Find Academic Supervisors

Malte PrießView profile

Professor

• Cloud Computing
• Artificial Intelligence
• Software Engineering
• +5 more

Prof. Dr. rer. nat. Malte Prieß is a Professor for Cloud Technologies at Kiel University of Applied Sciences since October 20224, following eight years as Dean and Professor of Applied Computer Science at Schleswig-Holstein Cooperative State University (DHSH) . He teaches modules including Cloud Computing , Web Applications , and Advanced Cloud Computing , with additional involvement in Agile Development Methods and Software Engineering . Academic Background: Diploma in Physics (with distinction) from Leibniz University Hanover and Max Planck Institute for Gravitational Physics (2002-2007) Dr. rer. nat. (magna cum laude) from Kiel University in Algorithmic Optimal Control (2008-2012) Research Interests focus on the intersection of cloud computing, artificial intelligence, and modern software engineering . His work includes surrogate-based optimization for climate models, AI-driven document capture systems , and ethical considerations in AI deployment within project work. Recent Publications demonstrate expertise in AI vulnerability assessment , deep learning training optimization , and document search algorithms for governmental agencies. Scientific Recognition: Best Paper Award at CLOUD COMPUTING 2025 for "Graph of Effort" vulnerability assessment Accepted fellowship at AI Campus (Stifterverband) for "Teaching AI, learning AI at DHSH" (2022) Research Projects: Central Innovation Programme for SMEs (ZIM): "AI MODULES for the skilled trades" (2024/25) HR dashboard for DRK Schwesternschaft, Lübeck Scalable Data Analytics project under BMBF FHprofUnt program (2018)

• Natural Language Processing
• Machine Learning
• Social Media Analysis
• +4 more

Vivek Kulkarni is a Professor at Stanford University's Department of Computer Science, with extensive contributions to natural language processing, machine learning, and intelligent IoT environments. His work bridges computational methods with social science applications. Key Affiliations: Stanford University (2024), Nara Institute of Science and Technology (2022), Stony Brook University (2014) Research Interests span NLP, social media analysis, energy-efficient computing, and IoT systems. He develops instruction-tuned models for social tasks, multilingual text editing frameworks, and socially sensitive pretraining methods. Publication Trends (2024–2014): 46% focus on NLP, 31% on IoT, 15% on social factors, and 8% on machine learning. Specialized subfields include instruction tuning, multilingual modeling, social language dynamics, and energy-efficient document classification. Collaborations with William Yang Wang, Steven Skiena, Bryan Perozzi, and H. Andrew Schwartz demonstrate interdisciplinary engagement. 15 recent articles highlight advancements in textual representations, social media mining, and contextual modeling.

Mounika MarreddyView profile

Researcher

• Natural Language Processing
• Machine Learning
• Human-AI Alignment
• +5 more

Mounika Marreddy is a Postdoctoral Researcher at Goethe-Universität Frankfurt am Main, focusing on advancing Natural Language Processing (NLP) through interdisciplinary research that bridges machine learning, cognitive science, and multilingual language modeling. Her work explores the alignment between human and AI annotations, brain activity prediction using language models, and addressing challenges in low-resource languages like Telugu. Research Focus : Human-AI annotator alignment across NLP tasks (e.g., sentiment analysis, stance detection) Task effects on concept representation in neural models Development of Telugu-specific NLP datasets and pretrained models (ELMo-Te, BERT-Te) Neuroimaging studies linking syntactic processing to brain activity Publications : Her research has been published in top-tier venues such as the European Conference on Information Retrieval (ECIR), ACL Findings, IEEE ICASSP, and ACM Transactions, with recent work on the USDC dataset for dogmatism analysis and robustness in transformer models. She actively collaborates with researchers like Alexander Mehler and Manish Gupta.

Dipendra YadavView profile

Researcher

• Natural Language Processing
• Artificial Intelligence
• Transfer Learning
• +5 more

Dipendra Yadav is a scientific researcher and PhD student at the Institute of Data Science, University of Greifswald, Germany, working under Prof. Dr.-Ing Kristina Yordanova since January 2023. His research focuses on natural language processing with expertise in transfer learning, multilinguality, and domain adaptation for low-resource languages, alongside innovative work on symbolic reasoning for explainability in large language models. Yadav holds an M.Sc. in Electrical Engineering from the University of Rostock (2020). Prior to his current role, he worked as a data science student assistant at Market Logic Software in Berlin and completed an NLP internship/Master's thesis at PlanetAI GmbH, where he continued as a software engineer. His research spans critical NLP challenges including cross-lingual transfer for languages like Nepali and Hindi, domain adaptation in resource-constrained environments, and enhancing LLM explainability through symbolic reasoning integration. He also investigates AI safety dimensions such as dangerous capability evaluation and situational awareness in large language models. Recent publications reveal strong trends in low-resource language processing through cross-lingual transfer techniques, domain-specific NLP applications (particularly in dementia research), and safety evaluations of large language models. His work consistently addresses real-world data challenges while advancing methodologies for underrepresented languages. No scientific awards are currently documented. Yadav has not taken formal advising roles for students. His research operates within the Institute of Data Science's framework, which emphasizes interdisciplinary applications in healthcare and language technologies through collaborative projects like ARDUOUS.

