CV

Education

• 2020 - Ph.D. in Network Engineering - UPC Universitat Politecnica de Catalunya (Barcelona, Spain)
• 2017 - Visiting Researcher - University of Maryland (Maryland, United States)
• 2015 - M.Sc. in Telecommunications Engineering - Università degli Studi di Padova (Padova, Italy)
• 2013 - B.Sc. in Information Engineering - Università degli Studi di Padova (Padova, Italy)

Work Experience

• Oct 2020 - Present: Machine Learning Engineer, Exein (Rome, Italy)
• Sep 2016 - Jun 2020: Research Assistant, CTTC, Barcelona, Spain
• Oct 2015 - Sep 2016: IT Consultant, SideUp Reply SpA, Milan, Italy

Certifications

• Udacity: Machine Learning Engineer Nanodegree
• Udacity: PyTorch Challenge - Facebook Scholarship
• Deeplearning.AI: Deep Learning Specialization
• Deeplearning.AI: Machine Learning Engineer Nanodegree

Skills

Coding

• Python (5+ years)
• Rust (1+ years)
• C++ (1+ years)
• PL/SQL (1+ years)

Python Tools

• Math: numpy, scipy, pandas, matplotlib, seaborn, plotly
• ML: sklearn, tensorflow, tflite, keras, pytorch, xgboost, ONNX, pyspark, dask

Miscellaneous

• Cloud: AWS (EC2, ECS, SageMaker), GCP
• DB: OracleDB, Postgres, MongoDB
• Misc: Docker, Terraform, Git, Linux

Languages

• Italian – Native
• English – Work Proficiency
• Spanish – Work Proficiency
• Vietnamese – Basic Proficiency

Publications

Proactive Wake-Up Scheduler based on Recurrent Neural Networks

S. Rostami, HD. Trinh, S. Lagen, M. Costa, M. Valkama, P. Dini. (2020). "Proactive Wake-Up Scheduler based on Recurrent Neural Networks." 2020 IEEE International Conference on Communications.

Wake-up Scheduling for Energy-Efficient Mobile Devices

S. Rostami, HD. Trinh, S. Lagen, M. Costa, M. Valkama, P. Dini. (2020). "Wake-up Scheduling for Energy-Efficient Mobile Devices." 2020 IEEE Transactions of Wireless Communications.

Detecting Mobile Traffic Anomalies through Physical Channel Fingerprinting: a Deep Learning Approach

HD. Trinh, E. Zeydan, L. Giupponi, P. Dini. (2019). "Detecting Mobile Traffic Anomalies through Physical Channel Fingerprinting: a Deep Learning Approach." JIEEE Access 2019.

Urban Anomaly Detection by Processing Mobile Traffic Traces with LSTM Neural Networks

HD. Trinh, L. Giupponi, P. Dini. (2019). "Urban Anomaly Detection by Processing Mobile Traffic Traces with LSTM Neural Networks." CyberEdge: - Edge Computing for Cyber Physical System Workshop, 2019 IEEE International Conference on Sensing, Communication and Networking SECON, Boston, USA.

Unveiling Radio Resource Utilization Dynamics of Mobile Traffic through Unsupervised Learning

A. Rago, G. Piro, HD. Trinh, G. Boggia, P. Dini. (2019). "Unveiling Radio Resource Utilization Dynamics of Mobile Traffic through Unsupervised Learning." 2019 TMA - Network Traffic Measurement and Analysis Conference, Paris, France.

Mobile Traffic Prediction from Raw Data Using LSTM Networks

HD. Trinh, L. Giupponi, P. Dini. (2018). "Mobile Traffic Prediction from Raw Data Using LSTM Networks." 2018 IEEE 29th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Bologna, Italy.

Analysis and Modeling of Mobile Traffic Using Real Traces

HD. Trinh, N. Bui, J. Widmer, L. Giupponi, P. Dini. (2017). "Analysis and Modeling of Mobile Traffic Using Real Traces." 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), Montreal, Canada .

Talks

A Deep Learning Approach for Classification of Mobile Services and Apps through Physical Channel Fingerprinting

September 22, 2019

Talk at “2020 SoftCom”, “Split, Croatia”

“Urban Anomaly Detection by Processing Mobile Traffic Traces with LSTM Neural Networks”

June 10, 2019

Talk at “2019 CyberEdge - Edge Computing for Cyber Physical System Workshop - IEEE SECON”, “Boston, Massachusetts, USA”

“SCAVENGE - a European Training Network for PhD students”

November 10, 2018

Talk at “2018 Science Week”, “CTTC, Barcelona, Spain”

“Machine Learning Techniques for Data Analytics in 5G Networks”

September 21, 2018

Talk at “2018 SCAVENGE mid-term review”, “Paris, France”

“Analysis and Modeling of Mobile Traffic Using Real Traces”

October 14, 2017

Talk at “2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)”, “Montreal, Canada”

“Data Analytics for 5G Networks using Machine Learning Techniques”

June 02, 2017

Talk at “2017 SCAVENGE Workshop”, “Strathclyde University, Glasgow, UK”

Service and Miscellaneous

• IEEE Conferences and Journals Manuscripts’ Reviewer
• MSCA Fellowship Awarded by the European Commission
• Best Doctoral Thesis Nominee at UPC (2020)