جست‌وجوی استاد و پژوهشگر

Benjamin Grimmerمشاهده پروفایل

استادیار

• Continuous Optimization
• Algorithms for Machine Learning
• Adversarial Optimization
• +۳ مورد دیگر

Benjamin Grimmer is an Assistant Professor in the Department of Applied Mathematics and Statistics at Johns Hopkins University. He is affiliated with the Mathematical Institute for Data Science (MINDS) and the Data Science & AI Institute. His research focuses on designing and analyzing algorithms for continuous optimization, particularly in nonconvex, nonsmooth, and adversarial settings. Grimmer’s work bridges classical optimization theory and modern machine learning challenges, leveraging computer-assisted proof techniques to advance algorithmic foundations. He earned his PhD in Operations Research from Cornell University, advised by Jim Renegar and Damek Davis. His doctoral work was supported by a National Science Foundation fellowship. Grimmer has held research positions at Google and the Simons Institute, exploring adversarial optimization and continuous-discrete optimization interfaces. His current work is supported by the Air Force Office of Scientific Research and a 2024 Alfred P. Sloan Fellowship. Research interests include algorithm design for stochastic/nonconvex/nonsmooth optimization, computer-aided proof methods, and meta-optimization tools like stepsize schedules. His recent studies, including work on gradient descent acceleration via long steps, were highlighted in Quanta Magazine (2023). Education: PhD in Operations Research, Cornell University (advisor: Jim Renegar and Damek Davis) Awards: Alfred P. Sloan Fellowship in Mathematics (2024) National Science Foundation Graduate Fellowship (PhD support) Dr. Grimmer advises a research group including PhD candidates Ning Liu, Thabo Samakhoana, Alan Luner, Yue Wu, and others. His lab explores optimization algorithms through both theoretical and applied lenses, collaborating closely with industry and academic partners.

Paul G Dupuisمشاهده پروفایل

استاد

• Probability Theory
• Stochastic Processes
• Control Theory
• +۴ مورد دیگر

Paul G Dupuis is the IBM Professor of Applied Mathematics at Brown University. His research focuses on applications of probability theory, stochastic processes, control theory, and numerical methods. He holds affiliations with the American Mathematical Society, Society for Industrial and Applied Mathematics (SIAM), and the Institute for Mathematical Statistics (IMS). His work emphasizes large deviation theory, Markov chain approximations, Monte Carlo simulation, and partial differential equations. Education: Ph.D. in Applied Mathematics from Brown University (1985), M.S. from Northwestern University (1982), and B.S. from Brown University (1981). Research Interests: Control of deterministic and stochastic processes, differential games, numerical methods, operations research, and stochastic processes. His contributions include foundational work on large deviation theory, risk-sensitive control, and queueing networks. Awards: Elected SIAM Fellow (2010), Fellow of the Institute for Mathematical Statistics (2011), IBM Professor of Applied Mathematics (2012), and AMS Fellow (2014). Previously held an NSF Postdoctoral Fellowship (1985-1988). Grants: Current funding from the Army Research Office and National Science Foundation. Key collaborations include work on stochastic approximation, constrained diffusions, and reflected Brownian motion. Teaching: Courses include Operations Research: Probabilistic Models, Information Theory, and Advanced topics in Probability and Stochastic Control.

Andrew B. Bocarslyمشاهده پروفایل

استاد

• Catalysis
• Synthesis
• Inorganic Chemistry
• +۴ مورد دیگر

Andrew B. Bocarsly is a Professor of Chemistry at Princeton University, affiliated with the Department of Chemistry within the Faculty of Arts and Sciences. His research focuses on physical inorganic chemistry, catalysis, materials science, and CO₂ conversion. He leads the Bocarsly Lab, which explores electrochemical and photochemical methods to convert CO₂ into fuels and valuable chemicals, emphasizing heterogeneous catalysts and novel materials like cyanogels. His work intersects with sustainability and energy applications, supported by collaborations with institutions like the Andlinger Center for Energy and the Environment. Research Interests: - Development of catalysts for CO₂ reduction to multi-carbon species - Electrocatalytic and photocatalytic mechanisms using transition metal complexes - Low-temperature synthesis of alloys and semiconductors via cyanogel systems - Design of photoelectrochemical systems for solar energy conversion Recent trends in his publications highlight advancements in catalyst design (e.g., Ni-enhanced oxides, manganese complexes), CO₂-to-CO/1-butanol conversion, and semiconductor materials for hydrogen evolution. His lab actively mentors students, with notable graduates like Andersen Dimon and Rebecca Evans. Collaborations extend to Princeton’s Materials Institute and the Electrochemical Society. Labs/Teams: The Bocarsly Lab operates in Frick Chemistry Laboratory, emphasizing interdisciplinary approaches to energy sustainability. Recent activities include hosting the 19th International Conference on Carbon Dioxide Utilization (2022) and fostering undergraduate and graduate research programs.

