جست‌وجوی استاد و پژوهشگر

Ramón García Alarciaمشاهده پروفایل

پژوهشگر

• Space Mission Design
• Systems Engineering
• Generative AI Applications
• +۳ مورد دیگر

Ramón García Alarcia is a Research Associate and Doctoral Candidate at the Chair of Spacecraft Systems, Technical University of Munich (TUM), under Prof. Alessandro Golkar. He holds dual Bachelor's degrees in Aerospace and Telecommunication Systems Engineering from the Polytechnic University of Catalonia (UPC), and a Master's in Aerospace Engineering (Space Systems specialization) from ISAE-SUPAERO. His research focuses on applying Large Language Models (LLMs) to streamline space mission design, particularly in requirements generation and high-level documentation. This work aims to reduce costs and democratize access to space. Key areas include generative AI for complex systems, autonomous space systems, and federated satellite networks. Ramón teaches courses on spacecraft systems, including 'Design and Simulation of Microsatellites' and 'Systems Engineering – Advanced.' He has authored/co-authored over a dozen peer-reviewed publications, covering topics like AI-driven mission design tools, event-based cameras for situational awareness, and telecommunication network analysis. His doctoral project involves developing a prototype AI-assisted mission design tool, leveraging generative models to enhance efficiency in early-stage spacecraft planning. Collaborations span institutions like ISAE-SUPAERO and UPC, with a focus on interdisciplinary aerospace challenges.

Toyin Ajibade Adisaمشاهده پروفایل

استاد

• Human Resource Management (HRM)
• Organizational Behavior (OB)
• Employee Relations in Sub-Saharan Africa
• +۴ مورد دیگر

Professor Toyin Ajibade Adisa is a faculty member at the University of East London (UEL), affiliated with the Royal Docks School of Business and Law and the Department of Strategy and Leadership. He holds the academic rank of Professor of Organisational Behaviour and HRM. As the course leader for the BSc Human Resource Management programme, he teaches both undergraduate and postgraduate courses in HRM and Organisational Behaviour. His research focuses on HRM/OB, Sub-Saharan Africa employee relations, diversity and inclusion, workplace discrimination, and work-life balance. He is a Senior Fellow of the Higher Education Academy, a Fellow of the Chartered Management Institute (CMI), and an Academy Fellow of the Chartered Institute of Personnel Development (CIPD). Professor Adisa’s research interests include African HRM practices, contemporary Sub-Saharan employment relations, and work-life interface dynamics. His recent publications emphasize racial and gender disparities in policing, tokenism among Black academics in the UK, and corporate ethics in Nigerian banking. He has authored/co-authored multiple books and edited volumes, including Work-Life Interface: Non-Western Perspectives (2021) and HRM 5.0: Unpacking the Digitalisation of Human Resource Management (2024). His work has been recognized with the Emerald Literati Network Award (2017). His articles highlight themes like workplace diversity, digitalization’s impact on HRM, and cultural barriers to work-life balance. Beyond academia, his research addresses practical challenges in global HRM, such as managing diasporic operations in banking and exploring military migrants’ career choices. He actively contributes to advancing HRM practices in developing economies and critically examines the intersection of culture and organizational policies.

Nizar Habashمشاهده پروفایل

استاد

• Natural Language Processing
• Computational Linguistics
• Arabic Language Processing
• +۱۲ مورد دیگر

Nizar Habash is a Professor of Computer Science at New York University Abu Dhabi (NYUAD) and a Global Network Professor at the Courant Institute of Mathematical Sciences. He is the director of the Computational Approaches to Modeling Language (CAMeL) Lab, where he leads research in natural language processing, computational linguistics, and Arabic language technologies. His educational background includes a BS in Computer Engineering and a BA in Linguistics and Languages from Old Dominion University, and MS and PhD degrees in Computer Science from the University of Maryland, College Park. Habash's research focuses on artificial intelligence, particularly natural language processing for Arabic and its dialects. His work spans machine translation, morphological and syntactic analysis, sentiment analysis, dialogue systems, and dialect identification. He has developed foundational resources such as the MADAR corpus, CODA orthography, and tools like MADAMIRA and CamelParser. His publications reflect a strong emphasis on creating robust, multilingual, and dialect-aware NLP systems for low-resource and complex linguistic environments. Habash has been involved in over 20 research grants and has authored more than 150 publications, including the influential book Introduction to Arabic Natural Language Processing . His recent work centers on improving machine translation, modeling Arabic orthography and morphology, and building large-scale annotated corpora for dialectal Arabic. His scientific recognition includes the ELRA Antonio Zampolli Prize in 2024 for outstanding contributions to language resources and evaluation in human language technologies. Habash advises numerous research projects and capstone theses at NYUAD. He has taught courses such as Natural Language Processing, Arabic Computational Linguistics, Discrete Mathematics, and the Computer Science Research Seminar. He has secured significant grant funding, particularly through projects like QALB and MADAR, which have advanced Arabic NLP research globally. He leads the CAMeL Lab, a vibrant research group focused on AI-driven language modeling, with active projects in Arabic readability (SAMER), dialect identification (ADIDA), dialogue systems (TOIA, BOTTA), and corpus development (GUMAR, Curras, Arab-Acquis).

