Philipp Altmann, M.Sc.

_{Winter Semester 2025/2026}
Anticipating Human Intentions using Multimodal Large Vision-Language Models
Theresa Geber, Ricardo Blasaditsch, Gerrit Grätz
This project benchmarks multimodal vision-language models for intention prediction from egocentric video sequences.
^{Computer Vision, Multimodal Analysis, Deep Learning, Prediction Modeling}

_{Winter Semester 2025/2026}
Affective Presentation Trainer
Yannic Kindermann, Laura Niemann, Nico Rosinus, Jonathan Singer
This project delivers a multimodal VR trainer for public speaking with audience simulation and integrated affective feedback.
^{Real-Time Systems, Speech Analysis, Emotion Recognition, Human-Computer Interaction, Multimodal Analysis}

_{Winter Semester 2025/2026}
The Impact of Parameter Count on Sarcasm Detection Using BERT-Based Models
Alexander Feist, Paul Hofbauer, Sanamjeet Meyer, Kai Treder
This project evaluates how BERT model scale affects sarcasm detection performance and efficiency across multiple benchmark datasets.
^{NLP, Deep Learning, Prediction Modeling, Machine Learning}

_{Winter Semester 2025/2026}
VibeSync: Comparing Vision Language Models and Modular Pipelines for Real-Time Activity Detection in Context-Aware Music Systems
Kevin Kafexhi, Christopher Pichler, Abdullah Koukash, Nina Vucenovic
This project compares modular and end-to-end vision-language pipelines for real-time activity-aware music selection.
^{Music, Computer Vision, Multimodal Analysis, Real-Time Systems, Recommender Systems}

_{Summer Semester 2025}
AffectiFeed: Facial Emotion Recognition for User Preference Prediction on Social Media
Daniel Högen, Meltem Özdağ, Charlotte Ren
This project combines real-time facial emotion recognition with interaction data to predict social media preferences more directly.
^{Social Media, Emotion Recognition, Recommender Systems, Computer Vision, Personalization}

_{Summer Semester 2025}
MoodDrive
Benjamin Heilein, Anton Utz, Kateryna Hamii, Tim Lindner
This project predicts music preference from multimodal listener reactions to provide implicit, emotion-driven feedback for recommendation systems.
^{Music, Multimodal Analysis, Prediction Modeling, Recommender Systems}

_{Summer Semester 2025}
Violence Detection in Videos
Gabriel D. Hamalwa, Terina Sarwari, Alexander Schätzl, Jakob Schleicher
This project develops an AI pipeline for violence detection in video streams to support safer moderation and monitoring scenarios.
^{Real-Time Systems, Computer Vision, Machine Learning, Behavior Analysis}

_{Summer Semester 2025}
Emotion and Gaze-Based Matchmaking: An Affective Computing Approach for Online Dating
Qifan Yang, Larissa Herrmann, Anitan Gunaratnam
This project predicts dating preferences from unconscious gaze and facial emotion signals captured while users view candidate profiles.
^{Online Dating, Emotion Recognition, Behavior Analysis, Machine Learning}

_{Winter Semester 2024/2025}
Trial Whisperer - Emotions in the Courtroom
Pia Koller, Liuxu Lu, Thu Mai Nguyen, Sebastian Wölckert
This project analyzes courtroom emotion signals from audio, video, and text to model links between legal argumentation style and verdict outcomes.
^{Machine Learning, Multimodal Analysis, Emotion Recognition, Prediction Modeling}

_{Winter Semester 2024/2025}
A Review on Empathetic Mental Health Support Voicebots
Lin Shui, Vinzenz Prakoso,Xingyu Jin, Xueni Zeng
This project reviews and evaluates an empathetic mental health voicebot architecture using prompt-based strategies for emotionally aligned responses.
^{Healthcare, NLP, Speech Analysis, Emotion Recognition, Affective Computing}

_{Winter Semester 2024/2025}
Emotion2Emoji - A Novel Approach to Visualize Emotions Using Emojis
Judah Boadu, Moritz Gärtner, Mana Jaqoubi, Leon Lantz
This project generates personalized emojis from facial emotion and context signals to enrich expressive communication in social interactions.
^{Generative AI, Emotion Recognition, Personalization, Social Media}