Nur Zincir-Heywoodمشاهده پروفایل

استاد

• Cyber Security
• Resilience
• Autonomous Cyber Operations
• +۹ مورد دیگر

Nur Zincir-Heywood is a Distinguished Research Professor and Associate Dean (Research) in the Faculty of Computer Science at Dalhousie University, Halifax, Nova Scotia, Canada. She has been a Full Professor since 2010, following progressive academic appointments from Assistant to Associate Professor. Her research centers on developing intelligent and secure systems for modeling and analyzing behaviors across networks and services. Key areas include: Cyber Security and Resilience Autonomous Cyber Operations Threat Analysis and Detection Machine Learning and Big Data Analytics Computer Communications and Networks Her recent recognition as a Distinguished Research Professor reflects her significant contributions to research and scholarship. She leads the NIMS Lab and is actively involved in research clusters focused on Systems, Big Data Analytics, AI, and Machine Learning. She also co-organized the 'Dal FCS Hands on Security Day' with industry partners like Cisco and 2Keys. A special issue she is involved with in IEEE TNSM on AI for network and service management highlights her leadership in cutting-edge domains. Scientific awards include: Distinguished Research Professor (2021–present) She advises students and leads research projects, with fellowship opportunities currently available in her lab. Her work bridges academic innovation with real-world applications in security and intelligent systems. She is also engaged with public outreach, occasionally appearing on CBC Information Morning.

• Theoretical Computer Science
• Error-Correcting Codes
• Approximation Algorithms
• +۵ مورد دیگر

Venkatesan Guruswami is a Chancellor's Professor in the Department of EECS and a Senior Scientist at the Simons Institute for the Theory of Computing at UC Berkeley . He also holds a Professor position in the Department of Mathematics . His academic journey began with a B.Tech in Computer Science from the Indian Institute of Technology, Madras (1997) , followed by a Ph.D. in Computer Science from the Massachusetts Institute of Technology (2001) . After a Miller Research Fellowship at UC Berkeley (2001–02), he held faculty roles at the University of Washington and Carnegie Mellon University before returning to UC Berkeley in January 2022. Education : B.Tech, IIT Madras (1997) Ph.D., MIT (2001) Professional Affiliations : Chancellor's Professor, UC Berkeley (EECS) Senior Scientist & Interim Director, Simons Institute Professor, UC Berkeley (Mathematics) Guruswami's research spans multiple domains within Theoretical Computer Science , focusing on Error-Correcting Codes , Approximation Algorithms , Randomness in Computing , Probabilistically Checkable Proofs , and Computational Complexity . His groundbreaking work in List Decoding has enabled codes with minimal redundancy for correcting worst-case errors, while recent advancements include Polar Codes , Deletion-Correcting Codes , and Constraint Satisfaction Problems . He has also contributed to Quantum Coding Theory , Locally Recoverable Codes , and Approximation Hardness in various computational contexts. His publications reflect a deep engagement with interdisciplinary topics. Key trends include: Quantum Information Theory : Quantum LDPC codes, transversal gates, and quantum storage. Algebraic Coding : Reed-Solomon codes, AG codes, and polynomial-based constructions. Computational Complexity : Hardness of approximation, CSPs, and parameterized intractability. Data Transmission : Polar codes, deletion channels, and feedback mechanisms. Algorithmic Techniques : Spectral methods, semirandom models, and Lasserre hierarchy applications. Guruswami has received numerous accolades, including the Simons Investigator Award , Presburger Award , Packard Fellowship , Sloan Research Fellowship , ACM Doctoral Dissertation Award , and the IEEE Information Theory Society Paper Award . He is an ACM Fellow (2017) and IEEE Fellow (2019) , with recent honors like the Guggenheim Fellowship (2023) and AMS Fellow (2023) . As an advisor, he has mentored over 25 PhD and postdoctoral researchers , including Atri Rudra , Prasad Raghavendra , and Peter Manohar , whose work has won awards like the Edmund M. Clarke Doctoral Dissertation Award and CRA Outstanding Undergraduate Researcher Award . His research is supported by grants from the National Science Foundation , Packard Foundation , and Sloan Foundation . He also serves as Editor-in-Chief of the Journal of the ACM and holds leadership roles in IEEE and arXiv moderation. Guruswami is actively involved in Simons Institute programs and co-organized workshops on Coded Computation and Information Theory . His work bridges theoretical advancements with practical applications in Cloud Storage , Quantum Computing , and Group Testing , including pandemic-era contributions like AC-DC: Amplification Curve Diagnostics for SARS-CoV-2 .

