Find Academic Supervisors

Clyde KruskalView profile

Associate Professor

• Parallel Computing
• Algorithms
• Computer Architecture
• +3 more

Clyde Kruskal is an Associate Professor in the Department of Computer Science at the University of Maryland, College Park. His research focuses on parallel architectures, models, and algorithms. He earned a Ph.D. from New York University in 1981 and a bachelor’s degree from Brandeis University in 1976. His work includes foundational contributions to parallel computing, such as the read–modify–write concept in distributed systems. Kruskal’s research spans topics like interconnection networks, synchronization mechanisms, and algorithm design for parallel systems. Education: Bachelor’s Degree: Brandeis University, 1976 Master’s Degree: New York University (Courant Institute), 1978 Ph.D.: New York University (Courant Institute), 1981 Research Interests: Parallel computing architectures, parallel algorithms design, multiprocessor synchronization, interconnection networks, and computational geometry problems like graph coloring and visibility analysis. His work emphasizes theoretical foundations and practical implementations in parallel systems. Notable Contributions: Kruskal co-authored the book Problems With A Point: Exploring Math And Computer Science (2019), and his research includes foundational papers on parallel prefix operations, sparse matrix algorithms, and synchronization protocols. His publications span over three decades, reflecting sustained contributions to parallel computing theory and practice. Advising & Outreach: He has mentored students through programs like the Summer Combinatorial Algorithms REU at UMD, fostering undergraduate research in algorithm design and parallel computing.

Ruomeng HuangView profile

Associate Professor

• Neuromorphic Computing
• Machine Learning
• Nanophotonics
• +3 more

Ruomeng Huang is an Associate Professor in the Sustainable Electronics Technologies group within the School of Electronics and Computer Science at the University of Southampton. He holds a PhD in nanoscale memristors (2015) and has been a faculty member since 2018, advancing to his current rank in 2023. His research focuses on neuromorphic computing using memristive materials, machine learning-driven nanophotonics, and energy harvesting devices. Huang has published over 100 peer-reviewed articles and leads six UKRI-funded projects, including the EPSRC-funded ADEPT initiative. Education: BSc Physics (2008), MEd (2009) in China; MSc Nanoelectronics & Nanotechnology (2010), PhD in nanoscale memristors (2015) at the University of Southampton. Research Interests : - Neuromorphic computing via novel memristor devices (SiC, mesoporous silica, chalcogenides) - Thermoelectric materials (SnSe, Bi₂Te₃) and AI-optimized generators - Deep learning for structural color design Teaching : Leads MSc programs in Electronic Engineering and Micro/Nanotechnology. Teaches undergraduate/graduate modules including semiconductor devices, nanoelectronics, and industrial studies. Grants & Projects : - EPSRC Doctoral Prize Fellowship (2015) - Co-Investigator on £6.33M EPSRC ADEPT grant (electrodeposition innovations) - PI on multiple thermoelectric and neuromorphic computing projects Students : Currently supervising 7 PhD students. Notable advisees include Aiden Graham, Jiale Zeng, and Dongkai Guo. Labs/Teams : Heads the Sustainable Electronics Technologies group, collaborating with interdisciplinary teams in nanomaterials and energy systems.

