Brian J. Stankiewicz, Ph.D.

3M Corporate Research Systems Lab

Principal Data Scientist • Jul 2017 — Present

Defined and developed the long-term vision of 3M Materials Informatics that focused on three technology pillars: Data, Analytics and Automation. Communicated and drove vision through 3M senior leadership that created a cross-functional program with 30+ scientists and engineers. These include data scientists, software engineers, data engineers, electrical engineers and material scientists.

• Technical lead for Materials Informatics in 3M Corporate Research Labs.
• Agile-Scrum cross functional team (software, mechanical, material science, artificial intelligence). Creating technical and business roadmaps.
• Accelerating research and development by creating and nurturing external relationships with vendors ( Citrine , ChemSpeed, Labman) and universities (University of British Columbia, University of Chicago, Argonne National Labs).

3M Health Information Systems

Principal Data Scientist • Jul 2012 – Jul 2017

Founded the Health Information Systems Data Science Lab and built to ten data scientists and data engineers. Developed new Natuaral Language Processing (NLP) applications and intellectual property portfolio for the business. Technical lead of a cross-company team between Google-Verily and 3M-HIS.

• Founded Data Science Lab in 3M Health Information Systems.
• Technical lead for 3M and Google-Verily Performance Matrix collaboration.
• Identify and develop new opportunities for in converting “Data to Dollars” in the 3M healthcare business.
• Develop methods and tools for working with Protected Health Information (PHI) data. Worked closely with internal 3M legal and external organizations.

3M Corporate Research Systems Lab

Data Scientist • Jul 2007 – Jul 2012

Founded the 3M Corporate Research Artificial Intelligence lab. Hired and acquired 20 scientists that included data scientists, machine learning experts and data engineers.

• Founder, 3M Corporate Research Labs (CRL) Artificial Intelligence Lab.
• Technical lead on Visual Attention Service. Create computer vision algorithms for predicting where visual attention will be allocated in an image.

University of Texas at Austin

Professor • Jun 2001 – Jul 2007

Developed research program focused on computer vision, virtual reality, robotics, and human navigation. Developed low-vision navigation aid technology that was patented and ultimately licensed. Taught courses in cognitive science, robotics and computer science.

• Created second largest VR working lab in the nation at the time.
• 20+ publications

University of Minnesota, Twin Cities

Postdoctoral Research Scientist • Jun 1997– Jun 2001

Reseach in human and computer vision and human spatial navigation.

University of California, Los Angeles

Doctorate, Cognitive Neuroscience • 1997

My dissertation focused on human and computer vision and the role that attention plays in creating robust representations of object shape. My work encompassed creating neural network models of human object recognition and testing the novel predictions made by those models by running empirical studies on the human visual system.

• Advisor: John E. Hummel, Ph.D.

Coursera

Structuring Machine Learning Projects • 2018

Course teaching modern machine learning and deep learning techniques and tools. (Certificate)

Coursera

Neural Networks and Deep Learning • 2018

Course teaching modern machine learning and deep learning techniques and tools. (Certificate)

AWS

AWS Practitioner Certification • 2020

My AWS Certificate The AWS Certified Cloud Practitioner examination is intended for individuals who have the knowledge and skills necessary to effectively demonstrate an overall understanding of the AWS Cloud, independent of specific technical roles addressed by other AWS Certifications.

University of California at Irvine

B.A. Cognitive Psychology • 1991

Worked in the Brain Imaging Center, David LaBerge lab in human visual attention. Photo editor for the New University newspaper.

SkyLab:Materials Informatics

Technical Lead • 2017—Present

MI is the integration of data, algorithms and automation to accelerate materials discovery. 3M has dedicated >30 scientists to building a software platform for collecting data that can be shared and analyzed by humans or algorithms. 3M is also investing in leveraging robotic technology to automate formulation, sample preparation and sample characterization. Provided 3M with initial vision. Created relationships with leaders in both the academic area (University of British Columbia, University of Chicago, Argonne National Labs) and industry (ChemSpeed, Labman, Citrine).

Performance Matrix

Technical Lead & Chief Product Owner • 2015—2017

Performance Matrix (PM) was developed as a collaboration between 3M HIS and Google Verily. PM is a population health management tool for hospitals that leverages medical records to make predictions about preventable events, root cause analysis for relative poor performance and help prioritize patient populations. Led a joint 3M-Google technical team to develop a proof of concept and initial production system.

Visual Attention Service

Lead Developer & Research Scientist • 2007—2009

Visual Attention Service is an on-line application that simulates the neurological properties of the human visual system to predict what people will notice in a scene in the first 3-5 seconds. Scoped and led the technical development and developed the IP strategy and contributed to the business model.

Program Champion

I build cross-functional research programs that require technical and business leadership. These efforts include communication to senior leadership (e.g., CTO, CEO, SVPs) on the vision, opportunity and risks. It also requires a clear, ambitious technical vision that the technical teams can 'see' and become passionate about.

Technical Leadership

In building a technical vision, I am responsible for understanding the relevant basic, and applied research in the relevant area (usually, machine learning, computer vision, natural language processing, data science). I am also responsible for leading the intellectual property roadmap that includes evaluating existing intellectual property along with identifying potential opportunities. I have been involved with mergers and acquisitions technical evaluations along with vendor evaluations. I am also responsible for providing 'guard rails' and 'technical paths' to the technical teams as they engage in research & development.

Organization Creation

Through program championing, I have been the founder of multiple cross-functional application and research teams through both internal acquisition and external hiring. This started in creating the Shape & Space Lab at the University of Texas, then the AI lab in 3M-Corporate Research Labs, and the Data Science lab in 3M-Health Information Systems.