Norman Sadehمشاهده پروفایل

استاد

• cybersecurity
• online privacy
• Human-AI Interaction
• +۱۱ مورد دیگر

Norman Sadeh is a Professor in the School of Computer Science at Carnegie Mellon University (CMU), where he has made significant contributions to cybersecurity, privacy, and AI research. He has co-founded and co-directed several groundbreaking graduate programs at CMU, including the Privacy Engineering Program (2012-present), the Ph.D. Program in Societal Computing (2003-2013), and the MBA track in Technology Strategy and Product Management (2005-2017). Carnegie Mellon University, School of Computer Science Software and Societal Systems Department CyLab Security and Privacy Institute Manufacturing Futures Institute Dr. Sadeh received his Ph.D. in Computer Science at CMU with a major in Artificial Intelligence and a minor in Operations Research. He holds an M.Sc. in computer science from the University of Southern California and a BS/MS degree in electrical engineering and applied physics from the Free University of Brussels (Belgium) as 'Ingénieur Civil Physicien.' Professor Sadeh's research spans cybersecurity, online privacy, Human-AI Interaction, AI governance, mobile computing, the Internet of Things, user-oriented machine learning, and language technologies. He is particularly known for his pioneering work on AI-based privacy enhancing technologies, including privacy assistants, automated privacy compliance tools, and NLP-based privacy solutions. His work has influenced the design of privacy features at major technology companies including Apple, Google, and Facebook/Meta, as well as privacy policies at regulatory agencies like the Federal Trade Commission and the California Office of the Attorney General. Analysis of his recent publications shows a strong focus on practical privacy solutions, particularly in mobile and IoT contexts, with an emphasis on making privacy more usable and understandable for end users. His work bridges technical innovation with policy implications, addressing both the technological and human aspects of privacy protection. 2018 Outstanding Entrepreneur of the Year award from the Pittsburgh Venture Capital Association Test of time award by the AAAI Conference on Web and Social Media (ICWSM) Gartner Group's Magic Quadrant leader in Security Awareness Computer-Based Training for 4 consecutive years Deloitte's Technology Fast 500 recognition for 3 consecutive years Professor Sadeh has advised numerous students, including PhD candidates like Aerin (Shikhun) Zhang, whose dissertation focused on understanding diverse privacy attitudes. His research has been funded through various grants, including NSF SaTC projects, and has resulted in technologies that protect tens of millions of users worldwide. He also founded Wombat Security Technologies, which was acquired by Proofpoint in 2018 and whose technologies are used by over 75% of Fortune 100 companies. Professor Sadeh leads several research initiatives including the Privacy Engineering Program, the Usable Privacy Policy Project, the Personalized Privacy Assistant Project, and CMU's Privacy Infrastructure for the Internet of Things. His Mobile Commerce Lab and E-Supply Chain Management Lab have produced influential research that has been commercialized by major organizations including IBM, Raytheon, Boeing, and the U.S. Army.

• Reconfigurable Computing
• Machine Learning Acceleration
• Hardware Acceleration
• +۵ مورد دیگر

Aman Arora is an Assistant Professor at Arizona State University's Ira A. Fulton Schools of Engineering, specializing in the School of Computing and Augmented Intelligence. His research focuses on reconfigurable computing, hardware acceleration of machine learning, and non-traditional computing paradigms like Processing-In-Memory. With over a decade of semiconductor industry experience, he bridges academic research and industrial applications. PhD in Computer Science from The University of Texas at Austin Research interests emphasize domain-specific acceleration through FPGA optimization , compute-in-memory architectures , and machine learning for CAD/EDA . His work addresses critical challenges in energy efficiency and throughput for AI workloads. Recent publications demonstrate trends toward compute-in-memory systems , FPGA-based deep learning acceleration , and sustainable hardware design . Key contributions include frameworks like SAF, CSR, and GAMA for dynamic hardware optimization. Laboratory Website: ADVENT Lab Teaching includes courses on digital hardware design (CSE 320) and advanced topics in machine learning acceleration (CEN 524/CSE 524). Industry experience informs his practical approach to research and education.

