جست‌وجوی استاد و پژوهشگر

Mario Trappمشاهده پروفایل

استاد

• Resilient Cognitive Systems
• Safety Assurance of AI-based Systems
• Self-Adaptive Software Systems
• +۷ مورد دیگر

Prof. Dr. Mario Trapp is a Full Professor and Chairholder of Engineering Resilient Cognitive Systems at the Technical University of Munich (TUM), within the TUM School of Computation, Information and Technology. He is also the Executive Director of the Fraunhofer Institute for Cognitive Systems IKS in Munich, leading a major research institute focused on the safe integration of artificial intelligence into critical systems. Education: PhD in Computer Science, TU Kaiserslautern, 2005 (with distinction) Habilitation in Computer Science, TU Kaiserslautern, 2016 Studied Technoinformatics / Computer Science, TU Kaiserslautern His research centers on resilient cognitive systems , where he combines expertise in model-based safety engineering with self-adaptive software systems. He advocates for safe intelligence , emphasizing that AI must be engineered to be both intelligent and safe, particularly in domains like autonomous driving and medical technology. His work addresses the challenge of ensuring dependability in open, adaptive systems where traditional safety methods fall short. The available publications reflect a consistent focus on dynamic safety assurance, adaptive certification, and runtime risk management for complex, open systems. His research trajectory shows a deep commitment to foundational methods that enable systems to maintain safety despite uncertainty and change. Scientific Affiliations and Recognition: Member, Bavarian State Government’s Council on AI (Bayerischer KI-Rat) Member, Bavarian State Ministry’s AI – Data Science Expert Panel Former Adjunct Professor, Department of Computer Science, TU Kaiserslautern Prof. Trapp is actively involved in technology transfer, advising numerous industrial partners on safety-critical software and AI assurance. He is a frequent speaker and author on the topics of AI safety, software engineering, and resilience. He leads a research team at Fraunhofer IKS focused on developing architectures and methods for dependable cognitive systems.

Qiang Zhuمشاهده پروفایل

استاد

• Data Science
• Data Management
• Machine Learning
• +۳ مورد دیگر

Qiang Zhu is a Professor in the Department of Computer and Information Science at the University of Michigan-Dearborn, holding the William E. Stirton Professorship (2017–2024). He founded the Data Science/Management Research Laboratory and is affiliated with the Michigan Institute for Data Science (MIDAS). His research spans data science, data management, and machine learning. Ph.D., University of Waterloo M.S., McMaster University M.Eng., Southeast University B.S., Southeast University Research focuses on advanced data indexing, query optimization, and AI-driven data management, with applications in genomics, network systems, and education. His work integrates machine learning with database systems for scalable solutions. Recent publications include topics in federated learning fairness, digital twin middleware, project-based CS education, and genome data indexing. Scientific contributions recognized through awards like the Wilkes Award (2008), ACM Distinguished Scientist (2013), and Springer Nature Editor of Distinction (2025). 2013–2018: Department Chair NSF, IBM, and Ford grants Over 250 conference committee roles He directs the Data Science/Management Research Lab, focusing on collaborative projects in genome analytics and smart computing infrastructures.