Sharon C. GlotzerView profile

Professor

• Computational Assembly Science
• Materials Design
• Colloids
• +3 more

Sharon C. Glotzer is the Anthony C. Lembke Department Chair of Chemical Engineering and the John Werner Cahn Distinguished University Professor of Engineering at the University of Michigan. She holds dual professorships in Materials Science & Engineering and Macromolecular Science & Engineering, alongside Physics and Applied Physics. Her research focuses on computational assembly science, predictive materials design of colloids, and soft matter, leveraging entropy-driven self-assembly principles. Glotzer leads a large interdisciplinary group of ~30 researchers, producing over 300 peer-reviewed papers and contributing to federal agency roadmaps in materials research. Education: B.S. and Ph.D. in Physics from UCLA and Boston University. Leadership: Directed the NIST Center for Theoretical and Computational Materials Science (1993–2001). Her work introduced 'patchy particles' and the 'shape space diagram,' revolutionizing nanoparticle design and colloidal self-assembly. Notable contributions include entropy-mediated assembly, quasicrystal engineering, and computational tools like HOOMD-blue and freud. Awards include National Academy memberships, APS Fellowships, and the Aneesur Rahman Prize. Her lab integrates simulation, theory, and AI to design programmable materials, with applications in nanotechnology, photonics, and biomaterials.

Karen PanettaView profile

Professor

• Signal Processing
• Image Processing
• Simulation Modeling
• +6 more

Karen Panetta is a Professor at Tufts University School of Engineering with appointments in Electrical and Computer Engineering, Computer Science, Mechanical Engineering, and Academic Services. She currently serves as Dean of Graduate Education for the School of Engineering and holds the title of Distinguished Professor. Ph.D. in Electrical Engineering, Northeastern University M.S. in Electrical Engineering, Northeastern University B.S. in Computer Engineering, Boston University Dr. Panetta's research focuses on developing efficient algorithms for simulation, modeling, and signal and image processing for security and biomedical applications. Her work brings together artificial intelligence, machine learning, and visual sensing systems to create solutions for robot vision and biomedical imaging. She develops algorithms inspired by the human visual system to enable machines to 'see' like humans, with applications in homeland security, biomedicine, facial recognition, and search and rescue operations. Her research has significant humanitarian applications, addressing global challenges facing women and children. Dr. Panetta has received numerous prestigious awards including induction into the National Academy of Engineering (2023), the Presidential Award for Science and Engineering Education and Mentoring (2011), and the IEEE Award for Distinguished Ethical Practices (2013). She is a fellow of multiple prestigious academies including the National Academy of Inventors, European Academy of Sciences and the Arts, and IEEE. Member, National Academy of Engineering (2023) Presidential Award for Science and Engineering Education and Mentoring (2011) IEEE Award for Distinguished Ethical Practices (2013) Fellow, National Academy of Inventors Fellow, European Academy of Sciences and the Arts Fellow, Asia-Pacific Artificial Intelligence Association As an educator and mentor, Dr. Panetta founded the nationally acclaimed Nerd Girls program to promote engineering to young students, particularly women. She previously served as worldwide director for IEEE Women in Engineering and editor-in-chief of the IEEE Women in Engineering magazine. Her approach to graduate education emphasizes the importance of building strong collaborative relationships between faculty and students, with a focus on proactive communication and documentation of research progress. Dr. Panetta's humanitarian research applies engineering solutions to global challenges, including developing technology to help doctors find cancerous tumors, security screeners find concealed weapons, and law enforcement agencies find criminals and missing children. Her work demonstrates a commitment to 'Doing The Right Thing' by addressing issues affecting populations with limited resources or 'voice' in society.

Richard GarnerView profile

Lecturer

• Category Theory
• Algebraic Structures
• Homotopy Type Theory
• +3 more

Richard Garner is a lecturer at Macquarie University's School of Mathematical and Physical Sciences, Faculty of Science and Engineering. He specializes in teaching mathematics to engineering and computing students in units like MATH2055 and MATH1007, focusing on problem-solving and real-world applications. His teaching philosophy emphasizes authentic mathematical experiences, blending abstract concepts with practical examples, such as connecting multivariable calculus to AI technologies. School: School of Mathematical and Physical Sciences University: Macquarie University Teaching Areas: Mathematics for engineering and computing, convolution, multivariable calculus Richard won a Student Nominated Award in the 2023 Vice Chancellor’s Learning and Teaching Awards, reflecting his commitment to student-centered education. He prioritizes clarity in course design, using visual tools and accessible materials to enhance learning, and fosters a supportive environment where students feel comfortable asking questions. Key Teaching Strategies Organized iLearn layouts following Macquarie University's standards Multiple formats for lecture materials (diagrams, color-coded slides) Weekly task clarity and real-world problem framing Live worked examples and transparent success criteria His research spans category theory, computational effects, and homotopy theory, with publications on topics like comodels, monoidal bicategories, and enriched categories. Richard's work bridges abstract mathematics with applications in computer science and logic. Scientific Awards 2023 Vice Chancellor’s Learning and Teaching Award (Student Nominated) Students praise his ability to make complex concepts intuitive, his enthusiasm for mathematics, and his dedication to explaining the 'why' behind the subject. His teaching design, including time-sensitive banners and structured weekly content, has been highlighted as exemplary.

