Our People

I am a data scientist at the Bosch Center for Artificial Intelligence, focusing on Time Series Analysis and Forecasting. I received my degree in Mathematics from the UNCPBA in Argentina. Since then I have worked mainly in developing forecasting and anomaly detection systems.

I am a research scientist at the Bosch Center for Artificial Intelligence in Renningen. My research aims at modeling of vehicle emissions with a focus on multi-output models. Previously, I worked on machine learning problems in statistical genetics and cancer research. Before that I did my PhD in probabilistic modeling for computational biology at the Max Planck Institute for Intelligent Systems.

I lead a research group at the Bosch Center for Artificial Intelligence on Deep Learning for perception. In particular, our goal is to develop accurate and explainable perception based on various sensor modalities to enable autonomous driving. Previously, I did my PhD at Bosch and TU Munich in the field of reinforcement learning. Subsequently, I was working with our autonomous driving team in Palo Alto.

I am an engineering manager at the Bosch Center for Artificial Intelligence in Sunnyvale. I completed my PhD in Cognitive and Neural Systems at Boston University in 2014. My primary focus is scaling and reliability for AI-powered products.

My research at the Bosch Center for Artificial Intelligence focuses on deep learning, in particular the automated design of deep neural networks for multi-task learning and hardware efficiency, and its applications to perception and autonomous driving tasks.

I received my PhD from the Technical University of Munich in collaboration with the Max Planck Institute for Brain Research in Frankfurt where I worked on automated methods to reconstruct neural circuits of organisms from electron microscopy data.

My research interest include: Automated Deep Learning, Hardware-aware Neural Architecture Search, Deep Learning for Perception and Traffic Scene Understanding.

As a Data Scientist at the Bosch Center for Artificial Intelligence, I am focusing on applied machine learning. Being exited about data-driven methods for real-world problems, I am interested in probabilistic modelling, Deep Learning, and Reinforcement Learning. Currently, I am involved in designing models for Autonomous Driving.

Before joining Bosch I was a theoretical astrophysicist studying the formation of galaxies. I received my PhD in computational astrophysics from the University of Heidelberg. After working as a Research Fellow in Garching and Cambridge, I led a group at the LMU Munich focusing on applying machine learning methods to astrophysical problems.

I have 6+ years of experience as software engineer. Last role was a software developer at IBM working in an IoT solution called Maximo worker insights. I was more focused on backend development using nodejs, edge event processing, and building real-time analytics using IBM Streams.I have also a background in ML and data science as I am doing a second Master course at TUM in data engineering and analytics.

I am coming from Daimler Mobility AG (Financial Services) where I worked for 4 years mainly around advanced analytics and data management platforms in the cloud. I'm currently finishing my Masters degree in Software Technology at the HFT Stuttgart and look forward to building up sustainable solutions for the BCAI.

I am a Data scientist at the Bosch Center for Artificial Intelligence. I have completed my PhD at electrical engineering department of University of Minneosta. During my PhD, I worked on deep learning, specifically self-supervised learning. I am excited to be a part and contributor to cutting-edge AI projects conducted at BCAI.

I received my PhD in astrophysics from the University of Chicago. Following a post-doc at the University of Michigan and a Kavli Fellowship at Stanford University, I joined Bosch as a data scientist in 2014.

I am a PhD student working on safe and efficient model-based reinforcement learning. The aim of my research is to enhance the performance and robustness of real-world dynamical systems, accounting for unpredictable environments and uncertain dynamics. I obtained my Bachelor's degree in Electronics engineering from University Simon Bolivar (Venezuela) and my Master's degree from University of Toronto. My Master's research focused on multi-robot motion planning with applications to drone swarms.

I am a PhD student at the Bosch Center for Artificial Intelligence and TU Berlin. My current work focuses on safe active learning for multi-task models. I obtained my Master's in Neural Information Processing from University of Tuebingen. My master's thesis was about dynamic modeling of monkey's motor system.

I am a PhD student at the Bosch Center for Artificial Intelligence (BCAI) in Pittsburgh studying deep generative models for time-series data. Before joining BCAI, I studied Electrical Engineering and Information Technology at university of Erlangen-Nuremberg. During my master thesis, I developed algorithms based on deep neural networks to detect the objects on the occupancy grid maps. Now, my goal is to explore novel ways to ensemble deep latent variable models for more robust unsupervised machine learning.