Manos Athanassoulisمشاهده پروفایل

دانشیار

• Data Systems
• Cloud Data Management
• Database Systems
• +۷ مورد دیگر

Manos Athanassoulis is an Associate Professor in the Department of Computer Science at the College of Arts and Sciences, Boston University. He is the Founder and Director of the BU Data-intensive Systems and Computing (DiSC) lab and a member of the BU MiDAS group. His research focuses on data systems, particularly cloud data management, hybrid transactional/analytical workloads, and integration with emerging hardware such as non-volatile memory and heterogeneous computing. His educational background includes a PhD from EPFL (2014), an MSc in Computer Systems Technology, and a BSc in Informatics and Telecommunications from the University of Athens, Greece. Prior to BU, he was a Postdoctoral Researcher and Research Associate at Harvard University, supported by a SNSF Postdoc Mobility Fellowship. His research interests span data systems, database architectures, LSM trees, indexing, storage systems, and performance optimization. He explores how novel hardware can be leveraged to improve data management efficiency and scalability, especially in cloud environments. His recent publications (2021–2025) predominantly focus on LSM trees, covering topics such as compaction policies, Bloom filter tuning, DPU offloading, adversarial resilience, and sustainable caching. Earlier works include foundational contributions on access methods (RUM Conjecture) and optimal key-value stores (Monkey). The trend shows a consistent focus on data system efficiency, adaptability, and robustness under varying workloads and hardware constraints. Scientific Awards: NSF CAREER Award (2022) Facebook Faculty Research Award (2020) NSF CRII Award (2019) Best of VLDB 2017 and Best of SIGMOD 2017 SIGMOD Most Reproducible Paper Award (2017) Multiple ACM SIGMOD Distinguished PC Member recognitions (2018–2025) VLDB 2023 Best Demo Award RedHat Collaboratory Research Incubation Awards (multiple, 2021–2023) SNSF Postdoc Mobility Fellowship (2015–16) IBM PhD Fellowship (2011–12) Dr. Athanassoulis has advised numerous students and collaborators, evident from his co-authorship on works with researchers such as Niv Dayan, Stratos Idreos, and A. Ailamaki. His grants include major awards from NSF, Facebook, and RedHat, supporting research in robust data systems, hardware-software co-design, and learned cost models. He has also been recognized for teaching excellence at Harvard University. He leads the DiSC lab at Boston University, which focuses on data-intensive computing and systems research. The lab explores next-generation data architectures, particularly in cloud and hardware-aware environments. Collaborations with the BU MiDAS group enhance interdisciplinary research in data science and AI.

Nele Mentensمشاهده پروفایل

استاد

• Applied Cryptography
• Hardware Security
• Secure Coprocessor Design
• +۱۲ مورد دیگر

Nele Mentens is a full professor at both KU Leuven and Leiden University, where she leads cutting-edge research in applied cryptography, hardware security, and secure embedded systems. At KU Leuven, she is affiliated with the Faculty of Engineering Technology and the Electrical Engineering Department (ESAT), leading the Emerging Technologies, Systems & Security (ES&S) research group at the Diepenbeek campus. Simultaneously, she holds a full professorship at Leiden University’s Leiden Institute of Advanced Computer Science (LIACS), focusing on applied cryptography and security. She has been instrumental in numerous national and international research initiatives, including Horizon Europe and NWO-funded projects. Full Professor, KU Leuven (since 2023) Full Professor, Leiden University (since 2020) Associate Professor, KU Leuven (2014–2023) Post-doctoral Researcher & Lecturer, KHLim / KU Leuven (2007–2014) Ph.D. in Engineering Science, KU Leuven (2007) M.Sc. in Electrical Engineering, KU Leuven (2003) Her research focuses on secure and efficient hardware design, particularly for cryptographic applications on FPGAs, reconfigurable architectures, IoT security, and neuromorphic computing. She explores physical attack resistance, side-channel analysis protection, and trusted computing architectures, with applications in healthcare, industrial monitoring, and endpoint AI. Her work bridges theoretical cryptography with practical hardware implementations, emphasizing energy efficiency and real-time performance. The 15 most recent publications reflect a strong trend toward secure, energy-efficient, and intelligent embedded systems. Topics include neuromorphic AI accelerators, trusted IoT architectures, dynamic reconfiguration for side-channel protection, and secure medical data processing. These works span disciplines such as computer architecture, cybersecurity, digital design, and embedded systems, with a focus on hardware-software co-design and real-world deployment. Nele Mentens has received recognition for her contributions, including: Best Paper Award, DATE'16 Best Paper Nomination, AsianHOST'17 Best Paper Award, CHES'19 She has supervised over 15 Ph.D. students and post-docs, both current and former, and has served as principal investigator in approximately 25 funded research projects. Her work has attracted significant grants from Horizon Europe, NWO, FWO, and national innovation programs. She actively contributes to the academic community through editorial roles in top journals and leadership in major conferences. Nele Mentens leads the ES&S research group at KU Leuven and collaborates closely with LIACS at Leiden University. Her team includes Ph.D. students, post-docs, and research experts working on projects like NimbleAI, NeuroSoC, and TrustedIoT. She has also established secure electronics labs through infrastructure grants and maintains strong international ties with institutions such as EPFL, Ruhr University Bochum, and ETH Zurich.

