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Karl-Erik ÅrzénView profile

Professor

• Control Engineering
• Cyber-Physical Systems
• Real-Time Systems
• +9 more

Karl-Erik Årzén is Professor and Head of the Department of Control Engineering at Lund University's Faculty of Engineering. He is also Co-director of the Wallenberg AI, Autonomous Systems and Software Program (WASP) and a key member of ELLIIT, the excellence center in information technology. His roles include leadership in AI and digitalization profile areas at both LTH and Lund University. His research lies at the intersection of control engineering and computer science, with a focus on cyber-physical systems, real-time systems, embedded control, and resource management in cloud and edge computing environments. He has pioneered methods for predictable performance in cloud applications and dynamic resource allocation using control-theoretic approaches. The recent publications highlight a strong trend in control over the cloud and edge, real-time scheduling co-design, distributed camera systems, and reinforcement learning for auto-scaling. Key topics include model predictive control, LQG-based scheduling, bandwidth allocation, and robustness in cyber-physical systems. The work spans theoretical control design and practical implementation in distributed systems. His scientific awards include multiple Best Paper Awards from IEEE and ACM conferences in 2018, 2016, and 2004, recognizing excellence in autonomic computing, edge computing, and real-time systems. Best Paper Award, IEEE International Conference on Autonomic Computing, 2018 Best Paper Award, IEEE International Conference on Edge Computing (EDGE), July 2018 Best Paper Award - RTNS 2016 Best Paper Award - RTCSA 2004 Årzén has supervised over 20 PhD students, including Mikael Johansson, Anton Cervin, Yang Xu, and Per Skarin, and currently supervises Ahmed Al Bayati and Max Nyberg Carlsson. His grant portfolio includes major projects such as WASP, AORTA (VINNOVA), and ELLIIT's 'Robust and Secure Control over the Cloud'. He has also contributed to innovation through tools like TrueTime and Jitterbug. He leads the RobotLab LTH initiative and is involved in the Nordic University Hub on Industrial Internet of Things (HI2OT). His work bridges academia and industry, with collaborations on adaptive control, cloud-native systems, and autonomous robotics.

Nicola BreugstView profile

Professor

• Entrepreneurship
• Psychology of Entrepreneurship
• Entrepreneurial Teams
• +3 more

Prof. Nicola Breugst is a Professor of Entrepreneurial Behavior at the TUM School of Management, Technical University of Munich. Her research focuses on the psychological dimensions of entrepreneurship, particularly the interplay between founders' thought processes, emotions, and their social/environmental contexts. She explores how entrepreneurial teams influence decision-making, employee motivation, and venture success. Her work challenges the 'lone entrepreneur' myth, emphasizing systemic interactions between founders and their ecosystems. Education: B.A. in Psychology from Ludwig Maximilian University of Munich; Ph.D. in Entrepreneurship from Friedrich Schiller University Jena. Professional Experience: Held academic roles at the University of Duisburg-Essen, Max Planck Institute for Economics, Indiana University Kelley School of Business, and National University of Singapore. Research Interests: Entrepreneurial cognition, team dynamics, equity distribution, founder relationships, and the socio-economic factors shaping new ventures. Notable contributions include studies on trust in teams, envy's role in performance, and pivoting strategies in uncertain markets. Awards: 2022 Teaching Excellence Award (TUM School of Management), 2020 Best Paper in Entrepreneurial Cognition (Academy of Management), and multiple recognitions for mentorship and scholarly contributions. Grants/Advising: Extensive supervision of doctoral students (2018 award), with research supported by international collaborations. Active in entrepreneurial education and cross-cultural studies.

Richard EvansView profile

Associate Professor

• Digital Innovation
• Human-Computer Interaction (HCI)
• Visualization
• +6 more