I am Director of Engineering and Research and Development at Robert Bosch LLC, I am responsible for the Bosch Research and Technology Center (RTC) and the Bosch Center for Artificial Intelligence (BCAI) in Pittsburgh, PA. Partnering with universities and national agencies, as well as others in the business sector, I help to guide Bosch strategy through early identification and shaping of technology and market forces for the Internet-of-Things (IoT), with a special focus on artificial intelligence (AI) and cybersecurity. I hold an undergraduate and graduate degree from Carnegie Mellon University's Department of Electrical and Computer Engineering (ECE) and have nearly 20 years of experience at Bosch in leveraging corporate and academic research to identify, create and transfer innovative products and services.

I am a research scientist at the Bosch Center for Artificial Intelligence. Previously, I received my PhD in robot learning from TU Darmstadt's IAS lab. My research interests focus on modeling and control of physical systems.

I am a research engineer at the Bosch Center for Artificial Intelligence (BCAI) in Renningen. I am interested in machine learning for robotics with a focus on perception. I have a background in particle physics where I did my PhD at the TU Munich.

I am interested in making robots see and understand the environment around them. During my PhD at the University of Edinburgh, I researched methods for visual articulated tracking for grasping tasks. Before joining Bosch, I was a Post-Doc at the University of Edinburgh, where I focused on model-free methods for object segmentation and tracking. My research interests currently cover hybrid state estimation methods that combine machine learning with classic approaches, in order to make those methods more robust and generically applicable without the need for task-specific prior knowledge.

I work as a communications manager at the Bosch Center for Artificial Intelligence and am responsible for the internal and external communications of the BCAI. This includes managing BCAI's media presence, designing our website and internal communication channels, and being responsible for our social media channels. Additionally, I am responsible for the conception and execution of BCAI events as well as our participation in external and internal events and scientific conferences.

Creating the new AI Campus, the home for top research and applied AI in Tübingen, which will shape Cyber Valley, one of the most well-known AI Ecosystems in Europe. This €100m investment is the single biggest investment by Bosch in AI, showing the company’s commitment in making Bosch the leading player in Industrial AI.

My research at the Bosch Center for Artificial Intelligence focuses on the development of safe active learning methodology in the context of Real-Driving Emissions. Safe active learning methodology supports the engine calibration process by suggesting experiments that maximize information gain while satisfying safety constraints. The general guideline for my research is: recognize the application's challenges, develop solid mathematical methods in response and return tailored solutions.

I obtained my PhD from the Heidelberg university in interdisciplinary mathematics and collaborated with systems biologists and epidemiologists during my postdocs at the center for modeling and simulations in the biosciences in Heidelberg and Yale School of Public Health.

My research interests include Calibration, Parameter Identifiability, and Stochastic Processes.

I am a research scientist at the Bosch Center for Artificial Intelligence. Currently I work on machine learning algorithms for the application domain of autonomous driving, based on probabilistic graphical networks. Other topics are predictive diagnosis of faults based on time series from sensor data and detection of anomalies.

I am a data engineer at the Bosch Center for Artificial Intelligence (BCAI) and will therefore focus on implementing pipelines to streamline processes. I did my PhD in Bioinformatics at the university of Würzburg, where I implemented pipelines to process, transform and analyze biological data.

I am a senior data scientist at the Bosch Center for Artificial Intelligence (BCAI) in Sunnyvale working on neural architecture search for video cameras. I received my PhD from UCLA majored in electrical engineering. Then I joined different industries including wireless chip design, autonomous driving, and network services/manufacturing, where I applied deep learning and computer vision to solve a variety of industrial problems.

I am a research scientist at the Bosch Center for Artificial Intelligence (BCAI), where my work focuses on probabilistic environmental modelling for autonomous driving applications. Before joining BCAI I completed my PhD in Neuroimaging at University College London, working on the development of image processing algorithms to analyse large data sets of structural brain scans. My research interests lie primarily in the field of unsupervised machine learning and Bayesian inference.

I am a Data Scientist for Deep Learning at the Bosch Center of Artificial Intelligence in Renningen. My current technical focus is on improving the internal processes at BCAI using the state-of-the-art Deep Learning techniques.

Prior to joining BCAI, I completed my Masters and Ph.D. in Computer Vision from TU Eindhoven, The Netherlands.

This was in collaboration with Cyclomedia Technology, a street-view imaging company, where I also worked as a Computer Vision Engineer.