Kerstin Raudonatمشاهده پروفایل

پژوهشگر

• Gender and Technology
• Human-Computer Interaction
• Diversity in Computing
• +۵ مورد دیگر

Dr. Kerstin Raudonat is a researcher at the Institute of Computer Science, Faculty of Mathematics and Natural Sciences, Humboldt University of Berlin. She has been working at the 'Computer Science and Society' chair since September 2022, focusing on the intersection of technology, gender, and society. Her research spans multiple domains including human-computer interaction, media education, and digital game culture, with particular emphasis on creating more inclusive technological environments. Dr. Raudonat's research interests center on gender equity in technology development, examining how societal biases manifest in IT systems and how to break cycles of discrimination in software design. Her work explores the complex relationships between technology and social structures, with special attention to how digital environments can be designed to promote diversity and inclusion. She investigates these issues through multiple lenses including practice theory, cyberfeminism, and participatory design methodologies, seeking practical approaches to make technology development more socially responsible. Her recent publications reveal a consistent trajectory examining gender dynamics in technology, with increasing focus on AI systems and their societal impacts. The research shows evolution from analyzing gaming cultures and communication patterns to addressing systemic biases in contemporary AI technologies. Her work demonstrates strong interdisciplinary connections between computer science, sociology, gender studies, and media education, reflecting a comprehensive approach to understanding technology's role in society. Dr. Raudonat has been actively involved in multiple significant research projects funded by the German Federal Ministry of Education and Research, including: KIRA (2021-2024): Developing AI-based matching for vocational training with gender sensitivity considerations IT&me (2017-2020): Creating multimedia knowledge resources for women in IT fields Gender-UseIT (2013-2014): Establishing a network for interdisciplinary research on gender perspectives in human-computer interaction VIT3A : International virtual teaching and collaboration initiatives Her research has been conducted in collaboration with multiple institutions including Fraunhofer IAO, Hochschule Heilbronn, and Vietnamese-German University, demonstrating strong national and international research partnerships. Dr. Raudonat's work contributes significantly to understanding how technology can be developed in more socially responsible ways that promote equity and inclusion.