• Network Security
• Cloud Computing
• Internet of Things
• +3 more

Olivier Festor is a Researcher at INRIA (French National Institute for Research in Digital Science and Technology), specializing in network security, cloud computing, and IoT. His work focuses on developing scalable solutions for modern network challenges, including in-network computation, cloud service security, and anomaly detection. Research Interests: Dr. Festor investigates vulnerabilities in distributed systems, designs protocols for efficient data processing (e.g., stateful in-network computation), and pioneers frameworks for IoT threat emulation. His recent work emphasizes cloud gaming optimization, automated security for service migrations, and darknet-based threat intelligence. Publication Trends: Over 200 publications (1993–2024) reflect a shift toward cloud/IoT security and programmable networks. Recent articles prioritize machine learning for traffic classification, TOSCA-based cloud orchestration, and P4-enabled data planes, highlighting applied research with industry relevance.

• Natural Language Processing
• Speech Recognition
• Machine Learning
• +5 more

Dietrich Klakow is a prominent researcher at Saarland University in Saarbrücken, Germany, with an extensive publication record spanning from 1997 to 2025. His work primarily focuses on natural language processing, speech recognition, and machine learning with significant contributions to multilingual models and African language processing. His research interests span a wide range of topics within computational linguistics and artificial intelligence. Klakow has made substantial contributions to Natural Language Processing , particularly in multilingual contexts and low-resource languages. His work on African language technologies has been particularly impactful, developing resources and models for languages that are often neglected in mainstream NLP research. He has also conducted significant research in speech recognition , transformer models , and computational linguistics , with a focus on practical applications and theoretical foundations. Klakow's recent publications demonstrate a strong focus on large language models, their capabilities, limitations, and applications across diverse linguistic contexts. His work spans both theoretical investigations of model architectures and practical applications addressing real-world challenges in language technology. His collaborative work spans numerous international partnerships, particularly with researchers working on African language technologies and multilingual NLP systems.

Axel RanischView profile

Visiting Professor

• Film Directing
• Artistic Film
• Visual Storytelling
• +4 more

Axel Ranisch serves as Graduate Director and Special Teaching Assistant for Moving Image/Artistic Film at Saarland University of Fine Arts' School of Media Art & Design since 2022, following a 2021 Visiting Professorship. An internationally recognized filmmaker, he bridges professional practice and academic instruction through courses spanning directing, visual storytelling, and artistic film development. His research focuses on sensory filmmaking techniques , particularly the intersection of auditory elements and visual narrative, German mumblecore traditions, and historical avant-garde adaptation. Workshops like Art of Intimacy and Dada, Trash and Expressionism explore these themes through hands-on experimentation with constrained environments and improvisational methods. Analysis of his creative output reveals consistent exploration of authentic human interaction across formats - from low-budget mumblecore features to television productions. His films demonstrate evolving technical mastery while maintaining focus on emotional truth, with recent works increasingly incorporating autobiographical elements and historical film movement techniques. Key recognitions include: Grimme Prize (2019) for Familie Lotzmann auf den Barrikades City of Hof Prize (2020) for contributions to German cinema International festival success with over 100 screenings for early works Ranisch's mentorship emphasizes collaborative development through structured project consulting, helping students navigate text-image relationships and actor-director communication. His current supervision of projects like PENROSE continues his commitment to supporting emerging filmmakers while maintaining active professional practice through Tatort episodes and radio collaborations. His laboratory of practice exists through immersive workshops that function as creative incubators, where students develop skills in constrained environments while exploring sensory storytelling techniques across multiple mediums.

Thomas StröderView profile

Lecturer

• Software Development Process
• Software Architecture
• Program Verification
• +7 more

Thomas Ströder is a Lecturer in Business Informatics at FHDW University of Applied Sciences since 2022, specializing in software engineering and formal methods. Previously, he served as Head of Full Stack Development at METRO (2016-2019) and Site Manager at IT-P GmbH (2020-2022), combining academic research with industrial leadership in software development organizations. His educational background includes: Diploma in Computer Science with Business Administration minor from RWTH Aachen University (2004-2010), featuring an exchange semester at UNSW Sydney (2008) funded by the Studienstiftung des Deutschen Volkes PhD in Computer Science from RWTH Aachen University (2019) focused on automatic quality assurance and software synthesis Ströder's research bridges theoretical computer science and industrial software engineering through core interests in program verification, formal methods, and software architecture. His work emphasizes practical applications of automated reasoning for termination analysis, memory safety, and complexity bounds in real-world systems, while extending to organizational development and data-driven decision processes in agile environments. This dual focus enables translation of formal verification techniques into enterprise software solutions. His 15 publications (2009-2018) reveal a consistent trajectory in program termination analysis and verification, primarily through the AProVE framework. Early work established foundations in term rewriting and logic program analysis, evolving toward memory-safe C program verification and bitvector arithmetic handling. Publications in top venues like Journal of Automated Reasoning and TACAS demonstrate specialization in bridging theoretical formal methods with practical software engineering challenges, particularly in pointer arithmetic and memory manipulation contexts. Professional activities include research collaborations with Microsoft Research Cambridge (2013) and leadership in building in-house software development organizations at METRO, reflecting strong industry-academia integration in his career trajectory.