I joined the Bosch Center for Artificial Intelligence in summer 2018 as a project assistant. My task is to support the project board in organizational and content-related topics.

I am currently a research scientist at the Bosch Center for Artificial Intelligence in Renningen. My research interest mainly includes discrete/combinatorial optimization. Recently I have focused on developing semantic segmentation methods via probabilistic graphical models (e.g., Conditional Random Fields) and deep learning. I graduated in 2011 from the University of Szeged, Hungary. I spent two years (2012-2014) as a Research Fellow at the National University of Singapore. I worked as a PostDoc at IST Austria in 2014. Before joining to BCAI, I was an Alexander von Humboldt Fellow (PostDoc) at TU Munich.

My research interest include discrete/combinatorial ooptimization, computer vision, semantic segmentation, and image registration.

I am a Research Engineer at the Bosch Center for Artificial Intelligence. As part of the NS-AI team, I aim to bring state-of-the-art AI solutions over knowledge graphs. I received my Master and Ph.D in Computer Science at Max Planck Institute for Informatics. My research interests are knowledge acquisition, knowledge base applications and applied machine learning. Previously, I worked on the problem of knowledge graph construction for specific domains such as healthcare and literature and developed end-user applications on top the knowledge graphs.

I am a research scientist at the Bosch Center for Artificial Intelligence, working on deep learning in particular from the Bayesian viewpoint. I received my PhD in electrical engineering from RWTH Aachen University. After that, I spent three years at TU Dresden, working as a postdoctoral researcher and also leading a research team at Vodafone chair mobile communications systems. During my PhD as well as my postdoctoral phase, my research focus was on investigation of approximate Bayesian inference techniques from theory to practice. The main application area was wireless communications. Combining deep learning with Bayesian techniques is an exciting research field. Since joining Bosch, I have been aiming at assessing the uncertainty in deep learning with the aid of Bayesian techniques.

My research interests include Deep Learning, Bayesian Inference, and Statistical Signal Processing.

A physicist by training, I joined Bosch in 2015 after two years in a startup. Before joining the BCAI, I worked in PS (and its predecessors) on predictive maintenance. I started work in BCAI with the Rapid OEM Release project as a data engineer focusing on spotfire-visualisations and the ETL pipeline.

Currently, I am a lead research scientist at the Bosch Center for Artificial Intelligence (BCAI). My main research interests lie in the area of neuro-symbolic AI. More specifically, I am focused on relational representation learning, rule learning and reasoning in knowledge graphs as well as exploitation of symbolic domain knowledge in machine learning models. Prior to joining Bosch I was a senior researcher at Max Planck Institute for Informatics, where I headed a group on Semantic Data. I obtained a PhD in computational logic from Vienna University of Technology (Austria) in 2015, where I worked on the problem of resolving inconsistencies in hybrid knowledge bases.

I am a PhD student working in the field of unsupervised video representation learning. Prior to that, I wrote my Master thesis in the Perceiving Systems Department at the MPI for Intelligent Systems followed by an internship. During that time I studied the use of synthetic training data for multi-human 2D/3D pose esitmation and optical flow estimation.

I am a Data Engineer at the Bosch Center of Artificial Intelligence (BCAI) in Renningen. I finished my master's degree in physics at the TU Darmstadt (Germany). Within my degree I got in touch with the world of AI, which brought me here.

In my research at the Bosch Center for Artificial Intelligence, I aim to contribute to a deeper and mathematically rigorous understanding of machine learning methods. My main interest lies in the generalization performance of learning algorithms, in particular for the case of limited sample size and noisy data which is relevant to the real world.

I am fond of Bayesian methods and currently applying them to problems in the automotive domain. Prior to Bosch, I worked as a postdoctoral researcher in the Quantum Information sciences, employing methods from Mathematical Physics and optimization.

I am a Data Scientist at the Bosch Center for Artificial Intelligence. Prior to joining BCAI, I worked as a Data Science Consultant developing and deploying machine learning solutions, designing and implementing analytics infrastructures in the cloud, and generally helping organizations create value through data. I believe that an "end-to-end mentality" is key to the success of data science and machine learning, and I am excited to create value at Bosch by applying cutting-edge AI to real-world problems.

I am a research scientist at the Bosch Center for Artificial Intelligence, focusing on robust deep learning and hybrid systems. Before joining Bosch, I received my PhD in math from University of Kentucky in 2018, focusing on deep learning and its application to problems in RNA structure inference.