Anthony Clarkمشاهده پروفایل

استادیار

• Autonomous Robotics
• Evolutionary Robotics
• Computer Vision
• +۷ مورد دیگر

Anthony Clark is an Assistant Professor of Computer Science at Pomona College, where he has been teaching since 2020. Previously, he served as an Assistant Professor at Missouri State University from 2016 to 2020. He directs the ARCS (Autonomous Robotics and Complex Systems) Lab, which focuses on improving the robustness and adaptability of autonomous robots, particularly small-scale systems that can navigate unpredictable terrain and adapt to potential damage. Clark earned his Ph.D. in Computer Science from Michigan State University in 2016, where he worked under Dr. Philip K. McKinley, and his B.S. in Computer Engineering from Kansas State University, graduating magna cum laude. His research centers on making autonomous robots more robust and adaptive through optimization algorithms and multimodal systems. He specializes in evolutionary robotics, computer vision, neural networks, and simulation methods for developing control systems that leverage multiple locomotion mechanisms. His recent work demonstrates strong trends across several domains: developing hybrid locomotion systems (wheel/leg transformations), applying deep learning to terrain classification and pathfinding, using simulation environments for training, and exploring pretraining techniques for evolutionary robotics. His research shows a consistent focus on bridging simulation and real-world applications while addressing challenges in robot adaptability and robustness. Faculty Excellence in Teaching, Missouri State University (2018) Best Paper Award, Workshop on Evolutionary and Reinforcement Learning (2013) Best Paper Award, ALIFE Conference, Behavior and Intelligence Track (2012) Outstanding Reviewer, Elsevier (2018) Master Advisor Certification, Missouri State University (2017) Clark has advised numerous undergraduate and graduate students through the ARCS Lab, with current research involving projects like the Adabot (a robot with multiple locomotion mechanisms) and thermal semantic segmentation for aerial field robots. His teaching portfolio includes courses on data structures, algorithms, neural networks, computer systems, and mobile robotics. He has also served as a Visiting Associate at Caltech's ARC Lab from 2023-2024, working with Dr. Soon-Jo Chung. The ARCS Lab develops simulation environments, optimizes control systems, and fabricates physical robots. Current projects include the Adabot with its geared coaxial shaft mechanism for hybrid locomotion, thermal semantic segmentation using satellite data, and creating dynamic simulation environments with Unreal Engine 5. The lab emphasizes practical applications of theoretical research while training students in both hardware and software aspects of robotics.

• Software Quality
• Quantum Computing
• Information Systems
• +۵ مورد دیگر

Mario Piattini is a Full Professor at the School of Computer Science of the University of Castilla-La Mancha (UCLM) in Spain, where he has served since 2002. He is the founder of the Alarcos research group and has held leadership roles including Director of the Mixed Center for Software Research and Development UCLM-Indra and Director of the Institute of Technologies and Information Systems (ITSI) at UCLM. He has also served as an associate professor at Universidad Complutense and Universidad Carlos III de Madrid. His educational background includes a PhD and degree in Computer Science from Universidad Politécnica de Madrid, a Psychology degree from UNED, and a Doctor Honoris Causa from Universidad de La Plata (Argentina). He holds multiple master's degrees in IT Audit, Human Resources Management, and Project Management, along with professional certifications including CISA, CISM, CRISC, CGEIT, PMP, and data governance certifications from DAMA. Professor Piattini is a leading expert in software quality, information systems, and security, with a recent strong focus on quantum computing and quantum software engineering. His research spans software engineering methodologies, data quality, AI systems, and the emerging field of quantum software development. He has been recognized as one of the top 15 scholars in systems and software engineering (2004-2008) and among the most active software engineering researchers (2010-2017). His recent publications reveal a significant shift toward quantum computing, with numerous articles on quantum software engineering, quantum-classical hybrid systems, quantum testing frameworks, and quantum software architecture. His work bridges theoretical foundations with practical engineering approaches for the emerging quantum computing paradigm. His scientific recognition includes multiple prestigious awards: Premio Nacional a la Trayectoria Profesional del Ingeniero Informático Premio Gabriel Alonso Herrera from JCCM for research trajectory Premio Grace Hooper from COIICLM Premio Aritmel from SCIE Premio FIUM from Universidad de Murcia Premio a la Trayectoria Profesional de ISACA Madrid As an academic leader, Piattini has founded several spinoff companies including Cronos Ibérica (now Alten), Kybele Consulting, Lucentia Lab, DQTeam, AQCLab (the first ENAC-accredited laboratory for software product quality and data evaluation), and I2SC. He serves as secretary of CTN71/SC7 and is a member of various ISO/IEC and UNE standardization committees, contributing significantly to software quality standards development. His research group has established AQCLab, which has been evaluating software quality for 25 years, demonstrating his long-term commitment to practical applications of software engineering research. Through his leadership in both academic and industrial contexts, Piattini has created a robust ecosystem connecting theoretical research with real-world software quality practices.