Zhuowen Tuمشاهده پروفایل

استاد

• Computer Vision
• Machine Learning
• Deep Learning
• +۹ مورد دیگر

Zhuowen Tu is a Professor in the Department of Cognitive Science at the University of California, San Diego (UCSD), with an affiliate appointment in the Department of Computer Science and Engineering. He leads the Machine Learning, Perception, and Cognition Lab (mlPC), where his research lies at the intersection of computer vision, machine learning, deep learning, natural language processing, and neural computation, focusing on statistical models for structured, large-scale, and multi-modal data. He received his Ph.D. from The Ohio State University and held faculty positions at UCLA before joining UCSD in 2013. He also served as a Lead Researcher at Microsoft Research Asia (2011–2013) and was an Amazon Scholar (2021–2022). His academic trajectory includes progression from Assistant to Associate and then Full Professor at UCSD. His research interests span computer vision , deep learning , generative modeling , vision-language models , diffusion models , and structured prediction . He has made seminal contributions to image parsing, auto-context models, introspective neural networks, and holistically-nested edge detection. His recent work emphasizes Bayesian diffusion models, panoptic 3D parsing, and multimodal learning. The analysis of his recent publications shows a strong trend toward diffusion-based generative modeling , particularly in 3D vision, image restoration, and vision-language tasks. He also continues to advance work in multimodal understanding, continual learning, and efficient transformers. His lab actively publishes in top venues such as CVPR, ICCV, NeurIPS, and TPAMI. Selected Scientific Awards and Honors: IEEE Fellow David Marr Prize (2003) David Marr Prize Honorable Mention (2015) NSF CAREER Award (2009) Test-of-Time Award, AISTATS 2025 (for Deeply-Supervised Nets) First Prize, MICCAI Grand Challenge on Caudate Segmentation (2007) Talbert Abrams Award Honorable Mention (2003) Advising and Grants: He has advised numerous PhD students who are now faculty at NYU, CMU, and Stanford, or research scientists at Apple, Microsoft, Intel, and Facebook. His lab has been supported by significant grants from the National Science Foundation (NSF) , Office of Naval Research (ONR) , Intel , Qualcomm , Samsung , and Northrop Grumman . Current and recent grants include NSF IIS-2433768 on Bayesian Diffusion Models and NSF IIS-2127544 on Panoptic 3D Parsing. Laboratories and Teams: He leads the Machine Learning, Perception, and Cognition Lab (mlPC) at UCSD, which brings together students and researchers working on fundamental and applied problems in AI, vision, and cognition. The lab has strong collaborations with industry and other academic institutions.

• Cryptography
• Blockchain Technology
• 5G Network Security
• +۷ مورد دیگر

Professor Danilo Gligoroski is affiliated with the Norwegian University of Science and Technology (NTNU) under the Department of Information Security and Communication Technology. His work bridges cryptography, blockchain technology, and 5G network security, with a focus on decentralized systems and privacy-preserving protocols. Key research trends in his recent publications include blockchain applications in healthcare and reseller markets, verifiable delay functions for consensus mechanisms, and cryptographic frameworks for chat-based systems. He explores data integrity, network coding, and scalable storage solutions for blockchain ecosystems. Major collaborations include co-authors like Mayank Raikwar, Katina Kralevska, and Anton Karl Oskar Hasselgren. His work often intersects with GDPR compliance, network slice isolation, and secure service implementation in modern telecommunications.