Maher Maaloufمشاهده پروفایل

دانشیار

• Machine Learning
• Data Mining
• Multivariate Statistics
• +۳ مورد دیگر

Dr. Maher Maalouf serves as an Associate Professor in the Department of Industrial and Systems Engineering at Khalifa University, where he has been a faculty member since 2011. He holds a PhD in Industrial Engineering from the University of Oklahoma and teaches core courses including Six Sigma Methodology and Applications (ISYE 445), Business Analytics (ESMA 610), and Advanced Business Analytics (ESMA 711). His academic credentials include: PhD in Industrial Engineering, University of Oklahoma (USA) MSc in Industrial Engineering, University of Oklahoma (USA) BBA in Management Information Systems, University of Oklahoma (USA) Dr. Maalouf's research integrates advanced analytical methodologies with industrial applications, focusing on classification and regression algorithms in machine learning, statistical process optimization through Lean Six Sigma frameworks, and operational excellence implementations. His work bridges theoretical data science with practical business process improvement across manufacturing and service sectors. He maintains active research supervision through the Socio-Technical Systems Lab, currently mentoring PhD students Toheeb Olajide Salahudeen and Kehinde Ganiyu Ismaila alongside Research Associate Assia Chadly. No scientific awards were documented in the source material.

Sara Dolnicarمشاهده پروفایل

استاد

• Sustainable Tourism
• Market Segmentation
• Social Marketing
• +۷ مورد دیگر

Professor Sara Dolnicar is an ARC Australian Laureate Fellow at the School of Business, Faculty of Business, Economics and Law, University of Queensland. With degrees in psychology and business administration from Wirtschaftsuniversität Wien, she specializes in market segmentation, sustainable tourism, social marketing, and environmental behavior. Born in Slovenia, raised in Austria, now based in Australia Over 300 refereed publications and 16 ARC grants Recipient of TTRA Distinguished Researcher Award (2017) and Slovenian Ambassador of Science (2016) Her research improves market segmentation methodology, addresses environmental sustainability in tourism, and develops behavioral interventions for eco-friendly tourist practices. She pioneered perceptions-based market segmentation and introduced bi-clustering techniques for improved data analysis. Recent publications focus on towel reuse interventions, buffet waste reduction, and smart sensor systems for hotel sustainability. She supervises PhD students in environmental behavior, tourism carbon emissions, and IoT applications for sustainability. Current grants include 'Mechanisms of Behaviour Change Theory' (2025-2028) and 'Reducing plate waste in hotels' (2021-2025). Key research areas: Sustainable tourism, market segmentation, social marketing Supervised over 15 PhD students in environmental behavior and disability employment Collaborates with industry partners like Energy Queensland and disability organizations

