Student offer

We are seeking students interested in carrying out their undergraduate or PhD thesis with us. Below we present our proposed research topics:

• Topic: Acquisition and processing of 2D and 3D images. 3D reconstruction using machine learning and artificial intelligence techniques
  Supervisor: Dr. Mercedes Morita
  E-mail: mercedesm@ciop.unlp.edu.ar
  Project description: Traditional 3D reconstruction techniques—such as laser scanning, structured light, or photogrammetry (structure from motion and multi-view stereo)—present limitations regarding the types of objects and surfaces they can model (e.g., they require opaque, static surfaces or features detectable by standard computer vision algorithms).
  With advances in artificial intelligence, particularly machine learning-based methods, new possibilities arise for reconstructing objects that are not accessible using conventional techniques. This proposal aims to investigate and develop innovative 3D reconstruction methods through AI-based image processing, with applications in industry and cultural heritage.
• Topic: Development of solar concentrators for energy conversion applications based on photonic films
  Supervisor: Dr. Gustavo Torchia
  E-mail: gustavot@ciop.unlp.edu.ar
• Topic: Development of sensors based on optical fiber tapers for the detection of chemical pollutants in water
  Supervisors: Dr. Valeria Arce and Dr. Diego Alustiza
  E-mail: varce@ciop.unlp.edu.ar
  E-mail: dalustiza@ciop.unlp.edu.ar
  Project description: Water contamination by chemical agents such as heavy metals, pesticides, and organic compounds represents a growing threat to human health and the environment. In this context, early, selective, and real-time detection of these contaminants is key to implementing effective mitigation and water recovery strategies. This thesis proposes to investigate the design, fabrication, and characterization of optical sensors based on tapered optical fibers, with the aim of developing highly sensitive and specific devices for detecting chemical contaminants in aqueous media.
• Topic: Development and characterization of compounds with photocatalytic activity for the degradation of environmental pollutants. Monitoring and evaluation of biological and chemical degradation processes using photonic methods
  Supervisor: Dr. Pedro David Gara
  E-mail: pedrodg@ciop.unlp.edu.ar
  Project description: In the Photophysics and Photochemistry in Solution group for systems of environmental and/or biological interest, we study processes in which light, in the presence of photosensitizing molecules, induces the degradation of pollutant compounds present in natural waters, such as agrochemicals, industrial waste, or urban residues. In these photosensitized processes, light produces energy changes in the photosensitizers (generating highly oxidizing reactive species) or in the contaminant (producing its photolysis). Within this research line, we study the mechanisms responsible for contaminant removal, the intermediates and products of the reactions, and their environmental impact.
• Topic: Design of structured optical beams: caustics, vortices, and novel structures; applications in optical tweezers and microscopy
  Supervisors: Dr. Pablo Vaveliuk and Dr. Dafne Amaya
  E-mail: pablovaveliuk@gmail.com
  E-mail: dafneamaya@gmail.com
• Topic: Design and implementation of integrated photonic sensors on different technological platforms
  Supervisor: Dr. Gustavo Torchia
  E-mail: gustavot@ciop.unlp.edu.ar
• Topic: Design and development of optical devices for aerospace quantum communications
  Supervisors: Dr. Fabián Videla and Dr. Gustavo Torchia
  E-mail: fabianv@ciop.unlp.edu.ar
  Project description: The main objective of this plan is to develop technological capabilities for building devices based on single-photon emission and detection systems, adapted for integration into a CubeSat-type platform and capable of withstanding the requirements of a mission involving launch and orbital flight conditions. The work will begin with non-integrated (bulk) systems, using more established technologies for the design of single-photon sources, and will progress toward integrated quantum circuits on photonic platforms. These are of interest for the development of the telecommunications industry, encryption systems for information security, and alternatives for modern computing and data processing systems.
• Topic: Study of the dynamics of complex optical systems using ordinal quantifiers
  Supervisor: Dr. Luciano Zunino
  E-mail: lucianoz@ciop.unlp.edu.ar
  Project description: Characterizing the mechanisms governing the dynamics of complex systems is essential for proper modeling. Since, in many cases, the only available information comes from time series of measurable observables, robust techniques for analyzing these signals are required. Ordinal analysis, based on mapping real-valued time series into ordered patterns, is a practical, fast, and effective tool for this purpose. In this context, the proposal is to investigate the advantages and limitations of this methodology, as well as its possible generalizations and new descriptors, within the study of complex optical systems.
• Topic: Study of optical field propagation in periodic absorbing media and/or with refractive index gradients
  Supervisors: Dr. Gustavo Forte and Dr. Pablo Vaveliuk
  E-mail: gforte@ciop.unlp.edu.ar
  E-mail: pablovaveliuk@gmail.com
• Topic: Plasmonic sensors
  Supervisor: Dr. Joaquín Mendoza Herrera
  E-mail: luisjh17061307@gmail.com
• Topic: Speckle-based processing techniques for nanoparticle studies
  Supervisor: Dr. Myrian Tebaldi
  E-mail: myrian.tebaldi@gmail.com
• Topic: Synthesis and characterization of nanomaterials. Optical properties and applications
  Supervisors: Dr. Jesica Santillán and Dr. Valeria Arce
  E-mail: jesicas@ciop.unlp.edu.ar
  E-mail: varce@ciop.unlp.edu.ar
• Topic: Deep learning techniques applied to optics
  Supervisors: Dr. Myrian Tebaldi and Dr. Damián Gulich
  E-mail: myrianc@ciop.unlp.edu.ar
  E-mail: dgulich@ciop.unlp.edu.ar
  Project description: Advances in artificial intelligence techniques, particularly deep learning, have opened new possibilities for addressing complex problems in optics and photonics that traditionally required intensive analytical or numerical models. This proposal aims to develop and apply deep learning models to analyze, model, and solve problems in modern optics, such as dynamic speckle characterization, detection and analysis of optical vortices, light propagation in turbulent media (such as the atmosphere), and compensation of distorted wavefronts.
  These challenges involve complex spatial and temporal patterns, highly sensitive to experimental conditions and environmental noise, making them ideal candidates for approaches based on convolutional neural networks and other contemporary models. The proposed techniques will not only improve real-time interpretation of optical data but also enable the design of adaptive systems for applications in imaging, optical communications, and adaptive optics.
  The work will be carried out within the framework of the Centro de Investigaciones Ópticas (CIOp, CONICET–CIC–UNLP), whose expertise in physical and applied optics provides an appropriate environment for the experimental validation of the proposed models. An interdisciplinary approach is envisioned, combining physics, optics, and data science, with potential for transfer to technological and biomedical fields.

General requirements:
Candidates with a background in physics, chemistry, engineering, information systems, or related fields.