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My academic background has leveraged my interest in making meaningful contributions to the operational research community. It was during bachelor's and master's degrees that I develop skills regarding simulation and optimization applied to manufacturing systems. First, through Simulation of Operations course unit, where I gained valuable expertise in simulating and analyzing complex industrial problems. Then, through the courses of Fundamentals of Operational Research and Complements of Operational Research, where it was fostered the development of mathematical models applicable to various engineering problems and meta-heuristic algorithms were introduced to tackle challenging combinatorial optimization problems. Given this context, I honed my critical thinking on various aspects of operations research and, in particular, on optimization models. Recently, I attended the NATCOR course in Stochastic Modeling, which is endorsed by the European Operational Research Society (EURO) at Lancaster University.
Identificação

Identificação pessoal

Nome completo
Marcelo Almeida Pinto
Data de nascimento
1998/12/10

Nomes de citação

  • Pinto, Marcelo

Identificadores de autor

Ciência ID
2414-8F11-C7F0
ORCID iD
0000-0002-6909-3829

Endereços de correio eletrónico

  • marceloalmeidapinto1998@gmail.com (Profissional)
  • marcelo.pinto@dem.uc.pt (Profissional)

Telefones

Telemóvel
  • (+351) 914390007 (Pessoal)

Moradas

  • Pólo II da Universidade de Coimbra, R. Luis Reis dos Santos, 3030-788, Coimbra, Coimbra, Portugal (Profissional)

Websites

Domínios de atuação

  • Ciências da Engenharia e Tecnologias - Engenharia Mecânica

Idiomas

Idioma Conversação Leitura Escrita Compreensão Peer-review
Português (Idioma materno)
Inglês Utilizador independente (B2) Utilizador proficiente (C1) Utilizador proficiente (C1) Utilizador proficiente (C1) Utilizador independente (B2)
Formação
Grau Classificação
2019/09 - 2022/02
Concluído
Industrial Engineering and Management (Mestrado)
Universidade de Coimbra Departamento de Engenharia Mecânica, Portugal
""Nesting and scheduling methods in additive manufacturing: bibliometric and systematic literature review"" (TESE/DISSERTAÇÃO)
17
2016/09 - 2019/06
Concluído
Industrial Engineering and Management (Licenciatura)
Universidade de Coimbra Departamento de Engenharia Mecânica, Portugal
14
Percurso profissional

Ciência

Categoria Profissional
Instituição de acolhimento
Empregador
2022/05 - Atual Investigador (Investigação) Universidade de Coimbra Centro de Engenharia Mecânica, Portugal
Universidade de Coimbra Departamento de Engenharia Mecânica, Portugal
Produções

Publicações

Poster em conferência
  1. Pinto, Marcelo; Silva, Cristóvão; Moniz, Samuel. "Nesting and scheduling towards additive manufacturing: emerging avenues". Trabalho apresentado em IO2022 - XXII Congress of the Portuguese Operational Research Association (APDIO), University of Évora., 2022.
  2. Jesus, Alexandre; Pinto, Marcelo; Silva, Cristóão; Vieira, Miguel; Moreira, Catarina; Moniz, Samuel. "Data-driven job-shop scheduling: the case of a metal packaging manufacturer". Trabalho apresentado em IO2022 - XXII Congress of the Portuguese Operational Research Association (APDIO), University of Évora., 2022.
Atividades

Participação em evento

Descrição da atividade
Tipo de evento
Nome do evento
Instituição / Organização
2022/11/06 - 2022/11/08 XXII Congress of the Portuguese Operational Research Association (APDIO), University of Évora
Congresso
IO2022
Associação Portuguesa de Investigação Operacional, Portugal
2022/09/29 - 2022/09/30 The 9th edition of the National Meeting of Industrial Engineering and Management - ENEGI 2022, was held on September 29th and 30th at the Porto Superior Engineering Institute (ISEP). It is an annual event that brings together students, professors, researchers, and professionals from all over the country who specialize in the field of Industrial Engineering and Management.
Encontro
ENEGI22
Instituto Politécnico do Porto, Portugal

Curso / Disciplina lecionado

Disciplina Curso (Tipo) Instituição / Organização
2023/04/17 - 2033/04/21 NATCOR Stochastic Modelling course - This course presents some of the theory behind such modeling processes, but also about the applications through case studies. Topics covered are: Stochastic processes; Queuing systems and networks; Maintenance and reliability; Inventory control; and Revenue management. Stochastic Modelling Lancaster University Management School, Reino Unido

Outro júri / avaliação

Descrição da atividade Instituição / Organização
2023/03 - 2023/03 Participation in the judging panel - The European BEST Engineering Competition (EBEC) Challenge Coimbra, is a yearly event that aims to encourage a competitive mentality among students of the Faculty of Sciences and Technology of the University of Coimbra. The goal is to solve challenging engineering problems proposed by partner companies, with the main purpose of promoting a stronger connection between academia and industry. EBEC Challenge Coimbra 2023, Portugal
Distinções

Prémio

2022 5% Best Students at University of Coimbra
Universidade de Coimbra, Portugal