Data Champions Search

Arian Jamasb

PhD student

Department of Biochemistry

Department of Computer Science and Technology

Areas Of Expertise:

Python, R language, Git, Data visualisation, Big data, Machine learning, Statistical analysis, Version control, Discipline-specific repositories, Data sharing, Code sharing, Open data, Cheminformatics, Bioinformatics

Contact Information

ORCiD:

Biography

My research focuses on the applications of machine learning to problems in structural biology and drug discovery.

Dequn Teng

PhD Candidate, Department of Engineering

Areas Of Expertise:

Python, SQL, Matlab, Machine learning, Statistical analysis, Data collection, Database design, Copyright, Data sharing, Code sharing, Open data, Imagin

Contact Information

dt517@cam.ac.uk

My LinkedIn Profile

Biography

Dequn (Peter) Teng is a Ph.D. candidate supervised by Dr. Veronica Martinez in the Business Model Innovation Group at the Institute of Manufacturing. His current research area is on blockchain and machine learning integrated methods for supply chain management.

Dequn graduated from University of Liverpool (2+2 route) with a first class honours degree in Computer Science and Electronic Engineering. His past research experiences relate to blockchain and digital innovation, with peer reviewed conference paper publications on IEEE Xplore and EI. Additionally, He has ten invention patent applications under substantive review process, ranging from Blockchain and Mechanical Design Innovation. For industrial exposure, he has taken research internships at Deutsche Bank (Shanghai) for digital transformation research, and Unilever (UK) for PowerBI visualization. Moreover, he loves mathematical modelling and was awarded Meritorious Winner at the Mathematical Contest in Modeling.

Jiri Benacek

Research Assistant

Chemical Engineering and Biotechnology

Areas Of Expertise:

Python, Matlab, Data visualisation, Big data, Machine learning, Statistical analysis, Experimental design, Sensitive data, Research data ethics, Data protection and research

Contact Information

jb2346@cam.ac.uk

My LinkedIn Profile

Biography

My background is neuropsychology, and later, computational neuroscience. During my studies, I developed strong skills in applied data science and machine learning, as well as fundamental knowledge of neural computation. Currently, I am based in the Cambridge Centre for Neuropsychiatric Research, where our team is working on biomarker discovery for neuropsychiatric disorders, as well as on developing algorithms for more data-informed diagnostics in mental healthcare.

Karla Cervantes Barron

PhD Student

Department of Engineering

Areas Of Expertise:

Data analysis, Data visualisation, Python, R language, Statistical analysis, Data collection, Database design, Data architecture, Surveys, Workshop delivery, Social media and digital communications

Contact Information

kc512@cam.ac.uk

@twin_karla

My LinkedIn Profile

Biography

Karla’s PhD is about the level of energy services used in different countries with a focus on development. The research involves analysing country-level databases, performing statistical analyses and making visualisations.

Karla holds a Bachelors’ degree in Chemical Engineering from the National Autonomous University of Mexico (UNAM) and an MSc from University College London (UCL).

Karla’s professional experiences before the PhD included working for the non-alcoholic beverage industry in Mexico in the areas of quality, environment protection and operations management.

Pingfan Song, PhD

Senior Research Associate

Areas Of Expertise:

Python, Git, Matlab, Machine learning, Code sharing, Imaging, Workshop delivery

Contact Information

ps898@cam.ac.uk

My LinkedIn Profile

Biography

Dr. Pingfan Song is a senior research associate at the Machine Learning group in University of Cambridge. He is endorsed under the Global Talent by UK Research and Innovation (UKRI) in recognition of his critical contributions.
   He has been working on trustworthy machine learning which aims to advance work on key technical underpinnings of interpretability/transparency, fairness, and robustness of machine learning systems, and to develop timely key applications in real world healthcare settings, such as medical imaging diagnosis systems. In addition to machine learning, he is also a professional in image processing, sparse modeling and sampling theory. His research has been applied to multi-disciplinary fields such as medical imaging, biological imaging, and other computational imaging tasks and inverse problems.
   He is a STEM ambassador in UK and a mentor of in2scienceUK where he provides free teaching, career guidance and advice for A-level students in order to empower students from disadvantaged backgrounds to achieve their potential and progress to STEM and research careers. He is also Co-president of London PhD Network (LPN), a non-profit academic association promoting interdisciplinary communication.