• Human-Computer Interaction (HCI)
• Virtual Reality (VR)
• Augmented Reality (AR)
• +۷ مورد دیگر

Dr. George Fitzmaurice is a Research Fellow at Autodesk, leading the Human Computer Interaction and Visualization Research group. With over 120 publications and 95 patents, his work spans 25 years of innovation in interactive systems, focusing on technology-assisted learning , 3D visualization , and novel input techniques . His notable contributions include the Maya 1.0 UI and SketchBook Pro design, as well as pioneering Graspable UIs and Spatially-Aware Displays . Education : MIT (B.Sc. Math/CS), Brown (M.Sc. CS), Toronto (Ph.D. CS) His research explores immersive visualization and generative AI applications in design workflows, with recent work focusing on VR/AR tools like TimeTunnel for motion editing and WhatIF for AI-assisted narrative design. Current projects examine the intersection of large language models , 3D design systems , and collaborative environments . Key article themes include: Generative AI integration (3DALL-E, WorldSmith) Immersive motion analysis (AvatAR, VideoPoseVR) Creative workflow optimization (MoodCubes, Immersive Sampling) Privacy-aware VR systems (Vice VRsa) Scientific Recognition: 2019 - Inducted into ACM CHI Academy 2024 - Awarded ACM Fellow for computing contributions He has developed foundational interaction techniques like ViewCube™ and SteeringWheels™ , and his work continues to shape modern 3D UI paradigms and spatial computing approaches through projects like DreamSketch and Tesseract.

Koushik Senمشاهده پروفایل

استاد

• Software Engineering
• Programming Languages
• Formal Methods

Koushik Sen is a Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. His research focuses on developing software tools and methodologies to enhance programmer productivity and software quality, with expertise in Software Engineering, Programming Languages, and Formal Methods. Education: B.Tech from Indian Institute of Technology, Kanpur M.S. and Ph.D. in Computer Science from University of Illinois at Urbana-Champaign Research Focus: Professor Sen pioneers automated testing techniques including concolic testing and DART (Directed Automated Random Testing). His work bridges formal methods with practical software development, emphasizing bug detection, program synthesis, and AI-driven software analysis tools. Recent innovations include machine learning approaches for code recommendation and fuzzing. Publication Trends: His recent publications (2019-2023) demonstrate strong emphasis on fuzzing techniques, program synthesis, and AI/ML applications in software engineering. Notable domains include smart contract security, automated testing, and developer tooling, with frequent collaborations in top-tier conferences. Awards and Honors: NSF CAREER Award (2008) Sloan Foundation Fellowship (2011) IFIP TC2 Manfred Paul Award (2010) Okawa Foundation Research Grant (2015) Multiple ACM SIGSOFT Distinguished Paper Awards UIUC Distinguished Alumni Educator Award (2014) Leadership: Active program committee member for premier conferences (PLDI, ICSE, ISSTA) and keynote speaker. His research is supported by NSF, Okawa Foundation, and Sloan Foundation.

Virpi Rotoمشاهده پروفایل

مدرس ارشد

• Experience Design
• Human-Computer Interaction
• B2B Design
• +۹ مورد دیگر

Virpi Roto is a Senior Lecturer at Aalto University's Department of Design (School of Arts, Design and Architecture). She specializes in Experience Design for business-to-business industries, focusing on transforming technology companies into experience providers through co-design and service design methodologies. Key research domains: Human-AI interaction, sustainable futures, and workplace experience design Collaboration hubs: Leads the Encore research group Global influence: Top-cited academic in UX research Her work explores the intersections between User Experience , Customer Experience , and Employee Experience , with a particular emphasis on automation maturity and sociomaterial approaches to transparency in remote teams. Recent publications highlight trends in Human-AI team dynamics and experience-driven industrial systems . She actively bridges Design Fiction with ethical awareness in co-design workshops and develops frameworks for measuring long-term UX. Virpi collaborates with researchers across Finland, Sweden, and international institutions, frequently co-authoring with experts like Philippe Palanque, Matthias Baldauf, and Wendy Ju.

