About Me

Hello! Since September 2016, I’m a Doctoral candidate advised by Prof. Jan Křetínský in the Chair for Foundations of Software Reliability and Theoretical Computer Science at the Technical University of Munich. My current work revolves around formal methods and verification and lately, its interactions with machine learning and neural networks. dblp, Google Scholar.

Publications

  1. P. Ashok, J. Kretinsky, M. Weininger. Statistical Model Checking: Black or White?. ISoLA 2020. (proceedings)

  2. P. Ashok, V. Hashemi, J. Křetínský, S. Mohr. DeepAbstract: Neural Network Abstraction for Accelerating Verification. ATVA 2020. (pre-print, paper)

  3. P. Ashok, J. Křetinsky, M. Weininger. Approximating Values of Generalized-Reachability Stochastic Games. LICS 2020. (pre-print, paper)

  4. P. Ashok, M. Jackermeier, P. Jagtap, J. Kretinsky, M. Weininger and M. Zamani. dtControl: Decision Tree Learning Algorithms for Controller Representation. HSCC 2020. (website, paper, conference talk, demo video).

  5. P. Ashok, J. Křetinsky, K. G. Larsen, A. Le Coënt, J. H. Taankvist and M. Weininger. SOS: Safe, Optimal and Small Strategies for Stochastic Hybrid Games. QEST 2019. (pre-print)

  6. P. Ashok, T. Brázdil, K. Chatterjee, J. Křetínský, C. H. Lampert and V. Toman. Strategy Representation by Decision Trees with Linear Classifiers. QEST 2019. (pre-print)

  7. P. Ashok, J. Křetínský, M. Weininger. PAC Statistical Model Checking for Markov Decision Processes and Stochastic Games. CAV 2019. (pre-print).

  8. P. Ashok, Y. Butkova, H. Hermanns, J. Křetínský. Continuous-Time Markov Decisions based on Partial Exploration. ATVA 2018. (pre-print).

  9. P. Ashok, T. Brázdil, J. Křetínský, O. Slámečka. Monte Carlo Tree Search for Verifying Reachability in Markov Decision Processes. ISoLA 2018. (pre-print).

  10. P. Ashok, K. Chatterjee, P. Daca, J. Křetínský, T. Meggendorfer. Value Iteration for Long-run Average Reward in Markov Decision Processes. CAV 2017. (pre-print).

Talks

  1. Compact and explainable strategy representations using dtControl at Highlights 2020. September 2020. Poster, Slides.
  2. PAC Statistical Model Checking for Markov Decision Processes and Stochastic Games at Highlights 2019. September 2019. Slides.
  3. SOS: Safe, Optimal and Small Strategies for Stochastic Hybrid Games at QEST 2019. September 2019. Slides.
  4. Strategy Representation by Decision Trees with Linear Classifiers at QEST 2019. September 2019. Slides.
  5. PAC Statistical Model Checking for Markov Decision Processes and Stochastic Games at CAV 2019. July 2019. Slides.
  6. Continuous-Time Markov Decisions based on Partial Exploration at ATVA 2018. October 2018. Slides
  7. Continuous-Time Markov Decisions based on Partial Exploration at Highlights 2018. September 2018. Slides.
  8. “Saving the planet with Scikit-learn… or maybe not” at DEIS Retreat, Aalborg University. August 2018.
  9. Monte-Carlo Tree Search in Verification of Markov Decision Processes at LiVe 2018 @ ETAPS. April 2018. Slides.
  10. Value Iteration for Long-run Average Reward in Markov Decision Processes at AVM 2017. September 2017. Slides.
  11. Long-Run Average Reward in MDP at DEIS Retreat, Aalborg University. August 2017. Slides.
  12. Mean-payoff Objectives for Markov Decision Processes at QAPL 2017. April 2017. Slides.
  13. Mean-payoff Objectives for Markov Decision Processes at Masaryk University. April 2017.

Tutorials

Students Supervised

  1. Christoph Weinhuber. Learning Domain-Specific Predicates in Decision Trees for Explainable Controller Representation. BSc. Thesis, 2020.

  2. Mathias Jackermeier. dtControl: Decision Tree Learning for Explainable Controller Representation. BSc. Thesis, 2020. Link

  3. Alexander Slivinskiy. Solving Simple Stochastic Games with Quadratic Programming. BSc. Thesis, 2020.

  4. Cristian Neufuss. Translating Natural Language for a Regex Compiler Language using Neural Networks. BSc. Thesis, 2020.

  5. Stefanie Mühlberger. Faster Verification of Neural Networks with Clustering-based Compression. MSc. Thesis, 2020.

  6. Safa Mert Akmese. Generating Richer Predicates for Decision Trees. BSc. Thesis, 2019.

  7. Tornike Kikalishvili. Off-line Model-Based UI and Functional Testing for iOS Application in Agile Environment. MSc. Thesis, 2018.

  8. Ondřej Slámečka. Monte Carlo Tree Search in Verification of Markov Decision Processes. MSc. Thesis, 2017.

Professional Activities

Past

Previously, I was a master’s student at Chennai Mathematical Institute, where I worked under Prof. B. Srivathsan on Probabilistic Timed Automata. Prior to this, I earned a bachelor’s degree in Computer Science and Engineering from National Institute of Technology, Calicut. After a brief stint as a developer at Commvault Systems, Hyderabad, I found my way back to academia. I am excited by algorithms and like building tools with strong theoretical frameworks. More on my academic and professional pursuits is detailed in my curriculum vitae.