Find Academic Supervisors

• Quantitative PET/CT and SPECT/CT Imaging
• Deep Learning in Medical Imaging
• Motion Correction Algorithms
• +2 more

Chi Liu is a Professor of Radiology & Biomedical Imaging at Yale School of Medicine . He serves as Associate Director of Biomedical Imaging Technology at the Yale Biomedical Imaging Institute and Director for Research Faculty Affairs in the Radiology & Biomedical Imaging department. Education : PhD from Johns Hopkins University (2008) Postdoctoral Training : University of Washington (2010) Certification : American Board of Science in Nuclear Medicine (Nuclear Medicine Physics and Instrumentation) His research focuses on quantitative cardiac and oncological PET/CT and SPECT/CT imaging , emphasizing deep learning algorithms , reconstruction algorithms , data correction , and dynamic imaging . Key clinical applications include early detection of chemotherapy-induced cardiotoxicity , multimodality imaging of heart failure , and motion variability elimination in therapy response assessment . The 15 most recent publications reveal a strong emphasis on deep learning techniques for low-dose imaging , motion correction , and cross-tracer generalizability in PET/SPECT systems. These works span applications in cardiac imaging , neuroscience , oncology , and theranostics . Scientific Award : Bruce Hasegawa Young Investigator Medical Imaging Science Award (2012) Contact: chi.liu@yale.edu | ORCID 0000-0002-7007-1037

Jennifer K. RyanView profile

Professor

• Numerical Analysis
• High-Order Numerical Methods
• Discontinuous Galerkin Methods
• +4 more

Jennifer K. Ryan is a Professor and Division Head for Numerical Analysis, Optimization & Systems Theory at the Department of Mathematics, KTH Royal Institute of Technology, Stockholm. She is affiliated with the Digital Futures Faculty, a cross-disciplinary research center jointly established by KTH, Stockholm University, and RISE Research Institutes of Sweden. Her research focuses on developing numerical schemes for extracting enhanced accuracy from simulations, with applications in imaging, data analysis, and fluid dynamics. Ryan’s work emphasizes improving computational efficiency through theoretical insights and practical algorithms. Her academic roles include teaching courses like Numerical Methods for Differential Equations II and supervising student projects in numerical analysis. She has contributed to the SIAC MAGIC toolbox, a software package for accuracy-enhancing filtering techniques. Ryan’s research group actively explores discontinuous Galerkin methods, SIAC filtering, and multi-resolution analysis, addressing challenges in computational physics and engineering. Her publications span high-order numerical methods, mesh adaptivity, and applications in plasma physics and wave equations. Projects include error estimation for boundary integral methods and developing filters for noisy data. Ryan collaborates internationally, contributing to both theoretical advancements and practical implementations in computational science.

• Space Propulsion
• Plasma Physics
• Fluid Dynamics
• +3 more

Pablo Fajardo Peña is a Full Professor in the Department of Aerospace Engineering at Universidad Carlos III de Madrid (UC3M). He leads the Plasmas and Space Propulsion Team (EP2) and co-directs the Aerospace Engineering Research Group. His research focuses on advanced propulsion technologies for space applications, including plasma thrusters, electric propulsion, and fluid-thermal systems. Professor Peña's work spans computational modeling of plasma dynamics, experimental characterization of propulsion systems, and development of novel thrusters like Hall effect thrusters and electrospray systems. His recent publications analyze plasma discharge mechanisms, thruster plume behavior, magnetic nozzle effects, and propellant interactions. He leads multiple EU and Spanish-funded projects including HIPATIA (Helicon Plasma Thruster), CHEOPS (Hall Effect Orbital Propulsion), and ADAPT (Advanced Plasma Propulsion). These initiatives focus on developing efficient propulsion systems for spacecraft and addressing challenges in space debris removal. Professor Peña supervises doctoral research on plasma diagnostics and thruster simulation, and has developed simulation tools like HYPHEN (Hybrid Plasma Thruster Holistic Environment). His team collaborates with ESA, Airbus, and SENER Aeroespacial on propulsion technology validation.