Programming skills

I have done a significant amount of machine learning development. My Ph.D. focused on hunman and computer vision using Neural Networks. Since then I have done work with Markov modeling using Partially Observable Markov Decision Processes (POMDPs), reinforcement learning and Deep Learning. Python is my preferred programming language and I have experience prgramming in Cobol, Pascal, C, Perl and Matlab. I have experience developing both on the Microsoft Azure and Amazon AWS cloud platforms and have certifications in the AWS environement.

1. System, method and apparatus for providing navigational assistance BJ Stankiewicz, AR Cassandra US Patent 7,620,493
2. Systems and methods for optimizing a scene Brian J Stankiewicz, Brian E Brooks, Brian L Linzie, Nathan J Anderson, Michael Kelly Canavan, Glenn E Casner, Timothy J Gardner, David K Misemer. US Patent 8,478,111
3. Systems and methods for multi-perspective scene analysis Brian J Stankiewicz, Brian E Brooks, Brian L Linzie, Nathan J Anderson, Michael Kelly Canavan, Glenn E Casner, Timothy J Gardner, David K Misemer. US Patent 8,577,156
4. System and method for concurrently conducting cause-and-effect experiments on content effectiveness and adjusting content distribution to optimize business objectives. Brian E Brooks, Brian J Stankiewicz, Jonathan B Arthur, Craig G Markell, Brian L Linzie. US Patent 8,458,103
5. Systems and methods for note recognition. Gabriel A Biller, Kristopher W Clover, Masuma W Henry, Stephen M June, Brian L Linzie, Robert D Lorentz, David M Mahli, Richard J Moore, Cristin E Moran, Tasuku Nakayama, Scott D Pearson, Dennard J Powell, Olen Ronning, Guruprasad Somasundaram, Brian J Stankiewicz, Diane R Wolk. US Patent 9,070,036
6. Systems and methods for note recognition. Gabriel A Biller, Kristopher W Clover, Masuma W Henry, Stephen M June, Brian L Linzie, Robert D Lorentz, David M Mahli,Richard J Moore, Cristin E Moran, Tasuku Nakayama, Scott D Pearson, Dennard J Powell, Olen Ronning, Guruprasad Somasundaram, Brian J Stankiewicz, Diane R Wolk. US Patent 9,378,426
7. Systems and methods for evaluating robustness of saliency predictions of regions in a scene. Brian J Stankiewicz, Brian E Brooks, Brian L Linzie, Nathan J Anderson, Michael Kelly Canavan, Glenn E Casner, Timothy J Gardner, David K Misemer. US Patent 8,811,753
8. Systems and methods for managing notes. Willem V Bastiaens, Gabriel A Biller, Kristopher W Clover, Brian R Hackerson, Masuma W Henry, Stephen M June, Brian L Linzie, Robert D Lorentz, David M Mahli, Richard J Moore, Cristin E Moran, Michael E O’brien, Scott D Pearson, Dennard J Powell, Olen Ronning, Guruprasad Somasundaram, Brian J Stankiewicz, Diane R Wolk. US Patent 9,563,696
9. Systems and methods for improving visual attention models. BE Brooks, BJ Stankiewicz, BL Linzie. US Patent 10,515,163
10. Estimating and predicting tooth wear using intra-oral 3D scans Evan J Ribnick, Guruprasad Somasundaram, Brian J Stankiewicz, Aya Eid, Ravishankar Sivalingam, Shannon D Scott, Anthony J Sabelli, Robert D Lorentz. US Patent 9,737,257
11. Obfuscating data using obfuscation table. BJ Stankiewicz, EC Lobner, RH Wolniewicz, WL Schofield. US Patent 10,503,928
12. Systems and method for obfuscating data using dictionary. BJ Stankiewicz, EC Lobner, RH Wolniewicz, WL Schofield. US Patent App. 15/036,537
13. Systems and methods for predicting hvac filter change. AR Fox, EC Lobner, TM Meyer, BJ Stankiewicz. US Patent App. 15/532,186
14. Identification of codable sections in medical documents. Kavita A Ganesan, Brian J Stankiewicz, David E Yarowsky, Anna N Rafferty, Michael A Nossal, Anthony R Davis. US Patent App. 15/517,648
15. Identification and analysis of copied and pasted passages in medical documents. BJ Stankiewicz, KS Peterson, GL Garrison. US Patent App. 15/303,334
16. Activity Recognition Using Accelerometer Data. EC Lobner, JW Howard, RJ Moore, JF Schumacher, BJ Stankiewicz. US Patent App. 15/117,943
17. Impairment detection. EC Lobner, JW Howard, JF Schumacher, BJ Stankiewicz, BL Weaver. US Patent App. 15/511,310
18. Systems and methods for generating random numbers using physical variations present in material samples. Jennifer F Schumacher, Glenn E Casner, Yanina Shkel, Andrew P Bonifas, Anthony J Sabelli, Brian J Stankiewicz, John A Wheatley, Ravishankar Sivalingam, Robert W Shannon. US Patent 10,331,411
19. Identification of low-efficacy patient population. BJ Stankiewicz, JF Schumacher, BE Brooks, NA Asendorf, KS Peterson US Patent App. 15/773,207
20. Batch authentication of materials for automated anti counterfeiting. Anthony J Sabelli, Jennifer F Shumacher, Yanina Shkel, Brian J Stankiewicz, Glenn E Casner,John A Wheatley, Andrew P Bonifas, Ravishankar Sivalingam. US Patent App. 15/533,290
21. Query optimizer for combined structured and unstructured data records. BJ Stankiewicz, NA Asendorf, JF Schumacher, KS Peterson. US Patent App. 16/092,483
22. Medical protocol evaluation. BJ Stankiewicz, JF Schumacher, BE Brooks, NA Asendorf, KS Peterson, US Patent App. 15/773,233