PID-Piper: Recovering Robotic Vehicles from Physical Attacks; , Stockholm, KTH, ML+Security Reading Group NSE Apr 19 2024, Division of Network and Systems Engineering. Kim HammarPDF
2024
Automated Security Response through Online Learning with Adaptive Conjectures; NSE seminar, Division of Network and Systems Engineering, Stockholm, Sweden, April 5 2025 Kim HammarSlidesPDFVideo
2024
Självlärande System för Cybersäkerhet; Besök av Handelsbanken, Stockholm, Sweden, Jan 11 2024 Kim HammarSlidesPDF
2023
Learning Automated Intrusion Response; Ericsson research, Stockholm, Sweden, Dec 8 2023 Kim HammarSlidesPDFVideo
2023
Intrusion Tolerance for Networked Systems through Two-Level Feedback Control; NSE seminar, Division of Network and Systems Engineering, Stockholm, Sweden, Nov 10 2023 Kim HammarSlidesPDF
2023
Scalable Learning of Intrusion Response through Recursive Decomposition; Avignon, France, Oct 18 2023 Kim HammarSlidesPDF
2023
3D-IDS: Doubly Disentangled Dynamic Intrusion Detection; , Stockholm, KTH, ML+Security Reading Group NSE Sep 22 2023, Division of Network and Systems Engineering. Kim HammarPDF
2023
Learning Near-Optimal Intrusion Response for Large-Scale IT Infrastructures via Decomposition; MIT, Boston, USA, May 19 2023 Kim HammarSlidesPDF
2023
Learning Near-Optimal Intrusion Response for Large-Scale IT Infrastructures via Decomposition; Siemens Research Princeton, USA, May 17 2023 Kim HammarSlidesPDF
2023
Learning Near-Optimal Intrusion Response for Large-Scale IT Infrastructures via Decomposition; Princeton University, USA, May 17 2023 Kim HammarSlidesPDF
2023
Learning Near-Optimal Intrusion Response for Large-Scale IT Infrastructures via Decomposition; New York University, USA, May 15 2023 Kim HammarSlidesPDF
2023
Digital Twins for Security Automation; Miami, USA, KTH, NOMS 2023: IEEE/IFIP Network Operations and Management Symposium May 8-12. Kim HammarVideoPDFSlides
2023
Learning Near-Optimal Intrusion Response for Large-Scale IT Infrastructures via Decomposition; Stockholm, Sweden, KTH, NSE Seminar, Mar 31 2023, Division of Network and Systems Engineering. Kim HammarSlidesPDF
2023
Självlärande system för cybersäkerhet; Stockholm, Sweden, KTH, CDIS, Division of Network and Systems Engineering, Besök av försvarsdepartementet 21 Feb 2023. Kim HammarSlidesPDF
2023
Optimal Patching in Clustered Malware Epidemics - Paper Review; , Stockholm, KTH, ML+Security Reading Group NSE Feb 16 2023, Division of Network and Systems Engineering. Kim HammarPDF
2023
Intrusion Response through Optimal Stopping; New York, USA, invited talk, Quanyan Zhu’s research group. 2023 30 January. Kim HammarSlidesPDFVideo
2022
Självlärande system för cyberförsvar; Linköping, Sweden, IT-försvarsdagen 2022 Dec 6. Kim HammarSlidesPDFVideo
2022
An Online Framework for Adapting Security Policies in Dynamic IT Environment; Thessaloniki, Greece, CNSM 2022: International Conference on Network and Service Management Oct 31 - Nov 4. Kim Hammar and Rolf Stadler SlidesPDFEventVideo
2022
Self-learning Systems for Cyber Defense; Lidingö, Sweden, CDIS fall retreat, October 28 2022. Kim HammarSlidesPDFVideo
2022
Self-learning Intrusion Prevention Systems; Stockholm, Sweden, KTH, NSE Seminar, October 21 2022, Division of Network and Systems Engineering. Kim HammarSlidesPDF
2022
Paper Review: Developing Optimal Causal Cyber Agents; Stockholm, KTH, ML+Security Reading Group NSE Sep 23 2022, Division of Network and Systems Engineering. Kim HammarPDF
2022
Learning Security Strategies through Game Play and Optimal Stopping; Baltimore, USA, ML4Cyber workshop at ICML 2022: International Conference on Machine Learning July 15-23. Kim Hammar and Rolf Stadler SlidesPDFVideo
2022
A System for Interactive Examination of Learned Security Policies; Budapest, Hungary NOMS 2022: IEEE/IFIP Network Operations and Management Symposium April 25-29. Kim Hammar and Rolf Stadler Video
2022
Intrusion Prevention through Optimal Stopping; London, UK, Alan Turing Institute, invited talk, Mar 25 2022 Kim HammarSlidesPDF
2022
Reinforcement Learning-based Hierarchical Seed Scheduling for Greybox Fuzzing; Stockholm, Sweden, KTH, ML+Security Reading Group NSE March 18 2022, Division of Network and Systems Engineering. Kim HammarPDF
2022
Intrusion Prevention through Optimal Stopping and Self-Play; Stockholm, Sweden, KTH, NSE Seminar, March 18 2022, Division of Network and Systems Engineering. Kim HammarSlidesPDF
2022
Introduktion till försvar mot nätverksintrång; Stockholm, Sweden, KTH EP1200, Feb 22 2022. Kim HammarSlidesPDF
2022
Intrusion Prevention through Optimal Stopping; Stockholm, Sweden, KTH, Netcon Seminar, invited talk, Feb 7 2022, Division of Decision and Control Systems. Kim HammarSlidesPDF
