API Design Assessment Professors and Supervisors

Ronny Standtkeمشاهده پروفایل

استاد

Bern University of Applied SciencesSwitzerland

Prof. Dr. Ronny Standtke is Co-group leader of the Digital Manufacturing Group at the Institute of Digital Construction & Wood Industries, Bern University of Applied Sciences in Biel, Switzerland. He holds a doctoral degree in Computer Science from the University of Freiburg and a Diplom-Informatiker from TU Dresden, with additional studies at TU Helsinki. His academic appointments include Professor for Digital Manufacturing at BFH (2021-2023) and lecturer positions at FHNW and PH FHNW. Research interests span digital manufacturing, computer science applications, and sustainable digitalization, with specialized focus on: Digital twins and BIM for construction industries CAD/CAM integration and process automation Data science applications in wood technology Open-source solutions for public sector IT infrastructure His publications demonstrate interdisciplinary contributions, evolving from early cybersecurity and anonymity research (2001-2008) toward educational technology innovations like the Lernstick platform (2011-2015), with recent work in public sector digitalization and civil engineering risk assessment (2023-2024). Awards include the IBM Open Education Award 2015 for developing the Lernstick learning environment. Current projects focus on: Secure remote assessment systems Open-source alternatives to proprietary software in government Business integration platforms for wood industry automation He leads bachelor thesis supervision in digital manufacturing optimization and has advised 10+ students on topics including: Production planning automation Shopfloor data analytics ERP system development

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Tamara Ilieva-Tsvetkovaمشاهده پروفایل

استادیار

University of Architecture, Civil Engineering and GeodesyBulgaria

Tamara Ilieva-Tsvetkova is a Senior Assistant Professor at the Department of Geodesy and Geoinformatics within the Faculty of Geodesy at the University of Architecture, Civil Engineering and Geodesy (UACEG) in Sofia, Bulgaria. She also serves as a Technical Associate at the Center for Quality and Accreditation and maintains her office in Cabinet 411P, with reception hours on Mondays from 11:30-12:30 during the winter semester of the 2025-26 academic year. Her educational background includes: Master's degree in Geodesy from UACEG, Sofia (2007) Master's degree in Marketing with specialization in "Advertising Management" from UNWE, Sofia (2015) Doctorate in "General, Higher and Applied Geodesy" from UACEG, Sofia (2019) Tamara Ilieva-Tsvetkova's research focuses on geospatial technologies and methodologies, with particular expertise in geodetic measurements, spatial databases, CAD and GIS systems development, engineering project management, and coordinate systems. She is proficient in English (excellent level) and Russian (basic level), and possesses extensive technical skills in AutoCAD, ArcGIS, QGIS, PostgreSQL with PostGIS, and web mapping libraries like Leaflet and OpenLayers. Her recent publications (2021-2024) show a strong trend toward web-based GIS applications, indoor positioning systems, climate change monitoring using geospatial data, and the integration of artificial intelligence with geospatial technologies. Her work spans practical applications in urban planning, transport infrastructure risk assessment, real estate management, and environmental monitoring, with a particular focus on Bulgarian territories. She is an active member of professional organizations: Chamber of Engineers in Investment Design Chamber of Engineers in Geodesy European Geosciences Union (EGU) Tamara Ilieva-Tsvetkova has participated in numerous research and construction projects: Upgrading information systems for AGKK (2013-2014) Information platform for environmental research and modeling at UACEG (2018-2019) Center of Excellence "Heritage BG" (2018-2023) Geodetic surveying for the South Stream gas pipeline Cadastral mapping for multiple Bulgarian villages and regions Geodetic survey for Sofia Metro expansion Geodetic survey for Sofia Airport infrastructure Her technical expertise spans multiple domains including geodetic measurement processing, GIS system development, spatial database management, and programming for geospatial applications using C#, SQL, JavaScript, and various GIS APIs.

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Shing-Chi Cheungمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Shing-Chi Cheung is a Professor of Computer Science and Engineering at the Hong Kong University of Science and Technology (HKUST), School of Engineering. He founded the CASTLE research group and co-founded the International Workshop on Automation of Software Testing (AST) in 2006. His leadership includes serving as General Chair of FSE 2014 and chairing multiple APSEC conferences. His research focuses on software quality enhancement through program analysis, testing, debugging, and AI techniques, targeting Android apps, open-source software, deep learning systems, smart contracts, and spreadsheets. Current projects include metamorphic testing frameworks, binary analysis tools, and vulnerability detection systems for emerging technologies. His publication portfolio demonstrates consistent contributions to software engineering since 2016, with recent work emphasizing AI-integrated testing methodologies, smart contract security, and deep learning system reliability. Key trends show increasing focus on cross-language analysis, data visualization quality, and compiler-level verification for modern software stacks. Distinguished Member of the ACM Fellow of the British Computer Society Editorial board member: Science of Computer Programming (SCP), Journal of Computer Science and Technology (JCST) Former editorial board member: IEEE Transactions on Software Engineering (2006-2009), Information and Software Technology (2012-2015) Four patents in China and the United States Cheung actively mentors through the CASTLE research group and serves on program committees for major conferences including ICSE, ESEC/FSE, and ISSTA. His work bridges academic research with practical applications through industry collaborations and tool development. He has contributed to numerous workshops and symposia as steering committee member and program chair.