Di Maمشاهده پروفایل

دانشیار

• Cybersecurity
• Privacy
• Applied Cryptography
• +۶ مورد دیگر

Di Ma is Associate Professor and Associate Dean for Graduate Education and Research in the College of Engineering and Computer Science at the University of Michigan-Dearborn. She also serves as Director of the Cybersecurity Center for Education, Research, and Outreach (CCERO) and the Security and Forensics rEsearch (SAFE) Lab, actively leading institutional cybersecurity initiatives since CCERO's founding in 2016. Her educational background includes: Ph.D. in Computer Science, University of California-Irvine (2009) Master of Engineering, Nanyang Technological University Bachelor of Engineering, Xi-an Jiaotong University Dr. Ma's research centers on security, privacy, and applied cryptography with emphasis on connected/autonomous vehicle systems (ECUs, infotainment), smartphone security (malware prevention, acoustic channels), and RFID/sensor protection. She investigates demographic inference from Wi-Fi metadata and develops location-aware cryptographic protocols, focusing on real-world vulnerabilities in transportation and mobile ecosystems. Her work bridges theoretical cryptography with practical safety-critical systems. Analysis of her 15 most recent publications reveals sustained leadership in automotive cybersecurity since 2012, with increasing focus on vehicle privacy (2019-2020), secure firmware updates, and cross-domain cryptographic access control. Key trends include adapting smartphone security techniques to automotive use cases and pioneering ambient sensor-based defenses against relay attacks, consistently published in IEEE flagship journals. Her scientific recognition includes: Trevor O. Jones Outstanding Paper Award (SAE, 2019) CECS Faculty Excellence Award for Research (2017) Tan Kah Kee Young Inventor's Award (Silver Medal, 2004) NSF-TRUST Fellowship (2009) Graduate Dean’s Dissertation Fellowship (UC Irvine, 2009) Air Force Summer Faculty Fellowship (AFOSR, 2011) Dr. Ma has advised PhD students including Ahmad Nasser (2019) and Nevrus Kaja (2019). Her research is funded by major grants from NSF (DGE-1419280 as PI, 2014), NHTSA (2015, 2017), AFOSR (2011), Ford (2016), Intel, and Research in Motion. Notably, she co-led a $7M Department of Energy project (2020) protecting EV charging infrastructure. As SAFE Lab Director, she develops security frameworks for mobile/IoT systems while CCERO coordinates university-wide cybersecurity education and outreach. Her teams include Vertically Integrated Project (VIP) groups designing automotive intrusion detection systems, and she organized the inaugural Dearborn Cybersecurity Day (2019) with 130+ industry participants.

Carla Lagorioمشاهده پروفایل

دانشیار

• Experimental Behavior Analysis
• Behavioral Pharmacology
• Behavioral Economics
• +۶ مورد دیگر

Dr. Carla Lagorio is an Associate Professor of Psychology at the University of Wisconsin-Eau Claire, affiliated with the College of Arts and Sciences. She conducts research in experimental and theoretical behavior analysis, with specific focus areas including behavioral economics, pharmacology, and social/environmental sustainability applications. Education : Postdoctoral work at University of Michigan (Behavioral Pharmacology), Ph.D. and M.A. from University of Florida (Experimental Psychology - Behavioral Science), B.S. from University of Wisconsin-Eau Claire (Psychology - Behavior Analysis) Her research explores: Risky choice decision-making mechanisms Compulsive-type behavior patterns Delay discounting processes Behavioral economics principles Behavioral pharmacology interactions Social/environmental sustainability applications Dr. Lagorio's publications demonstrate expertise in behavioral neuroscience, cognitive psychology, and comparative analysis. Her work spans from basic research in animal models to applied interventions addressing real-world problems like food waste reduction and canine adoptability. Scientific Awards : Multiple research competition placements, honor society recognition, and specialized program funding Advising : Mentors students in applied behavior analysis, drug administration studies, and sustainability initiatives Professional Roles : Past-President of Mid-American Association for Behavior Analysis, Treasurer for Society for Quantitative Analysis of Behavior, program coordinator for ABA International

• Machine Translation
• Natural Language Processing
• Computational Linguistics
• +۷ مورد دیگر

Dr. Steffen Eger is a professor at the Technical University of Darmstadt, focusing on Natural Language Processing, Machine Translation, and Computational Linguistics. His work spans both theoretical and applied aspects of NLP, including adversarial robustness, evaluation metrics, and creative text generation. Key Contributions: • Pioneering research in LLM-based evaluation metrics • Development of efficient translation quality frameworks • Analysis of social solidarity in historical discourse • Exploration of poetic creativity through neural models His recent publications demonstrate expertise in: - Human-Aware Translation Evaluation - Summarization of Historical Texts - Adversarial Defense Mechanisms - Explainable AI for Generation Metrics While no explicit awards or student supervision details are provided, his collaborative work appears across major NLP venues like ACL, EMNLP, and COLING. His research frequently intersects with human-centric NLP tasks, emphasizing reproducibility and robustness in system design.