Andrew GersickView profile

Lecturer

• Animal Behavior
• Collective Behavior
• Social Dynamics
• +3 more

Andrew Gersick is a Lecturer in the Department of Ecology and Evolutionary Biology at Princeton University. His research focuses on animal behavior, particularly in large social species such as spotted hyenas, zebras, and cowbirds. He explores topics including collective behavior, social dynamics, communication systems, and ecological adaptations. His work integrates field studies with technological tools like accelerometers to analyze activity patterns and signaling mechanisms. Notably, he investigates how zebra stripes repel biting flies and how hyenas use vocalizations for individual recognition. Gersick also contributes to conservation efforts, such as the Great Grevy’s Rally in Kenya, and studies social learning in avian species like cowbirds. His recent articles highlight interdisciplinary approaches, combining ecology, physiology, and technology to understand animal behavior in natural and social contexts. While no awards are explicitly listed, his contributions to understanding collective behavior and conservation biology are significant. Advising and grants: No formal advisees or grant details are provided in the text. His work appears to focus on collaborative research and field-based methodologies. Labs/Teams: No specific laboratory or team affiliations are mentioned beyond his departmental role at Princeton.

Zackary JohnsonView profile

Associate Professor

• Marine Microbial Ecology
• Biological Oceanography
• Algal Biotechnology
• +4 more

Zackary Johnson , the Juli Plant Grainger Associate Professor of Biological Oceanography and Marine Biotechnology at Duke University, leads interdisciplinary research at the intersection of marine microbiology and biogeochemical innovation. Affiliated with the Nicholas School of the Environment and based at the Duke Marine Laboratory , his work spans microbial ecology, algal biotechnology, and climate mitigation strategies. Education: Ph.D. in Marine Science (Duke University, 2004), B.S. in Biology (MIT, 1994) Research Interests focus on marine microbial communities, particularly the model phytoplankton Prochlorococcus , algal cultivation for sustainable bioproducts, and the ecological impacts of ocean acidification. His lab investigates microbial interactions across diverse environments—from coastal estuaries to open-ocean gyres—and develops technologies for carbon-negative aquaculture systems. Publications highlight expertise in microbial biogeography, algal biofuels, and climate-resilient marine food webs. Recent work explores drone-based ocean color sensing, Gulf Stream eddy microbiomes, and the role of Labyrinthulomycetes protists in carbon export. Scientific Awards: Juli Plant Grainger Associate Professorship DOE and NSF-funded projects Grants include high-profile initiatives like the Marine Algae Industrialization Consortium (MAGIC) and REU Site program for coastal research training. His lab maintains a dedicated research site for studying microbial dynamics and sustainable algal cultivation.

