“Anyone who finds them in a position to work with Wolfgang would be missing out on the opportunity if they did not. It was my pleasure to work for Wolfgang, among 3 others, during my time at JUUL Labs where he demonstrated an innate ability to motivate, collaborate, and incentivize those working for him and working with him. Wolfgang was my manager early in my career and even though I had little experience, comparatively speaking, he worked alongside me as a player-coach, never once making me feel that he was above the work he asked for my help with or that he was not invested in it. What stands out the most is the way he approached and addressed conflict and feedback with me. Once when I had over committed myself to too many requests and was not going to meet the deadlines, Wolfgang approached me and coached me on how to handle deadline slippage through providing proper notice and increasing visibility to prevent over committing myself and my resources and to prevent me from experiencing burnout. The way in which he approached this was both professional, helping me and my shareholders to understand the situation and work balance, but also personal in that I felt supported and part of the team. He helped me understand why it was happening and helped me put in place a new protocol to protect my time and avoid the issue in the future. This was crucial for me to learn at an early point in my career. During my time working with Wolfgang our team was focused on Thermal performance and Simulations validation. When evaluating a complex product with multiple matter phases (multi-physics of fluids and gases), fast reaction times, and microfluidic forces at play this was a hugely cross functional effort. We would regularly meet and discuss with; firmware, to confirm that the control laws in place were correct for the different heater types; chemistry, to gather and help prepare fluid for testing; and Electrical and Battery teams, to confirm optimum conditions for testing and how performance may vary. There was a lot of coordinating, collaboration, and competing ideas that needed to be evaluated and Wolfgang handled it all with humility and poise. In addition to this endeavor, we also launched research projects that continued through COVID with both of us going to extreme lengths to continue the experimentation and development, finding places to work outside, bringing lab tools and equipment, a whole production in pursuit of science. I genuinely miss the days when we would work together, and I cannot recommend Wolfgang enough. 12/10, Would recommend to a friend.”
Wolfgang Black, PhD
San Francisco, California, United States
952 followers
500+ connections
About
Applied scientist in Machine learning classically trained in Mechanical Engineering with…
Activity
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Building a GenAI proof of concept? Perhaps a few weeks. Try deploying that globally at scale? That is a whole other ball of wax. I've been…
Building a GenAI proof of concept? Perhaps a few weeks. Try deploying that globally at scale? That is a whole other ball of wax. I've been…
Liked by Wolfgang Black, PhD
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Repeat after me: EVs are the solution to save the car industry, not the climate. We've forgotten what it was like to live in cities designed for…
Repeat after me: EVs are the solution to save the car industry, not the climate. We've forgotten what it was like to live in cities designed for…
Liked by Wolfgang Black, PhD
Experience
Education
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- Developed end-to-end modeling pipelines to tackle object detection, semi-supervised learning for biomedical image classification, and conversational AI utilizing SOTA deep learning
- Deployed models on AWS utilizing Docker and EC2 instances -
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Activities and Societies: Teaching assistant for Solid Modelling, Thermodynamics Research assistant for the Missouri Shock Tube Facility
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Licenses & Certifications
Courses
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Advanced Thermodynamics
8380
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Computational Heat Transfer and Fluid Dynamics
8420
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Gas Dynamics
7450
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Intermediate Fluid Mechanics
7420
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Intermediate Heat Transfer
7310
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Introduction to Turbulence
8450
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Introduction to Two-Phase Flow
8430
Projects
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Contrastive Learning for OCT Disease Classification
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Retinal OCT image analysis for eye disease diagnosis: The OCT (Optical Coherence Tomography) is an imaging method used to capture cross sections of the retinas of patients. The captured images are used to diagnose the patient’s retinal health into four categories: Normal, CNV, DME, and DRUSEN. The goal of the first part of the project is to reproduce the state of art classification accuracy by training Deep Convolution Networks following the standard Supervised Learning paradigm. The second…
Retinal OCT image analysis for eye disease diagnosis: The OCT (Optical Coherence Tomography) is an imaging method used to capture cross sections of the retinas of patients. The captured images are used to diagnose the patient’s retinal health into four categories: Normal, CNV, DME, and DRUSEN. The goal of the first part of the project is to reproduce the state of art classification accuracy by training Deep Convolution Networks following the standard Supervised Learning paradigm. The second part of the project is about learning features from images without labels (Unsupervised Learning) based on the recent ‘Self-Supervised Learning’ method, with the goal of improving the classification accuracy over the baseline established from the first part of the project.
Other creatorsSee project
Languages
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Japanese
Limited working proficiency
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German
Limited working proficiency
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English
Native or bilingual proficiency
Recommendations received
2 people have recommended Wolfgang
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