• Experienced Vice President in AI and global software development with MIT and NASA research background in artificial intelligence, software engineering, parallel computing

• Strategic technology vision development & business model development

• Leadership of multi-cultural global AI & software divisions/teams/projects across multiple time zones

• Research and IT strategy. Tech architecture & operations under multi-country legal frameworks (e.g., regulations in AI, IP, product liability and compliance)

• IP portfolio strategy & management. M&A integration

• Talent scouting, recruiting, career development

• Budget acquisition, negotiation, accounting oversight, controlling

• Public funding sources in US and EU.

Victor has served at MIT as a Principal Research Scientist and principal investigator in NASA and NSF projects. His research spanned MIT's Kavli Institute for Astrophysics and Space Research, MIT's Haystack Observatory, MIT's department of Earth, Atmospheric, and Planetary Sciences (EAPS), and MIT's Computer Science & Artificial Intelligence Laboratory (CSAIL). Prior to MIT he headed the Multicore Software Engineering research group at KIT in Germany, supported by the Excellence Initiative and the "Eliteprogramm für Postdocs" of Baden-Wuerttemberg. 

• Computer Science

  • Foundations for Computer-Aided Discovery systems advancing new methods in artificial intelligence, parallelism, software engineering. Devising and building systems that scale the human discovery process with machine intelligence for applications in the Petabytes/second rate range.

  • Industrial-strength algorithms & solutions in collaboration with IBM, Intel, Sun Labs, Oracle, with applications to industrial problems / data.

• Data Science
  Case study driven research advancing computer-aided discovery in various contexts, such as:

  • Astronomy: algorithmic exoplanet search in the NASA Transiting Exoplanet Survey Satellite (TESS) context, software aspects for chemistry and biology in search for life beyond our solar system; software aspects in ALMA Phasing project to enhance the ALMA Observatory's Very-Long Baseline Interferometry capabilities; software imaging for the Event Horizon Telescope (EHT) project

  • Geoscience: Exploration of Earth surface deformation, volcanics, earthquakes, and atmospheric lee wave phenomena.

  • Solar science: Murchison Widefield Array (MWA) observation analytics of solar phenomena

  • Space science: Analytics of space weather and the Earth's ionosphere; contributions to Radio Array of Portable Interferometric Detectors (RAPID). Lead of NSF Mahali project that paved the way for new ionospheric data collection and analytics using mobile phones.

  • Planetary science: Techniques for AI-supported landing site selection on the Moon and on Mars

Victor has international teaching experience in the US, Germany, and Switzerland. He enjoyed working with students while teaching several graduate and undergraduate level university courses and advising more than 30 graduate and undergraduate thesis students.

• MIT

  • Artificial Intelligence in Science, IAP lecture (2019)

  • Artificial Intelligence for Transiting Exoplanet Survey Satellite Applications, 12S680, co-teaching with Prof. Sara Seager, new course designed by Seager/Pankratius (2019)

  • Computational Methods in Scientific Programming, Lectures on Python, 12.010 with T.Herring / C.Hill (2018)

  • Fundamentals of Machine Learning; Research Opportunities for Undergraduate Students Program (2017)

  • Geoinformatics for Natural Hazards Monitoring, 12.S590, co-teaching with Prof. Herring, new course designed by Pankratius/Herring (2017)

  • Astroinformatics for Exoplanets, 12.S680, co-teaching with Prof. Sara Seager, new course designed by Seager/Pankratius (2015, 2016)

  • Parallel Programming on Multicore Systems and Clouds; Research Opportunities for Undergraduate Students Program (2015, 2016)

  • Multicore Software Engineering; Research Opportunities for Undergraduate Students Program (2013, 2014)
    
    

• University of Zurich 

  • Summer School, course on Multicore Software Engineering (2013)
    
    

• Karlsruhe Institute of Technology - Faculty of Computer Science

  • Course: Edge-AI in software and sensor applications (ongoing)

  • Course: Software development for modern, parallel platforms (2008-2012)

  • Course: Multicore computers and clusters (2007-2010)

  • Course: Multicore programming in practice: tools, models, languages (2009-2012)

  • Course: Empirical Software Engineering (2009)

  • Multicore lab: tools, models, languages (2008-2009)

  • Multicore lab (2007)
    
    

• University of Karlsruhe - Faculty of Business & Economics

  • Course: Applied computer science I (with labs, University of Karlsruhe, 2003-2007)

  • Course: Data management in organizations (with labs, WU Vienna, 2003-2007)

  • Course: Business processes and software engineering (with labs, Hector School of Engineering and Management, 2006)

  • Course: Information systems development (with labs, Virtual Global University, 2003-2007)

  • Lab: Software engineering tools (University of Karlsruhe, 2006-2007)

• Scikit Data Access: Data Interfaces for Python, github.com/MITHaystack/scikit-dataaccess (Python, MIT License)

• Scikit Discovery: Data Discovery for Python, github.com/MITHaystack/scikit-discovery (Python, MIT License)

• Science Case Studies: Code for Scientists and Educators, github.com/MITHaystack/science-casestudies (Jupyter/Python notebooks, MIT License)

• CorrelX: A Cloud-Based Software Correlator for Very Long Baseline Interferometry (VLBI), github.com/MITHaystack/CorrelX (Hadoop, MIT License)

• MCheetah: Data Processing Framework for Android Phones with Multicore CPUs/GPUs, github.com/MITHaystack/mcheetah (Android/Java, MIT License)

• PyInSAR: Data Tools for Interferometric Synthetic-Aperture Radar Satellite Dat, github.com/MITeaps/pyinsar (Python, MIT License)
  
  

• Teaching repository: Python - A Crash Course by Example: github.com/vpankratius/teaching/tree/master/python