Mathematical Software Design Professors and Supervisors | ApplySharif

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Petros KaramanakosView profile

Assistant Professor

Tampere UniversityFinland

Petros Karamanakos is an Assistant Professor in the Department of Electrical Engineering at Tampere University's Faculty of Information Technology and Communication Sciences. His research focuses on advanced control methodologies for power electronic systems, emphasizing optimization, mathematical programming, and model predictive control. He holds a Ph.D. and Diploma in Electrical and Computer Engineering from the National Technical University of Athens (2007–2013). Prior to his academic role, he worked at ABB Corporate Research Center (2010–2011) and was a PostDoc Research Associate at Technische Universität München (2013–2016). His mission involves developing control methods that maximize hardware capabilities while minimizing hardware requirements. Key research topics include variable speed drives, grid-connected converters, multilevel power converters, and modulation strategies. He has received prestigious awards, including the Third Best Paper Award in IEEE Transactions on Industry Applications and four IEEE conference prize paper awards. Teaching responsibilities include courses on power electronics and control systems. He actively supervises BSc, MSc, and PhD students. His work bridges theoretical advancements with practical implementations in power electronics, with a focus on real-time control and system optimization.

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Wei LiView profile

Professor

Graz University of TechnologyAustria

Wei Li is a Professor at the School of Computer Science and Engineering, Beihang University (since 1986), and Director of the State Key Laboratory of Software Development Environment (since 1992). He has held visiting positions at institutions including the University of Minnesota and Universität Saarlandes. Education: Ph.D. in Computer Science, University of Edinburgh (1979–1983) B.Sc. in Mathematics, Peking University (1961–1966) Research Interests span Mathematical Logic, Concurrent Programming Languages, Satisfiability Problems, Artificial Intelligence, Software Crowdsourcing, and Big Data. His work includes foundational contributions to logical frameworks for belief revision and specification evolution, with applications in software trustworthiness and constraint satisfaction. Publication Trends reveal a focus on formal methods (R-calculus, open logic systems), software crowdsourcing, and phase transitions in constraint satisfaction problems. His research integrates theoretical rigor with practical applications in information science and engineering. Scientific Awards include: Chinese Government Award for Publishing (2017) Tsiolkovsky Medal (2007) National Prize of First Class for Achievements in Education (2005) Ho Leung Ho Lee Prize (1998) Academician, Chinese Academy of Sciences (1997) He also supervised 8 post-docs, 52 Ph.D., and over 100 graduate students.

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Sven ScheweView profile

Professor

Saarland UniversityGermany

Sven Schewe is a Professor in the Department of Computer Science at the University of Liverpool, affiliated with the School of Electrical Engineering, Electronics and Computer Science. He leads the AI Section and is a founding member and former leader of the Verification Group. He also has secondary affiliations with the Algorithms, Complexity Theory and Optimisation Group and the Institute for Risk and Uncertainty. Research Interests: His research centers on automata theory and game theory, particularly their applications in the verification and synthesis of reactive and safety-critical systems. He investigates infinite-duration games, automata over infinite words and trees, and develops algorithms and tools for automated verification, synthesis, and learning of optimal control strategies. His work extends to reinforcement learning with formal guarantees, cyber-physical systems, and AI safety. Recent Research Trends: His recent publications demonstrate a strong integration of formal methods with machine learning, particularly in adversarial training, neural network robustness, and model-free reinforcement learning under omega-regular objectives. He also applies formal reasoning to interdisciplinary domains such as chemical space exploration and materials science. Scientific Awards: Finalist for the ERCIM Cor Baayen Award 2010 Dr. Eduard Martin Preis 2009 GI Dissertation Award 2008 Advising and Grants: He actively supervises numerous PhD students and postdoctoral researchers. He is Principal Investigator (PI) or Co-Investigator (CI) on multiple major grants, including EPSRC Programme Grants, Royal Society Fellowships, and Horizon Europe projects. His funded research spans topics such as game theory, verification, synthesis, reinforcement learning, and risk analysis. He has hosted visiting researchers and collaborated internationally with institutions in Germany, France, India, Taiwan, and the US. Labs and Teams: He co-founded and led the Verification Group and previously led the AI Section at the University of Liverpool. These groups focus on formal methods, automata, games, and their applications in AI and safety-critical systems.