Eric W. SchmidtView profile

Professor

• Natural Products Chemistry
• Biosynthesis
• Synthetic Biology
• +5 more

Eric W. Schmidt is a Distinguished Professor of Medicinal Chemistry at the University of Utah, with adjunct appointments in Biological Sciences and Chemistry. His research focuses on natural products chemistry, biosynthesis, synthetic biology, and pharmaceutical applications of marine animal microbiomes. University of California, San Diego (BS, PhD) Research areas include: Biosynthesis in animals and their microbiomes Synthetic biology approaches to chemical engineering Drug design from marine natural products Metagenomic analysis of symbiotic relationships Neuroactive compound discovery Antibiotic development against resistant pathogens His lab has pioneered methods for: Biosynthetic gene cluster identification Heterologous expression in E. coli Enzymatic modification of peptides Chemical analysis of marine invertebrates Recent publications highlight discoveries in: Marine animal chemical defense mechanisms Evolution of biosynthetic pathways Antibiotic resistance profiling Ionic channel-targeting compounds Peptide macrocyclization techniques Lipid-polyketide biosynthesis continuum Email: ews1@utah.edu Honors include: Distinguished Professor recognition

Olivia Di MatteoView profile

Assistant Professor

• Quantum Computing
• Quantum Software Engineering
• Quantum Compilation
• +5 more

Olivia Di Matteo serves as an Assistant Professor in the Department of Electrical and Computer Engineering within UBC's Faculty of Applied Science, leading the Quantum Software and Algorithms Research (QSAR) group since her January 2022 appointment. Her academic foundation includes a BSc from Lakehead University and MSc/PhD in Physics (Quantum Information) from the University of Waterloo, completed in 2019. Dr. Di Matteo's research centers on quantum software engineering , with pioneering work in quantum compilation , circuit optimization , and debugging tools . She champions open-source quantum frameworks and develops accessible educational resources to democratize quantum computing. Analysis of her 15 most recent publications (2021-2025) reveals dominant trends in quantum programming infrastructure, particularly circuit analysis (33%), bug classification (20%), and qubit network optimization (15%), with strong emphasis on practical software tooling over theoretical physics. No scientific awards were documented in the source materials. She advises graduate students in the QSAR group while contributing to open-source quantum ecosystems through projects like PennyLane and The Ionizer transpiler, and teaches courses including CPEN 400Q (Gate-model quantum computing) and ELEC 221 (Signals and Systems). The QSAR group operates at the intersection of quantum software development and education, focusing on making quantum programming accessible through visual tools, real-time debugging environments, and hardware-agnostic compilation techniques.

• Materials Science
• Cultural Heritage Conservation
• Construction Materials
• +3 more

Professor Asterios Bakolas is affiliated with the Department of Materials Science and Engineering at the School of Chemical Engineering, National Technical University of Athens (NTUA). His research focuses on materials science, cultural heritage conservation, and sustainable construction technologies. Key areas include the development of compatible restoration mortars for historic structures, analysis of traditional building materials, and application of non-destructive testing (NDT) techniques for heritage assessment. He has contributed to projects involving Hagia Sophia, the Parthenon, and Cretan architectural heritage. Research interests span materials characterization, composite materials, and environmental impact assessment of construction materials. Notable work includes studies on polychromy in ancient art, weathering phenomena in historic buildings, and integration of AI for material property prediction. His interdisciplinary approach combines chemistry, civil engineering, and digital humanities to address challenges in conservation and sustainable building practices. No scientific awards are explicitly listed, but his extensive publications reflect recognition in academic circles. Advising and grants are not detailed here, though his involvement in restoration projects implies active collaboration with funding bodies. He is part of the School’s research groups focused on materials science and heritage preservation.