2022
Intrusion Prevention through Optimal Stopping; Stockholm, Sweden, KTH, Machine Learning Day Digital futures, Jan 17 2022, Division of Network and Systems Engineering. Kim HammarSlidesPDF
2021
A Game Theoretic Analysis of Intrusion Detection in Access Control Systems; Stockholm, Sweden, KTH, FEP3301 Computational Game Theory Course, Dec 8 2021, Division of Network and Systems Engineering. Kim HammarSlidesPDF
2021
Learning Intrusion Prevention Policies through Optimal Stopping; Izmir, Turkey, CNSM 2021: International Conference on Network and Service Management October 25-29. Kim Hammar and Rolf Stadler SlidesPDFEventVideo
2021
Reinforcement Learning Algorithms for Adaptive Cyber Defense against Heartbleed; Stockholm, Sweden, KTH, ML+Security Reading Group NSE October 22 2021, Division of Network and Systems Engineering. Kim HammarSlidesPDF
2021
Självlärande system för cybersäkerhet; Stockholm, Sweden, KTH, CDIS, Division of Network and Systems Engineering, Besök av riksdagens försvarsutskott (S) 20 Oct 2021. Kim HammarSlidesPDF
2021
Learning Intrusion Prevention Policies Through Optimal Stopping; Balingsholm, KTH, CDIS Research Workshop October 15 2021. Kim Hammar and Rolf Stadler SlidesPDF
2021
Learning Intrusion Prevention Policies Through Optimal Stopping; Stockholm, KTH, NSE Seminar October 8 2021, Division of Network and Systems Engineering. Kim Hammar and Rolf Stadler SlidesPDF
2021
Self-Learning Systems for Cyber Security; Enköping, Sweden, Ledningsregementet, August 18 2021. Kim HammarSlidesPDF
2021
MuZero; Stockholm, Sweden, KTH, ML+Security Reading Group NSE April 23 2021, Division of Network and Systems Engineering. Kim HammarSlidesPDF
2021
Self-Learning Systems for Cyber Security; Stockholm, Sweden, KTH, NSE Seminar April 9 2021, Division of Network and Systems Engineering. Kim Hammar and Rolf Stadler SlidesPDF
2021
Self-Learning Systems for Cyber Security; Stockholm, Sweden, KTH, CDIS Spring Conference March 24 2021. Kim Hammar and Rolf Stadler SlidesPDF
2020
Self-Learning Systems for Cyber Security; Stockholm, Sweden, KTH, NSE Seminar 4 Dec 2020, Division of Network and Systems Engineering. Kim Hammar and Rolf Stadler SlidesPDF
2020
Finding Effective Security Strategies through Reinforcement Learning and Self-Play; Izmir, Turkey, CNSM 2020: International Conference on Network and Service Management November 2-6. Kim Hammar and Rolf Stadler SlidesPDFEventVideo
2020
Self-Learning Systems for Cyber Security; Stockholm, Sweden, KTH, Center for Cyber Defense and Information Security, October 15 2020. SlidesPDF
2020
A Deep Journey of Playing Games with Reinforcement Learning; Stockholm, Sweden, KTH, Division of Network and Systems Engineering, January 31 2020. SlidesPDF
2019
End-to-End ML Pipelines with Databricks Delta and Hopsworks Feature Store; Amsterdam, Netherlands, Spark+AI Summit October 2019. EventVideoSlidesPDF
2019
Distributed Deep Learning with Hopsworks; Bosön, Sweden, EIT Big Data Summer School, 10 August 2019. EventSlidesPDF
2019
Introduction to Large Scale Machine Learning; Stockholm, Sweden, CGI Trainee Lecture, May 2019. SlidesPDF
2019
Machine Learning Infrastructure for the Steel Industry; Hagfors, Sweden, meeting at Uddeholm AB, May 8 2019. SlidesPDF
2019
Distributed Deep Learning with Hopsworks; San Francisco, USA, SF machine Learning Meetup, 25 April 2019. SlidesEventVideoPDF
2019
Distributed Deep Learning with the Hopsworks Feature Store; Palo Alto, USA, HopsML Meetup, 23 April 2019. SlidesPDFEvent
2019
Feature Store: the missing data layer in ML pipelines; Stockholm, Sweden, Spotify Machine Learning Guild Fika, February 26 2019. SlidesPDF
2019
Feature Store: the missing data layer in ML pipelines; Brussels, Belgium, FOSDEM, January 30 2019. EventSlidesVideoPDF
2019
Feature Store: the missing data layer in ML pipelines; Stockholm, Sweden, HopsML meetup, January 29 2019. EventSlidesPDF
2018
Deep Text Mining of Instagram Data Without Strong Supervision; Santiago, Chile, International conference on Web Intelligence, December 4 2018. EventPDFSlides
2018
The Future of Deep Learning; Stockholm, Sweden, HopsML Meetup panel discussion. Event
2018
Distributed Deep Learning; Stockholm, Sweden, RISE Machine Learning Study group. SlidesPDF
2018
Building a Fault-Tolerant ETL Pipeline for Claims CAFé; Chicago, USA, Internship Presentation, Allstate, August 30 2018. SlidesPDF
2018
Deep Text Mining of Instagram Data Without Strong Supervision; Stockholm, Sweden, Master’s Thesis Defense, KTH, June 1 2018. VideoSlidesPDF
2018
Human Activity Recognition: On-Edge Inference and Distributed Deep Learning; Stockholm, Sweden, Hadoop User Group Meetup, January 9, 2018. EventSlidesPDF