I manage a research group at Haifa, Israel on Vision based and Computational Methods for Reinforcement Learning. I did my PhD at the Technion, Israel Institute of Technology on Actor Critic methods. Before Bosch I was a senior research scientist at Yahoo! Research and worked on ML and Big Data problems. Before that, I worked for IBM reseach and for several startups. My main interests are autonomous systems, both real and virtual, RL theory, and robotics.

I am a Research Engineer at the Bosch Center for Artificial Intelligence (BCAI). Before joining BCAI, I was a co-founder of a startup Ambiverse, that focused on Natural Language Understanding technologies, specifically, named entity recognition and disambiguation, concept recognition and disambiguation and open information extraction. I have also worked at the Max Planck Institute for Informatics in Saarbrücken as a Scientific Programmer/Researcher for few years. I hold a Master's Degree in Computer Science from Saarland University. My Master's thesis, completed at the Max Plank Institute for Informatics, focuses on hybrid Entity Recommendations System, that leverages the Wikipedia revision history and the type hierarchy of the entity categories. I obtained my Bachelor's Degree from the University Ss. Cyril and Methodius in Skopje, Macedonia.

I am a research scientist at the Bosch Center for Artificial Intelligence in Renningen. I am interested in developing probabilistic models for various application areas, such as control and robotics. I hold a PhD degree in machine learning from the Max Planck Institute for Biological Cybernetics (Tübingen), where I was a member of the "Robot Learning Lab" focusing on Gaussian process models for robot control. At Bosch, I have continued to pursue my work in model learning. Over the past years, I have become more interested in control and policy learning, which can be useful for numerous automotive and industrial applications.

I am a Research Engineer at Bosch Center of Artificial Intelligence (BCAI) in Haifa. I completed my Master's in Computer Science at the Technion. My main focuses are deep learning for Video Processing and Graph Neural Networks.

I am originally from Venezuela, I studied and worked in Colombia and I moved to Germany in 2018. The first years of my professional life I started developing software with Java based frameworks, then I started working at IBM as an application developer. Afterwards I had the opportunity to do an internship and work as a software developer in a startup in Germany where I focused mainly on web development, first using Flask and then Angular and Bootstrap. Since October 2021 I work at BCAI, where I apply and increase my knowledge during the creation of graphical interfaces to bring new features and improve the user experience.

As a consultant of the Bosch Center for Artificial Intelligence (BCAI), I am responsible for acquiring new data driven projects within different Bosch departments. Prior to this I worked on my Master thesis at BCAI Research where I developed driving policies imitating human driving behaviour. I am exited to help different departments to utilize AI in order to increase their revenue.

I started in the early 90ies as a classical software developer at Bosch, being interested both in coding and harmonizing and highly automating the development environment. After a few years, I changed gears and focussed on running different projects, groups and departments. Carving processes, software usability (nowadays called User eXperience), driving architecture to enable reuse, and introducing agile methods excite me. Recent assignments brought me into the world of clouds and IT service management.

I'm thrilled to be a member of BCAI, now! I've joint the team to enable industrialization of our great BCAI services. The new industrialization department will boost the maturity of our services to become scalable, robust, and reliable on a leading edge industry level.

I am a research scientist at the Bosch Center for Artificial Intelligence. Currently, I work on machine learning algorithms for the application domain of autonomous driving, based on probabilistic graphical networks. Previously, I have worked on bringing machine learning to automotive ECU calibration and function development. I strive to bridge the gap between theoretical advances and business impact of machine learning.

My research interests include: efficient inference, probabilistic graphical networks, reinforcement learning, and numerical optimization methods.

Evgeny is a Senior Expert in AI methods for Semantic Digital Twins and Knowledge Graphs at the Bosch Center for Artificial Intelligence and an Associate Professor in AI at the University of Oslo. Evgeny does AI-centered R&D on Semantic Technologies, Digital Twins, Ontologies, Knowledge Graphs and on their combination with Machine Learning methods. This in particular accounts for knowledge representation, symbolic methods and database techniques as well as for knowledge embedding, reinforcement and deep learning over and for knowledge graphs and ontologies. Evgeny's work allows to enhance data and knowledge access, exploration, and analyses and it is motivated by and applied to the context of Industry 4.0. Evgeny's work led to 130+ publications at conferences and journals. Evgeny raised or participated in raising of about 3M EUR of research funding. He was in charge of several industrial collaborations of the University of Oxford with companies and of several EU projects (FP7, H2020).