_{Winter Semester 2024/2025}
EmoGroove: Zero-Shot Music Recommendations with LLMs and VLMs Based on Multimodal Diary Input
Felix Topp, Karola Schneider, Max Erler, Simon Schlichting
This project proposes a zero-shot music recommender that combines diary text and image context through language and vision-language models.
^{Music, Recommender Systems, Multimodal Analysis, NLP, Personalization}

_{Winter Semester 2024/2025}
Safe Driving System
Xinyu Xie, Zihao Li, Tanjia He, Lei Huang
This project integrates fatigue detection, risky behavior recognition, and emotion analysis into a unified driver safety monitoring system.
^{Behavior Analysis, Computer Vision, Emotion Recognition, Real-Time Systems, Healthcare}

_{Summer Semester 2024}
Moodify - The Playlist That Understands You
Clarissa Kümhof, Katja Meißner, Artur Schneider, Dejvis Toptani
This project builds an emotion-aware music playlist system that recommends songs from facially inferred valence and arousal signals.
^{Music, Recommender Systems, Emotion Recognition, Personalization}

_{Summer Semester 2024}
Matching App
Aylin Aldemir, Cindy Döttl, Marius Sorin Pop
This project matches users by analyzing real-time happiness responses to humorous content and estimating compatibility from shared reactions.
^{Online Dating, Facial Analysis, Machine Learning, Social Media}

_{Summer Semester 2024}
FocusPlay: Game-Based Therapy Approaches for Children with ADHD and Monitoring for Parents
Fiona Mariele Lau, Lena Altinger, Timothy Maxwell Summers, Violetta Constanze Meier
This project provides game-based ADHD support for children and a companion dashboard for parents to monitor attention and emotional trends.
^{Healthcare, Gaming, Emotion Recognition, Human-Computer Interaction}

_{Summer Semester 2024}
EmotionRate: How Films Evoke Emotions
Cristian Gavriliu, Leonie Münster, Lea Sigethy, Tudor Teofanescu
This project introduces a streaming prototype that maps audience emotion and boredom signals to describe the emotional profile of films and series.
^{Recommender Systems, Emotion Recognition, Media Applications, Personalization}

_{Winter Semester 2023/2024}
SpicySense
Timo Krapf, Rea Sangiovanni, Yanyu Chen, Isabell Hans
This project detects spicy taste reactions from facial expressions and uses the predictions to generate highlight segments from video content.
^{Computer Vision, Facial Analysis, Deep Learning, Media Applications}

_{Winter Semester 2023/2024}
MooDS: Mood-Dependent Stories
Ivo de Souza Bueno Júnior, Kevin Chen, Qi Feng
This project generates mood-dependent stories tailored to the user’s current emotional state to support emotion-aware reading experiences.
^{NLP, Generative AI, Personalization, Emotion Recognition}

_{Winter Semester 2023/2024}
Emotion Art
Leon Oskui, Nina Mandl, Mert Türkekul
This project creates an interactive art system that transforms visual and musical output based on real-time facial emotion recognition.
^{Interactive Art, Generative AI, Emotion Recognition, Human-Computer Interaction}

_{Winter Semester 2023/2024}
Dating App with Affective Computing: An Investigation of Eye Tracking and Emotion Recognition to Improve the User Experience
Peiwen Du, Alexander Richter, Henrike Schuster, Sikuan Yan
This project develops a dating web application that combines eye tracking and emotion recognition to model user preferences during profile interactions.
^{Online Dating, Emotion Recognition, Behavior Analysis, Machine Learning}

_{Summer Semester 2023}
Automatic Entity and Multimodal Sentiment Extraction and Linkage From YouTube Videos
Huixin Chen, Huangyan Shan, Melvin Tjiok, Ingo Ziegler
This project extracts product entities and multimodal sentiment from YouTube videos and links both signals for interactive insight analysis.
^{NLP, Multimodal Analysis, Social Media, Machine Learning, Media Applications}

_{Summer Semester 2023}
The Training - Designing an Immersive Audio-Visual Affective Experience
Pauline Leininger, Quirin Müller, David Neubauer, Janina van Rinsum, Zihang Sun
This project presents an immersive audio-visual installation that captures participant emotion and pulse data to simulate training an emotionally responsive AI.
^{Interactive Art, Multimodal Analysis, Emotion Recognition, Human-Computer Interaction}

