary Ulissi is an Adjunct Professor in the Department of Chemical Engineering at Carnegie Mellon University. He holds a B.S. in Physics and B.E. in Chemical Engineering from the University of Delaware (2009), an M.A.S. in Mathematics from the University of Cambridge (2010), and a Ph.D. in Chemical Engineering from MIT (2015). His research applies systems engineering and machine learning to nanoscale carbon nanotube devices, catalyst networks, and electrochemical reduction processes. His core research focuses on catalysis, surface science, energy systems, and machine learning applications in chemical engineering. Key areas include developing computational methods to optimize catalyst reactions for sustainable fuel production and designing nanoscale sensors. Dr. Ulissi has contributed to projects funded by the Scott Institute for Energy Innovation, including green chemistry initiatives aimed at reducing industrial emissions. He actively engages in academic discourse on energy innovation and reaction kinetics, as noted in Engineering & Technology Magazine. His work emphasizes cross-disciplinary collaboration, particularly in integrating machine learning with chemical engineering to address energy challenges.

Christoph T. KochView profile

Professor

• Electron Microscopy
• Materials Science
• Condensed Matter Physics
• +3 more

Christoph T. Koch is a Professor of Physics at Humboldt-Universität zu Berlin, where he has held the W3 Chair since 2015. Previously, he held a similar position at Ulm University (2011–2015), supported by the Carl Zeiss Foundation. His research focuses on advanced electron microscopy techniques, including quantitative transmission electron microscopy (TEM), electron holography, and strain mapping. He leads the AG Strukturforschung/Elektronenmikroskopie group, advancing materials science through innovations in imaging and spectroscopy. Education: B.Sc./M.Sc. in Physics at Heidelberg University (1996–1998), followed by an exchange at Arizona State University (1997–1998). PhD in Physics from Arizona State University (2002, advisor: Prof. John C.H. Spence). Postdoctoral research at the Max Planck Institute for Metals Research, Stuttgart (2002–2011). Research interests include: Electron diffraction and phase retrieval Nanometer-scale strain and defect analysis Electron energy-loss spectroscopy (EELS) for plasmonics and bandgap mapping Development of FAIR data infrastructure for materials science Leadership: Managed the Department of Physics at Humboldt University (2020–2024). Collaborates widely, with key co-authors including P.A. van Aken, W. Sigle, and C. Felser. His work bridges experimental microscopy and computational modeling, addressing challenges in semiconductors, ceramics, and 2D materials. Notable contributions include pioneering methods for 3D reconstruction via electron ptychography, dynamic electron diffraction analysis, and strain mapping in advanced CMOS technologies. Current efforts emphasize real-time imaging and AI-driven data analysis in materials research.

Fan HongjinView profile

Professor

• Nanomaterials
• Nanotechnology
• Semiconductor Nanocrystals
• +5 more

Professor Fan Hongjin serves as Director Professor in the Division of Physics & Applied Physics at Nanyang Technological University's School of Physical & Mathematical Sciences, with a courtesy appointment in the School of Chemistry, Chemical Engineering and Biotechnology. He leads the SMILE research group focusing on sustainable energy materials and has established himself as a leading researcher in aqueous battery systems and electrocatalysis. His research interests span nanomaterials and nanotechnology, semiconductor nanocrystals, surfaces and coatings, with particular focus on aqueous batteries (especially zinc-based systems), electrocatalysis for hydrogen generation and CO2 reduction, and energy storage materials . Fan's group pioneered research on aqueous zinc-ion batteries since 2018 and has developed innovative approaches to hydrogel electrolytes, iodine conversion chemistry, and dual-plating strategies for large-scale energy storage. His publication record demonstrates consistent high-impact research, with 15 recent articles (2024-2025) appearing in journals including Nature Communications , Journal of the American Chemical Society , Energy & Environmental Science , and Joule . These works collectively advance understanding of zinc-halogen battery chemistry, strain engineering in catalysts, and novel electrolyte design principles. Highly Cited Researcher by Clarivate Analytics (2016-present) Fellow of Royal Society of Chemistry (FRSC, 2018) Young Scientist Award by Singapore Institute of Physics Editor-in-Chief of Materials Today Energy (since 2021) Member of editorial boards for Energy & Environmental Sciences, Advanced Science, Small, and other top journals Professor Fan actively mentors PhD students including Rao Ruijun, Annisaa Hayya Arundati, Liu Qingyi, and Wu Jiawen, with recent successes including Yang Jin-Lin winning the MRSS Metal in Physics (July 2025). His research group continues to expand with new members joining regularly, reflecting ongoing research momentum and funding support in the sustainable energy field. The group maintains strong industry and academic collaborations across Asia, Europe, and North America.