Richard Evans is an Associate Professor in Digital Innovation at the Faculty of Computer Science, Dalhousie University, where he contributes to research and teaching in digital transformation, human-computer interaction, and information management. He is actively involved in the IEEE Technology and Engineering Management Society, currently co-chairing the Design and Engineering Technical Activity Committee and serving on the editorial board of IEEE Transactions on Engineering Management . His educational background includes a PhD in Knowledge Management for Collaborative Product Design from the University of Greenwich (2013), a PG Cert in Higher Education (2015), an MSc from the University of Wales (2010), and a BA (Hons.) from the University of Exeter (2008). Richard's research focuses on digital innovation and transformation, with strong emphasis on design and engineering management, information systems, and knowledge management in distributed environments. His work bridges academic research and industrial applications, particularly in aerospace and manufacturing sectors. He has published over 90 scientific papers and helped co-found the International Conference on Artificial Intelligence for Good , highlighting his commitment to socially beneficial technology. His research output spans topics such as collaborative systems, user-centered design, and knowledge modeling, indicating a consistent trajectory toward human-centric technological innovation and digital transformation strategies. University of Greenwich prize for Best PhD student in 2013 Richard has supervised and mentored students at various levels during his tenure at multiple institutions including Brunel University London, University of Westminster, and Dalhousie University. He has secured research funding through industrial partnerships such as BAE Systems and has built a global network of academic and industry collaborators. His work often involves interdisciplinary grants focused on engineering management, digital design, and AI for societal good. Richard is affiliated with key research clusters in HCI, Visualization & Graphics at Dalhousie and leads initiatives connecting design, engineering, and digital innovation. He collaborates with international teams through IEEE and co-founded a major conference promoting ethical AI, demonstrating strong leadership in building research communities.

• Medical Physics
• Radiation Oncology
• Therapeutic Radiology
• +7 more

Huixiao Chen is an Assistant Professor and Clinical Medical Physicist II in the Department of Therapeutic Radiology at Yale School of Medicine. She holds a primary appointment in Therapeutic Radiology and is actively engaged in clinical and research activities related to radiation oncology physics. Assistant Professor, Department of Therapeutic Radiology, Yale School of Medicine Clinical Medical Physicist II, Therapeutic Radiology Education: Resident, Yale University (2016) Postdoctoral Fellow, Harvard University (2013) Postdoctoral Fellow, Virginia Commonwealth University (2011) PhD, University of Heidelberg, Germany (2010) MS, Zhejiang University, China (1998) BS, Zhejiang University, China (1995) Huixiao Chen's research centers on medical physics in radiation oncology, with a focus on treatment planning optimization, dosimetry, and image-guided radiotherapy. Her work includes the development and evaluation of advanced radiotherapy techniques such as VMAT and SBRT, with applications in spine, lung, and prostate cancers. She has contributed to improving the accuracy of dose calculations using Monte Carlo methods and has explored the impact of patient motion on treatment delivery. Her research also extends to the design of clinical devices to support safe and effective radiotherapy for diverse patient populations. Her recent publications demonstrate a consistent focus on enhancing the precision and efficiency of radiotherapy. Key themes include multicriteria optimization in treatment planning, dosimetric validation of radiochromic films, and the development of supportive devices for image-guided radiotherapy. These works reflect a strong commitment to advancing clinical medical physics through both computational and engineering innovations. Scientific Contributions: Characterization of GafchromicTM EBT4 film for clinical dosimetry Design of a small-footprint couch-top support for heavy patients in IGRT Application of multicriteria optimization in VMAT planning for spine and prostate cancers Comparison of Monte Carlo vs. pencil beam algorithms in lung SBRT Analysis of diaphragm motion effects on spine SBRT Huixiao Chen has collaborated with researchers such as Emily Draeger and Zhe Jay Chen on various projects. While no formal students or grants are listed, her role as a clinical medical physicist and faculty member suggests active mentorship and potential involvement in funded research. She is a key contributor to the medical physics team at Yale, ensuring high standards in treatment planning and delivery.

• Reliability Engineering
• Asset Management
• Maintenance Optimization
• +13 more

Patrik Hilber is a Professor at KTH Royal Institute of Technology, working in the Division of Electromagnetic Engineering and Fusion Science within the School of Electrical Engineering and Computer Science (EECS). He serves as Deputy Director of First and Second Cycle Education at EECS and heads the QED AM research group. He is also a board member of YH-electrical engineering. Research Interests: His research focuses on reliability engineering, asset management, maintenance optimization, and smart grid technologies in electric power systems. Key areas include transmission and distribution systems, dynamic line and transformer rating, wind power integration, multiobjective optimization, condition monitoring, and data quality in power systems. He applies advanced modeling and data-driven approaches to improve power system planning, operation, and resilience. The recent trends in his publications (2020–2025) highlight a strong emphasis on dynamic rating technologies (DLR and DTR), data quality and machine learning applications in outage analysis, reliability-centered planning for wind farms and distribution systems, and the integration of renewable energy and electric vehicles. His work bridges theoretical modeling with practical utility applications. Teaching and Academic Leadership: He is examiner and course responsible for several degree projects in electrical engineering, power systems, and energy innovation. He also teaches courses on reliability evaluation, asset management, and innovation in electric power engineering. Publications and Books: He has authored a book titled Reliability Analysis and Asset Management Applied to Power Distribution (2014) and a book chapter on cable segment replacement optimization. His scholarly output includes numerous peer-reviewed articles in leading journals such as IEEE Transactions on Power Systems , Reliability Engineering & System Safety , and Applied Energy . Education: He holds a Ph.D. (2008), a Licentiate degree (2005), and an M.Sc. (2000), all from KTH. He became a Docent (Associate Professor) in 2014.

