Find Academic Supervisors

• Bioethics
• Ethics of Technology
• Feminist Philosophy
• +3 more

Vera Tripodi is an Associate Professor at the Department of Electronics and Telecommunications (DET) at Politecnico di Torino. Her academic career spans multiple institutions including the University of Milan 'La Statale,' University of Turin, University of Barcelona, University of Oslo, and Columbia University. She serves on the Single Guarantee Committee and is actively involved in gender equality initiatives. Dr. Tripodi earned her PhD in Logic and Epistemology from Sapienza University of Rome. Her academic journey includes postdoctoral research positions at prestigious international institutions and a research position at the University of Milan from July 2021 to March 2022. Her research focuses on the intersection of philosophy, technology, and gender. She specializes in bioethics, ethics of technology, feminist philosophy and ethics, and social ontology. Her work addresses critical contemporary issues including climate change ethics, reproductive technologies, AI ethics, and gender equality in philosophy and academia. She has made significant contributions to understanding the ethical dimensions of emerging technologies and their social implications. Dr. Tripodi's publication record demonstrates a consistent focus on ethical frameworks for technological development, gender issues in philosophy and society, and the philosophical implications of medical and technological innovations. Her work bridges theoretical philosophy with practical ethical concerns in rapidly evolving technological landscapes. Vice President of SWIP Italia (Society for Women in Philosophy) for two terms (2018-2021, 2021-2024) Member of the Bioethics Committee since 2019 Member of SIFA (Italian Society of Analytical Philosophy) since 2008 Associate Editor of AESTHETICS MAGAZINE since 2022 Member of the APHEX editorial board since 2010 Dr. Tripodi advises PhD students in philosophy programs at the University of Pavia and University of Eastern Piedmont. She teaches courses on Research Ethics in Dual-Use Technology, Gender and Diversity in Research, Ethics of Technology, and Bio- and Nanotechnologies in Medicine across various engineering programs at Politecnico di Torino. She also serves on course committees for Biomedical Engineering and Electronic, Telecommunications and Physics Engineering programs. She leads the NOW research project (2023-2025) titled 'Understanding Natural History: Nature, Evolution and Human Beings. A New Philosophical Framework' funded through the National Research PRIN program.

• Logic-in-memory
• Machine learning
• Nanocomputing
• +7 more

Marco Vacca is an Associate Professor in the Department of Electronics and Telecommunications (DET) at Politecnico di Torino and a member of the Interdepartmental Center PIC4SeR - PoliTO Interdepartmental Centre for Service Robotics. His work bridges electronics, nanotechnology, and computing architecture with a focus on innovative solutions to the memory wall problem. His research spans Logic-in-memory computing, Machine learning hardware acceleration, and Nanocomputing with specific emphasis on circuit architectures for probabilistic computing, magnetic devices, hybrid technologies integration, and CAD tools for emerging technologies. Dr. Vacca leads research in RISC-V extensions, hardware accelerators for AI, and autonomous robot systems for agricultural applications through the VLSILAB research group. Recent publications reveal a strong trend toward solving fundamental computing challenges through nanoscale innovations, particularly in memory-centric architectures, molecular field-coupled computing, and novel transistor technologies. His work demonstrates how logic-in-memory approaches can overcome traditional von Neumann limitations while improving energy efficiency for AI workloads. Editorial board member of ELECTRONICS (2021-2023) Program committee member for Design, Automation and Test in Europe Conference (DATE) 2020-2021 Dr. Vacca supervises PhD student Alessandro Varaldi working on 'Hardware AI Accelerators for Automotive Applications' and has led significant research projects including 'Device for Storage and Processing Data and Related Method' (2020-2021) and 'Quantum Computing and Quantum Communication: State of the Art and Applications in the Telco Sector' (2020). His grant portfolio shows strong industry and competitive funding support. As a core member of the VLSILAB research group, Dr. Vacca contributes to advancing VLSI theory and design applications with particular focus on implementing Big Data, Machine Learning, and Neural Networks in specialized hardware architectures that push the boundaries of conventional computing.

