I am a Software Engineer focused on building scalable multimodal machine-learning systems. I hold an M.S. in Computer Science from UNC Chapel Hill, with a specialization in Robotics and Machine Learning. Before that, I completed my B.S. in Computer Science at the Karlsruhe Institute of Technology in Germany. I also spent over four years as a student research engineer at Fraunhofer IOSB. I've been fortunate to receive a Fulbright Scholarship during my studies.
My work focuses on building and evaluating scalable machine-learning systems that generalize across tasks and modalities, with experience in multimodal models, large-scale distributed training, and adversarial evaluation of LLM behavior.
A model that generates music aligned to a given video by fusing optical-flow motion cues with CLIP-based visual embeddings to condition an autoregressive music decoder.
An extension of an existing benchmark for evaluating Vision-Language-Action Models in simulation that is more comprehensive, faster, and easier to extend.
A demonstration that current LLMs (late 2024) are still susceptible to persuasion-based jailbreaking, along with an investigation into defense strategies.
An LLM-based natural language control interface for Pollen Robotics' Reachy robot, allowing users to control the robot through voice. A user study compares it against VR teleoperation.
A holistic view of reactive shield synthesis that unifies existing literature and provides a complete formal proof for the construction of winning regions in safety g.
Proposes two scheduling policies for Cyber-Physical Systems in dynamic environments that maximize processor utilization while maintaining a safety margin.
A proof of concept for decentralized identities in the context of car rental, consisting of microservice-based applications that issue and verify digital driver licenses.
An in-depth analysis of decentralized identity protocols (OpenID4CI, OpenID4VP, SIOPv2, OAuth 2.0, OIDC) and a discussion of their applicability in a proof of concept.