• Migration Policy
• Refugee Policy
• Local Governance
• +3 more

Hannes Schammann is Professor of Political Science with a focus on migration policy at the University of Hildesheim , where he leads the Migration Policy Research Group since 2018. His work bridges academic research and practical implementation through the Research and Transfer Center for Migration Policy , addressing migration, integration, and refugee policy challenges. In January 2025, he joined the German Council of Experts on Integration and Migration (SVR) as a scientific advisor. Research Focus: Schammann specializes in local authorities' scope for action in refugee-related migration, national migration policy analysis, and educational integration aspects. He co-authored the textbook Migration Policy (2021) and contributes to international journals like Journal of Refugee Studies and Journal of Ethnic and Migration Studies . Key Projects: He leads third-party funded initiatives including Match'In (algorithmic asylum seeker distribution), SOLDISK (solidarity discourses in migration), Country.Home.Future (rural integration), When Mayors Make Migration Policy (municipal EU influence). Expert Engagements: Schammann serves on editorial boards including Zeitschrift für Flucht- und Flüchtlingsforschung , and participates in advisory roles for institutions like the German Federal Ministry for Family Affairs and Robert Bosch Foundation . He also engages in public discourse through media appearances in Deutschlandfunk , ARD , and SWR regarding migration challenges.

Alex John LondonView profile

Professor

• Ethics of Artificial Intelligence
• Bioethics
• Research Ethics
• +5 more

Alex John London is the K&L Gates Professor of Ethics and Computational Technologies at Carnegie Mellon University, where he also serves as co-lead of the K&L Gates Initiative in Ethics and Computational Technologies, Director of the Center for Ethics and Policy, and Chief Ethicist at the Block Center for Technology and Society. His work spans multiple institutions, including affiliations with the Center for Bioethics and Health Law at the University of Pittsburgh. Dr. London earned his Ph.D. in Philosophy from the University of Virginia, followed by a post-doctoral fellowship at the University of Minnesota's Center for Bioethics. He joined Carnegie Mellon University in 2000 and has established himself as a leading scholar in ethics at the intersection of technology, medicine, and policy. His academic journey includes being a Visiting Scholar at Harvard University's Program in Ethics and Health. Professor London's research spans ethical and policy issues surrounding novel technologies in medicine, biotechnology and artificial intelligence, methodological issues in theoretical and practical ethics, and cross-national issues of justice and fairness. His work in AI ethics critically examines structural obstacles to safe and effective technologies, challenges conventional notions of algorithmic bias, and questions requirements for explainability in medical contexts. His foundational work on clinical equipoise and the 'integrative approach' to risk assessment has shaped research ethics guidelines globally. He has made significant contributions to international research ethics, particularly regarding justice, responsiveness to host community health needs, and post-trial access. Professor London's scholarly output demonstrates a trajectory toward addressing the ethical challenges of emerging technologies, with increasing focus on justice-led approaches to AI innovation, accountability frameworks, and the sociotechnical dimensions of healthcare AI systems. His work increasingly addresses how AI can be designed to respect human dignity while navigating complex ethical terrain in healthcare settings. New Directions Fellowship from the Andrew W. Mellon Foundation (2005, 2010) Hastings Center Fellow (2011) Elliott Dunlap Smith Award for Distinguished Teaching (2016) Distinguished Service Award from the American Society of Bioethics and Humanities (2017) As an educator, Professor London teaches courses on ethical theory, bioethics, ethics and AI, and research ethics. His influential textbook 'Ethical Issues in Modern Medicine' (8th edition) is one of the most widely used resources in medical ethics education. His book 'For the Common Good: Philosophical Foundations of Research Ethics' (2022) provides a comprehensive framework for understanding research ethics as serving the common good. Professor London has advised numerous students and mentored early-career researchers in bioethics and technology ethics. His policy work extends to multiple national and international organizations including the World Health Organization Expert Group on Ethics and Governance of AI, the National Academy of Medicine Action Collaborative, and the U.S. National Science Advisory Board for Biosecurity. Professor London leads several significant research initiatives, including serving as co-leader of the ethics core for the NSF AI Institute for Collaborative Assistance and Responsive Interaction for Networked Groups (AI-CARING). His Center for Ethics and Policy at CMU serves as a hub for interdisciplinary research addressing pressing ethical challenges in technology and healthcare. He is actively involved in shaping policy through his membership on the steering committee of the AAAI/ACM Conference on Artificial Intelligence, Ethics and Society (AIES) and his co-chair role in the U.S. National Academies planning committee on computational modeling of biological agents.