Xiaolei FanView profile

Associate Professor

• Nonthermal Plasma Catalysis
• Catalytic CO2 Conversion
• Zeolite-Based Catalysis
• +5 more

Xiaolei Fan is an Associate Professor in the Department of Chemical Engineering at The University of Manchester. He holds a BEng in Environmental Engineering from Jilin Institute of Chemical Technology (2003), an MRes in Chemical Engineering from East China University of Science and Technology (2006), and a PhD in Continuous Flow Heterogeneous Catalysis from the University of Bath (2010). His research focuses on nonthermal plasma catalysis, CO2 conversion, catalytic biorefinery, and zeolite-based catalysts. He has contributed to over 180 publications, supervised 20+ students, and led projects like the EU-funded SPACING initiative for biofuel production. Research interests include porous materials, reaction engineering, and process intensification through structured reactors/catalysts. He chairs the RSC Heterogeneous Catalysis committee and has organized conferences like the International Conference on Environmental Catalysis. His work aligns with UN Sustainable Development Goals, particularly in clean energy and sustainable chemistry. Education: BEng (Environmental Engineering), Jilin Institute of Chemical Technology, 2003 MRes (Chemical Engineering), East China University of Science and Technology, 2006 PhD (Chemical Engineering), University of Bath, 2010 Awards: Lee Hsun Lecture Award (2018) Zhenxing Scholar Professor Award (2018) Outstanding Achievement Recognition (2018) Grants/Projects: SPACING: Sustainable Production of ACrylic Acid from Renewable Waste Glycerol (2021–2024) Labs/Teams: Catalysis and Porous Materials Group at The University of Manchester

Raphael FranziniView profile

Associate Professor

• Drug Discovery
• Medicinal Chemistry
• Bioorthogonal Chemistry
• +3 more

Raphael Franzini serves as Associate Professor of Medicinal Chemistry at the University of Utah, actively contributing to the Biological Chemistry PhD Program. His research pioneers innovative chemical approaches for therapeutic development, with dual focus on DNA-encoded library technologies and bioorthogonal drug delivery systems. His educational foundation includes an M.S. from the Swiss Federal Institute of Technology (Lausanne) and a Ph.D. from Stanford University. This training underpins his group's multidisciplinary methodology combining organic synthesis, bioconjugation, computational modeling, and advanced imaging techniques. Dr. Franzini's research program centers on two transformative areas: First, advancing DNA-encoded library screening through computational integration to identify leads for challenging targets like Tankyrase and Sirtuin 6, with recent work addressing false negatives in machine learning prediction. Second, developing novel bioorthogonal release chemistry using isonitrile-tetrazine reactions for spatiotemporally controlled drug activation, validated in zebrafish models. His group emphasizes both technological innovation and therapeutic translation, with chemistry designed to minimize off-target effects in solid tumors. Analysis of his 15 most recent publications reveals escalating integration of computational methods with experimental library screening, alongside refinement of bioorthogonal release kinetics. The work spans chemical biology, medicinal chemistry, and pharmaceutical sciences, with growing emphasis on machine learning for library data interpretation and in vivo validation of drug-release systems. Dr. Franzini maintains an active research laboratory that provides comprehensive training in cutting-edge drug discovery methodologies. His group culture prioritizes both scientific innovation and researcher development, with projects spanning from fundamental reaction kinetics to therapeutic applications. The lab's infrastructure supports organic synthesis, molecular imaging, and computational analysis for advancing precision therapeutics.

Michael John JanikView profile

Professor

• Density Functional Theory
• Electrocatalysis
• CO2 Reduction
• +7 more

Michael John Janik is a Professor in the Department of Chemical Engineering at Pennsylvania State University, with significant affiliation to the Institute of Energy and the Environment (IEE). His academic profile demonstrates exceptional research productivity with 270 research outputs, 25 funded projects, and substantial scholarly impact reflected in 17,238 citations and an h-index of 61. His research expertise centers on computational chemistry with particular focus on Density Functional Theory applications to catalysis and electrocatalysis. The fingerprint analysis of his work reveals strong concentrations in Density Functional Theory (76%), Oxidation Reactions (36%), Carbon Dioxide research (29%), Adsorption phenomena (27%), and First Principles Chemistry (22%). His work significantly contributes to UN Sustainable Development Goals related to clean energy and climate action. Analysis of his recent publications (2020-2025) reveals a strong research trajectory in electrocatalysis, particularly examining cation effects on CO 2 reduction mechanisms, intermetallic catalyst design, and computational modeling of electrochemical systems. His work bridges fundamental computational chemistry with practical applications in sustainable energy conversion. h-index of 61 17,238 total citations Multiple high-impact publications in journals including Nature Catalysis, Journal of the American Chemical Society, and Science Advances Professor Janik actively leads and collaborates on numerous research projects, particularly with Dr. Rioux and other colleagues, focusing on advanced catalyst development and electrochemical energy conversion systems. His current research portfolio includes multiple active NSF-funded projects extending through 2027 that address critical challenges in electrocatalysis, CO 2 reduction, and intermetallic catalyst design. His research group maintains strong connections with the Institute of Energy and the Environment, positioning his work at the intersection of fundamental computational chemistry and applied energy solutions. Current projects include combining DFT with classical simulations to predict solvation effects, developing high-entropy alloys for catalysis, and studying oxide overlayers in CO 2 reaction systems.