Find out more about Evgeny in this interview.

I work in the enabling group and have several roles in the team. I work as an instructor and mentor for the Data Engineer Expert course, in which we cover topics related to data pipelines. I am also responsible for parts of our internal infrastructure that we have created to support all our training courses, as well as for the maintenance of internal systems that support, among other things, self-study learning formats and AI competitions within Bosch.

I have a master's degree in astrophysics from the University of Munich.

Before I joined Bosch, I developed web applications (full-stack) with the goal to map and improve internal processes of companies.

I am a PhD candidate at the Bosch Center for Artificial Intelligence (BCAI). I obtained my master's degree in computer science at TU Darmstadt. In parallel to my master’s, I worked part-time on uncertainty estimation and improving time series forecasting methods with deep and hybrid methods.

My research focus at the BCAI is on reinforcement learning and its applications to robotic grasping. Currently, I am looking into mathematically more principled approaches for trust region methods in deep reinforcement learning.

I started at the Bosch Center for Artificial Intelligence (BCAI) as a research engineer to solve challenging real-world problems using machine learning. Previously, I did my PhD with Intelligent Autonomous Systems (IAS) group at the TU Darmstadt in collaboration with the Honda Research Institute (HRI). During this time, I focused on making robots learn control policies such that these are transferable from simulation to the real world. Prior to that, I obtained my MSc in mechnical engineering from the TU Munich.

I'm a machine learning research scientist at the Bosch Center for Artificial Intelligence in Pittsburgh. My research interests are robust machine learning, deep learning, and image processing. Before joining Bosch, I was a post-doctoral research associate at Carnegie Mellon University, working on robust medical image classification (bimagicLab) and deep learning on socio-economical networks (SLD). I received my PhDs from Carnegie Mellon University and from University of Lisbon, where my thesis focused on robust image classification with context and rejection.

I am interested in using uncertainty information in reinforcement learning to make better decisions - both in terms of data-efficiency and safety (constraint satisfaction) during the exploration/learning process.

Before I joined BCAI, I worked on user-centered planning and decision making, first at Ulm University, where I received my Ph.D., and later in the user monitoring and modeling research group within Bosch. At BCAI, I work on Reinforcement Learning and Combinatorial Optimization.

I am a research scientist at the Bosch Center for Artificial Intelligence, working on adversarial machine learning. In particular, I am interested in improving the robustness of neural networks. I hold a PhD degree in computer science from the university of Bonn. As a postdoctoral researcher, I visited universities in London (Ontario), Paris (France), Freiburg (Germany) and Munich (Germany).

My research interests are in developing efficient and mathematical consistent algorithms that solve practically relevant problems. In the past, I worked on computer vision and geometric problems. Depending on the problem, I worked either on discrete or continuous approaches which involved but were not restricted to differential geometry, partial differential equations, convex and non-convex optimization as well as planar graphs, integer linear programming and hierarchical model estimation.

I am a Big Data Architect at the Bosch Center for Artificial Intelligence, located in Bangalore, India. At Bosch I am part of the data engineering team of Manufacturing Analytics Solution. Prior to Bosch, I have worked in designing big data pipelines and developing products enabling data analytics and machine learning in the automotive test domain.

I am a doctoral student at the Bosch Center for Artificial Intelligence and the Intelligent Autonomous Systems group at TU Darmstadt. My research focuses on how the sample complexity of reinforcement learning algorithms can be improved by transferring prior knowledge from previous problems.

I am a research scientist at the Bosch Center for Artificial Intelligence. My research interests comprise reinforcement learning, deep learning, generative and probabilistic modelling.

Before joining Bosch I did my PhD at the university of Karlsruhe in theoretical physics.

I am a software engineer with a passion for robust, clean and open software. In my past I worked with several projects in the area of mobile robotics. Here I already focused on robustness of our software stack and working prototypes. Recently, I started to focus on general software engineering and tooling for developers in my environment. I helped to strengthen the use and integration of Linux for developers in an open and collaborative fashion. My current mission is to shape and impove the software developer ecosystem within the Bosch Center for Artificial Intelligence (BCAI).

I am Machine Learning Engineer at the Bosch Center for Artificial Intelligence, Bangalore, India. Post graduate in Computer Science and Engineering . Prior to Bosch, I have worked as Associate developer with SAP Labs India pvtltd. I am passionate about Artificial Intelligence to solve real world problems.

