My name is Falk Pollok. I am a Senior Research Software Engineer at the MIT-IBM Watson AI Lab.
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- PalmQA: Question answering ensemble for e-learning and research at RWTH Aachen that was able to defeat PhDs on factoid open domain question answering tasks
- IBM Sapphire: I was the lead developer of IBM Sapphire at the University of Michigan, a dialog system for academic advising which consisted of over 30 neural and non-neural AI services.
- IBM’s Fabric for Deep Learning (FfDL) / Watson Machine Learning: Open source heart of Watson Machine Learning (WML) for framework-agnostic distributed deep learning on top of Kubernetes that integrates with a wide ecosystem of related open source projects like Uber Horovod, the Adversarial Robustness Toolkit (ART), AI Fairness 360 (AIF360), H20.ai, Seldon and kube-batch. Won InfoWorld’s Best of Open Source Award 2018.
- IBM Verdi / Watson Orchestrate: Multi-Agent System for Business Process Optimization and Automation, foundation of Watson Orchestrate
- DARPA Machine Common Sense: My current main focus is the DARPA MCS project. I am a part of the MIT-Harvard-Stanford team to mimic the development of commonsense in young children working in close collaboration with Josh Tenenbaum, Dan Gutfreund and Vikash Mansinghka. We were able to defeat Berkeley and OSU by total score two times in a row. Furthermore, we acquired a robot to test our AI components in the real-world as well rather than purely in simulation.
- Global Advanced Prototyping Team: While remaining part of the MIT-IBM team, I have devoted some of my time to start collaborating with our Global Advanced Prototyping Teams as a catalyst to accelerate the transfer of cutting edge research into product. For instance, I have delivered Multivariate Singular Spectrum Analysis (mSSA) into our Smarter Resources and Operations Management solution and am now working on enhancing IBM’s plant optimization solutions such as the Cognitive Plant Advisor.
- Engineering Excellence: I have founded IBM’s Engineering Excellence Platform and led it for the first year. Now that it has grown bigger and has executive support, I serve on its steering committee.
Me with my colleagues Grady Booch and Lee Martie at the MIT-IBM Lab in Cambridge on the left as well as with Scott Boag at Stanford on the right.
I have a Bachelor’s and Master’s degree of Computer Science from RWTH Aachen.
Furthermore, I have for multiple years worked for the University of Michigan and with MIT (ongoing).
My publications can be found here, my IBM Researcher Profile is here, my microcredentials can be found here which include:
I also hold the Executive Leadership certificate from Cornell University as well as Performance Leadership and Change Management.
Outstanding Technical Achievement 2022: Neuro-Symbolic Models and World Simulators for Machine Common Sense
Congratulations Falk for being selected to receive an Outstanding Technical Achievement Award for your research on Neuro-symbolic Models and World Simulators for Machine Common Sense. Thank you for the work that you and your team do to solve difficult AI problems by collaborating with top research institutions on innovative ideas. Together with your collaborators you have demonstrated scientific leadership in the important AI field of common-sense reasoning. Your contributions include both algorithmic development and dataset creation, and through your work you have shown how common sense can be incorporated into neuro-symbolic AI models. The importance of your work on common-sense reasoning, and the strength of your team which includes collaborators from MIT, Harvard and Stanford, has also been recognized by the contract awarded to you by DARPA. In addition, you have impacted the broader AI research community by publishing numerous papers, giving many invited talks and tutorials at top conferences, and sharing datasets, challenges and your photo-realistic simulation platform for training and testing AI agents. Altogether this is an impressive example of cross institution teaming. Your research leadership on important and fundamental AI problems is what helps to make IBM Research known for its innovation, and your collaboration with the broader research community enriches IBM as a research institution and helps make it a great place to work. I and the Exploratory Science team appreciate and applaud your excellent work and look forward to future developments.Jeff Welser, COO IBM Research / VP Exploratory Science & University Collaborations / VP Almaden, Brazil & Japan Research
Research Accomplishment 2021: Neuro-Symbolic Models and World Simulators for Machine Common Sense
From a very young age, humans are able to grasp basic physical and social principles that govern their environment. For example, at around 4 months of age, babies understand that an object does not vanish out of existence even when it is out of sight. Often such principles are not labeled or taught in a direct supervised manner and we refer to them as common sense. As humans grow and develop the ability to communicate in natural language, their common sense understanding develops as well. For example, adults possess an intuitive understanding of Newtonian physics and are able to make accurate predictions and answer questions about dynamic scenes involving interactions between several objects. Common sense is necessary for humans, and other animals, to successfully interact with their environment and achieve their goals, and it is often a prerequisite for learning and solving higher-level tasks, e.g. changing a flat tire. It is likely that the road to general AI and embodied agents will require developing models and systems that have common sense. This accomplishment is for a body of work that led to a significant scientific impact, including more than 20 publications in top tier conferences, invited talks and organized workshops and patents, as well as [budget redacted since confidential, but a multi-million] 4-year DARPA contract, several open source projects including a highly realistic simulation environment for training and testing AI agents, numerous released datasets and benchmarks, and media coverage. This impact is a result of a long-term, cross-organizational and multi-disciplinary teaming effort between researchers and engineers from IBM and our academic partners at MIT, Harvard and Stanford. [If you are within the IBM network, you can read more here.]