_{Summer Semester 2023}
Music Generation with MoodMuse: A Novel Approach to Emotion-Driven Compositions
Ardit Mazreku, Franziska Wörle, Laura Schröder, Lea Goerl, Phi Linh Phan
This project generates music from detected user emotions by combining facial expression analysis with prompt-based AI composition models.
^{Music, Emotion Recognition, Generative AI, Personalization}

_{Winter Semester 2022/2023}
Project Report: Autmotion
Max Schlowak, Michael Wahl, Lydia Kondylidou, Van Nguyen
This project proposes a web application that helps autistic children learn caregiver emotions through AI-based classification of uploaded facial images.
^{Assistive Technology, Emotion Recognition, Healthcare, Human-Computer Interaction}

_{Winter Semester 2022/2023}
GoodSpeech - Improving Speech Performance
Chrysa Bika, Sophia Licklederer, Stefan Perović
This project analyzes speech performance with affective computing methods to detect emotional states and support expressive communication training.
^{Speech Analysis, Emotion Recognition, Human-Computer Interaction, Affective Computing}

_{Winter Semester 2022/2023}
Aimotions - Preventing from a Broken Heart: How Artificial Intelligence Can Help Finding a Significant Other
Robert Barlog, Sofie Henghuber, Simon Heß, Qinzi Li
This project investigates AI-supported partner matching by estimating emotional similarity from facial emotion recognition rather than self-report alone.
^{Online Dating, Facial Analysis, Prediction Modeling, Personalization}

_{Winter Semester 2022/2023}
Affective Minetest
David Mosbach, Monica Riedler, Celal Yilmaz, Xiaoqian Li
This project extends Minetest with multimodal emotion recognition to enable affective game mechanics driven by player mood and expression.
^{Gaming, Emotion Recognition, Multimodal Analysis, Affective Computing}

_{Summer Semester 2022}
SEEmotion - Emotion Recognition with a Vibrotactile Device to Support Communication of Visually Impaired People
Simona Maiolo, Marion Botsivali, Sina Schnebelt
This project combines facial emotion recognition and vibrotactile feedback to support nonverbal communication for visually impaired users.
^{Assistive Technology, Affective Computing, Emotion Recognition, Human-Computer Interaction}

_{Summer Semester 2022}
FitBrain: An Attention Control System
Manuel Totzauer, Jan Alexander Welling, Ronny Kohlhaus, Yuting Zhao
This project presents an attention control prototype that combines eye gaze, head pose, and emotion tracking to support focused and sustainable work sessions.
^{Behavior Analysis, Computer Vision, Human-Computer Interaction, Machine Learning}

_{Summer Semester 2022}
Emo-Vie - Automated trailer editing driven by emotions
Leonie Adams, Danilo Pejakovic, Clara Sofie Goldmann
This project explores automated trailer editing by combining facial expression recognition and affective computing to identify emotionally salient scenes.
^{Media Applications, Emotion Recognition, Computer Vision, Affective Computing}

_{Summer Semester 2022}
Comparison of Algorithmic rPPG Methods at High Heart Rates
Maximilian Tränkler, Lukas Jost
This project benchmarks algorithmic rPPG methods at high heart rates to assess robust camera-based pulse estimation beyond standard resting conditions.
^{Healthcare, Prediction Modeling, Computer Vision, Machine Learning}

_{Winter Semester 2021/2022}
Studimotion: A Learning Application Adapting Task Difficulty Based on Integrated Overload and Underload Detection
Sophia Sigethy, Julia Pühl, Yara Fanger
This project introduces an adaptive learning application that detects overload and underload and adjusts task difficulty to improve engagement and learning quality.
^{Affective Computing, Emotion Recognition, Personalization, Human-Computer Interaction}

_{Winter Semester 2021/2022}
Recognizing Strokes via an Affective and Responsive F A S T System
Johannes Eykman, Sophia Münch, Ludwig Trauner
This project builds an affective and responsive FAST system to detect stroke-related symptoms automatically and support faster emergency response.
^{Healthcare, Computer Vision, Prediction Modeling, Real-Time Systems}

_{Winter Semester 2021/2022}
Affective AI Lie Detection
Jonathan Haudenschild, Vivian Alexandra Kafadar, Hanna Tschakert, Louisa Ullmann
This project implements an AI-based lie detection prototype and evaluates classification performance for deception detection in video-based interactions.
^{Affective Computing, Machine Learning, Facial Analysis, Prediction Modeling}

