Curriculum vitae

Summary

Multilateral, versatile and results-oriented data scientist & researcher with more than seven years of experience in data science and a PhD in chemical engineering. Working in the semiconductor industry. Area of interest and expertise includes an array of multidisciplinary research involving methods of chemometrics/machine learning, mathematical programming and computational chemistry in fields ranging from separation science, *omics, cancer diagnostics to novel pharmaceutical design and screening. Communicative and cogent in forming professional relationships with management, peers, and staff. An abridged version of my CV can be downloaded from the following link: [PDF].

Skills and abilities

  • Analytical techniques: HPLC-MS(-MS), (nanodrop)-UV-VIS and spectrofluorometry, MALDI-MS, FTIR.
  • Inter-personal skills: Strong networking, managerial and communication skills (both oral and written), leadership and teaching.
  • Coding skills: MATLAB – strong, Python (numpy, pandas, scipy, matplotlib, keras, tkinter, Flask, etc.) -strong, Bash – intermediate, Mathematica – basic, R- basic (> 11 years of experience).
  • Software engineering skills: build systems (Jenkins), scripting, versioning (GIT/TFS).
  • Machine learning / chemometric methods: Strong understanding of PCA, MLR, PLS, PLS-LDA, ANNs, CNNs, SVM/SVR, kPLS, kNN, single- and multi-objective optimization, non-linear programming.
  • Statistical analysis and data visualization: Strong grasp of statistics and data visualization. Software: OriginPro, Tableau, Simca-P, Statistica, Minitab, ProMV, Python (matplotlib).
  • Comfortable in both Windows and Linux platforms, experienced in the use of high-performance computing (HPC).
  • Molecular modelling, simulation, and visualization: DFT, semiempirical, MD, molecular docking, Monte Carlo. Software: Gaussian, Gromacs, NAMD, HyperChem, VMD, Avogadro, ChemSketch, Dragon
  • Image Processing: Adobe Photoshop – intermediate
  • MS Office Tools (365): strong proficiency in all the Office programs.
  • Research, searching and organizing literature.
  • Professional scientific paper preparation and writing.

Experience

Manager, Data Science, Onto Innovation Inc. (ex. Nanometrics Inc.), Singapore. (2023-04-02~ )

Developing disruptive algorithms, products and technologies in semiconductor metrology powered by machine learning & AI. Actively contributing to the R&D and SW processes in Onto Innovation.

Scope:
(i) driving high impact ML/AI/SW R&D projects towards development/invention of novel semiconductor metrology solutions & improvement of existing ones,
(ii) strategic ML/AI and SW project management, PLC management, software development and integration (feature design, scoping, risk analysis, documentation, experienced in both Agile and Waterfall),
(iii) troubleshooting and support of the internal & external company stakeholders, internal (supporting all key accounts) & external customer engagement (key accounts in Taiwan and S. Korea),
(iv) continuous training, mentoring and management of new and existing R&D, data scientists and SW engineers.

Key deliverables & achievements:
– CEO impact award for invention of a key proprietary technology in Onto Ai-Diffract suite of metrology analysis tools (> 10 million $USD revenue impact)
– Invention, development and ownership of a unified ML-based OCD metrology recipe creation and optimization product (strong impact on business growth in advanced tech nodes across global Onto customers by adoption of Onto ML solutions)
– Continuous delivery of high impact ML/AI R&D OCD metrology prototypes & recipes
– 10+ white papers, trade secrets, and patents (applications)

Senior Data Scientist, Onto Innovation Inc. (ex. Nanometrics Inc.), Singapore. (2021-04-02~ 2023-04-02)
Data Scientist, Onto Innovation Inc. (ex. Nanometrics Inc.), Singapore. (2019-12-11~2021-04-01 )
Research Fellow, National University of Singapore, Singapore. (2017-04-17 ~ 2019-12-10)

Development of quantitative machine learning models (regression, classification) focused on feature engineering, selection and interpretability. Inference of chemical information from large-scale MD/QM models and simulations. Training and supervising undergraduate and graduate students. Active networking with local and international collaborators.

Key projects:

  • HPLC elution order prediction via machine learning and mathematical programming.
  • Cross-HPLC column retention time prediction using machine learning and mixture modelling.
  • Large-scale MD and QM models/simulations for elucidation of binding of zinc to ovalbumin.
  • Python(Flask)-powered web platform for GC-MS experimental-based modelling and optimization of (bio-crude) mixtures.

Key deliverables:

  • Articles: 8 peer-reviewed research articles published in top-tier research journals, 4 pending.
  • Intellectual property: 1 patent granted (KRPTO: KR-10-2017-0085981, EU PCT pending), 4 patents pending (USPTO, KRPTO).
  • Student supervision: trained and supervised four FYP students, and one Master student.
  • Presentations: several invited lectures at PKNU, Busan, Korea; UNIST, Ulsan, Korea, ~10 oral and poster presentations at renowned conferences.
Researcher and Teaching Assistant, Pukyong National University, Busan, Korea. (2013-10-30 ~ 2017-03-30)

Development and optimization of high-throughput computational methods to tackle analytical problems. Nature-inspired algorithms for feature engineering and selection. Quantitative linear and non-linear machine-learning models built from high-dimensional data. Teaching undergraduate experimental chemical engineering labs. Supervision and training of graduate students. Productive scientific output. Networking with local and international cooperators.

Key projects:

  • Feature selection in supervised learning in proteomics, spectroscopy, and cancer diagnostics
  • Large-scale QSRR model development in proteomics through machine learning
  • Modelling and simulation of lactoferrin-functionalized silver nanoparticles

Key deliverables:

  • Articles: 8 peer-reviewed research articles published in top-tier research journals, 4 pending.
  • Intellectual property: 1 patent granted (KRPTO: KR-10-2017-0085981, EU PCT pending), 4 patents pending (USPTO, KRPTO).
  • Student supervision: trained and supervised four FYP students, and one Master student.
  • Presentations: several invited lectures at PKNU, Busan, Korea; UNIST, Ulsan, Korea, ~10 oral and poster presentations at renowned conferences.
Lecturer, Busan Global Center, Busan, Korea. (2014-03-16 ~ 2014-05-17)

Teaching a group of students about Croatian language and culture in the Busan Global Center, in Busan, South Korea. Creating a curriculum, active engagement with students.

Key deliverables:

  • Building a curriculum which comprised of Croatian history, basic communication, culture and tourism
  • Optimization of a curriculum to adapt to interaction with Korean students in different age groups
Administrative Secretary, 2nd FOREBIOM Workshop, Busan, Korea. (2013-12-03 ~ 2014-02-14)

Organization and administration of the 2nd FOREBIOM Workshop conference held in Busan, Republic of Korea as part of the FOREBIOM project, funded through the FP7 EU scheme (FP7-226154).

Key deliverables:

  • Contact and coordination of the invited speakers
  • Creation of a visual identity of the conference
  • Logistic support to the chairman and the organization committee
CEEPUS III Research Fellow : Nicolaus Copernicus University, Toruń, Poland (2013/03/08 ~ 2013/06/08)

Three month stay at the Department of Environmental Chemistry and Bioanalytics, Nicolaus Copernicus University in Toruń, and Department of Pharmaceutical Chemistry, Medical University of Gdańsk, in Poland. The work involved the “Ion chromatographic retention modelling using quantitative structure-retention relationships” project as a part of my Master’s thesis project. Several key problems were addressed by professional advice from Professors Buszewski, Kaliszan, Bączek, and Markuszewski. The three-month stay in Poland was supported by a CEEPUS III grant.