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Cruz IzuView profile

Lecturer

The University of AdelaideAustralia

Dr. Cruz Izu is a Lecturer in the School of Computer and Mathematical Sciences at the University of Adelaide. She holds a BSc (Hons) in Computer Science and a PhD in Computer Architecture from the University of the Basque Country, along with a Graduate Certificate in Online Learning from the University of Adelaide. Her research focuses on two primary areas: interconnection network design for parallel systems and computer science education methodologies. Research Interests: Interconnection networks in parallel systems and Network-on-Chip architectures Computer Science Education, including program comprehension, code quality assessment, and pedagogical strategies for novice programmers Computational thinking and problem-solving in early university education Teaching Contributions: Coordinator for Masters of Computing and Innovation program Lead developer of Systems, Programming, and Problem Solving courses Former coordinator of the Google-funded Educators PD program (2011-2020) Collaborations: International partnerships with institutions in Spain, Italy, and Australia Contributions to the design of the SACE Digital Technologies curriculum Professional Activities: Editor of Informatics in Education (2021 Special Issue on Abstraction) PC member for SIGCE and ITiCSE conferences

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Arunabha SenView profile

Professor

Arizona State UniversityUnited States

Professor Arunabha Sen is a faculty member at Arizona State University (ASU), affiliated with the School of Computing and Augmented Intelligence and the College of Health Solutions as a Health Solutions Ambassador. He joined ASU in 1987 and holds a Ph.D. in Computer Science from the University of South Carolina (1987). His research focuses on resource optimization in telecommunication networks, VLSI circuits, hardware-software co-design, and network security. Key areas include algorithm design, combinatorial optimization, and network processor systems. His work spans wireless, optical, and sensor networks, with contributions to video transmission over mobile ad-hoc networks and interference-aware channel assignment. Notable projects include robust network design against WMD attacks and tools for resilient communication networks. He has served on multiple technical committees for conferences like IEEE and IFIP, and contributed to academic initiatives such as capstone courses on network processors. Grants include NSF, DOD-DTRA, and Motorola Labs funding, emphasizing interdisciplinary research in network science and communications. Teaching responsibilities include courses on algorithms, game theory, and network design. His service roles include Associate Editor for IEEE Transactions on Mobile Computing and leadership in graduate program committees. Research outputs include over 30 peer-reviewed publications, with recent work in algorithmic network design and social computing data mining.

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Yanja DajsurenView profile

Assistant Professor

Eindhoven University of TechnologyNetherlands

Yanja Dajsuren is an Assistant Professor and Program Director of the PDEng Software Technology program at Eindhoven University of Technology's Department of Mathematics and Computer Science. Her work bridges academic research and industry applications in software engineering and mobility systems. Education: PhD in Computer Science (2015), TU/e PDEng in Software Technology (2005), TU/e MBA (2002), Maastricht School of Management Research Focus: Yanja specializes in software architecture for autonomous and cooperative driving systems, with a focus on model-driven development, functional safety, and system modularity. Her work contributes to Cooperative Intelligent Transport Systems (C-ITS) and aligns with UN Sustainable Development Goals related to smart cities and innovation. Projects: Current projects include i-CAVE (Project #6) and Horizon 2020 C-MobILE, addressing challenges in automotive software integration and cooperative driving systems. Past projects at Philips Research, NXP Semiconductors, and CWI demonstrate her long-term expertise in industrial software development. Academic Contributions: She co-founded the International Workshop on Automotive Software Architectures (WASA) and launched the Journal of Automotive Software Engineering (JASE). Her collaborations span academia and industry, including partnerships with ASML, Philips Hue, and international research teams.

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Sofia KyratziView profile

Assistant Professor

University of the AegeanGreece

Sofia Kyratzi is an Assistant Professor of Geometric Modeling and Computer-Aided Design at the University of the Aegean's Department of Product and Systems Design Engineering. She holds a PhD (2007) in Computer Graphics and Geometric Modeling from the same university, an MSc in Medical Informatics (2002) from Aristotle University of Thessaloniki, and a BSc in Mathematics (2000) from Aristotle University. Roles: Teaches courses like Computer Graphics, Computer-Aided Design, and related graduate topics. Research Focus: Parametric modeling, sketch-to-solid algorithms, design intent recognition, and Industry 4.0 integration in manufacturing. Her work includes developing algorithms for reconstructing 3D models from sketches, leveraging cloud computing for CAD applications, and optimizing footwear design via biomechanical modeling. Key contributions span over 15 peer-reviewed publications in journals like Computer-Aided Design and conferences addressing geometric modeling challenges. She collaborates on projects exploring Industry 4.0 technologies for SMEs, emphasizing cloud-based CAD tools and parallel computing optimizations. Her research bridges theoretical geometric principles with practical industrial applications.