Thomas J Riveraمشاهده پروفایل

استادیار

• Blockchain Economics
• Corporate Finance
• Banking
• +۳ مورد دیگر

Thomas J Rivera is an Assistant Professor of Finance at the Desautels Faculty of Management, McGill University. He holds a PhD in Economics and Decision Sciences from HEC Paris (2020), an M.Sc in Economics from Toulouse School of Economics (2012), and an MA in Economics and Finance from Barcelona Graduate School of Economics (2011). Current affiliation: Desautels Faculty of Management, McGill University Research focus: Theoretical issues in DeFi, blockchain economics, banking stability, corporate finance, and incomplete information Member of the Finance Theory Group Education: PhD, HEC Paris, Economics and Decision Sciences (2020) M.Sc, Toulouse School of Economics (2012) MA, Barcelona Graduate School of Economics (2011) Research Interests: His work bridges blockchain economics and traditional finance. Key areas include decentralized finance (DeFi) protocols, proof-of-work vs proof-of-stake mechanisms, liquidity modeling in decentralized exchanges, corporate signaling under information asymmetry, and banking regulation. His research employs economic modeling to address technical challenges in blockchain systems and financial markets. Scientific Contributions: Thomas has published in top journals like Review of Financial Studies, Management Science, and Review of Finance. His recent work includes economic models of decentralized exchanges, equilibrium staking dynamics, and corporate finance implications of blockchain technology. He has been recognized with the PBCSF Award for Best Paper in Fintech (2024). Recognition: PBCSF Award - Best Paper in Fintech (2024) Mentioned in multiple research recognitions at McGill Desautels Faculty of Management

• Computational Complexity
• Cryptography
• Zero-Knowledge Proofs
• +۵ مورد دیگر

Boaz Barak is a Professor at the Weizmann Institute of Science in the Department of Computer Science, Faculty of Mathematics and Computer Science. With an h-index of 64 and over 17,301 citations, he is a leading researcher in theoretical computer science with significant contributions spanning computational complexity, cryptography, and machine learning theory. His research interests include: Computational Complexity Cryptography Zero-Knowledge Proofs Program Obfuscation Interactive Proofs Privacy-Preserving Computation Machine Learning Theory Barak's publication record reveals a trajectory from foundational work in theoretical computer science to contemporary research at the intersection of theory and practice. His early work established impossibility results for program obfuscation and advanced techniques for zero-knowledge proofs beyond black-box simulation. His influential textbook "Computational Complexity: A Modern Approach" has become a standard reference in the field. More recently, his research has expanded into machine learning phenomena like double descent and scaling laws for language models, demonstrating the evolving nature of his theoretical contributions. His work consistently bridges deep theoretical insights with practical implications for computing. His notable collaborations include extensive work with Sanjeev Arora (77 publications, 6,879 citations), David Steurer (95 publications, 4,945 citations), and Oded Goldreich, among others. Professor Barak leads a research group at the Weizmann Institute focused on theoretical aspects of computer security and complexity theory. His work has been consistently supported by major research funding, enabling significant contributions to the theoretical foundations of computer science. He maintains an active research program with publications spanning over two decades, demonstrating sustained impact in multiple subfields of theoretical computer science.