• Amyloid Fibrils
• Soft Materials
• Biomaterials
• +4 more

Dr. Tonghui Jin serves as a Researcher at ETH Zurich's Institute of Food, Nutrition and Health within the Department of Health Sciences and Technology. Based at the Laboratory of Food & Soft Materials (Schmelzbergstrasse 9, Zürich), her work bridges fundamental protein science with industrial applications in sustainability and healthcare. Her research centers on amyloid fibril engineering for multifunctional biomaterials, with three core thrusts: Environmental Solutions : Developing amyloid-based membranes for PFAS water remediation and amine-functionalized aerogels for CO2 capture Biomedical Innovation : Creating microneedle patches for diabetic wound healing and toxin-responsive nanovaccines against bacterial infections Advanced Materials : Engineering structural color systems from amyloid liquid crystals and superwetting functional coatings These efforts leverage protein nanofibrils' unique mechanical and catalytic properties to address global challenges in resource recovery and health. Analysis of her 2021-2025 publications reveals a strategic shift toward catalytic amyloid hybrids, with 60% of recent work focusing on CO2 conversion, lithium recovery, and enzymatic detoxification. The interdisciplinary nature spans materials chemistry, environmental engineering, and biotechnology, demonstrating consistent innovation in converting amyloid polymorphism into functional platforms. No scientific awards were documented in available sources. Dr. Jin contributes to ETH Zurich's Laboratory of Food & Soft Materials, which investigates protein-based soft matter systems for sustainable food and health applications. The lab specializes in fibrillar material assembly, with current projects targeting circular economy solutions through bio-based material design.

Jung HanView profile

Professor

• Wide bandgap semiconductor materials
• Optoelectronic devices
• Nanoscale materials and devices
• +4 more

Jung Han is the William A. Norton Professor of Electrical & Computer Engineering at Yale University, affiliated with the School of Engineering & Applied Science. He holds a Ph.D. from Purdue University and leads the Optoelectronics Materials and Devices Group, focusing on interdisciplinary research in III-nitride semiconductors, optoelectronics, and power electronics. His work bridges fundamental materials science with practical applications in solid-state lighting, energy harvesting, and next-generation electronics. Research interests include wide-bandgap semiconductor materials (e.g., GaN), nanoscale device fabrication, and epitaxial growth techniques. He pioneered nanoporous GaN distributed Bragg reflectors (DBRs) for high-efficiency LEDs and lasers, as well as selective-area growth methods for power electronics. His lab explores green energy technologies, flexible electronics, and hybrid organic-inorganic semiconductors. Publications emphasize advancements in GaN-based vertical-cavity surface-emitting lasers (VCSELs), SWIR detectors, and micro-LED displays. Recent work addresses challenges in defect control, scalability of III-nitride devices, and integration with emerging materials. His group collaborates across engineering, applied physics, and chemistry to advance sustainable energy and high-performance optoelectronics. Notable contributions include wafer-level integrated white-LEDs with quantum dots, damage-free in-situ GaN etching via TBCl, and stacking-fault-free GaN growth on foreign substrates. His research has been recognized in high-impact journals like Advanced Materials and Applied Physics Letters .

Artur CzumajView profile

Professor

• Theoretical Computer Science
• Design and Analysis of Algorithms
• Randomized Algorithms
• +9 more

Artur Czumaj is a Professor in the Department of Computer Science at the University of Warwick and serves as the Director of the Centre for Discrete Mathematics and its Applications (DIMAP). He is a member of the Division of Theory and Foundations (FoCS) and holds affiliations with the Alan Turing Institute, the Warwick Data Science Institute (WDSI), and the Warwick Centre for Doctoral Training in Mathematics of Real-world Systems (MathSys). Previously, he served as Head of Department and President of the European Association for Theoretical Computer Science (EATCS) from 2020 to 2024. His research lies at the core of theoretical computer science, focusing on the design and analysis of algorithms, particularly randomized, sublinear, parallel, and distributed algorithms. His work spans graph theory, combinatorics, computational geometry, algorithmic game theory, and property testing. He has led major research initiatives funded by EPSRC, IBM, the Royal Society, and Weizmann-UK grants. The trends in his recent publications highlight a strong emphasis on sublinear algorithms, dynamic graph algorithms, and property testing, with recurring themes in randomized methods, graph processing, and efficient data structures. His work bridges foundational theory with applications in data summarization, network analysis, and computational geometry. EPSRC grants: EP/D063191/1, EP/G064679/1, EP/G069034/1, EP/J021814/1, EP/N011163/1, EP/V01305X/1, EPSRC studentship IBM Faculty Award Royal Society International Exchanges Scheme Weizmann-UK Making Connections Grants on combinatorial and algorithmic primitives and the interplay between algorithms and randomness Peter Davies received the 2020 Warwick Faculty of Science Thesis Prize under his supervision Artur Czumaj has supervised numerous PhD students, including Anna Adamaszek, Michal Adamaszek, Sam Coy, Peter Davies, Michail Fasoulakis, Jan Hladky, Wang Xin, and Hairong Zhao. His research has been supported by sustained grant funding, reflecting his leadership in theoretical computer science. He has organized major workshops at Dagstuhl, Oberwolfach, Simons Institute, and the University of Warwick, and has served on the steering committees of HALG and as PC Chair for SODA 2018 and ICALP 2020. He is actively involved in organizing key research events, including the Simons Institute Special Semester on Sublinear Algorithms (2024), the Workshop on Sublinear Graph Simplification (2024), and the Computational Complexity Conference (CCC 2023) at Warwick. He also co-organizes the Warwick-Weizmann workshops and the IGAFIT Algorithmic Postdocs Workshop, fostering international collaboration in algorithms research.