_{Winter Semester 2021/2022}
Visualizing Discriminative Regions of Facial Emotion Recognition Networks
Hyeri An, Johannes S. Fischer, Anna Simon, Michael Neumayr
This project compares visualization techniques for facial emotion recognition networks and analyzes which facial regions drive model predictions.
^{Machine Learning, Facial Analysis, Deep Learning, Emotion Recognition}

_{Summer Semester 2021}
Show Me What You Write and I’ll Tell You How You Feel - Emotion Recognition by Using Contextual Chat Information
Felicitas Buchner, Romy Gruber, Konstantin Hegestweiler, Daniel Hirsch, Daniel Panangian
This project develops context-aware emotion recognition for chat conversations by modeling short, dialogue-dependent messages instead of isolated text snippets.
^{NLP, Emotion Recognition, Affective Computing, Machine Learning}

_{Summer Semester 2021}
Needs Recognition in Older Adults to Support Nursing Home Care
Johanna Prinz, Tabea Blenk, Sebastian Müller, Julia Achatz
This project investigates affective support for nursing home care by identifying and modeling the needs of older adults in care-related interactions.
^{Healthcare, Affective Computing, Human-Computer Interaction, Assistive Technology}

_{Summer Semester 2021}
CORmotion - A Career Test That Does More
Sarah Berbuir, Helena Stoll, Matthias Knoll, Olivér Palotás
This project presents a web-based career aptitude test that combines task performance with affective signals to provide more personalized career guidance.
^{Affective Computing, Personalization, Human-Computer Interaction, Prediction Modeling}

