Giuseppe Castiglione

Cross-platform machine learning on embedded, mobile (iOS + Android), and web. Extensive work in C, Python, and Java.

• Constructed convolutional and recurrent neural networks for real-time human motion recognition. Theano and Tensorflow for model training and validation, deployed from scratch on mobile and embedded.
• Base accuracy increased by over 20% on mobile devices, and over 30% on embedded - further gains with automatic unsupervised personalization.
• Reduced embedded computations from 7 MIPS to just under 1, while maintaining RAM. Net improvements yield up to 3x longer battery life. Algorithm development through Scipy stack, deployed from scratch on embedded.
• Deployed web services for human face analysis and transformation, including sentiment classification and face merges. Built on Flask using OpenCV and OpenFace.
• Working closely with product development team, personalised Facebook chatbot content via mood tracking through natural language processing, using Tensorflow, NLTK, and Sci-kit learn.

Quantifying loss in quantum coherence due to scattering imperfections in nanostructured optical waveguides, using a combination of numerical and theoretical methods

• Developed a theory of open quantum fields, allowing for the derivation, and solution, of an optical master equation.
• Used equation to construct a rudimentary model of entangled photon-production via spontaneous parametric down conversion.
• Extended model to include pump-driven feedback mechanisms for quantum control.

Lead a small team in the design and construction of a Michelson Interferometer (MI) for use in the Advanced Physics labs. Project focused on using an MI to perform Fourier Transform Spectroscopy of different optical sources.

• Aligned and calibrated HeNe lasers, and other optoelectronic components.
• Chiefly responsible for noise filtering at both the hardware and software level, and time series analysis. Extensive use of LabView and Matlab.
• The new device allowed full time-domain study of reflected sources, thus solving previous problem of artificial broadening.

Thesis : Scattering Losses in Integrated Quantum Optics

Using deep neural networks to turn amateur camera phone portraits into professional quality ones, by treating photographic quality as an image transformation problem. Fast prototyping on MS-COCO dataset using style transfer as guide for optimisation. Using data parallelism for distributed training on AWS.

Augmentation to the OkCupid matching algorithm via interest alignment through NLP. Prototyped a web-service which acts as an interactive user explorer. Document vectors are trained on a corpus of users and dimensional reduction techniques are used to assist interactive exploration. Feature selection at the word-level is performed to explain compatibility.

Present work focuses on using skip-thought vectors to generate messages seeded by critical features.