Cecilia Lealمشاهده پروفایل

استاد

• Soft Condensed Matter
• Biomaterials
• Drug Delivery
• +۵ مورد دیگر

Cecilia Leal is a Professor and Racheff Faculty Scholar in the Department of Materials Science and Engineering at the University of Illinois at Urbana-Champaign, with additional appointments at the Carle Illinois College of Medicine, Materials Research Laboratory, and Beckman Institute. Her interdisciplinary research program bridges materials science, biophysics, and medicine to develop innovative therapeutic delivery systems. Dr. Leal's research focuses on the self-organization of biomolecular systems, particularly lipid membranes, peptides, and nucleic acids. Her lab investigates how structural complexity of lipids and bio-membranes relates to disease mechanisms and informs the design of better gene and drug delivery systems. Key projects include developing lipid nanoparticles for mRNA delivery, studying polymer-lipid hybrid membranes, and characterizing lipid droplet dynamics in metabolic diseases. The lab employs advanced techniques including Small Angle X-ray Scattering, Cryo-EM, and live cell imaging. Her recent publications (2023-2025) reveal a strong emphasis on lipid-based delivery systems for mRNA therapeutics and cancer treatment, with particular attention to how nanostructure affects delivery efficiency. The research spans from fundamental biophysics of lipid-polymer interactions to applied therapeutic development, demonstrating consistent translation of basic science to medical applications. University of Illinois Provost's Distinguished Promotion to Full Professor Award (2024) University of Illinois Scholar (2023) NIH New Innovator Award (2016) NSF CAREER Award (2016) Racheff Faculty Scholar Award (2019) Dr. Leal has mentored numerous graduate students and postdocs, many now in prominent positions at MIT, Stanford, Dow Chemical, and pharmaceutical companies. Her research is supported by multiple NIH and NSF grants, and she maintains active collaborations with medical researchers studying obesity, cancer, and respiratory diseases. She teaches core courses including MSE 201 (Phases and Phase Relations) and MSE 473 (Biomolecular Materials Science), consistently earning excellent teaching ratings. The Leal Lab operates as an interdisciplinary team of materials scientists, physicists, and chemists using cutting-edge characterization tools to solve biomedical challenges. The lab's work on lipid nanoparticle structure has direct relevance to next-generation mRNA vaccines and cancer therapies, with several publications highlighted in C&EN News and other prominent scientific media.

• Biomedical Engineering
• Wound Care
• Medical Devices
• +۵ مورد دیگر

Professor Patricia Connolly serves in the Department of Biomedical Engineering within the Faculty of Engineering at the University of Strathclyde, United Kingdom. Her research directly contributes to UN Sustainable Development Goals through biomedical innovation. Her research spans wound monitoring systems , engineered biomaterials (particularly silk-based surgical solutions), and digital health technologies . Key focus areas include: Non-invasive physiological monitoring devices Iontophoresis and transdermal drug delivery Surgical wound healing biomaterials mHealth interventions for cardiac conditions Digital twin applications in surgery Her recent publications reveal strong trends in merging real-time physiological data with surgical decision support systems , particularly through digital twin technology and biomaterial innovation for wound care. Award highlights: Real-time Digital Twin Assisted Surgery (DTAS) award (2023) Professor Connolly actively supervises postgraduate research (8 students documented) and secures major grants including Wellcome Trust and Medical Research Scotland funding. Her current projects span wound monitoring systems, engineered silks for surgical applications, and collaborative research cultures. She operates within Strathclyde's Biomedical Engineering facilities, utilizing advanced equipment including the Metrohm Autolab PGSTAT302N Potentiostat for electrochemical analysis in wound monitoring research.

• Geomechanics
• Rock Deformation
• Subsidence Modeling
• +۴ مورد دیگر

Dr. Peter Fokker is a Researcher at Utrecht University's Faculty of Geosciences, specifically within the Department of Earth Sciences and the Experimental Rock Deformation/HPT group. He is affiliated with the Research Programme in Earth Sciences Utrecht (DES/IVAU) and has been actively publishing in geomechanics, subsidence modeling, and induced seismicity for over three decades. His work primarily focuses on the application of geomechanical principles to understand and model subsurface processes related to resource extraction and geothermal energy. Dr. Fokker's research interests span several interconnected domains in geomechanics and subsurface engineering. His primary focus is on experimental rock deformation , studying how rocks behave under various stress conditions. He has made significant contributions to subsidence modeling , particularly in the context of gas field depletion in the Netherlands. His work on induced seismicity has helped understand the relationship between subsurface operations and seismic events. Additional interests include geothermal energy systems , reservoir engineering , and the application of data assimilation techniques to improve subsurface characterization. His research often bridges theoretical models with practical applications in energy resource management. An analysis of Dr. Fokker's recent publications (2020-2025) reveals a strong focus on practical applications of geomechanics to real-world challenges. His work increasingly integrates InSAR technology and data assimilation methods to monitor and model subsidence processes. There's a clear emphasis on geothermal energy applications , reflecting growing interest in sustainable energy solutions. His research also demonstrates a sophisticated approach to modeling complex reservoir behaviors across multiple scales, from laboratory experiments to field-scale operations. The interdisciplinary nature of his work is evident in collaborations spanning geology, engineering, and environmental science. Dr. Fokker has supervised multiple research projects and students throughout his career, as indicated by the "Supervised Work (4)" reference in his profile. His research has been supported by various grants focused on subsidence modeling, geomechanics of energy resources, and induced seismicity. He has been involved in significant collaborative efforts, including the Dutch National Scientific Research Program on Land Subsidence. Dr. Fokker is part of the Experimental Rock Deformation/HPT group at Utrecht University, which conducts laboratory experiments and develops theoretical models to understand rock behavior under various conditions. His work contributes to the broader research ecosystem focused on sustainable resource management and understanding subsurface processes, with particular relevance to the Dutch context of gas extraction and land subsidence.