• Anton Utz, Maximilian Zorn, Philipp Altmann, Thomas Gabor, Claudia Linnhoff-Popien, “Curriculum-Discovery for Reinforcement Learning of Bipedal Robotic Locomotion,” 2026 (Master).
• Przemek Miskowiec, Maximilian Zorn, Philipp Altmann, Thomas Gabor, Claudia Linnhoff-Popien, “Curriculum Reinforcement Learning for Drone Navigation in Confined 3D-Environments,” 2026 (Bachelor).
• Patrik Felbinger, Philipp Altmann, Thomas Gabor, Claudia Linnhoff-Popien, “Mathematical reasoning in small language models: Comparing challenges and potentials of different prompting strategies,” 2026 (Master).
• Florian Helmberger, Philipp Altmann, Thomas Gabor, Claudia Linnhoff-Popien, “Comparing Echo State Networks and Spiking Neural Networks for Reservoir Computing,” 2025 (Bachelor).
• David Engel, Maximilian Zorn, Philipp Altmann, Claudia Linnhoff-Popien, “Enhancing Cooperative MARL with Curriculum Learning for Dynamic Role Assignment,” 2025 (Bachelor).
• Johannes Kindermann, Philipp Altmann, Jonas Nüßlein, Claudia Linnhoff-Popien, “Query-Efficient Reinforcement Learning from Preferences,” 2025 (Master).
• Nicole Kilian, Maximilian Zorn, Philipp Altmann, Claudia Linnhoff-Popien, “Efficient Reinforcement-Learning Curriculum Generation via Quality-Diversity Methods,” 2025 (Bachelor).
• Simon Salfer, Michael Kölle, Philipp Altmann, Claudia Linnhoff-Popien, “Quantum Architecture Search for Solving Quantum Machine Learning Tasks,” 2025 (Bachelor).
• Marcel Davignon, Maximilian Zorn, Philipp Altmann, Claudia Linnhoff-Popien, “Confidence Based Robotic Grasping With Reinforcement Learning,” 2025 (Bachelor).
• Joel Friedrich, Tobias Rohe, Philipp Altmann, Claudia Linnhoff-Popien, “Exploring Entanglement-intensity in Variational Quantum Eigensolver Algorithms for Combinatorial Optimization,” 2025 (Master).
• Josef Stolz, Maximilian Zorn, Philipp Altmann, Claudia Linnhoff-Popien, “Cooperative Sequential Robotic Manipulation with Multi-Agent Reinforcement Learning,” 2025 (Bachelor).
• Clarissa Kümhof, Philipp Altmann, Maximilian Zorn, Claudia Linnhoff-Popien, “Multi-Objective Reinforcement Learning using Evolutionary Algorithms for Diverse Policy Selection,” 2025 (Master).
• Isabella Debelic, Michael Kölle, Philipp Altmann, Claudia Linnhoff-Popien, “Reinforcement Learning-Based State Preparation Using Parameterized Quantum Gates,” 2024 (Bachelor).
• Nicolas Holeczek, Leo Sünkel, Philipp Altmann, Claudia Linnhoff-Popien, “Comparison of different hybrid quantum machine learning approaches for image classification on quantum computers,” 2024 (Bachelor).
• Martin Obwexer, Thomas Gabor, Philipp Altmann, Claudia Linnhoff-Popien, “Enhancing Object Recognition with Uncertainty-Based Fusion Techniques: A Comparative Analysis of Voting Techniques and Machine Learning Models,” 2024 (Master).
• Amelie Trautwein, Philipp Altmann, Maximilian Zorn, Claudia Linnhoff-Popien, “Evolutionary Prompt-optimization Operators for Code-Generation using LLMs,” 2024 (Bachelor).
• David Fischer, Jonas Stein, Jago Silberbauer, Philipp Altmann, Claudia Linnhoff-Popien, “A Path Towards Quantum Advantage for the Unit Commitment Problem,” 2024 (Bachelor).
• Jonas Wild, Maximilian Zorn, Philipp Altmann, Claudia Linnhoff-Popien, “Designing Meta-Rewards for Multi-Agent Reinforcement Learning Cooperation,” 2024 (Master).
• Timo Witter, Michael Kölle, Philipp Altmann, Claudia Linnhoff-Popien, “Improving Variational Quantum Circuits for Hybrid Quantum Proximal Policy Optimization Algorithms,” 2024 (Bachelor).
• Llewellyn Hochhauser, Philipp Altmann, Michael Kölle, Claudia Linnhoff-Popien, “Influencing behavior through reward manipulation in multi-agentreinforcement-learning,” 2024 (Master).
• Céline Davignon, Philipp Altmann, Maximilian Zorn, Claudia Linnhoff-Popien, “Portraying Reinforcement Learning Policies via Diverse Behavior selected using Evolutionary Algorithms,” 2024 (Master).
• Simon Hackner, Philipp Altmann, Maximilian Zorn, Claudia Linnhoff-Popien, “Diversity-Driven Pre-Training for Efficient Transfer Reinforcement Learning,” 2023 (Bachelor).
• Katharina Winter, Philipp Altmann, Thomy Phan, Claudia Linnhoff-Popien, “Consensus-Based Mutual Acknowledgment Token Exchange,” 2023 (Master).
• Tom Schubert, Michael Kölle, Philipp Altmann, Claudia Linnhoff-Popien, “A Reinforcement Learning Environment for directed Quantum Circuit Synthesis,” 2023 (Bachelor).
• Sarah Gerner, Thomas Gabor, Philipp Altmann, Claudia Linnhoff-Popien, “Final Productive Fitness in Evolutionary Algorithms and its Approximation via Neural Network Surrogates,” 2023 (Bachelor).
• Jonas Maurer, Michael Kölle, Philipp Altmann, Claudia Linnhoff-Popien, “Dimensionality Reduction with Autoencoders for Efficient Classification with Variational Quantum Circuits,” 2023 (Bachelor).
• Alain Feimer, Thomy Phan, Philipp Altmann, Claudia Linnhoff-Popien, “Generalization in Multi-Agent Reinforcement Learning using Minimax Learning,” 2023 (Master).
• Arnold Unterauer, Thomy Phan, Philipp Altmann, Claudia Linnhoff-Popien, “Hidden Attacks in Multi-Agent Reinforcement Learning,” 2023 (Master).
• Leonard Feuchtinger, Philipp Altmann, Fabian Ritz, Claudia Linnhoff-Popien, “Distributional Shift in Reinforcement Learning – Learning from a single gridworld,” 2022 (Bachelor).
• Marco Börner, Thomy Phan, Philipp Altmann, Claudia Linnhoff-Popien “Predicting the optimal approximation level for Quantum Annealing,” 2022 (Bachelor).
• Felix Sommer, Thomy Phan, Philipp Altmann, Claudia Linnhoff-Popien “Learning Trust in Multi-Agent Systems,” 2020 (Master).