• Heterogeneous Catalysis
• Energy Sustainability
• Computational Materials Science
• +7 more

Alyssa Hensley is an Assistant Professor at the Charles V. Schaefer, Jr. School of Engineering and Science, Stevens Institute of Technology, affiliated with the Department of Chemical Engineering and Materials Science. She holds a PhD in Chemical Engineering from Washington State University (2015) and a BS in Chemical Engineering from New Mexico Institute of Technology (2012). Education: PhD (2015) and BS (2012) in Chemical Engineering Experience: Postdoctoral Fellow (University of Toronto, 2018-2021) and Postdoctoral Research Assistant (Washington State University, 2016-2018) Teaching: Courses include Chemical Engineering Thermodynamics I (CHE 233) and Reactor Design (CHE 650) Her research focuses on heterogeneous catalysis for energy and sustainability, addressing fundamental challenges in connecting nanoscale catalyst surface dynamics to chemical bond activation. Key areas include computational modeling of multi-component catalysts, machine learning applications, and reaction mechanism analysis for biomass/plastic waste conversion and CO₂ capture. Recent work explores configurational space sampling, transition state identification, and catalyst design using density functional theory and data science. Publications highlight reactions involving Pt, Fe, and PdFe surfaces with applications in CO oxidation, guaiacol hydrogenolysis, and hydrodeoxygenation. Professional service includes editorial roles (Scientific Reports, Nature Communications), NSF and DOE proposal review, and conference organization (AIChE, ACS meetings). She contributes to institutional committees including Research Computing and Curriculum Development.

Andrew I. CooperView profile

Professor

• Advanced organic functional materials
• Conjugated microporous polymers
• Porous organic cages
• +5 more

Andrew I. Cooper is a Professor at the University of Liverpool, Director of the Materials Innovation Factory, and Honorary Professor at East China University of Science and Technology (ECUST). He pioneers research in advanced organic functional materials, including conjugated microporous polymers, porous organic cages, and porous liquids, and developed the first autonomous mobile robotic chemist. Fields of Interest: Materials chemistry, robotics, AI-driven synthesis, and computational design of functional materials. Scientific Impact: Over 200 SCI-indexed papers, 52,000+ citations, H-index 117. Key journals: Nature , Science , JACS , Angewandte Chemie . Awards: Royal Society of Chemistry Professorship, Outstanding AI Leader award, Fellow of the Royal Society and European Academy of Sciences. Leadership: Editor-in-Chief of Chemical Science , trained 47 Chinese postdoctoral fellows and PhD students, and leads international collaborations with Chinese universities. Research Trends: Articles focus on robotics, AI, computational materials design, photocatalysis, and dynamic porosity in molecular systems.

Robert PolliceView profile

Lecturer

• Computational Chemistry
• Quantum Chemistry
• Machine Learning
• +6 more

Robert Pollice is a Lecturer at the Faculty of Science and Engineering , University of Groningen , specializing in Homogeneous Catalysis . His research integrates computational chemistry , machine learning , and automated experimentation to accelerate molecular design and catalyst development . Research Interests focus on homogeneous catalysis , quantum chemistry , and machine learning applications. His work addresses challenges in reaction mechanism modeling , noncovalent interactions , and inverse molecular design , leveraging closed-loop optimization and large language models for chemical data analysis . Publications span quantum chemical simulations , solvation energy calculations , excited state engineering , and automated catalyst discovery . His recent studies explore inverted singlet-triplet gaps , machine learning for reaction modeling , and SELFIES for molecular string representations . Peer-review Contributions include evaluations for journals like Organic Process Research & Development , Materials Advances , and Chem , reflecting his expertise in catalysis , quantum chemistry , and AI-driven chemical discovery .