Pratheeba Vimalnath, PhD

Post-doctoral Research Associate

Department of Engineering, Institute for Manufacturing (IfM)

Areas Of Expertise:

Licensing, Copyright, Data analysis, RDM training, Data Management Plans, Intellectual Property (IP), Statistical analysis, Data collection, Database design, Data protection and research, Data sharing, Open data, Illustration

Contact Information

pv302@cam.ac.uk

My LinkedIn Profile

Biography

Dr Pratheeba Vimalnath is a Post-Doctoral Research Associate at the University of Cambridge, Institute for Manufacturing. She is currently working for the interdisciplinary and international research project IPACST that aims to study the role of IP strategies in accelerating sustainability (social, environmental and economic) transitions. Her research interests broadly include intellectual property strategies, green innovations, and technology and innovation management. She is also a College Research Associate at Wolfson College and an Interest Group Champion for Cambridge Global Challenges (CGC). She holds a doctorate degree in Intellectual Property Management, a Master’s degree in Technology Management and a Bachelor’s degree in Computer Science and Engineering, from India.

Swati Rajwal

Research Assistant

Department of Engineering

Areas Of Expertise:

Python, Git, SQL, Machine learning, Data collection, Version control, Research data ethics, Data protection and research, Code sharing, Writing/publishing data papers, Surveys, Bioinformatics, Social media & digital communications

Contact Information

sr2050@cam.ac.uk

@SwatiRajwal

My LinkedIn Profile

Biography

Swati is a Research Assistant in the Department of Engineering at the University of Cambridge. Currently, her research focuses primarily on understanding the temporal structure of pain through behavioral assessment of chronic pain patients. In addition to her research, she actively participates in mentorship initiatives such as Google’s WomenTechmaker Program. Prior to joining Nox lab, she worked with collaborators from Mayo Clinic, Oxford University, and Accenture Research Lab.

Yasmin Fathy, PhD

Research Associate in Construction Information Technology

Areas Of Expertise:

Python, Git, SQL, Data mining, Machine learning, Data collection, Writing/publishing data papers, Digitisation

Contact Information

ORCiD:

Biography

Yasmin Fathy is a Research Associate at the Department of Engineering, University of Cambridge and a Fellow of the Higher Education Academy. Before joining Cambridge, she was a Software Developer at Genomics Analytics Group at European Bioinformatics Institute (EMBL-EBI), Research Associate in IoT and Machine Learning at Cambridge University, and a KTP Research Associate in Data Science and Machine Learning at UCL. She obtained her PhD from the Institute for Communication Systems (ICS) at the University of Surrey and an MSc in Applied Science and Engineering from the Artificial Intelligence (AI) Lab at Vrije Universiteit Brussel (VUB) in Belgium. Her research interests include IoT, data analytics, digital twin and applied machine learning.

She is an active reviewer and a technical program committee member for multidisciplinary and international journals and conferences, including CCNC, The Web Conference (WWW), IEEE Systems, IEEE IoT Journal, IEEE Transactions on Big Data, and IEEE Access. She is a Topic Editorial in Frontiers in Big Data: Women in Machine Learning and Artificial Intelligence Initiative, a Data Champion at the University of Cambridge and a member of the Cambridge Centre for Data-Driven Discovery (C2D3). She was a BSF (Become a Science Founder) Fellow for entrepreneurship scientists in 2021 and was awarded MEDASTAR Erasmus Mundus and University of Surrey scholarships.

Yasmin is also a volunteer mentor for supporting students with soft & English skills development at Manara and a volunteer instructor at Code First Girls (CFGs).

http://yasminfathy.github.io/

Arian Jamasb

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Dequn Teng

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Biography

Jiri Benacek

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Karla Cervantes Barron

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Biography

Pingfan Song, PhD

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Biography

Pratheeba Vimalnath, PhD

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Biography

Swati Rajwal

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Biography

Yasmin Fathy, PhD

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Biography

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