• Machine Learning
• Artificial Intelligence
• Computer Vision
• +۷ مورد دیگر

Xinchao Wang is an Assistant Professor and Presidential Young Professor in the Department of Electrical and Computer Engineering at the National University of Singapore (NUS), College of Design and Engineering. He leads the xML Lab, focusing on machine learning and artificial intelligence. Prior to joining NUS, he was an Assistant Professor at Stevens Institute of Technology in the Department of Computer Science and a Postdoctoral Researcher at the Beckman Institute, University of Illinois Urbana-Champaign, under the late Professor Thomas Huang. He earned his Ph.D. in Computer Vision from École polytechnique fédérale de Lausanne (EPFL) under Professor Pascal Fua and a B.Sc. in Computing from the Hong Kong Polytechnic University with first-class honors and a perfect GPA. His research spans machine learning, computer vision, and artificial intelligence, with a focus on diffusion models, vision-language models, 3D generation, and dataset distillation. His recent publications demonstrate strong trends in efficient generative modeling, including acceleration techniques for diffusion models, 3D scene reconstruction, and novel architectures for vision and language tasks. His work frequently appears in top-tier conferences such as CVPR, NeurIPS, ICCV, ECCV, and ICLR. AI's 10 to Watch, IEEE (2025) Young Research Award, NUS (2025) Young Research Award, NUS CDE (2024) Best Paper Award, IEEE VCIP 2022 Outstanding Early Career Award, NUS CDE (2023) College Teaching Excellence Award, NUS CDE (2023) He actively advises Ph.D. students, many of whom have received prestigious awards including the Google Fellowship and ByteDance Scholarship. He has served as an Associate Editor for IEEE Transactions on Image Processing since 2023. His lab is actively recruiting Ph.D. students, postdocs, visiting scholars, and research assistants in machine learning and AI. He teaches core courses at NUS including Introduction to Machine Learning, Deep Learning, and Pattern Recognition.

• Special Education
• Applied Behavior Analysis
• Early Childhood Special Education
• +۱۳ مورد دیگر

Jennifer Neyman is a Senior Lecturer in the Special Education & Applied Behavior Analysis Department at Gonzaga University, where she teaches evidence-based instruction, inclusive practices, behavior management, and response-to-intervention strategies. She also oversees the Early Childhood Special Education Program and directs the on-campus Integrated Lab Preschool, providing inclusive education for young children with and without disabilities. Education: B.Ed., Special Education, Gonzaga University M.Ed., Special Education, Gonzaga University Her research and teaching focus on applied behavior analysis and academic interventions in special education. She emphasizes bridging theory and practice through action research, guiding both undergraduate and graduate students in designing and implementing evidence-based strategies. Her work spans interventions in reading, mathematics, spelling, handwriting, behavior management, and communication for students with diverse disabilities including autism, intellectual disabilities, and learning disabilities. Her recent publications and conference presentations (2023–2024) demonstrate a consistent focus on direct instruction methods such as flashcards, racetrack procedures, model-lead-test, token economies, and precision teaching. These studies target skill acquisition in academic, behavioral, and life skills domains across preschool, elementary, middle, and high school settings. The research often involves students with autism spectrum disorder, learning disabilities, ADHD, and developmental delays, primarily in self-contained or inclusive classrooms. Scientific Awards: No awards listed in the provided text. Jennifer Neyman actively mentors students, co-authoring numerous research projects with them, particularly through undergraduate research conferences such as the Spokane Intercollege Research Conference. She emphasizes field supervision and maintains strong connections with K–12 classrooms. She also contributes to college-level instruction by promoting data-based decision-making among teacher candidates. Her work is deeply rooted in practitioner-focused, behavior-analytic approaches to improving educational outcomes for individuals with special needs. She leads the Integrated Lab Preschool, an on-campus facility that serves as both an educational program for young children and a training ground for future special educators. This lab supports experiential learning and applied research in early childhood special education and inclusive practices.

Valentina Gatteschiمشاهده پروفایل

دانشیار

• Blockchain
• Ethereum
• Human-computer interaction
• +۶ مورد دیگر

Valentina Gatteschi is an Associate Professor at the Department of Control and Computer Engineering (DAUIN) at the Polytechnic University of Turin, Italy. She is a member of the GRAphics and INtelligent Systems (GRAINS) research group and has been actively involved in teaching and research in the fields of blockchain technology, human-computer interaction, and distributed systems. Dr. Gatteschi received her BSc and MSc degrees in management engineering and her PhD degree in computer engineering from Politecnico di Torino in 2005, 2008, and 2013, respectively. Her research focuses on blockchain technology, smart contracts, and their applications across various domains. She has made significant contributions to understanding how blockchain can be applied in areas such as decentralized finance, sustainable mobility, energy data marketplaces, and digital identity. Her work often bridges the gap between theoretical blockchain concepts and practical implementations, with a particular emphasis on user experience and system integration. She has led several research projects including "B4A - Blockchain for All" (2023-2025), which aims to make blockchain technology more accessible to diverse user groups. Her recent publications reveal a strong trend toward practical blockchain applications, particularly in sustainability contexts (CO2 tracking, circular economy), finance (DeFi), and transportation (smart mobility solutions). She has also been exploring the intersection of blockchain with emerging technologies like large language models for smart contract generation and analysis. Dr. Gatteschi serves as a supervisor for PhD students working on blockchain-related topics, including Alberto Butera (researching Blockchain Technology for Intelligent Vehicles) and Emanuele Antonio Napoli (analyzing smart contracts). She has been involved in multiple research projects funded by both national and commercial sources, demonstrating the practical relevance of her work to industry and government sectors. She is actively involved in teaching courses related to information visualization, digital transformation technologies, and database systems at both undergraduate and graduate levels at the Polytechnic University of Turin.