Yiguang JuView profile

Professor

• Energy Engineering
• Environmental Engineering
• Combustion Science
• +4 more

Yiguang Ju is the Robert Porter Patterson Professor of Mechanical and Aerospace Engineering at Princeton University, affiliated with the HMEI Grand Challenges Program. His research focuses on plasma-assisted combustion, alternative fuels, and nano-material synthesis via flame processes. He investigates energy-efficient systems for microscale energy conversion, catalytic reactions, and low-temperature plasma chemistry. Research interests include non-equilibrium plasma dynamics, ammonia synthesis, and high-pressure oxidation kinetics. He develops advanced diagnostics like hybrid laser spectroscopy and machine learning models to study reaction mechanisms. Recent work explores plasma-enhanced combustion for hydrogen and alternative fuels, with applications in energy storage and emission reduction. His studies address challenges in plasma-chemistry interactions, material synthesis, and high-pressure combustion systems. His articles highlight innovations in plasma catalysis, combustion kinetics, and atmospheric chemistry. Collaborative projects include plasma-based material recycling and supercritical-pressure reactor analysis. He leads initiatives in clean energy technologies and sustainable chemical processes.

Mohammadreza KaramadView profile

Assistant Professor

• Electrochemistry
• Heterogeneous Catalysis
• Material Science
• +3 more

Mohammadreza Karamad is an Assistant Professor in the School of Sustainable Energy Engineering at Simon Fraser University (SFU), with a joint appointment in the Sustainable Energy Engineering department. His research focuses on computational materials discovery, leveraging quantum-mechanical methods (e.g., DFT) and machine learning (ML) to design advanced energy materials for clean technologies like hydrogen storage and catalysis. He holds a Ph.D. from the Technical University of Denmark (DTU) and completed postdoctoral research at Stanford University. His academic background includes leadership roles in the CMD Lab (Computational Materials Discovery), where he explores novel materials for electrochemical energy conversion processes. Key research areas include electrochemistry, heterogeneous catalysis, and material science, with a particular emphasis on CO2 reduction, ammonia synthesis, and sustainable energy storage solutions. Dr. Karamad collaborates with industry and academic partners to advance materials discovery through high-throughput computational screening and AI-driven approaches. He actively seeks motivated students (undergraduate and graduate) to join his research program, focusing on developing next-generation energy materials. His lab is located in room B8220, and he can be reached at mkaramad@sfu.ca. Notable technical contributions include pioneering work on transition metal nitrides for CO2 reduction, single-atom catalysts for ammonia synthesis, and machine learning frameworks for predicting material properties. His research bridges fundamental theory with practical applications, addressing global challenges in sustainable energy and environmental technology.

Andreas JentysView profile

Professor

• Catalysis
• Surface Chemistry
• Material Science
• +5 more

Andreas Jentys is a Professor at the Department of Technical Chemistry within the TUM School of Natural Sciences at Technische Universität München (TUM). His research focuses on understanding surface reactions and transport phenomena in mesostructured, micro- and mesoporous oxides with acid/base or redox properties, as well as supported metal catalysts for gas and condensed phase reactions. He prepares materials with tailored functionality and studies their sorptive and catalytic properties using in situ electron and vibrational spectroscopy combined with microkinetic experiments. Education: PhD (Dr. techn.) in Chemistry from TU Wien (1991) Postdoctoral: Royal Institution of Great Britain (1992-1993) with Prof. Richard Catlow Academic Career: TU Wien (1998: Associate Professor), TUM (1999: Senior Scientist; 2011: Professor) Teaching: Active in TUM Asia since 2006 Research interests span catalysis, surface chemistry, material science, and chemical reaction engineering. He specializes in zeolites, bimetallic catalysts, and in situ spectroscopic methods. Recent work examines: Hydrogen evolution and carbon-carbon coupling on Cu Methane activation via Co²⁺ sites in ZSM-5 Photocatalytic systems using metal-organic frameworks Solvent effects in palladium-catalyzed hydrogenation CO₂ hydrogenation over bifunctional catalysts Publications trend toward heterogeneous catalysis, with emphasis on: Design of mesoporous and microporous materials Characterization of metal clusters and oxo species Microkinetic modeling of catalytic systems Environmental applications (NOx/CO₂ reduction) Hydrogen and hydrocarbon processing Teaching includes courses on: Reaction Engineering and Kinetics Industrial Chemical Processes I & II Fundamentals of Catalysis TC Praktikum (internship)