I am the assistant to the Global Head of the Bosch Center for Artificial Intelligence. I am responsible for all administration tasks relevant to the global head's office.

I am a Security Coordinator at BCAI with 15 years experience in security topics.
I have been working at Bosch since 2002.

I am a Data Engineer at the Bosch Center for Artificial Intelligence (BCAI) based out of Renningen, Germany. I am part of the data engineering team of Manufacturing Analytics Solution, which is the flagship product of BCAI for industrial IOT and manufacturing intelligence. Prior to joining BCAI, I have designed and built demand forecasting services for retail and supply chain and designed data-acquisition systems for autonomous driving.

I am Frontend Engineer at Bosch Center for Artificial Intelligence (BCAI) in Renningen.

Before joining BCAI I worked as Software Developer with focus on frontend using modern technologies such as Angular. In addition to frontend, I have experience in backend development with Java and Spring Framework.

I hold a degree in Computer Science from the University Lucian Blaga in Sibiu, Romania.

I am a research scientist at the Bosch Center for Artificial Intelligence. My research focuses on deep learning, particularly with a combination of adversarial machine learning, automated machine learning, and in computer vision applications. Before joining Bosch, I received my PhD from the University of Bremen where I was part of the robotics group and the Robotics Innovation Center at the German Research Center for Artificial Intelligence (DFKI) where I did research in hierarchical reinforcement learning, Bayesian optimization, and brain computer interfaces.

My research interests include: deep learning, adversarial examples, hierarchical reinforcement learning, Bayesian optimization, and automated machine learning.

I am a research scientist at the Bosch Center for Artificial Intelligence. My research focuses on deep learning, particularly in medical image analysis and object localization. I am responsible for technical development in an international project to ease detection of diabetic retinopathy. I am an engineer and statistician by training.

My research interests include: deep learning, uncertainty in deep learning, as well as adversarial examples and detection.

I am a research engineer at the Bosch Center for Artificial Intelligence in Renningen. I hold a doctoral degree in bioinformatics from the Max Planck Institute of Biochemsitry (Munich), where I was a member of the "Computational Systems Biochemistry Lab" focusing on Proteomics data analysis. At Bosch I am developing and applying machine learning methods to solve real-world problems.

I am a Data Scientist for Deep Learning at the Bosch Center for Artificial Intelligence. As part of the industrialization team, I aim to bring state-of-the-art AI solutions into internal Bosch processes. I received my Masters in Cognitive Science from the University of Tübingen and worked as a research associate at the Hertie Institute for Clinical Brain Research. Previously, I worked for SAP in various software development and customer-facing roles.

I am a PhD student at the Bosch Center of Artificial Intelligence (BCAI) in the field of Reinforcement Learning for Decision Making in Autonomous Driving. Before joining the BCAI, I studied Electrical Engineering and Information Technology at the Technical University of Munich. During my MA thesis, I developped deep neural network based algorithms to estimate human hand poses from depth images. Now, my goal is to develop novel algorithms for autonomous driving based on reinforcement learning that can efficiently handle complex traffic situations and no longer stand back behind human drivers.

I am interested in (deep) reinforcement learning algorithms and concepts for autonomous driving.

I am a Data Scientist at the Bosch Center for Artificial Intelligence in Sunnyvale. I have a PhD in Theoretical Particle Physics from UC Davis. As a postdoctoral researcher at Rutgers, University of Illinois, and University of Cincinnati, I performed original research on the physics of dark matter and methods for detecting new particles in experiments, such as the Large Hadron Collider. Before joining Bosch, I went through the Insight Data Science program as a Data Science Fellow. I joined Bosch in 2021 and am currently working on lifetime optimization for Battery in the Cloud.

I have multiple experiences revolving around Artificial Intelligence and robotics (Ph. D., research engineer, data scientist, machine learning engineer). I am now very interested by all elements revolving around "putting AI in production". I am looking forward to apply my skills on the robotics domain within Bosch.

I am the assistant of the Research team at the Bosch Center for Artificial Intelligence (BCAI) focusing on administrative and organizational tasks. My journey at Bosch started back in February 2011 and I joined BCAI in 2017.