Ross HorneView profile

Senior Lecturer

• Security protocols
• Privacy-preserving technologies
• Concurrency theory
• +7 more

Ross Horne is a Senior Lecturer in the Department of Computer & Information Sciences at the University of Strathclyde, Glasgow, United Kingdom. He is a member of the StrathCyber and Mathematically Structured Programming research groups. Education: PhD (University of Southampton, 2012), BA (Oxford University, 2005) Prior Appointments: Research Fellow at University of Luxembourg (2018-2023), Senior Research Fellow at Nanyang Technological University (2015-2018), Associate Professor at Kazakh-British Technical University (2012-2015) Research Interests: Dr. Horne's work focuses on security and privacy protocols for digital systems, particularly addressing threats in payment technologies, ePassports, and decentralized identity management (e.g., Solid protocol). His theoretical contributions bridge concurrency theory, proof theory, and logic through applications to security verification and process calculi. Developed formal models for unlinkability in EMV payment protocols Created intuitionistic logical frameworks for process equivalence Explored graphical proof systems beyond formulaic representations Investigated legal-compliant AI for space systems (CubeSat anomaly detection) Scientific Contributions: He has published extensively in top venues including ACM CCS, IEEE CSF, LICS, and CONCUR. His 2017 CONCUR best paper introduced intuitionistic characterizations of bisimilarity. Principal Investigator for EU COST Action on Distributed Knowledge Graphs Co-developed privacy models adopted in Luxembourg parliamentary responses Advising: Currently accepting PhD students with strong mathematical and computer science skills for research in security/privacy of emerging systems. Former student Semen Yurkov completed a thesis on privacy-preserving smart card payments. Interdisciplinary Work: Collaborates with space lawyers through the Interdisciplinary Master Program in Space Resources. Projects include AI for CubeSat reliability and legal-compliant software certification frameworks.

• Computational Linguistics
• Formal Grammar
• Minimalist Grammars
• +4 more

Jens Michaelis is a Professor at the Faculty of Linguistics and Literary Studies, Bielefeld University, specializing in Computational Linguistics, Text Technology, and Linguistic Creativity. He serves as Deputy Head of the Department of Linguistics, Clinical Linguistics, Text Technology and Computational Linguistics, and provides academic advising for Computational Linguistics programs. His office is located at UHG U5-231, with contact details including telephone +49 521 106-6915 and email jens.michaelis@uni-bielefeld.de . Maintaining active research roles, he leads project B01 'Coercion as a creative mechanism in compositional interpretation' within the SFB 1646: Linguistic Creativity in Communication. His teaching responsibilities span modules like 23-CL-BaCL2.1 Selected methodological aspects 23-CL-BaCL5 Advanced Module 23-CL-BaCL6 Project Module 23-LIN-Ma3.1 Basics of Computational Linguistics 23-MeWi-HM3a_a Mathematical-linguistic language modeling across both undergraduate and graduate programs. His scholarly work focuses on formal grammar properties, syntactic mechanisms, and computational modeling of language. As an ordinary member of the Faculty Conference and Habilitation Committee, he contributes to academic governance while maintaining an extensive publication record in mathematical linguistics, minimalist grammars, and formal language theory.

Andrej BogdanovView profile

Professor

• Cryptography
• Computational Complexity
• Pseudorandomness
• +6 more

Andrej Bogdanov is a Professor at the University of Ottawa in the School of Electrical Engineering and Computer Science . He earned his B.S. and M.Eng. from MIT and Ph.D. from UC Berkeley . Before joining Ottawa, he held positions at the Chinese University of Hong Kong , ITCS (Tsinghua) , DIMACS (Rutgers) , and the Institute for Advanced Study . He has served as a Visiting Professor at the Tokyo Institute of Technology (2013) and the Simons Institute (2017, 2021). Research Interests : Computational complexity, cryptography foundations, pseudorandomness, one-way functions, property testing, quantum algorithms, and sublinear-time algorithms. Teaching : Courses on Discrete Mathematics, Great Algorithms, Computational Complexity, and Cryptography at University of Ottawa, Chinese University of Hong Kong, and Rutgers University. Publications : 15+ recent works in TCC , CRYPTO , ICALP , RANDOM , and journals like Journal of Cryptology and Theory of Computing . Service : Program co-chair for SAC 2026 , and committee member for major conferences including CRYPTO , TCC , Eurocrypt , and FOCS . Advising : 12 current and former Ph.D./M.Phil. students, with postdoctoral advisees at institutions like IIT Palakkad and Academia Sinica . His work bridges theoretical computer science with applications in cryptography, quantum computing, and network security.