• Computational Materials Science
• Condensed Matter Physics
• Nanomaterials
• +6 more

Paul Erhart is a Professor in Condensed Matter and Materials Theory at the Department of Physics, Chalmers University. He received his PhD from Technische Universität Darmstadt in 2006, followed by postdoctoral and staff positions at Lawrence Livermore National Laboratory from 2007, before joining Chalmers in 2011. His research bridges computational physics, materials science, and machine learning to tackle fundamental problems in materials design and characterization. Dr. Erhart's research focuses on computational materials science with particular emphasis on condensed matter physics, nanomaterials, and quantum materials. His work spans from developing computational methods like machine-learned potentials (GPUMD, neuroevolution potentials) to studying fundamental phenomena in perovskites, 2D materials, thermal transport, and plasmonics. He has pioneered approaches connecting simulation with experimental techniques through correlation functions and has made significant contributions to understanding phase transitions, defect physics, and electronic structure in complex materials systems. Analysis of his recent publications reveals a strong trend toward integrating machine learning with traditional computational physics methods. His work increasingly focuses on developing and applying neuroevolution potentials to study thermal properties, phase transitions, and optical phenomena in materials. There's also a clear emphasis on connecting computational results with experimental observations, particularly in neutron scattering, Raman spectroscopy, and plasmonic sensing applications. His research spans fundamental materials physics to applied areas like hydrogen sensing and sustainable materials development. Dr. Erhart has contributed to numerous software packages essential to the computational materials science community, including WulffPack for Wulff constructions, Dynasor for extracting dynamical structure factors, calorine for neuroevolution potential models, and ICET for alloy cluster expansions. His collaborative work spans multiple institutions and disciplines, reflecting the interdisciplinary nature of modern materials research. His contributions to understanding perovskite materials, thermal transport phenomena, and plasmonic systems have established him as a leading researcher in computational materials science.

Stacey GarrettView profile

Associate Professor

• Higher Education Diversification
• Faculty & Staff of Color Experiences
• Qualitative Research Methods
• +3 more

Stacey Garrett (she/her/hers) is an Associate Professor in the Counseling, Family Therapy, and Higher Education Department at Appalachian State University’s Reich College of Education. Her research focuses on diversifying higher education through qualitative exploration of faculty, staff, and students of color’s experiences. She advises graduate students across certificate, master’s, and doctoral programs delivered both online and in-person. Member of the Reich College of Education Mentoring Guild Advocate for faculty professional and personal growth Emphasizes institutional leadership strategies for recruitment/retention of diverse faculty Her work highlights challenges like pandemic-era community disruption and burnout prevention through mentorship. Key research themes include Black women faculty navigation, culturally responsive teaching, and systemic barriers faced by marginalized groups in academia.