• Adaptive nonparametric statistics
• High-dimensional data analysis
• Financial time series modeling
• +5 more

Prof. Vladimir Spokoiny is a leading figure in stochastic algorithms and nonparametric statistics at the Weierstrass Institute for Applied Analysis and Stochastics (WIAS) and Humboldt University of Berlin . His work bridges mathematical statistics with practical applications in finance, medicine, and machine learning. Born in 1959 in Moscow, USSR PhD from Lomonosov Moscow State University (1988) Habilitation from Humboldt University (1996) Head of WIAS research group since 2000 Professor at Humboldt University since 2002 Spokoiny's research focuses on adaptive nonparametric methods, high-dimensional data analysis, and statistical finance. His innovations in local homogeneity testing and propagation-separation methods have advanced volatility modeling, image analysis, and manifold learning. He employs Bayesian optimization frameworks and stochastic control techniques for financial instrument pricing. Recent scientific contributions include generalized bootstrap procedures for Bures-Wasserstein barycenters (2024), dimension-free Laplace approximation bounds (2023), and structure-adaptive manifold estimation (2022). His 19+ PhD students and editorial roles in top journals like The Annals of Statistics demonstrate sustained academic impact. International Statistical Institute member American Statistical Association fellow Institute of Mathematical Statistics member Bernoulli Society member

Simon DeakinView profile

Professor

• Tort Law
• Contract Law
• Labour Law
• +7 more

Professor Simon Deakin is a Fellow and Director of Studies in Law at Peterhouse, University of Cambridge, specializing in private law (tort and contract law) and labour law. He teaches on the undergraduate Law Tripos and the LLM programme, with research focusing on law and economics, artificial intelligence, and historical legal analysis. Current research on Is Law Computable? and AI ethics Co-editor of computational law essay collection Developed Cambridge Leximetric Database for quantitative legal analysis His research spans tort law, corporate governance, digital economy regulation, and sustainability. Recent work explores the Anthropocene's legal implications and labour law's computational approaches. Scientific awards include the Cambridge Students' Union teaching prize (2023) He supervises doctoral students annually and contributes to legal education through widely used textbooks. As a Centre for Business Research (CBR) affiliate, he advances data-driven analysis of global labour regulation.

• Magnetic Materials
• Soft Magnetic Composites
• Nanomaterials
• +5 more

Michael E. McHenry is a Professor of Materials Science and Engineering at Carnegie Mellon University's College of Engineering. He holds appointments with multiple research centers including the Data Storage Systems Center, Engineering Research Accelerator, Materials Research Science and Engineering Center, and Wilton E. Scott Institute for Energy Innovation. Dr. McHenry received his BS in Metallurgical Engineering and Materials Science from Case Western Reserve University in 1980, his PhD in Materials Science and Engineering from MIT in 1988, and completed a postdoctoral fellowship at Los Alamos National Laboratory. His research focuses on soft magnetic nano-composites for power and energy applications, with particular expertise in metal amorphous nanocomposites (MANCs) for high-efficiency electric motors and power systems. His work spans advanced materials processing, magnetic properties under various conditions, and rare earth materials criticality. His research portfolio demonstrates a clear progression toward practical applications of magnetic materials, particularly in high-power density, high-efficiency motors that can operate at high rotational speeds with minimal energy loss. His publications reveal a strong focus on translating fundamental materials science into engineering solutions for energy conversion, with significant emphasis on rare earth-free alternatives and high-frequency applications. IEEE Distinguished Lecturer (2013) TMS Awardee for Research Excellence (2014) Subject of TMS Symposium in Honor of M. E. McHenry (2016) NATO Series Lecturer on Rare Earth Criticality (2016/17) Dr. McHenry has co-founded CorePower Magnetics Inc. with Paul Ohodnicki and Samuel Kernion, commercializing soft magnetic technologies with applications in grid modernization and electric vehicles. His extensive publication record and leadership in major research initiatives including a MURI on high-temperature magnetic materials and an ARPA-E program demonstrate significant impact in both academic and industrial contexts. He has served in various leadership roles for Magnetism and Magnetic Materials and Intermag Conferences, and continues to advise on rare earth scarcity issues for organizations like NATO.