Cole A. DeForestView profile

Associate Professor

• Biomaterials
• Tissue Engineering
• Stem Cell Biology
• +7 more

Cole A. DeForest is a Weyerhaeuser Endowed Professor and Associate Professor in the Department of Chemical Engineering at the University of Washington, where he also serves as Associate Chair for Graduate Studies. Additionally, he holds appointments as Associate Professor in Bioengineering and Adjunct Associate Professor in Chemistry, and is the Director of Education at the Molecular Engineering & Sciences Institute and a Core Faculty member at the Institute for Stem Cell & Regenerative Medicine. Dr. DeForest earned his Ph.D. in Chemical and Biological Engineering from the University of Colorado, Boulder in 2011 and completed postdoctoral training at Caltech before joining the UW faculty in 2014. His research focuses on developing user-programmable hydrogels with tunable biochemical and biophysical properties, utilizing cytocompatible bioorthogonal chemistries, particularly those initiated with light. His work spans several key areas including User-Programmable Biomaterials for Directing Dynamic Stem Cell Fate, Biomolecular and Tissue Engineering, Controlled Delivery of Therapeutics to Treat Disease, and Tool Development for Enhanced Proteomic Studies. His publication record demonstrates consistent high-impact contributions to biomaterials science, with numerous papers in Nature family journals, JACS, and Advanced Materials. His research approach integrates principles of rational design with fundamental concepts from material science, synthetic chemistry, and stem cell biology to create next-generation materials addressing health-related problems. UW College of Engineering Junior Faculty Award (2020) Society for Biomaterials Young Investigator Award (2020) Society for Biomaterials Mid-Career Award (2025) NSF CAREER Award (2017) UW Presidential Distinguished Teaching Award (2016) 35 Under 35 Award, AIChE Bioengineering Category (2017) Dr. DeForest has mentored numerous graduate students, postdocs, and undergraduates, many of whom have received prestigious fellowships including NSF GRFP, NIH F30, and HHMI Gilliam Fellowships. His lab has secured significant funding including collaborative grants from the Institute for Translational Health Sciences, the Institute for Stem Cells & Regenerative Medicine, and the Allen Institute for Brain Science. His educational leadership extends to directing the MolES Education program and teaching courses including Biological Frameworks for Engineers and Biomaterials Seminar.

Brigitte PientkaView profile

Professor

• Programming Languages
• Verification
• Type Theory
• +6 more

Brigitte Pientka is a Professor at McGill University's School of Computer Science , where she leads the Computation and Logic group . She earned her PhD from Carnegie Mellon University in 2003 and previously studied at the University of Edinburgh and Technical University of Darmstadt. Education PhD in Computer Science, Carnegie Mellon University (2003) University of Edinburgh Technical University of Darmstadt Research Interests Her work focuses on the theoretical and practical foundations for building reliable software systems, combining logic, type theory, and verification with system-building. Key areas include: Type Theory and Dependent Types Logical Frameworks and Mechanized Metatheory Session-Typed Concurrency and Linear Logic Metaprogramming and Contextual Type Systems Theorem Proving and Formal Verification Functional Programming and Language-Based Security Professional Roles She has served as: PC Chair for ICFP'24 and CPP'24 General Chair for POPL'20 Executive Editor of Logical Methods in Computer Science Steering Committee Member for LICS, POPL, and ESOP Scientific Awards Dr. Pientka has received: Test of Time Award at PPDP'18 Humboldt Fellowship for research at MPI-SWS, Germany Labs & Teams She actively develops the Beluga programming language , a tool for mechanizing meta-theory proofs and type-driven program manipulation.

• Intelligent Control Systems
• Fault and Anomaly Detection
• Virtual and Robust Sensors
• +5 more

Dr. José Luis Calvo Rolle serves as a Professor in the Department of Industrial Engineering at the School of Engineering, Universidade da Coruña (UDC), specializing in Systems Engineering and Automation. His research focuses on intelligent control systems, fault detection, and virtual instrumentation within the Cybernetic Science and Technology Research Group. Teaches across multiple programs including Master's in Industrial Computing and Robotics, Textile Technology, and Occupational Risk Prevention Coordinates thesis supervision across Industrial Engineering and related disciplines His research spans intelligent control systems and optimization, with significant contributions in virtual sensors, fault detection, and AI-driven modeling for industrial applications. Current projects integrate machine learning with industrial processes for naval construction, wastewater treatment, and precision livestock farming, demonstrating cross-disciplinary impact from energy systems to agricultural technology. Recent publications reveal strong trends in applying deep learning to industrial metaverse frameworks, wastewater optimization, and livestock monitoring systems. His work bridges theoretical control engineering with practical implementations in energy management, naval manufacturing, and sustainable agriculture, frequently utilizing dimensionality reduction and one-class classification techniques. Dr. Calvo Rolle actively mentors students through thesis supervision across multiple engineering disciplines and coordinates research projects with diverse funding sources including the European Commission, Spanish National Research Agency, and industrial partners like Navantia and Telefónica. His laboratory work centers on the Cybernetic Science and Technology Research Group, developing testbeds for industrial automation, virtual instrumentation, and AI-driven monitoring systems. Current initiatives include digital twin implementations for naval manufacturing and smart energy management systems.