Ying-Yi Chihمشاهده پروفایل

استاد

• Project Management
• Public-Private Partnerships
• Value Co-Creation
• +۳ مورد دیگر

Ying-Yi Chih is a Professor of Project Management at the Research School of Management, Australian National University (ANU) , and serves as the Associate Dean (Students and Industry Experience) for the College of Business and Economics. Her research focuses on project management, public-private partnerships (PPPs), value co-creation in projects, and employee well-being in project-based environments like the construction industry. She has published extensively in journals such as International Journal of Project Management and Journal of Construction Engineering and Management , with funding from government and industry sources. Education: PhD in Project Management Research Interests include: Infrastructure Project Planning and Management Public-Private Partnerships (PPPs) Value Co-Creation in Professional Services Employee Psychological Well-being and Performance Management Recent Publications highlight trends in green innovation, crisis resilience, leadership dynamics, and technology adoption in construction and project management. Her work bridges theoretical frameworks with practical applications in the AEC (Architecture, Engineering, Construction) industry and public sector projects. Editorial Roles: Associate Editor for Journal of Management in Engineering and Editorial Board member for Journal of Vocational Behavior . Research Projects have explored value co-creation, international development projects, and performance management in multi-project environments, with collaborations across Australia, Taiwan, Vietnam, and the Philippines.

Chunyan Laiمشاهده پروفایل

دانشیار

• Electric drives
• Motor control
• Power electronics
• +۲ مورد دیگر

Dr. Chunyan Lai is an Associate Professor at the Department of Electrical and Computer Engineering, Concordia University. Her research focuses on electric drives, motor control, power electronics, electrified vehicles, and vehicle-to-grid solutions. She contributes to both graduate and undergraduate education through courses such as Controlled Electric Drives and Hybrid Electric Vehicle Power Systems . Research Emphasis : Electric motor drives and control systems, electrified transportation, power electronics innovations, and energy management strategies. Publications : Specializes in sensorless control techniques for Permanent Magnet Synchronous Motors (PMSM), thermal management in electric machines, and advanced energy trading frameworks for smart grids. PhD Opportunities : The Power Electronics and Energy Research (PEER) Group under Dr. Lai offers positions for developing efficient motor drives for EVs and grid-connected power converters. Collaboration : Industry-adjacent research with requirements for professional communication, patent development, and technical dissemination.

Robert Blickمشاهده پروفایل

استاد

• Nanoscience
• Atomic Layer Deposition
• Nanostructuring
• +۷ مورد دیگر

Prof. Dr. Robert Blick is a faculty member at the University of Hamburg , leading the Institute for Nanostructure and Solid State Physics under the Faculty of Mathematics, Informatics, and Natural Sciences. He serves as Director of the Center for Hybrid Nanostructures (CHyN) and Head of the Board of Examiners of Nano-Science. Research Focus: Atomic Layer Deposition (ALD), quantum dots, superconducting thin films, biomaterials, and nanomechanical devices. Key Collaborations: Deutsches Elektronen-Synchrotron (DESY), molecular-beam epitaxy groups, Forschungslabor Mikroelektronik Deutschland. His academic contributions span nanoscience, materials growth, and biomedical applications. Current funding includes support from the Deutsche Forschungsgemeinschaft (DFG), Exzellenzcluster CUI, and the Joachim Herz Foundation. The CHyN research group operates a state-of-the-art clean room facility for electron-beam and focused-ion-beam lithography, enabling 8nm feature definition on 6-inch wafers. Applications of his work include memristor technology, quantum devices, and advanced biosensors. His PhD students include Ahmed Alshaikh, Kristian Deneke, Daniel Hensel, Marianna Brede, Daniel Schmidt, Malte Siegmund, and Jan Stelzner. Senior researchers Dr. Stefanie Haugg and Dr. Robert Zierold contribute to materials growth and atomic layer deposition.