About Me

A common denominator in my work is modeling and using state of the art software technical methods to accomplish the task at hand. One view of my research is to mimic human reasoning with software technical means. In combustion modeling, this manifests itself in a software expert and database system that mimics the way a combustion engineer would model large reaction mechanisms.

A dominant theme of my current work with database applications is the use of ontologies for the representation of meta-data and for being the basis of model-driven software.

One primary advantage of my multidisciplinary background is that I can communicate in the language of chemists, mathematicians, computer scientists and engineers. The primary disadvantage is that, seen from the viewpoint of each of the disciplines, that he am an expert in the ‘other’ field. Chemists will tag me as a computer scientist. And, for example, at RISC in Austria, a computer science/mathematical institute, I was mostly tagged as a chemist.

Experience

Through my modeling activities I have developed a deep and intuitive knowledge of chemical processes. This is exemplified by my degrees from the Chemistry Deparment of the University of California, Irvine, in biology (Bach. Sci), Chemistry (Bach. Art) and theoretical chemistry (Ph.D) and from Combustion Physics Department of Lund University the title of docent in physical organic and combustion chemistry. My modeling and mathematical abilities were honed at the Research Institute of Symbolic Computation under Bruno Buchberger of Johannes Kepler University of Linz, Austria, where I focused in, but not exclusively, on applications of state-of-the-art techniques, for example artificial intelligence, machine learning, data representation and data management, to production quality control in the Steel industry (financed by EU and the Austrian Steel industry) and to chemical information applications (initially financed by the Austrian chemical industry). During a European Union project under which my fuzzy logic machine learning (ANALYSIS) was developed I was working in close connection the Fuzzy Logic Lab Linz under Prof. Peter Klement (my assistant was employed by this institute). My modeling, mathematical and software technical skills were used to develop detailed combustion kinetic models, mostly in cooperation with Combustion Physics at the University of Lund, simplified mathematical models of complex combustion processes, started at the Energy Sciences Department of the University of Lund and a web based tool for the determination of thermodynamic properties based on chemical bonding structure (basically a ‘2D graphical’ lewis structure representation started through several 3 month research visits to the Reactions and Chemical Engineering Laboratory (LRGP) is a joint unit of CNRS with Frederique Battin-LeClerc Nancy, France.

Blurock Consulting AB

Blurock Consulting AB is the company encompassing all the research activities and cooperation of Edward Blurock. The focus of the company is state of the art data management and interpretation in the broadest sense.A common theme in this work is the automation of processes normally done by hand. This work began with projects in (fuzzy logic) machine learning to extract general concepts and rules (decision trees and clustering) from data. In chemical kinetics the process of automating the generation of kinetic mechanisms for large mechanisms from general kinetic rules in 2D-graphical representations of chemical species has been developed with corresponding software. The web service employed ontological relationships to search and catalog large kinetic mechanisms. Related work in the calculation of thermodynamic data needed for these complex mechanisms, JThermodynamicsCloud, evolved through several generations of development from hand with rules, through software to manage the data needed to perform the calculation to finally JThermodynamicsCloud, a SaaS web service using state of the art data management techniques, including ontologies. This web service is based on ChemConnect, where ontologies are used not only in a model driven software, but the organization of observational data and in the generic descriptions of the instrumentation used in generating this data. A current ongoing project is ReSpecTh where a hand-written specification is being translated into an machine interpretable ontology.

Through all this work Blurock Consulting AB is an ideal partner for projects dealing with information and data management.

Multidisciplinary

A common thread throughout my career is the combination of chemistry, mathematics and computer science resulting in a multidisciplinary career focusing primarily (but not exclusively) on physical organic chemical modeling. However, a common thread of my research, independent of domain, is to attempt to mimic how a researcher approaches analysis. These multidisciplinary skills form the basis of CHEMCONNECT, JThermdynamicCloud and the ReSpecTh specification translation.

Ontologies

For more than 6 years ontologies have been an integral part Edward Blurock’s work in data management, both from data representation and from the organization of software dealing with the organization of data and the promotion of FAIR and TOP data practices. For example, the ReSpecTh project is translating a written specification to a machine interpretable ontology for the kinetic data. The ChemConnect project uses ontologies both for the management of data, but also is an integral part of the model-driven software design. JThermodynamicsCloud, a SaaS for the management of data for the calculation of thermodynamic quantities, builds upon ChemConnect in its use of ontologies.

Data management Plans

Edward S. Blurock is an ideal partner for the formulation of data management plans in proposals due to his expertise in state of the art database management techniques and extensive participation in numerous EU projects and Actions.The motivation of incorporating a data management plan with is project can be summarised by the recommendations recently published by the G7 Science Ministers:

• Include Open Science research indicators and metrics during the evaluation and assessment of researchers

• Ensure every researcher’s ability to deposit, access, and analyze scientific data across disciplines and borders

• Adhere to the FAIR data principles of being findable, accessible, interoperable, reusable

• Train researchers in Open Science and data skills

• Develop common good practice standards

With Horizon 2020, all projects from 2017 (before it was restricted to certain areas) are now Open Research Data (ORD) pilot projects.

Teaching

Edward Blurock’s general teaching competence is acknowledged by the docent degree of Lund University. My teaching qualifications are based not only on extensive graduate and undergraduate teaching, comprising over 40 semester courses (more than 1000 hours in the classroom) and advising graduate students, but also on a wide variety of teaching from junior high and high school students, to layman, to professionals in industry and research. This includes numerous international conference research presentations. I have also supplemented my teaching credentials with general pedagogic classes (in total 21.5 hp in the swedish system). Edward Blurock has designed and implemented (meaning a set of course slides with a learning management system such as Google classroom or Moodle) a whole range of courses from graduate and undergraduate courses in computer science and physical organic chemistry and high school courses in math, physics and chemistry.