Achilleas BoukisView profile

Associate Professor

• Branding
• Technology-Enabled Marketing
• Employee-Customer Interactions in Service Industries
• +4 more

Achilleas Boukis is an Associate Professor in Marketing at the University of Birmingham's Birmingham Business School. With a PhD from Strathclyde University (2014) and a PGCert in Higher Education (2015), he focuses on branding, technology-enabled service interactions, and employee-customer dynamics in hospitality and sharing economy contexts. His work appears in top journals like Tourism Management , Journal of Business Research , and British Journal of Management . PhD: Strathclyde Business School (2014) PGCert: University of Sussex (2015) MSc: Athens University of Economics and Business (2008) BSc: Athens University of Economics and Business (2005) His research examines value creation in service interactions and branding strategies for blockchain technologies. Recent work includes NFT classification frameworks, employee social media impact on service performance, and customer threat dynamics in hospitality. He collaborates with institutions in the UK, Australia, and the US. Scientific achievements include: Highly Commended Award (Emerald/EFMD 2014) BAFTA 2014 Honourable Mention Active in curriculum development and online education, he supervises PhD/DBA students while integrating service-dominant logic into teaching methodologies to foster critical thinking and global collaboration.

Ayan MukhopadhyayView profile

Researcher

• Multi-Agent Systems
• Cyber-Physical Systems
• Smart Cities
• +5 more

Dr. Ayan Mukhopadhyay serves as a Senior Research Scientist in the Department of Electrical Engineering and Computer Science at Vanderbilt University's School of Engineering. Previously, he was a Post-Doctoral Research Fellow at Stanford Intelligent Systems Lab where he received the 2019 CARS post-doctoral fellowship. His academic journey includes a Ph.D. from Vanderbilt University's Computational Economics Research Lab with a doctoral thesis nominated for the Victor Lesser Distinguished Dissertation Award 2020. His research spans critical domains in smart infrastructure systems with particular focus on: Developing robust decision-making frameworks for cyber-physical systems under uncertainty Creating multi-agent solutions for emergency response optimization Designing machine learning approaches for urban mobility and energy management Building proactive incident detection pipelines using heterogeneous data sources Analysis of his recent publications reveals strong thematic continuity in applying artificial intelligence to real-world infrastructure challenges, particularly in transportation systems, emergency response, and energy management. His work consistently bridges theoretical AI advances with practical implementation in smart city contexts, demonstrating expertise in both algorithmic innovation and systems integration. Award highlights include: CARS Post-Doctoral Fellowship (2019) Best Paper Award at ICLR's AI for Social Good Workshop Victor Lesser Distinguished Dissertation Award Nomination (2020) Dr. Mukhopadhyay leads significant research initiatives through ScopeLab, focusing on creating deployable solutions for public transit, emergency response, and energy systems. His work on vehicle-to-building charging, traffic incident localization, and equitable transit network design demonstrates commitment to solving high-impact urban challenges through rigorous computational methods. Current projects involve developing simulation environments for non-stationary environments (NS-Gym) and explainable planning frameworks integrating formal logic with large language models.

Spyros ReveliotisView profile

Professor

• Discrete Event Systems
• Multi-Agent Systems
• Automated Workflow Control
• +5 more

Spyros Reveliotis is a Professor at the Stewart School of Industrial & Systems Engineering within the College of Engineering at Georgia Institute of Technology. His work bridges theoretical advancements with practical applications in automation and control systems. Education : PhD in Industrial Engineering (University of Illinois at Urbana-Champaign), B.Sc. in Electrical Engineering (National Technical University of Athens), M.Sc. in Computer Systems Engineering (Northeastern University) Reveliotis focuses on discrete event systems theory , emphasizing control of flexible automation and traffic management for multi-agent systems. His research integrates machine learning and Markov decision processes to optimize scheduling and coordination in complex environments like robotics and manufacturing systems. Recent trends in his publications address deadlock avoidance , min-time coverage in constrained spaces, and liveness enforcement for transport systems. These works often leverage combinatorial optimization and graph theory for scalable solutions. Scientific Awards : IEEE Fellow As a core faculty member of the Institute for Robotics and Intelligent Machines (IRI) , Reveliotis contributes to interdisciplinary robotics research. His affiliations with professional societies like INFORMS reflect his impact on operations research and automation fields.