One of Five Faces of IBM Research 2021
I was featured as one of the five Faces of IBM Research in 2021 for leading IBM’s Engineering Excellence platform. If you are within the IBM network, you can read more here (“Spotlighting our Engagement Catalysts – 5 researchers driving positive change and culture”). [I also received two Manager’s Choice awards in the years before.]
InfoWorld’s Best of Open Source (BOSSIE) Award 2018
My team received InfoWorld’s Best of Open Source (BOSSIE) award in 2018 for our work on the Fabric for Deep Learning.
Here is a selection of press coverage about projects I worked on.
Fabric for Deep Learning
- IBM wants to open up the deep learning expertise bottleneck
- Q&A on IBM’s Fabric for Deep Learning with Chief Architect of Watson
- IBM and University of Michigan develop human computer
- Your guidance counselor may one day be a robot
- U-M, IBM Partner on $4.5M Development of Conversational Computer
- IBM Watson Orchestrate uses AI to help improve sales, HR and operations
- IBM Introduces Watson Orchestrate for Task Automation
There were multiple articles about the DARPA Machine Common Sense project that I am currently working on, but since they tend to be about the whole project and not my team in particular, I will skip them for now.
“I am convinced that with his abilities and dedication he will be a great addition to any team aiming at pushing the boundaries of machine learning, reasoning and natural language processing for smarter and more natural interaction between humans and computer systems.”— Prof. Ulrik Schroeder, Professor at RWTH Aachen
“Falk is an exceptionally hard-working and dedicated member of the UMich team making this project happen. He is the lead developer for the project, and as such, manages the integration of research ideas into stable, well-engineered software. He has proven himself to be a critical piece of this multi-million-dollar collaboration between industry and academia.”— Prof. Walter Lasecki, Professor and PI at University of Michigan
“Falk’s leadership role as an experienced engineer at the MIT-IBM Watson AI lab has been crucial in achieving the goals and deliverables on some of the most central projects in the lab.”— Dan Gutfreund, Principal RSM and Manager at MIT-IBM Watson AI Lab
“Falk is a research engineer at the MIT-IBM Watson AI Lab. Since he joined IBM, he made important contributions to several projects touching on different aspects of AI such as NLP, vision and reasoning. His expertise in developing integrated AI architectures is invaluable. He is also known to work relentlessly, making sure no problem remains unsolved before he goes to sleep.“— Jessie Rosenberg and Dan Gutfreund (managers at MIT-IBM Watson AI Lab) in my nomination for IBM’s Stage for the Research Engineer
“I don’t think I’ve had a collaborator who writes such nice code (and cleans up my mistakes nearly as well)!“— Dan Bear, Postdoctoral Research Fellow at Stanford
“Falk, I want to thank you for your incredible contribution to the Engagement Catalysts efforts in 2021. Yours is the most significant contribution – you laid the ground for our Engineering Excellence platform (announced by Dario!). Your Engineering Excellence talk series is an admirable achievement, that professional event organizers would envy”— Michal Jacovi, Global Engagement Leader for IBM Research