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Thomas OttoView profile

Lecturer

University of St AndrewsUnited Kingdom

Dr Thomas Otto is a Lecturer at the University of St Andrews' School of Psychology and Neuroscience. His research focuses on the interface between perceptual and cognitive neuroscience, employing mental chronometry and mathematical modeling to investigate multisensory decision-making processes. Current work examines cognitive architectures underlying human decision-making in multisensory contexts, logical decision gates, and variability in response time tasks. He has supervised four PhD students and led a BBSRC-funded project on multisensory decision frameworks (2016–2019). Research interests include multisensory integration mechanisms, response time analysis, and decision-making models. Key contributions involve testing race models for audiovisual motion and semantic congruency effects in multisensory responses. Recent studies explore contextual influences on decision processes and subjective visual awareness effects. Publications span 20 years, focusing on perceptual decision-making, race models, and multisensory integration. Developed the RSE-box analysis tool for response time studies. Active in presenting at conferences and leading collaborative datasets (e.g., audiovisual decision-making projects). Labs/Teams: Directs the Cognitive Chronometry Lab (http://lclab.wp.st-andrews.ac.uk/), focusing on temporal aspects of perception and decision-making.

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Anjali SandipView profile

Academic

University of North DakotaUnited States

Anjali Sandip is a Teaching Assistant Professor in the Mechanical Engineering Department at the University of North Dakota's College of Engineering and Mines. She holds a Ph.D. in Mechanical Engineering from the University of Kansas and maintains an active research program in computational mechanics, high-performance computing, and machine learning. Her educational background includes a Doctor of Philosophy and Master of Science in Mechanical Engineering from the University of Kansas, and a Bachelor of Engineering in Mechanical Engineering from Osmania University in Hyderabad, India. She previously served as a post-doctoral researcher at the University of Nebraska, where she developed patient-specific computational models for peripheral artery disease treatment. Dr. Sandip's research spans computational mechanics, high-performance computing, uncertainty quantification, physics-informed machine learning, and multi-physics modeling. Her work has significant applications in ice sheet dynamics, medical device modeling, and multi-phase flow simulations. She has developed open-source software frameworks that integrate finite element and finite volume methods with uncertainty quantification tools. Her recent publications demonstrate a strong focus on developing computational frameworks for multi-physics problems, with particular emphasis on GPU acceleration, uncertainty quantification, and machine learning integration. The research shows consistent application of these methods to challenging problems in earth sciences, biomedical engineering, and traditional mechanical engineering domains. Scientific Awards: NSF EPSCoR Research Fellow (2024-25) Dr. Sandip actively mentors both undergraduate and graduate researchers, and she is currently seeking Master's and Ph.D. students interested in computational mechanics, applied mathematics, scientific machine learning, and earth sciences. She serves as an active member of the Association of Computational Mechanics (USACM & IACM) and has delivered numerous presentations at professional conferences. Her research has received support from prestigious organizations including the National Science Foundation (NSF), Department of Energy (DOE), and NVIDIA. She teaches courses including Introduction to Mechanical Engineering, Thermodynamics, Machine Component Design Laboratory, Advanced Finite Element Methods, Modeling Glaciers and Ice Sheets, Statics, and Engineering Ethics, demonstrating her broad expertise across mechanical engineering disciplines.