Bart SomersView profile

Associate Professor

• Combustion Engineering
• Alternative Fuels
• Internal Combustion Engines
• +3 more

Bart Somers is an Associate Professor at Eindhoven University of Technology , affiliated with the Department of Mechanical Engineering . His primary affiliations include the Power & Flow Group and his own research group, Group Somers , alongside cross-cutting roles in EAISI (Eindhoven Artificial Intelligence Systems Institute) and EIRES (Eindhoven Research on Innovation and Sustainability in Energy Systems). He focuses on advancing combustion science , sustainable fuels , and engine efficiency , leveraging computational fluid dynamics (CFD) and experimental methods. His research interests span alternative fuels (hydrogen, bio-oils, biofuels), high-pressure spray combustion , and low-emission engine design . He investigates combustion optimization through CFD tools like large-eddy simulation (LES) and flamelet-generated manifolds (FGM), emphasizing fuel stratification , ignition dynamics , and emission control . His work bridges experimental diagnostics (e.g., spray visualization, OH* chemiluminescence) and numerical modeling. Academically, he teaches courses such as Thermodynamics , Clean Engines and Future Fuels , and Sustainable Vehicles , integrating practical projects into curricula. His educational activities emphasize interdisciplinary sustainability and innovation, including honors programs focused on professional development. Recent publications highlight his contributions to hydrogen injection strategies, biofuel applications in genset engines, and optimization of diesel-biofuel blends. His work aligns with global sustainability goals, addressing energy transition challenges through advanced combustion technologies.

Alexander VladimirskyView profile

Professor

• Numerical Analysis
• Applied Mathematics
• Nonlinear PDEs
• +5 more

Roles & Affiliations: Professor of Mathematics at Cornell University, Department of Mathematics. Member of graduate programs in Mathematics, Applied Mathematics, Operations Research and Information Engineering, Theoretical & Applied Mechanics, and Computational Science & Engineering. Co-organizer of the Scientific Computing and Numerics (SCAN) Seminar and founder of the Cornell Mathematical Contest in Modeling. Education: Ph.D. in Applied Mathematics from University of California, Berkeley (2001); B.A. in Applied Mathematics (with high honors) from University of California, Berkeley (1995). Research Interests: Focuses on numerical analysis, nonlinear PDEs, control theory, and dynamical systems. Explores applications in optimal control, front propagation, anisotropy, bifurcation theory, and mathematical biology. Develops methods for invariant manifold approximation, Eikonal equations, and stochastic systems. Recent work includes studies on cancer therapy optimization, surveillance evasion, and pedestrian flow modeling. Teaching: Teaches courses like Introduction to Partial Differential Equations, Differential Games, Numerical Analysis, and Mathematical Modeling. Recent courses include Math 4280 (Spring 2025) and Math 3610 (Fall 2024). Labs/Teams: Active in interdisciplinary collaborations, including work on computational biology, robotics path planning, and mathematical contest problem-solving initiatives.

Makhlouf M. MakhloufView profile

Professor

• Physical Metallurgy
• Materials Processing
• Solidification of Metals
• +4 more

Makhlouf M. Makhlouf is a Professor of Mechanical & Materials Engineering at Worcester Polytechnic Institute (WPI). He served as Director of the Advanced Casting Research Center (ACRC) from 1992 to 2015, leading it to become the world's leading foundry-industry consortium. His expertise spans physical metallurgy, materials processing, and nanocomposite development. He holds 5 US/European patents and has authored over 150 papers. Education : BS (High Honors), American University in Cairo, 1978 MS, Mechanical Engineering, New Mexico State University, 1980 PhD, Materials Science & Engineering, WPI, 1990 Research Interests : Makhlouf focuses on developing high-performance alloys (e.g., aluminum alloys for high-temperature applications), solidification processes, and metal-matrix nanocomposites via methods like RIGLI. His work integrates thermodynamics, kinetics, and heat/mass transfer modeling for materials engineering challenges. Articles Overview : His recent publications address topics like aluminum alloy precipitation strengthening (2017), gas-liquid synthesis of nanocomposites (2017), and casting process optimization (2017). These contributions emphasize practical applications in foundry and aerospace sectors. Grants & Advising : He has directed federally/non-federally funded projects, mentored 10 PhD students, 20 MS students, and 8 postdoctoral fellows. His work bridges academic research and industrial collaboration. Labs/Teams : He leads research through WPI's ACRC and collaborates with industry partners to advance foundry technologies and nanocomposite manufacturing.