• Machine Learning
• Natural Language Processing
• Predictive Maintenance
• +۴ مورد دیگر

Tony Lindgren is an Associate Professor at the Department of Computer and Systems Science, Stockholm University, affiliated with the Data Science Research Group and Natural Language Processing Research Group. His work bridges data science and NLP , focusing on interpretable models, constraint programming, and predictive maintenance systems. Research interests include: Machine Learning for explainability and fairness Constraint Programming in maintenance optimization Natural Language Processing for risk analytics and troubleshooting Recent publications demonstrate trends in multi-objective optimization (2025 satellite scheduling), conformal prediction (2024 CoPAL), and fault detection (2024 Automotive Nowcasting). His work often integrates domain-specific constraints with scalable algorithms across applications like food safety and autonomous vehicles. Software tools developed by Lindgren include: Example-based Feature Tweaking Rule Indexing Frameworks His research groups focus on AI-driven decision support for high-stakes domains, combining technical innovation with societal impact considerations.

Brent Lagesseمشاهده پروفایل

دانشیار

• Cybersecurity
• Machine Learning
• Pervasive Computing
• +۶ مورد دیگر

Brent Lagesse is an Associate Professor at the University of Washington - Bothell , affiliated with the Division of Computing & Software Systems under the School of Science, Technology, Engineering & Mathematics . His research focuses on security in emerging environments , particularly secure machine learning and privacy in sensor-rich systems . Ph.D. in Computer Science from the University of Texas at Arlington (2009) Research Interests include: Detecting and locating hidden webcams Scalable AI/ML defense mechanisms Privacy-preserving video sharing AI systems for air quality prediction Automated yeast cell analysis CRISPR/CAS9 guide-donor libraries Article Trends : Recent publications emphasize secure machine learning for smart city applications, privacy-preserving technologies , and resource-constrained security in crowdsensing environments . Collaborative work spans cybersecurity education , environmental monitoring , and context-aware systems . Scientific Awards : Cybersecurity Fulbright Scholar (University of Cambridge, 2018) Johann-von-Spix International Guest Professorship (University of Bamberg, 2019-20) Advising & Grants : Advises current research students Neil Prakasam and Nicholas Handaja NSA grant ($96k) for GenCyber curriculum development (2022) NSF grant ($300k) for AI-enhanced cybersecurity workforce studies (2021) T-Mobile grants for ML security metrics and dataset anonymization (2020-2022) Laboratory : Leads the Security of Emerging Environments (SEE) Lab , developing practical and theoretical frameworks for smart city security and privacy-preserving technologies .

Stephanie Forrestمشاهده پروفایل

استاد

• Cybersecurity
• Software Engineering
• Computational Immunology
• +۸ مورد دیگر

Stephanie Forrest is a Professor of Computer Science at Arizona State University and serves as Director of the Biodesign Center for Biocomputation, Security and Society . She holds affiliations with the School of Computing and Augmented Intelligence , Global Futures Laboratory , and Santa Fe Institute External Faculty . Education: B.A. from St. John's College M.S. and Ph.D. in Computer Science from the University of Michigan Research Interests: Forrest specializes in the intersection of biology and computation , with key contributions to cybersecurity (anomaly detection, instruction-set randomization), automated software repair (evolutionary methods), and biological modeling (immune systems, SARS-CoV-2 spread). Her work bridges complex adaptive systems , AI/ML , and defense applications . Scientific Contributions: 2020 IEEE S&P Test of Time Award 2019 ICSE Most Influential Paper Award 2011 ACM/AAAI Allen Newell Award NSF Presidential Young Investigator (1991) IEEE Fellow Evolutionary Computation Pioneer award Publications & Grants: Her research appears in top venues (ICSE, IEEE S&P, PNAS) and is funded by the National Science Foundation , DARPA , Air Force Research Lab , and Santa Fe Institute . Key projects include Crispy (CRISPR-inspired DoS defense), GenProg (automated bug correction), and SIMCoV-GPU (agent-based pandemic modeling).