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Maxime Lamotheمشاهده پروفایل

استادیار

Max Planck Institute for Security and PrivacyGermany

Maxime Lamothe is an assistant professor at Polytechnique Montreal specializing in empirical software engineering and mining software repositories. His research focuses on software APIs, build systems, and the intersection of AI and software engineering. Previously, he was a postdoctoral researcher at the University of Waterloo's Software REBELs Lab under Prof. Shane McIntosh. Dr. Lamothe's educational background includes: Ph.D. in Software Engineering from Concordia University (2020) M.Eng from Concordia University (2017) B.Eng from McGill University (2013) His research interests center around empirical studies of software engineering practices, with particular focus on API design and evolution, software build systems, and performance analysis. Dr. Lamothe investigates how developers interact with APIs, how build systems operate in practice, and how AI techniques can enhance software engineering processes while maintaining human oversight of critical decisions. Dr. Lamothe's publication record shows a consistent focus on empirical approaches to understanding software engineering practices. His work frequently examines API usage patterns, code review processes, and continuous integration systems. A notable trend is his growing interest in applying AI techniques to software engineering challenges while maintaining empirical validation of proposed solutions through rigorous case studies and longitudinal analyses. Dr. Lamothe actively serves the academic community as a reviewer for top journals including Transactions on Software Engineering (TSE), Empirical Software Engineering (EMSE), and Journal of Systems and Software (JSS). He has served on program committees for major conferences including ASE, ICSE, ESEC/FSE, MSR, and SANER across multiple years, with particular involvement in the NIER Track, Research Papers track, and Tool Demonstration tracks. Currently seeking Masters and Ph.D. students, Dr. Lamothe leads research at the intersection of traditional software engineering practices and emerging AI techniques. His work combines rigorous empirical methods with practical applications to solve real challenges in software development, with implications for improving API design, enhancing code review processes, optimizing build systems, and developing trustworthy AI-assisted software engineering tools.

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Qing Huangمشاهده پروفایل

دانشیار

Max Planck Institute for Security and PrivacyGermany

Qing Huang is an Associate Professor in the School of Computer and Information Engineering at Jiangxi Normal University in Nanchang, China. His academic career focuses on bridging software engineering with artificial intelligence, particularly through the application of large language models to enhance software development processes. His research interests span multiple interconnected domains: Software Engineering Knowledge Graphs Human-Computer Interaction Programming Languages Artificial Intelligence applications in software development Dr. Huang's recent work demonstrates a strong focus on leveraging large language models (LLMs) to address fundamental challenges in software engineering. His research explores how AI can enhance code generation, API understanding, software testing, and knowledge representation in programming contexts. A significant portion of his work investigates the intersection of knowledge graphs and LLMs to create more intelligent software development tools. His publications reveal a consistent pattern of innovation in applying cutting-edge AI techniques to practical software engineering problems, with particular emphasis on improving developer productivity through better tooling and knowledge management. Dr. Huang has made notable contributions to the field of prompt engineering for software development tasks, exploring how natural language interfaces can serve as "APIs" for human-AI interaction. His work on AI Chains represents a novel approach to connecting human developers with LLM capabilities through structured knowledge representations. Additionally, he has conducted significant research on smart contract analysis, code reuse, and type inference in partial code contexts. His scientific contributions have been recognized through publications at major software engineering conferences including ASE and ICSE, with multiple papers accepted across different tracks (Research Papers, Journal-First, Tool Demonstrations). Dr. Huang serves as a Program Committee member for ASE 2025 in the Research Papers track, demonstrating his standing in the software engineering research community. Dr. Huang collaborates extensively with researchers from various institutions, including Data61 (Australia), Nanyang Technological University, and other Chinese universities. His work demonstrates strong interdisciplinary connections between traditional software engineering and emerging AI technologies.

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Andy Ammonsمشاهده پروفایل

استاد

Goshen CollegeUnited States

Andy Ammons is a Professor of Biology at Goshen College specializing in stress physiology, behavioral genetics, and entomology with a primary focus on honey bee research. His work bridges biomedical and ecological perspectives using Apis mellifera as a model organism for studying alcohol addiction mechanisms and stress responses. His educational background includes: B.A. from Berea College (2003) Ph.D. from Purdue University West Lafayette (2007) Ammons' research centers on physiological and genomic responses to stressors including ethanol, aging, and environmental challenges. He investigates how substances like alcohol affect neurophysiological systems through quantitative trait loci mapping and behavioral assays, with implications for human addiction treatments. His work extends to evolutionary genetics of social insects and circadian rhythm variations between honey bee subspecies. Publication trends reveal sustained focus on honey bee genomics (60% of works), with recent emphasis on aging-related gene expression (2013) and ethanol sensitivity mechanisms (2008). His interdisciplinary approach integrates molecular biology, toxicology, and behavioral ecology, complemented by pedagogical research in biology education (2011). Ammons actively mentors 17 undergraduate researchers across 15 concurrent projects including honey bee navigation, pheromone effects on alcohol sensitivity, innate immunity studies, and native bee biodiversity surveys. His lab employs techniques ranging from RT-PCR gene expression analysis to field behavioral observations, often collaborating with Dr. Kris Schmidt on Drosophila immunity research. Current work examines ethyl oleate pheromone interactions with ethanol sensitivity and genetic polymorphisms in circadian rhythm genes.

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