Joseph DumplerView profile

Lecturer

• Food Engineering
• Dairy Science and Technology
• Sustainable Food Processing
• +4 more

Dr. Joseph Dumpler is a Lecturer at the Department of Health Sciences and Technology at ETH Zürich, specializing in Sustainable Food Processing. He holds a PhD in Dairy Science and Technology from the Technical University of Munich, Weihenstephan, with a focus on UHT treatment of concentrated milk. His work emphasizes advancing food processing technologies, particularly in protein refinement, non-thermal methods, and membrane filtration. Educations: PhD in Dairy Science and Technology, Technical University of Munich, Weihenstephan (2017) MSc Food Engineering, Technical University of Munich, Weihenstephan His research interests include Natural Deep Eutectic Solvents (NADES) for plant protein extraction, microwave vacuum drying of dairy products, and membrane filtration optimization for microalgae and dairy systems. He has pioneered methods to refine rapeseed and pea proteins while minimizing antinutrients, and his work on microfiltration of milk products addresses emerging microbial risks. Key contributions span kinetic modeling of heat-induced protein aggregation, sustainable food processing , and non-thermal concentration techniques . His articles reflect a focus on bridging lab-scale innovations with industrial applications. Awards: J.T.M. Wouters Young Scientist Award Julius Maggi Research Award (2018) Best PhD Thesis Award from the Association of Dairy, Food and Biotechnologists (Weihenstephan) Dr. Dumpler collaborates with industry partners to translate research into scalable processes, such as NADES-based protein extraction and microwave drying systems. His current role at ETH Zürich’s Sustainable Food Processing Lab (Prof. Mathys) focuses on plant-based meat analogs and novel protein refining concepts .

Vishnu PareekView profile

Professor

• Multiphase Flow Modelling
• Computational Fluid Dynamics
• Flow Assurance
• +7 more

Professor Vishnu Pareek is the John Curtin Distinguished Professor at Curtin University, leading the Western Australian School of Mines (WASM) within the Faculty of Science and Engineering. He has held academic roles including Dean of Engineering, Head of School, and various professorships since 2002. His research focuses on multiphase flow modeling, computational fluid dynamics, and reactor engineering, with applications in energy and chemical processes. He holds a BE (Hons) from MNIT, MTech from IIT Delhi, and a PhD from UNSW. Key research interests include LNG process modeling, erosion modeling, and granular flow dynamics. He has authored over 200 peer-reviewed publications, with recent work emphasizing structured packing design, biomass gasification, and additive manufacturing for process intensification. Notable projects include CFD-ANN hybrid models for fluidized beds and experimental studies on 3D-printed structured packings. His expertise spans industrial collaborations in LNG safety, fluid catalytic cracking, and biofuel production. Teaching areas include chemical engineering fundamentals and process systems engineering. He advises on energy policy and leads research teams in multiphase flow and reactor design.

Nadia ShardtView profile

Associate Professor

• Interfacial thermodynamics
• Phase behavior with curvature
• CO2 storage in subsurface reservoirs
• +9 more

Nadia Shardt is an Associate Professor in the Department of Chemical Engineering at the Norwegian University of Science and Technology (NTNU). Her research focuses on interfacial thermodynamics, particularly in systems with nanoscale curvature, with applications spanning atmospheric science, biomedical cryopreservation, and industrial process optimization. She contributes to teaching courses such as TKP4580 - Chemical Engineering Specialization Project and KP3100 - Chemical Engineering . PhD in Chemical Engineering (University of Alberta, 2019) BSc in Chemical Engineering (University of Alberta, 2015) Postdoctoral researcher at ETH Zurich (2020-2022) Her work addresses fundamental challenges in phase behavior under curvature constraints, combining microfluidic experimentation , Gibbsian thermodynamic modeling , and machine learning techniques to study systems like CO 2 storage media, cloud microphysics, and food emulsions. Recent publications emphasize surface tension modeling for complex multi-component systems and cryoprotectant loading efficiency. Scientific awards include the ETH Postdoctoral Fellowship Natural Sciences and Engineering Research Council of Canada (NSERC) Postdoctoral Fellowship Outstanding Academic Fellows Programme 2024-2028