As an experienced materials science and AI academic, I am comfortable in conceptualizing ideas, developing and executing business models, developing on the backend, collaborate with academics and industrial partners on design and strategies, and discussing solutions with stakeholders. When I’m not actively engaged in projects I am refining my development process, networking with experts in the field, and researching new tools. I’m seeking out a role where my experience and existing skills can be utilized most efficiently, but also to increase my responsibilities so that I continue to grow as a developer, an entrepreneur and a leader.


Postdoctoral research associate, University of Wyoming, United States (2019-Current)

Project: NASA-funded Artificially Intelligent Manufacturing of Flexible Electronics (grant nr. 80NSSC20M0050)
  • Proposal design and writing for federal grants (see Awards/funding)
  • Design, develop, test, and validate model-based Bayesian optimization and decision pipelines for closed-loop manufacturing of real-world electronic devices
  • Integrate mixed data source types and qualities (tabular, image processing) using pandas, SciPy, PyTorch
  • Generate synthetic spectroscopic, tabular, time-series data (GANs)
  • Data acquisition and wrangling of mixed hardware and software-interfaces (LabVIEW, .NET, python)
  • Scientific atomistic modelling and simulations for accelerated materials screening and discovery, multi-fidelity and multi- information source fusion optimizations
  • Analysis of uncertainty quantifications and interpretability
  • Automate workflow managers including failure handling and preserving provenance at HPCs (High Performance Computing)
  • Present findings/demo to international conferences (MRS, AAAI) and NASA stakeholders
  • Meet expectations and supervise with clear communications to a multidisciplinary group of chemical engineers, computer scientists (2 PhDs, 5 Masters graduated)

Blockchain R&D consultant, Genius Yield, Zug CH (remote, 2022-2023)

  • conceptualizing, research, authoring white paper for concurrent decentralized exchange
  • create and maintain data ingestion and processing pipeline
  • work with colleagues globally, close to 24/7 availability for quick fixes, commits, PR reviews
  • clear communication and teamwork with infrastructure engineers, front-end devs, user community managers, CSO
  • devOps, PostgreSQL, CI/CD, GCP scheduler
  • fraud investigations for rewards distribution on Cardano mainnet
  • optimize concurrent airdrops and tests with nix develop and cabal
  • agents-based orderbook simulation, and create API schema

Postgraduate Researcher, University of New South Wales, Australia (2014-2018)

Project: DAAD Australia-Germany Joint Research Cooperation Scheme
  • Proposal writing for time at national laboratories and HPCs
  • Run complex data analysis and modelling using python
  • Submit slurm jobs at national HPC clusters
  • Clear communication between international collaborators (Australia, Germany, Korea) in both English and german
  • Publish and present at international conferences
  • Manage DAAD budget

Postgraduate Research Assistant, Laser Center University of Applied Sciences Münster, Germany (2012-2014)

Project: German BMBF federal-funded optical technologies in innovative small and medium-sized enterprises (grant nr: 13N12282)
  • Characterized high-power diode laser systems as manufacturing tools
  • Designed and deployed statistical design of experiments using python to optimize real-world cutting efficiency of stainless steel up to 6 mm thick
  • Automated systems in laser processing semiconductor substrates for industrial customers (output 3000 pieces/day)
  • Meet expectations and tasks by project managers
  • Presented results to industrial partners (LIMO GmbH) and international conferences


2008-2010 Tutor Mechanics/Construction, UAS Münster (in German) 2010-2011 Lab assistant, Physics, UAS Münster (in German) 2012-2014 Laser Materials Processing, UAS Münster (in German) 2015-2016 Mathematics, UNSW 2016-2018 Physics, UNSW 2020-2022 Python (remote), UWYO 2022-2023 Workshop automated workflow manager (aiida), UWYO


2 PhD students (graduated) 5 Master students (2 Females, 3 males, graduated) 2 Master students (submitting 2023)


Development python, R, plutus, haskell, nvim, bash, postgresql, sqalchemy, postman
Tooling git, nix, npm, homebrew, cli-tools, docker, poetry, mongodb
Frameworks and Libraries pytorch, tensorflow, mlr3, mlr
DevOps github actions, ec2, s3, google cloud functions, cloud scheduler
Computational modelling DFT - quantum espresso, VASP FAIR guided data management and workflow - aiida, nomad, pymatgen
Experimental surface science - NEXAFS, XPS, ellipsometry, XMLD, Raman, XRD, SEM
Miscellaneous linux, fzf, vscode, photoshop, lightroom, photography, Documentation, Project Management, Teaching
Interests rust, solidity, YouTube, Content creation / editing


