Markus Bohlin, Docent, Professor
Markus is an experienced (20+ years) leader (14+ years) in in academia and industrial research with a background in leading and managing R&D groups, teams, portfolios, projects, bids, strategies, proposals and project sales, and experience from budgeting, recruiting, staffing and team development. His academic background is from applied AI in production systems, transportation, logistics, power generation and cyber-physical systems development. He defended his doctoral thesis in 2009 and was appointed as associate professor (docent) in 2013, both at Mälardalen University. Between 2012 and 2016 he served as president of the Swedish Operations Research Association. In 2014 he was appointed as adjunct professor in analysis of rail traffic systems at KTH Royal Institute of Technology, and served on the Trafikverket Board on Capacity in Railways. In 2019 he was appointed full professor in Computer Science with a focus on Applied Artificial Intelligence at Mälardalen University. He has acted as program chair and main organizer for several national and international conferences and workshops, including the 8th International Conference on Railway Operations Modelling and Analysis (ICROMA), the bi-annual Swedish Operations Research Conference (twice) and the annual Industrial Efficiency conference (four times). He serve as reviewer and PC member for several scientific journals and conferences. His work has been presented in more than 75 peer-reviewed papers in international journals, conferences and workshops. He serve on several national and international research boards and councils, and have participated as expert advisor in recruitments of senior faculty both nationally and internationally. He has leadership experience from organisations with up to 60 employees and more than 40 projects, including several H2020 and cluster projects, involving up to 20 people. He has supervised four PhD students until their PhD defence, 9 until their licentiate defense, and currently supervises five Ph.D. students. He currently serves as division manager for Product Realization at Mälardalen University, and as School Director for the INDTECH Industrial Graduate School.
Research interests:
- Planning and scheduling
- Machine learning
- Optimization
Mapping optimization requirements for construction sites: A study in heavy-duty vehicles industry (Sep 2023) Abdulkarim Habbab, Anas Fattouh, Bobbie Frank , Markus Bohlin, Koteshwar Chirumalla 64th International Conference of Scandinavian Simulation Society (SIMS 2023)
Requirement or Not, That is the Question: A Case from the Railway Industry (Apr 2023) Sarmad Bashir, Muhammad Abbas, Mehrdad Saadatmand , Eduard Paul Enoiu, Markus Bohlin, Pernilla Lindberg Requirements Engineering: Foundation for Software Quality (REFSQ 2023)
Dynamic Maps Requirements for Autonomous Navigation on Construction Sites (Dec 2022) Philip Wickberg, Anas Fattouh, Sara Afshar, Johan Sjöberg , Markus Bohlin The 5th International Conference on Communications, Signal Processing, and their Applications (ICCSPA’22)
Machine Learning Testing in an ADAS Case Study Using Simulation-Integrated Bio-Inspired Search-Based Testing (Mar 2022) Mahshid Helali Moghadam, Markus Borg , Mehrdad Saadatmand , Seyed Jalaleddin Mousavirad , Markus Bohlin, Björn Lisper
Using NLP tools to detect ambiguities in system requirements - A comparison study (Mar 2022) Aleksandar Bajceta, Miguel Leon Ortiz, Wasif Afzal, Pernilla Lindberg , Markus Bohlin 5th Workshop on Natural Language Processing for Requirements Engineering @ REFSQ (NLP4RE)
Performance Testing Using a Smart Reinforcement Learning-Driven Test Agent (Jul 2021) Mahshid Helali Moghadam, Golrokh Hamidi , Markus Borg , Mehrdad Saadatmand , Markus Bohlin, Björn Lisper, Pasqualina Potena 2021 IEEE Congress on Evolutionary Computation (IEEE CEC 2021)
Abdulkarim Habbab
Aleksandar Bajceta
Ingrid Johansson (former)
Jennifer Warg (former)
Johan Högdahl (former)
Kivanc Doganay
Philip Wickberg
Sara Gestrelius (former)
Sarmad Bashir
| Thesis Title | Status |
|---|---|
| Simulation-based optimization of dual non-crossing stacking cranes | on-hold |