Andrew F. BrahamView profile

Professor

• Asphalt Emulsion
• Pavement Maintenance and Rehabilitation
• Sustainability in Civil Engineering
• +3 more

Andrew F. Braham is a Professor in the Department of Civil Engineering at the University of Arkansas, College of Engineering. He holds a Ph.D. from the University of Illinois at Urbana-Champaign and is a licensed Professional Engineer (P.E.). His research focuses on asphalt emulsion technology, pavement maintenance and rehabilitation, and sustainability in civil engineering. Dr. Braham directs a comprehensive laboratory specializing in flexible pavement materials research and serves as Associate Director of the Southern Plains Transportation Center. Dr. Braham earned his Ph.D. from the University of Illinois at Urbana-Champaign (2008), M.S. (2002) and B.S. (2000) from the University of Wisconsin-Madison. Following his doctoral studies, he completed a Post-Doctoral Research Fellowship at Southeast University in Nanjing, China (2009-2010). His research interests center on asphalt emulsion technology, pavement maintenance and rehabilitation techniques, and sustainability applications in civil engineering. Dr. Braham has developed innovative testing methodologies for asphalt emulsion particle size analysis and has extensively studied cold in-place recycling and full-depth reclamation processes. His work bridges laboratory research with practical field applications, focusing on extending pavement life while reducing costs and environmental impacts. Analysis of Dr. Braham's recent publications reveals a strong focus on asphalt emulsion characterization, pavement preservation techniques, and sustainable infrastructure solutions. His research spans material science, transportation engineering, and environmental considerations, with particular emphasis on practical applications for state transportation agencies. The work demonstrates progression from fundamental material characterization to applied field implementation and economic analysis. Associate Director of Southern Plains Transportation Center (SPTC) (2023-present) Chair of TRB Committee AKN18 'Pavement Maintenance, Preservation, and Rehabilitation' (2025-present) Co-chair of AASHTO TSP-2 Emulsion Task Force Research Subcommittee (2023-present) Member of International Slurry Surfacing Association (ISSA) Sustainability Committee (2025-present) Dr. Braham has advised numerous graduate students through their doctoral and master's research, with many now working in transportation agencies and research institutions. His research has been funded by diverse sources including the Arkansas Department of Transportation, Federal Highway Administration, National Science Foundation, and various industry associations. He has developed and taught multiple courses on transportation infrastructure, sustainability in civil engineering, and pavement design. His laboratory capabilities include comprehensive testing for asphalt binder, asphalt emulsion, and asphalt mixture analysis. He also directs the TREAT Mobile Lab, which provides hands-on training for asphalt emulsion applications and pavement preservation techniques across the country.

Yuzhe YangView profile

Assistant Professor

• Machine Learning
• Artificial Intelligence
• Healthcare Technology
• +3 more

Yuzhe Yang is an Assistant Professor of Computational Medicine and Computer Science at UCLA, with a visiting research scientist role at Google Health. He holds a PhD in Computer Science from MIT (2024), advised by Dina Katabi, and a B.S. with honors from Peking University. Research Focus: Machine learning for healthcare, medical AI fairness, and AI-driven biomedical discovery Key Contributions: Ten Notable Advances (Nature Medicine) and Ten Crucial Advances (The Lancet Neurology) His lab develops Trustworthy Learning Algorithms and Generalist Health Models that integrate Multimodal Data for personalized health coaching. Notable projects include AI-based Parkinson's Disease Biomarkers via nocturnal breathing and Foundation Models for Equitable Medicine . Recent publications at ICLR 2025 (wearable foundation models), Nature Medicine 2024 (medical AI fairness), and Science Advances 2025 (vision-language medical bias) highlight his interdisciplinary work. He serves on ML4H workshops and reviews for top conferences like NeurIPS and ICML. Awards include Forbes 30 Under 30 , Takeda Fellowship , and Baidu PhD Fellowship . Advising opportunities: Recruiting PhD students (CS/CompMed) and postdocs in AI for health. Lab: Health Intelligence Lab (HAIL)