• B2B Marketing
• Innovation Management
• Marketing Strategy
• +۷ مورد دیگر

Maria Restuccia is an Associate Professor in Marketing (Strategy and Marketing) at the University of Sussex Business School, where she has been a faculty member since 2014. She holds a PhD in Business Administration from HEC Montréal, an M.Sc. in Marketing from the same institution, and a Bachelor of Economics and Management for Arts, Culture, and Communication from Bocconi University, Italy. She also completed a PGCertHE at the University of Sussex. PhD in Business Administration, HEC Montréal, Canada M.Sc. in Business Administration (Marketing), HEC Montréal, Canada Bachelor of Economics and Management for Arts, Culture and Communication, Bocconi University, Milan, Italy PGCertHE, University of Sussex, United Kingdom Maria's research centers on B2B marketing and innovation management, with a strong emphasis on healthcare and the creative industries. She has recently focused on the impact of Non-Fungible Tokens (NFTs) and blockchain technology in creative sectors. Her work bridges academic rigor with practical relevance, exploring branding, digital transformation, and sustainability in global markets, particularly in Africa and the UK. Her recent publications reveal a clear trend toward digital innovation, especially in the creative economy. She investigates how NFTs are reshaping art markets, how B2B brands position themselves in emerging economies, and how sustainability is being driven by funding organizations in cultural sectors. Her research combines qualitative and quantitative methods, often involving content analysis and managerial interviews. Maria has secured significant research grants, including projects funded by the British Academy and the Academy of Marketing, focusing on NFTs and university spin-outs. She actively contributes to the academic community through peer review for journals such as the Journal of Product Innovation Management and conferences like the European Marketing Academy Conference. She has played a key role in curriculum development, leading the restructuring of the MSc in Strategic Marketing and designing courses in B2B marketing, global marketing, and new product development. Her teaching spans online, hybrid, and in-person formats, reflecting her adaptability and commitment to pedagogical innovation. Maria is also involved in collaborative research networks and maintains an active professional presence through her website and LinkedIn. She is a fluent speaker of English, French, Italian, and is learning Spanish and Portuguese.

Tjerand Sildeمشاهده پروفایل

دانشیار

• Lattice-Based Cryptography
• Zero-Knowledge Protocols
• Post-Quantum Cryptography
• +۹ مورد دیگر

Tjerand Silde is an Associate Professor in Cryptology at the Department of Information Security and Communication Technology at the Norwegian University of Science and Technology (NTNU). He serves as Research Group Leader of the NTNU Applied Cryptology Lab and as Security and Cryptography Expert at Pone Biometrics . His academic journey includes a PhD thesis titled Privacy-Preserving Cryptography from Zero-Knowledge Proofs (2022). Primary affiliation: NTNU (Department of Information Security and Communication Technology) Secondary affiliation: NTNU Department of Mathematical Sciences Industry role: Security and Cryptography Expert at Pone Biometrics His research focuses on lattice-based cryptography and zero-knowledge protocols , with broader interests in post-quantum cryptography , anonymous communication , multiparty computation , homomorphic encryption , electronic voting , and secure implementation . The research demonstrates trends in advancing lattice-based cryptographic solutions for real-world applications, particularly in authentication, e-voting, and secure communication. Notable scientific achievements include receiving a 765K NOK equipment grant from the IE Faculty - Research (2025) to establish the CRYPTO-LAB for cryptographic research and education. He has held leadership roles as General Chair for IACR PKC 2025 and coordinates the Cryptographic Engineering profile in NTNU's master's program. His teaching portfolio includes courses like TTM4205 Secure Cryptographic Implementations , IIK8105 Quantum-Secure Cryptography , and TM8107 Cryptographic Protocols and Applications . He actively supports Electronic Frontier Foundation , Tor Project , and Signal Foundation .