2018 / University of New South Wales, Canberra / PhD Physics
2014 / University of Applied Sciences, Münster / MSc Photonics
2011 / University of Applied Sciences, Münster / BSc Physical Engineering


2021 / Haskell: Functional Programming / Packt Publishing Credential ID
2018 / Machine learning / Andrew Ng Credential ID



2022 $1.25M Carbon Ore Processing DOE-FOA-0002620 2021 $900k Baker Hughes Additive Manufacturing , Wyoming 2020 $50k School of Energy Resources RFP, Laramie 2017 A$20k InnovationACT, Canberra, Australia 2017 500EU Travel grant, BESSY, Berlin, Germany 2015 A$25k Go8/DAAD Australia-Germany Joint Research Cooperation Scheme 2015 650EU Travel grant University of Applied Sciences Muenster, Germany 2014 A$6k PhD Fellowship, Canberra, Australia


2022 Wyoming Department of Health HHS-FOA-DO-22-001 2022 Sony Focused Research Award 2021 Integrated Computational And Data Infrastructure DOE FOA-0002482 2021 Future Manufacturing, NSF 21-564 2020 Advanced Coal Processing Program, Department of Energy FOA-0002185
Participation 2019, top ten for Fisher Innovation, Laramie, USA 2017, top five for blockchain hackathon Blockathon, Sydney, Australia

Select Publications

  • L. Kotthoff, J. Heil, A. Tyrell, T. Muller, A. Tyrell, M. Seas, H. Wahab, P. Johnson, Optimizing Laser-Induced Graphene Production, Frontiers in Artificial Intelligence and Applications (PAIS-IJCAI Conference) 351 (2022), 31-44
  • L. Kotthoff, H. Wahab, P. Johnson, Bayesian Optimization in Materials Science: A Survey, arXiV preprint 2108.00002 (2021)
  • H. Wahab, V. Jain, A. Tyrell, M. Seas, L. Kothoff, P. Johnson, Machine-learning-assisted fabrication: Bayesian optimization of laser-induced graphene patterning using in-situ Raman analysis, Carbon, 167 (2020), 609-619
  • H. Wahab, V. Jain, A. Tyrrell, L. Kotthoff, P. Johnson, In-situ Raman investigation of Laser-Induced Graphene using Machine Learning, Bulletin of the American Physical Society 65 (2020)
  • L. Kotthoff, V. Jain, A. Tyrell, H. Wahab, P. Johnson, AI for Materials Science: Tuning Laser-Induced Graphene Production and Beyond, IJCAI 2019 Data Science Meets Optimisation Workshop (2019), 1-6
  • H. Wahab, J. Gröninger, K. Dickmann, P. Bruns, M. Voß, I. Kardosh, J. Meinschien, L. Aschke, Optimization of Laser Cutting Quality with Design of Experiments, Laser Technik Journal, 11 (2014) 27-31
For the full list, see Google scholar page.

Recent Talks

  • L. Kotthoff, H. Wahab, P. Johnson, Optimizing Laser-induced Graphene Production, Invited talk NASA Marshall (2022)
  • H. Wahab, L. Kotthoff, P. Johnson, Single- and batch-optimizations of laser-induced graphene, MRS Spring Meeting, Hawaii (2022)
  • C. Jansing, H-Ch. Mertins, A. Gaupp, M. Krivenkov, A. Varykhalov, O. Rader, A. Sokolov, H. Wahab, H. Timmers, Soft-X-ray refractive index of graphene across the C 1s edge exploiting total-electron-yield and specular reflection spectroscopies, EXRS Conference (2022)
  • H. Wahab, Gaurav Raj, Patrick Johnson, Dilpuneet Aidhy, Lars Kotthoff, Multi-Fidelity Information Fusion DFT Study of Doped-Graphene Single Atom Catalysts, Virtual MRS Spring Meeting and Exhibit, online (2021)
  • V Jain, A Tyrrell, H Wahab, L Kotthoff, P Johnson, In-situ Raman investigation of Laser-Induced Graphene using Machine Learning, Bulletin of the American Physical Society 65, Colorado (2020)
  • H Wahab, V Jain, A Tyrrell, L Kotthoff, P Johnson, Optimization of Laser-Reduced Graphene with Automated Parameter Tuning: Towards Human-Less Advanced Manufacturing, ECS Meeting Abstracts, 753 (2020)
For the full list, see Google scholar page.


Publications: Green card holder ML Certification (Stanford) Fastai course on deep learning (University of San Francisco) AutoML course (German Research Centre for AI) GitHub : LinkedIn: Fluent in English, German and Malay Experience with UHV equipment, construct or modify optomechanical setups Cope with steep learning curves Full American/German driving license Member of MRS (Materials Research Society), ANN (Australian Nanotechnology Network)
Last modified 11mo ago