Bettina V. LotschView profile

Professor

• Nanochemistry
• Solid-State Chemistry
• Materials Science
• +4 more

Prof. Dr. Bettina V. Lotsch is Director of the Nanochemistry Department at the Max Planck Institute for Solid State Research (Stuttgart) and Honorary Professor at Ludwig-Maximilians-Universität München's Faculty for Chemistry and Pharmacy. She holds a prestigious Leibniz Prize (2025) and leads research in nanochemistry, materials science, and energy conversion technologies. Her multidisciplinary research focuses on developing multifunctional materials through solid-state and nanochemistry approaches, with emphasis on covalent organic frameworks, photonic nanostructures, and solid electrolytes for energy applications. Current projects explore solar batteries, electrocatalysis, and quantum materials. Prof. Lotsch has received numerous international honors including Baker Lectureship (Cornell), Materials Lectureship (Warwick), and EU-40 Materials Prize. She coordinates a large research team of >20 doctoral students and postdocs working on solid-state electrolytes, COF photocatalysis, and 2D material design. Education: PhD (summa cum laude) from LMU Munich, postdoctoral training at University of Toronto with G.A. Ozin, and visiting studies at University of Oxford. Research Leadership: Manages laboratories at both Max Planck Institute (Stuttgart) and LMU Munich (Chemistry Department) with specialized facilities for materials synthesis and characterization.

Derek HaoView profile

Research Fellow

• Materials Science
• Nanotechnology
• Environmental Engineering
• +5 more

Derek Hao is a materials scientist and environmental engineer holding the Vice Chancellor’s Postdoctoral Fellowship at RMIT University's School of Science. His research focuses on advanced materials for environmental sustainability and energy conversion, particularly in waste plastic valorization, photocatalytic systems, and nanotechnology. He has secured over AU$1.2m in research funding and commercialized two patents on bismuth catalysts, generating significant industry impact. His work spans collaborations across Australia, Germany, China, and beyond. Education: PhD in Engineering (University of Technology Sydney, 2022); Bachelor’s in Chemical Sciences (China University of Geosciences). Research Priorities: Sustainable waste plastic solutions, photocatalytic energy conversion, nanomaterials, and environmental toxicology. Awards: Humboldt Research Fellowship (2022), RMIT Vice Chancellor’s Fellowship (2023), inclusion in Stanford’s Top 2% Scientists (2022–2023). Teaching: Teaches Analytical Chemistry and supervises 5 PhD students in areas like electrocatalysts for hydrogen production and CO₂ reduction. Grants & Patents: AU$1.2m+ in funded projects; commercialized bismuth catalyst patents yielding AU$500k+ annually. His research bridges fundamental science and practical environmental solutions, with over 100 peer-reviewed papers (H-index 46), including ESI Highly Cited and Hot Papers. He serves on editorial boards for journals like Science for Energy and Environment and Nano Research Energy .

Susanna M. ThonView profile

Associate Professor

• Renewable energy conversion and storage
• Photovoltaics
• Optoelectronics
• +4 more

Susanna M. Thon is an Associate Professor of Electrical and Computer Engineering at Johns Hopkins University and a Marshal Salant Faculty Scholar. She serves as Associate Director of the Ralph O’Connor Sustainable Energy Institute (ROSEI) and is affiliated with the Data Science and AI Institute. Education: B.Sc. in Physics (MIT, 2005), M.Sc. and Ph.D. in Physics (UC Santa Barbara, 2008, 2010) Postdoctoral Fellow (University of Toronto) Her research focuses on nanostructured materials and devices for renewable energy and optoelectronics, particularly solar energy conversion and sensing. Key projects include plasmonic-photocatalytic systems using aluminum nanoparticles, colloidal quantum dots for multicolored/transparent solar cells, and machine learning-driven solar cell optimization. Funding: National Science Foundation, American Chemical Society, Maryland Energy Innovation Institute, U.S. Army, Cohen Translational Engineering Fund Professional Memberships: American Chemical Society, American Physical Society, IEEE, Optica, Materials Research Society, Association for Women in Science Her team has published over 50 peer-reviewed papers and actively mentors students like Kyle, Jill, Sreyas, Ekin, Ariel, Delancy, Joseph, Sasha, and Kevin, who have presented at Design Day and published in journals like Coordination Chemistry Reviews and Optics Express. Scientific awards include the Johns Hopkins Catalyst Award, Discovery Award, and WSE Excellence in Mentoring Award.