• Distributed Systems
• Cybersecurity
• Sports Technology
• +۷ مورد دیگر

Dag Johansen is a Professor in the Department of Informatics at UiT The Arctic University of Norway, Tromso campus. His work spans multiple research areas at the intersection of computer science, sports science, medicine, health technology, and nutrition science. He leads the interdisciplinary "Corpore Sano" research center and is actively involved in several research groups including the Cyber Security Group (CSG) and Crime Control and Security Law. Professor Johansen's research focuses on developing fundamental software solutions for secure and error-free data processing in heterogeneous distributed systems, ranging from lightweight "Internet of Things" devices and mobile phones to large-scale cloud solutions. His work particularly emphasizes applications in sports technology, edge computing, and compliance technology. His research interests include distributed systems, cybersecurity, sports technology, edge computing, data privacy, AI for sports analytics, multimedia forensics, and compliance technology. His recent publication trends show a strong focus on AI applications for sports video analysis, particularly in soccer and ice hockey, where his team has developed AI-based cropping systems for social media representations. He also has significant work in data privacy and GDPR compliance, especially regarding the "third country problem," as well as applications of AI in sustainable fishing practices. His 2024-2025 publications demonstrate continued work in self-healing microservices, lightweight encryption for video feeds, and virtual reality training environments. Professor Johansen is actively involved in mentoring students and research collaborators, as evidenced by his extensive publication record with numerous co-authors including doctoral students and postdoctoral researchers. His work has received funding through various research projects focused on data analytics, privacy technology, cybersecurity, and sports technology applications. He leads the interdisciplinary "Corpore Sano" center, which brings together researchers from computer science, sports science, medicine, health technology, and nutrition science. His work also involves collaboration with the "Njord" project focused on sustainable fishing through AI applications, and he's involved in developing the "Áika" distributed edge system for AI inference.

Ajitha Rajanمشاهده پروفایل

استاد

• Software Testing
• Software Verification
• Automated Testing
• +۱۲ مورد دیگر

Ajitha Rajan is a Professor (Personal Chair of Software Testing and Verification) at the School of Informatics, University of Edinburgh. Previously, she was a post-doctoral researcher at Oxford University's Computer Science Department and Laboratoire d'Informatique de Grenoble (LIG) in France. She earned her PhD in Computer Science from the University of Minnesota in August 2009 under the supervision of Prof. Mats Heimdahl. Her research spans two main directions: Automated Software Testing Techniques covering test input generation, test oracles, and coverage metrics; and Biomedical Artificial Intelligence focusing on cancer survival models, interpretability for biological sequences, and medical images. Her work bridges software engineering and biomedical applications, particularly in the development of trustworthy AI systems for healthcare. Professor Rajan leads several significant research projects including a Royal Society Industry Fellowship (2022-2025) on AutoTest for autonomous vehicle perception safety, the H2020 European Project KATY (2021-2025) on AI for genomics and personalized medicine where she serves as Edinburgh Lead PI, and an EPSRC Trustworthy Autonomous Systems Node project (2020-2024). Her recent publications demonstrate strong activity across software testing, explainable AI, and biomedical applications, with numerous papers accepted to top conferences in 2025 including ML for Healthcare, IJCAI, and ESEM. Among her scientific recognitions, she received the Best Reviewer Award at ISSTA'25. Her work has been consistently published in leading venues including ICSE, ICASSP, and Communications Biology. Professor Rajan actively mentors PhD students working on diverse topics from automated testing of speech recognition systems to explainable AI for medical image analysis and cancer immunotherapy. She teaches undergraduate courses in Software Testing, Computer Programming, and Embedded Systems, and has been instrumental in establishing several fully funded PhD positions through Centres for Doctoral Training at the University of Edinburgh.