• Software Verification
• Formal Methods
• Program Synthesis
• +4 more

Madhusudan Parthasarathy is a Professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign, College of Engineering. His research focuses on software verification, formal methods, and logic in computer science, with significant contributions to trustworthy AI systems, program synthesis, and security. Ph.D. in Theoretical Computer Science (2002), Institute of Mathematical Sciences, University of Madras Research interests include automating software verification, building correct-by-design systems, and exploring synergies between machine learning and program synthesis. He pioneered visibly pushdown languages , impacting XML processing and program verification. His tools like VEX and Strand advanced security and heap reasoning. Recent articles focus on blockchain verification, timed automata, and learning logics from data. His work has been widely cited, with the visibly pushdown language paper alone generating over 940 scholarly entries. Best Paper Award, 19th USENIX Security Symposium (2010) He has advised numerous students and postdocs, with former advisees now at institutions like Purdue University and Google. His outreach initiatives include the ConTraIL privacy-preserving contact tracing project and the MASSIVELY EMPOWERED CLASSROOMS MOOC platform for Indian undergraduates. He teaches courses like CS 521: Advanced Topics in Programming Systems and CS 474: Logic in Computer Science , while actively serving on program committees for top-tier conferences such as POPL and PLDI.

• Control Theory
• Optimization
• Machine Learning
• +7 more

Michael M. Zavlanos is the Yoh Family Professor in the Thomas Lord Department of Mechanical Engineering and Materials Science at Duke University's Pratt School of Engineering. He also holds secondary appointments in the Department of Computer Science and the Department of Electrical and Computer Engineering. Currently serving as the Director of the Healthcare Systems Optimization program with Duke AI Health and as an Amazon Scholar with Amazon Robotics, his academic career spans control theory, optimization, and artificial intelligence with applications across multiple domains. Dr. Zavlanos received his educational foundation from prestigious institutions: Diploma in Mechanical Engineering from the National Technical University of Athens (NTUA), Greece (2002) M.S.E. in Electrical and Systems Engineering from the University of Pennsylvania (2005) Ph.D. in Electrical and Systems Engineering from the University of Pennsylvania (2008) His research program spans multiple interconnected domains, with a strong foundation in control theory, optimization, and learning methodologies . This theoretical work directly enables applications in robotics and autonomous systems , where his team develops algorithms for multi-robot coordination, motion planning under complex constraints, and network connectivity maintenance. A significant portion of his work addresses networked and distributed control systems , focusing on how multiple agents can coordinate effectively with limited communication. More recently, he has expanded his research into cyber-physical systems with healthcare applications, leveraging his expertise to optimize healthcare delivery systems through the Duke AI Health initiative. Dr. Zavlanos' work demonstrates a consistent trajectory from theoretical foundations to real-world applications. His early work established fundamental principles for maintaining connectivity in mobile robot networks, which evolved into more sophisticated approaches for temporal task planning and risk-averse decision making in uncertain environments. The most recent phase of his research integrates machine learning with traditional control theory to address complex healthcare system optimization problems. His significant contributions to the field have been recognized through prestigious awards: Office of Naval Research Young Investigator Program (YIP) Award (2014) National Science Foundation Faculty Early Career Development (CAREER) Award (2012) National Science Foundation Faculty Early Career Development (CAREER) Award (2011) Duke University Distinguished Faculty Rank (2019) Duke University Distinguished Professor designation (2018) As an educator, Dr. Zavlanos has taught courses including ME 627: Linear System Theory, ME 592: Research Independent Study, ECE 391/291: Projects in Electrical and Computer Engineering, and CEE 627: Linear System Theory. His research program has been supported by multiple grants from the National Science Foundation and the Office of Naval Research, enabling him to mentor numerous graduate students and postdoctoral researchers in the development of cutting-edge control and optimization algorithms. Dr. Zavlanos leads research efforts at the intersection of control theory, optimization, and artificial intelligence, with particular focus on translating theoretical advances into practical applications. His recent work with Duke AI Health represents a strategic expansion of his research portfolio into healthcare systems optimization, where he applies his expertise in algorithmic decision making to improve patient scheduling, resource allocation, and operational efficiency in medical settings. Through his Amazon Scholar role, he also contributes to advancing robotics technologies for real-world applications.