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Noortje VenhuizenView profile

Assistant Professor

Saarland UniversityGermany

Noortje Venhuizen is an Assistant Professor in the Department of Cognitive Science and Artificial Intelligence at the Tilburg School of Humanities and Digital Sciences, Tilburg University. She serves as Academic Director for the BSc Cognitive Science and Artificial Intelligence program since 2024, and has held academic positions at Saarland University (2015-2022) including roles as Scientific Staff member and Principal Investigator in SFB 1102 projects. PhD in Computational Semantics (University of Groningen, 2015) MSc in Logic (ILLC, University of Amsterdam, 2011) BSc in Artificial Intelligence (Utrecht University, 2009) Her research focuses on expectation-based language comprehension, neurocomputational modeling of semantic processing, distributional formal semantics, and pragmatic reasoning in discourse. Key contributions include PDRT-SANDBOX (Haskell NLP library) and DFS Tools (Prolog implementation of distributional formal semantics). Recent publications (2023-2025) explore multimodal word meaning, informativity in reference production, and neurocognitive models of surprisal processing. Her work combines formal semantics with cognitive neuroscience and computational modeling. LOT Grotevragenprijs essay contest - Second Prize She has presented research at major conferences including CogSci, AMLaP, and Sinn und Bedeutung. Current teaching includes courses on artificial intelligence, statistics, and semantic theory.

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Douglas D. HodsonView profile

Professor

Air Force Institute of TechnologyUnited States

Douglas D. Hodson is a Professor of Computer Engineering at the Air Force Institute of Technology (AFIT), Wright-Patterson AFB, Ohio, affiliated with the Department of Systems and Engineering Management within the Graduate School of Engineering and Management. He holds a PhD in Computer Engineering from AFIT (2009), an MBA and MS in Electro-Optics from the University of Dayton, and a BS in Physics from Wright State University. His research focuses on computer engineering, software engineering, real-time distributed simulation, and quantum communications , with a strong emphasis on Quantum Key Distribution (QKD) systems, modeling and simulation (M&S), and Live-Virtual-Constructive (LVC) environments. His work integrates cybersecurity, network performance, and advanced simulation frameworks such as AFSIM and SwarmSim. His recent publications (2021–2022) reflect a trend toward secure distributed systems, AI-driven classification, fog modeling in military simulations, and opinion dynamics in social systems. These works span disciplines including cybersecurity, artificial intelligence, defense modeling, and environmental effects in multi-domain operations. Scientific Awards and Honors: IEEE Senior Member (2021) Outstanding Achievement Award, World Congress in CSCE (2018) SOCHE Faculty Excellence Award (2017) Harold Brown Award (2015) Multiple AFIT Civilian Category III Awards (2014, 2013) Dayton Area Graduate Studies Institute Scholar (2003–2007) Rev. Raymond A. Roesch, S.M., Award of Excellence, University of Dayton MBA (1998) Advising and Grants: Dr. Hodson has advised numerous graduate students, many of whom are co-authors on his publications. His research has been supported by AFIT, AETC, and collaborative defense-focused grants, particularly in quantum communications and simulation technologies. He has led or contributed to teams receiving Air Force Modeling and Simulation Team Awards and QKD Research Team Awards. Labs and Teams: He is a key contributor to the AFIT Quantum Communications and Modeling & Simulation research teams, working on projects involving AFSIM, QKD system modeling, decoy state protocols, and swarm UAV simulation. His lab environment fosters interdisciplinary collaboration in cybersecurity, physics, and software engineering.

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Georgios BardisView profile

Assistant Professor

University of West AtticaGreece

Georgios Bardis is a permanent Assistant Professor at the Department of Informatics and Computer Engineering , School of Engineering , University of West Attica . He holds a PhD in Informatics from University of Limoges (2006), an MSc in Software Systems from University of California, Santa Barbara (1994), and a Diploma in Computer Engineering & Informatics from University of Patras (1992). His career spans multiple academic roles, including Lecturer at University of West Attica (2018-2021) and Professor of Applications at TEI of Athens (2010-2018). Research Interests : Focus on Intelligent Computer Graphics , Declarative Modeling , and Multicriteria Decision Analysis . His work integrates AI into 3D scene synthesis, urban planning, and semantic decision systems. Awards : Master Microsoft Office Specialist (MOS), 2003 NAT Scholarships for Academic Excellence (1989-1992) 1984 Monetary Prize from Hellenic Mathematical Society Leadership : Member of AKIIS Research Lab (University of West Attica), Editorial Board of International Journal of Systems Biology and Biomedical Technologies , and Reviewer for International Journal of Digital Earth . Publications : 5 peer-reviewed journals, 2 books, 8 book chapters, and 22 conference papers. Key areas include WebGL avatars, urban data analysis, and 3D modeling with AI.