• Hydrogen Energy Storage
• Negative Emissions Technologies
• Life Cycle Assessment
• +7 more

Hanna Breunig is a Research Scientist at Lawrence Berkeley National Laboratory and Deputy of the Sustainable Energy & Environmental Systems Department. She holds a secondary appointment in the Earth Systems and Society Domain within the Climate and Ecosystem Science Division. Her work focuses on validating emerging energy technologies through process design, techno-economic modeling, and market analysis. Education: PhD in Civil and Environmental Engineering from UC Berkeley (2015), MSc (2011), and BSc from Cornell University (2010). Her research spans hydrogen storage , CO2 capture/utilization , brine management , and technoeconomic modeling for systems in data centers, hospitals, mines, aviation, and ports. She co-leads the DOE HyMARC consortium and the systems analysis team for the ARCHES California Hydrogen Hub. Recent publications highlight advancements in metal-organic frameworks (MOFs) for hydrogen storage, solar hydrogen production , and high-temperature thermal energy storage . She has received accolades like the 2023 Energy & Environmental Science Lectureship and 2014 Schmidt MacArthur Fellowship. Scientific Awards: 2023 Energy & Environmental Science Lectureship 2021 Early Scientific Career Award 2019 CEC Bioenergy Project Leadership 2017 LDRD Early Career Award 2014 Schmidt MacArthur Fellowship Hanna mentors graduate and undergraduate students and contributes to tools like the BioSiting v2 software for U.S. bioeconomy resource analysis.

• Catalysis
• Computational Chemistry
• Heterogeneous Catalysis
• +3 more

Dr. Guanna Li is an Assistant Professor in the Biobased Chemistry and Technology group at Wageningen University & Research. Her research focuses on catalyst design and reaction mechanism studies in heterogeneous catalysis, leveraging advanced computational methodologies such as DFT, ab initio molecular dynamics (AIMD), and machine learning. She investigates dynamic catalyst behavior under reaction conditions and aims to establish structure-activity relationships for rational catalyst design. Key areas include biomass conversion, CO2 hydrogenation, and plastic upcycling. Dr. Li holds a dual PhD from Eindhoven University of Technology (TU/e) and Dalian Institute of Chemical Physics, with postdoctoral experience at TU/e and Delft University of Technology, supported by a VENI Talent Programme grant (NWO, 2016). She collaborates closely with experimental groups to bridge theory and practice in catalytic processes. Education: PhD in Heterogeneous Catalysis (TU/e), PhD in Raman Optical Activity (DICP), postdoctoral research at TU/e and Delft University of Technology. Research Interests: Multiscale modeling of catalytic reactions, transition metal carbide catalysts, CO2 hydrogenation to methanol, plastic upcycling via mechano-catalysis, and surface reaction dynamics. Her methodologies include DFT, AIMD, and machine learning for mechanistic insights. Projects: Transition metal carbide catalyst design, CO2 hydrogenation collaborations with DICP, and plastic upcycling initiatives. These projects emphasize synergy between computational and experimental approaches. Awards: VENI Talent Programme Grant (2016). Grants/Advising: Supervises MSc/PhD students and postdocs on catalysis and computational chemistry projects. Open to collaborations and applications for research positions. Labs/Teams: Leads a research team in Wageningen’s Biobased Chemistry and Technology group, emphasizing computational catalysis and sustainable chemical processes.