• Artificial Intelligence
• Natural Language Processing
• Computational Linguistics
• +6 more

Ayşenur Akyüz Birtürk serves as a Lecturer in the Department of Computer Engineering at Middle East Technical University (METU), Ankara, where she has taught since February 1994. Her academic career spans foundational programming courses to advanced graduate seminars in AI and Computational Linguistics, reflecting 30+ years of institutional commitment. She earned all her degrees from METU, culminating in a 1998 Ph.D. focused on Turkish language computational analysis. Her educational journey includes: B.S. in Computer Engineering (1985) M.S. in Computer Engineering (1988) with thesis on “A Model for Representing Concepts: Conceptual Dependency Theory” Ph.D. in Computer Engineering (1998) with thesis on “A Computational Analysis of Turkish using the Government-Binding Approach” Dr. Birtürk’s research centers on Artificial Intelligence and Natural Language Processing , with pioneering work in Turkish language parsing evolving into modern Recommender Systems . She integrates semantic relations and multi-domain data to build hybrid engines for movies, books, and music, emphasizing user modeling through knowledge representation and data mining techniques. Analysis of her 2010-2015 publications reveals two dominant threads: adaptive recommender systems (80% of output) using semantic similarity and dynamic clustering, and renewable energy analytics (20%) applying machine learning to wind/hydrological data. This pivot from NLP to energy forecasting demonstrates methodological versatility while maintaining core AI expertise. Her scientific recognition includes: TUBITAK scholarships throughout education (1977-1988) Multiple national contest awards in high school (1979-1980) Leadership in TUBITAK-funded energy and healthcare projects Dr. Birtürk has supervised 17 Master’s theses in NLP and recommender systems while securing competitive grants including METU-ISTEC #17435 (2006-2008; 504,000 YTL) and HASAT (2010-2013; 601,637 YTL). Her industry consultancy spans medical form design (FormAnalitik), question-answering systems, and retail intelligence platforms, translating academic research into real-world tools.

Eugene Y. VassermanView profile

Associate Professor

• Network and distributed system security
• Privacy and anonymity
• Censorship resistance
• +4 more

Eugene Y. Vasserman is an Associate Professor in the Department of Computer Science at Kansas State University's College of Engineering, where he also serves as Director of the Center for Cybersecurity and Trustworthy Systems. His office is located in 2171 Engineering Hall, and he holds office hours on Tuesdays from 2:30 pm to 4:00 pm and Wednesdays from 11:30 am to 1:00 pm during the Fall 2025 semester. Dr. Vasserman's research spans multiple critical areas of cybersecurity including network and distributed system security, privacy and anonymity, censorship resistance, operating system security, medical and IoT security, usable security, and applied cryptography. His work bridges theoretical security concepts with practical implementations, addressing real-world challenges in diverse domains from medical systems to blockchain technologies. His recent publications reveal a research trajectory that has evolved from foundational network security work to increasingly interdisciplinary research intersecting with artificial intelligence, medical systems, and cybersecurity education. The 15 most recent publications demonstrate his ongoing commitment to both theoretical advances and practical security solutions across multiple domains. Outstanding short paper award for 'Hypersparse Traffic Matrix Construction using GraphBLAS on a DPU' at IEEE HPEC 2023 Best graduate student poster award for 'Empowering pre-service teachers to utilize programming in the classroom' at ASEE Midwest Conference 2013 Dr. Vasserman has mentored numerous graduate students through the Systems and Network Security (SyNeSec) Lab, with alumni now working at organizations including Paycom, Corelight, Sandia National Labs, Microsoft, and Cerner. He teaches multiple cybersecurity courses each semester including CIS 525: Introduction to Network Programming, CIS 755: Systems Security, and CIS 351: Cyber Defense Basics, demonstrating his long-term commitment to cybersecurity education since at least 2010. As Director of the Center for Cybersecurity and Trustworthy Systems, he leads initiatives that address critical security challenges across multiple domains, fostering collaboration between researchers, students, and industry partners to develop trustworthy systems for the future.