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Charles HoltView profile

Professor

University of VirginiaUnited States

Charles Holt is the A. Willis Robertson Professor of Political Economy at the University of Virginia's Department of Economics and Director of the Veconlab. His work bridges experimental economics , game theory , and economic education , with a focus on quantal response equilibrium (QRE), asset market bubbles , and belief/risk elicitation methods. He co-founded the journal Experimental Economics and has advised students like Ricky Sahu and Angela Smith on award-winning research. Education: BA, Washington & Lee University MS, PhD, Carnegie Mellon University Holt’s research demonstrates how stochastic decision-making in QRE explains systematic deviations from Nash equilibrium across social dilemmas, auctions, and voting games. His experimental auction designs for institutions like the FCC and Regional Greenhouse Gas Initiative have informed real-world policy. He also pioneered the Holt-Laury measure of risk aversion and the Veconlab software , used by 15,000 students monthly. Scientific awards include the 2023 AEA Distinguished Economic Education Award , the 2018 UVA Thomas Jefferson Award , and the 2008 SEA Kenneth Elzinga Teaching Award .

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Wei KeView profile

Adjunct Associate Professor

New York UniversityUnited States

Dr. Wei Ke is an Adjunct Associate Professor in the Marketing Department at the Leonard N. Stern School of Business, New York University, joining in 2024. He holds a Ph.D. in Decision, Risk & Operations from Columbia Business School and a B.Sc. in Electrical Engineering and Applied Mathematics (summa cum laude) from Columbia University. His professional career is centered at Oliver Wyman, where he serves as a Partner in the pricing, sales, marketing, retail, and business banking practices. Ph.D., Decision, Risk & Operations, Columbia Business School (2009) MPhil, Decision, Risk & Operations, Columbia Business School (2006) B.Sc. (Summa Cum Laude), Electrical Engineering and Applied Mathematics, Columbia University (2003) Wei Ke's research focuses on pricing algorithms and behavioral pricing , exploring how psychological and computational models influence pricing decisions in digital, retail, and financial contexts. His work bridges data science with consumer behavior, emphasizing real-world applications in customer value management and digital sales effectiveness. His recent publications reveal a strong trend in algorithmic and behavioral approaches to pricing across industries such as SaaS, ride-hailing, financial services, and e-commerce. The articles span disciplines including marketing, behavioral economics, data science, and operations research, with recurring subfields like dynamic pricing, consumer segmentation, discount framing, and machine learning for elasticity modeling. His work often combines empirical analysis with strategic implications for firms. Wei has authored over 50 publications in academic and industry journals, contributing significantly to pricing thought leadership. Though no formal awards are listed, his prolific output and consulting leadership underscore his influence in the field. Advises global financial institutions, retailers, and tech firms on pricing and marketing strategy Teaches Pricing Strategies (MKTG-GB.2353.30) at NYU Stern Previously taught at Columbia Business School and Queen’s University Smith School of Business Extensive experience in grant-like consulting engagements with Fortune 500 clients While not affiliated with a formal lab, Wei collaborates closely with industry teams at Oliver Wyman and Simon-Kucher & Partners, contributing to real-world pricing innovation and strategy development in retail, banking, and technology sectors.

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Michael WehmöllerView profile

Professor

Osnabrück University of Applied SciencesGermany

Prof. Dr.-Ing. Michael Wehmöller is a full Professor at the Faculty of Engineering and Computer Science, Osnabrück University of Applied Sciences. His career spans roles as a technical director in medical device companies and interdisciplinary research leadership in DFG/EU-funded programs, integrating CAD/CAM, additive manufacturing, and biomechanics. Research interests focus on dental technology , medical device innovation , biomechanics , biomaterials , and 3D printing . His work bridges engineering precision with clinical applications , particularly in craniofacial reconstruction and selective laser melting for implants. The 15 most recent publications highlight trends in computer-aided implant design biodegradable materials testing automated surgical planning with a strong emphasis on clinical translation of engineering solutions. Scientific recognition includes Innovationspreis NRW (1996) Innovationspreis Ruhrgebiet (2002) and ongoing membership in VDI medical technology panels . He leads the Digitale Dentale Technologien lab, focusing on next-generation implant systems.

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