• CO2 Electrolysis
• Heterogeneous Catalysis
• Sustainable Chemistry
• +3 more

Matthew Kanan is a Professor in the Department of Chemistry at Stanford University, teaching core courses including CHEM 31E: Chemical Foundations and 21st Century Problems (Autumn) and CHEM 121: Understanding the Natural and Unnatural World through Chemistry (Spring). He actively mentors students through year-round independent studies (CHEM 90, CHEM 190) and research programs (MATSCI 300, CHEM 301, CHEM 200). His research pioneers sustainable solutions for carbon management, focusing on electrochemical CO 2 reduction, catalyst development for reverse water-gas shift reactions, and novel carbon capture technologies. Key innovations include carbonate-promoted carboxylation processes, membrane-free electrochemical systems for acid-base production, and metamaterial reactor designs for energy-efficient thermochemical conversion. His work bridges fundamental electrochemistry with scalable engineering for carbon-neutral chemical synthesis. Recent publications (2023-2025) demonstrate a cohesive research trajectory toward industrial-scale CO 2 utilization, with emphasis on energy efficiency, catalyst durability, and impurity tolerance. Dominant themes include electrochemical engineering for concentrated product streams, computational modeling of catalyst microenvironments, and thermal processes for mineral-based carbon removal. This integrated approach targets practical implementation in sustainable fuel and chemical production. Professor Kanan supervises undergraduate research (CHEM 190), directed instruction (CHEM 90), and Ph.D. candidates across chemistry and materials science. His research group likely secures substantial funding for projects addressing critical challenges in carbon conversion, though specific grants aren't detailed in the source material. Collaborative work spans electrochemical engineering, materials design, and process optimization for decarbonization.

Alexander SumichView profile

Professor

• Biopsychology
• Neuroimaging
• Neurobiology of mental health
• +6 more

Alexander Sumich is Professor of Mental Health and Biopsychology at Nottingham Trent University , School of Social Sciences. He co-directs the Centre for Public and Psychosocial Health and co-leads the Affect, Personality and Embodied Brain (APE) Research Group . He also serves as Adjunct Professor in Psychology at Auckland University of Technology, New Zealand , and holds editorial and leadership roles in organizations like the British Society for the Psychology of Individual Differences (Treasurer) and Personality and Individual Differences (Associate Editor). Education: MA in Psychology (First Class Honors), University of Auckland PhD in Psychology as Applied to Medicine, Institute of Psychiatry, London His research spans neuroimaging and electrophysiological methods to investigate the neurobiology of affect-driven behaviors (depression, aggression, hallucinations) and the immune system's role in mental health . He employs virtual reality exposure therapy (VRET) , spiking neural networks , and computational models to enhance mental health interventions. Key areas include gaming disorder , mindfulness effects , and gut-brain axis interactions . Notable research grants include: BIAL Foundation (2023-2024): €58,765 for trauma-paranormal-mental health links MBIE-Catalyst Programme (2020-2024): NZ$2,134,847 for computational neurogenetics UKRI KTP (2021-2024): £204,000 for therapeutic digital displays His external roles include: Treasurer, British Society for the Psychology of Individual Differences Associate Editor, Personality and Individual Differences Co-host, APE2020 Conference

Tyler DerrView profile

Assistant Professor

• Data Mining
• Social Network Analysis
• Graph Representation Learning
• +5 more

Dr. Tyler Derr is an Assistant Professor in the Department of Computer Science at Vanderbilt University, with affiliate roles in the Data Science Institute and the Frist Center for Autism and Innovation. He holds a PhD from Michigan State University (2020) and focuses on data mining, machine learning, and graph neural networks with applications in drug discovery, ethical AI, and neurodiversity research. Education: PhD in Computer Science, Michigan State University (2020) M.S. in Computer Science, Pennsylvania State University B.S. in Computer Science and Mathematics, Pennsylvania State University His research emphasizes interdisciplinary social good, including drug discovery, education equity, and autism innovation. He directs the Network and Data Science (NDS) Lab, mentoring students who have won 50+ awards. Notable contributions include tools like FairNNV for fairness certification and datasets like WelQrate for drug discovery benchmarking. Awards include the NSF CAREER Award (2023), NVIDIA Academic Grant (2024), and Vanderbilt’s Career Catalyst Impact Award (2025). He co-founded the MLoG workshop series and serves on editorial boards for ACM TKDD and IEEE Transactions on Big Data . Grants & Leadership: NSF Grant for student travel to KDD2024 NVIDIA BioNeMo Platform grant for peptide design DOE Computational Science Fellowship advising His work bridges theory and practice, with tutorials on graph ML at AAAI/KDD and keynotes on ethical AI. The NDS Lab hosts interdisciplinary collaborations in computational biology, transportation, and neurodiversity advocacy.