Sebastian SeungView profile

Professor

• Neuroscience
• Machine Learning
• Connectomics
• +5 more

Sebastian Seung is a Professor at Princeton University , affiliated with both the Department of Computer Science and the Princeton Neuroscience Institute . His career spans Harvard University (Ph.D., 1990), Bell Laboratories, and Massachusetts Institute of Technology before joining Princeton in 2014. An External Member of the Max Planck Society and 2008 Ho-Am Prize recipient, Seung merges machine learning with neuroscience . Research Focus : Pioneering connectomics , Seung developed technologies for reconstructing neural circuits from high-resolution brain images, including FlyWire for collaborative brain mapping. His work explores brain function, development, and plasticity , drawing parallels between fly visual systems and convolutional networks . Awards & Affiliations : 2008 Ho-Am Prize in Engineering External Member, Max Planck Society Technical Contributions : Led breakthroughs in 3D connected component labeling and high-throughput EM imaging for mammalian brains, partnering with NIH’s BRAIN Initiative to scale connectomics to whole mouse brains. Seung’s team has shifted from EM analysis to interpreting connectomes , focusing on neural circuit function and biological mechanisms in flies and mice. His lab alumni network spans institutions, advancing AI and neuroscience globally.

Jonas SchützenederView profile

Professor

• Digital Journalism
• Artificial Intelligence in Media
• Social Media and Journalism
• +7 more

Prof. Dr. Jonas Schützeneder is a Professor of Digital Journalism at the University of the Bundeswehr Munich, where he serves as Deputy Chair of the Examination Board. He holds a doctorate in Sports Journalism and Sports Communication and completed his habilitation in Innovation Communication. His academic responsibilities include teaching digital journalism in the Management and Media program (BA/MA), with a focus on data journalism, social media strategies, and online formats. Schützeneder's research explores transformative trends in journalism, with core interests in: Artificial intelligence applications in newsrooms Social media's impact on journalism practices Innovation communication and media evolution Podcast formats and audio storytelling strategies Ethical dimensions of digital journalism His publications demonstrate a consistent focus on journalism's digital transformation, particularly examining how emerging technologies like AI and social platforms are reshaping content production, distribution, and ethical frameworks across European media landscapes. His scientific recognitions include: University Teaching Award from Catholic University of Eichstätt-Ingolstadt (awarded twice) Multiple nominations for Teaching Award at Magdeburg-Stendal University of Applied Sciences Schützeneder leads the podcast project 'Held:innen von Magdeburg' where students research and produce content about contemporary and historical figures. Since 2018, he has served on the editorial board of Communicatio Socialis, an academic journal on media ethics, where he manages peer review processes. Since 2024, he co-heads the DGPuK Journalism Section, a 400-member organization within the German Society for Journalism and Communication Studies.

Li HuiView profile

Professor

• Cryptographic Information Security
• Privacy Computing
• Information Theory
• +5 more

Professor Li Hui serves as the executive dean of the School of Network and Information Security at Xidian University, where he holds the position of second-level professor and doctoral supervisor. He is nationally recognized as a distinguished teacher and serves in multiple prestigious roles including member of the National Steering Committee for Postgraduate Education in Cryptography, inaugural president of ACM SIGSAC CHINA, and director of several major academic societies related to cryptography and information security. Professor Li's research spans cryptographic information security, privacy computing, information theory, and coding theory, with significant contributions to network and cyberspace security. His work demonstrates a strong focus on both theoretical foundations and practical applications, particularly in developing security protocols for emerging technologies like blockchain, federated learning systems, and IoT environments. His research output shows consistent innovation in balancing security requirements with computational efficiency across diverse application domains. With over 300 publications and more than 15,000 Google Scholar citations (H-index 60), Professor Li's scholarly impact is substantial. His recent publications demonstrate increasing emphasis on privacy-preserving machine learning, secure multi-party computation, and cryptographic protocols for distributed systems, reflecting the evolving security challenges in the AI era. Three second-class national teaching achievement awards Special prize and first-class national teaching achievement awards Four first-class provincial and ministerial science and technology progress awards Privacy Computing Theory award (Qian Weichang Chinese Information Processing Science and Technology Award) Multiple patents with over 80 granted inventions Professor Li leads the Cyber Changan Team and serves as head of the Shaanxi Provincial Innovation Team for Mobile Internet Security. He has successfully supervised numerous doctoral and master's students who have gone on to win prestigious competitions like the National College Student Information Security Competition. His research is supported by major national grants including a National Key R&D Program project and key projects from the National Natural Science Foundation of China.