I am a PhD student at the BCAI, currently working on model-based RL approach for robotic manipulation tasks. Before joining BCAI, I attained my master's degree, in Mechanical Engineering, from the University of Politecnico di Milano with my thesis topic on Model-Based Reinforcement Learning Variable Impedance Control for Human-Robot Collaboration.

I am a PhD student working on Meta Learning, with a focus on multi-objective Bayesian Optimization. The goal of my research is to improve the data efficiency of machine learning algorithms and enable them to learn new tasks more easily.

Before joining BCAI, I completed my Bachelor's degree in information engineering at Guangdong University of Technology and my Master's degree in information and communication technology at Friedrich-Alexander-Universität Erlangen-Nürnberg.

I am a software engineer at the Bosch Center for Artificial Intelligence in Bangalore. I completed my Bachelor's degree in Computer Science and Engineering from West Bengal University of Technology, Kolkata. I have expertise on DevOps, Cloud and Microservices. My interests are in Big Data and Machine Learning.

I enjoy working with motivated teams and users on high quality software solutions. My favorite topics are clean code and architecture, functional programming, and other tools and techiques to prevent long-lasting codebases from drifting towards chaos. My latest endeavers are a project on automated highway lane change decision making, where I was responsible for architecture, deep learning, and DevOps questions, as well as a few spare time projects where I made first experiences in building dynamic websites and Android app development.

Before joining the Bosch Center for Artificial Intelligence as a research engineer, I studied computer science with focus on software engineering and machine learning. After receiving the master degree I co-founded a startup focussing on time series analysis and unsupervised learning. Afterwards I joint Bosch as development engineer for automated driving. Currently I am working in the research group on environmental understanding and decision making, developing novel approaches for behavior planning based on reinforcement learning.

I am interested in bringing machine learning solutions in driver assistance and automated driving.

Being a curious person, I like gaining new insights using data-driven methods. In the past, I had the opportunity to do this for Bosch radar and camera sensors as well as for driverless vehicle projects. Before, I worked in the retail and electromobility area, e.g. on predicting the remaining lifetime of a lithium-ion battery.

I am a research engineer at the Bosch Center for Artificial Intelligence in the research group on deep learning, located in Renningen. I am currently working on deep learning-based methods to fuse, predict and temporally integrate the information of sensors, with the aim of generating a robust representation of the environment.

My research interests include: recurrent neural networks, multi-modal deep learning, temporal prediction and integration, and semi-supervised learning.

I am a data engineer at the Bosch Center for Artificial Intelligence, located in Sunnyvale, California. I have a PhD in Physics from the University of Oregon where I did Gravitational Wave data analysis. Prior to joining Bosch, I completed a Data Engineering fellowship at Insight Data Science.

I'm a Data Visualization Specialist - UX Designs working with the services team of Bosch Center for Artificial Intelligence located in Bangalore. I’ve completed my Bachelors in Engineering from Anna University in 2015. My interest lies in projects with User research, Visual wireframing and BI dashboard design. In the past I’ve worked with Data visualization and User eXpericence design projects for multiple industry groups ranging from FMCG, Hospitality, Insurance, Logistics to Airlines supporting their Sales, Marketing, HR, Ticket management and Finance domains.

I am part of the Bosch Center for Artificial Intelligence Consulting Team in Renningen. I completed my master degree in Computer Engineering in Bari (Italy) mainly focusing on Machine Learning. I worked for a year as a research assistant at Polytechnic University of Bari and my main research topic was Recommender Systems. Afterwards, in 2019 I've been selected for the Bosch Industry 4.0 Talent program in Italy and then joined BCAI in 2021. I am highly interested in the application of machine learning techniques to solve the real world problems.

After studying maths and computer science at the university of Stuttgart, I joined the Bosch Center for Artificial Intelligence as a PhD student. During my PhD, I've worked on learning control on continuous domains and stability analysis of learned controllers and dynamics models. As a research scientist, I continue to work on reinforcement learning, robust control and theoretical analysis of learning control.

Since my early years I am developing software for the web. Starting with pure HTML/CSS/JS pages and PHP backends, I nowadays am a lover of frameworks (Angular, Bootstrap, ...) and modern languages for backend programming (Go, Node).

I studied IT Automotive at the DHBW Stuttgart some years ago, so I count my self as part-engineer. I love to tinker with eletronic circuits, 3d printing and any kind of automations.

In the past, I was doing projects as DevOps engineer, both for Dev and Ops sides. So I call myself familiar with technologies in that chains.