Paolo Dini | Data Analysis | Best Researcher Award

Dr. Paolo Dini | Data Analysis | Best Researcher Award

Dr. Paolo Dini | Data Analysis | Leading Researcher at Centre Tecnològic de Telecomunicacions de Catalunya | Spain

Dr. Paolo Dini is a distinguished researcher in the field of information engineering, currently affiliated with the Centre Tecnològic de Telecomunicacions de Catalunya (CTTC), where he leads research at the intersection of sustainable computing, wireless communication, and artificial intelligence. Dr. Paolo Dini holds a Ph.D. in Information and Communication Technologies, and his academic foundation has enabled him to make impactful contributions to the development of energy-efficient and intelligent network infrastructures. Over the years, he has amassed a prolific research portfolio with more than 60 peer-reviewed publications and over 2,300 citations, earning him an h-index of 25 and an i10-index of 54, according to Scopus. Professionally, Dr. Paolo Dini has held research and leadership roles in multiple European and international collaborative projects, contributing both to academia and industrial innovation. He has worked alongside prominent researchers from institutions like Ericsson, Politecnico di Bari, University of Padova, and CTTC, fostering multidisciplinary research in areas such as mobile traffic modeling, green networking, and edge intelligence. His expertise includes machine learning for network optimization, distributed systems, multi-agent systems, 5G and beyond architectures, and sustainable AI. These skills are further demonstrated by his role in developing algorithms and models for energy harvesting in mobile networks and predictive analytics for traffic anomaly detection. Dr. Paolo Dini’s research interests continue to evolve with the current technological landscape, focusing on combining AI with wireless systems to enable smarter, greener, and more adaptive communication environments.

Professional Profile: ORCID | Google Scholar

Selected Publications:

  1. Mobile traffic prediction from raw data using LSTM networks (2018) – 245 Citations

  2. HetNets powered by renewable energy sources: Sustainable next-generation cellular networks (2012) – 201 Citations

  3. SolarStat: Modeling photovoltaic sources through stochastic Markov processes (2014) – 108 Citations

  4. Detecting mobile traffic anomalies through physical control channel fingerprinting: A deep semi-supervised approach (2019) – 81 Citations

 

 

Dr. Kianoosh Boroojeni | Data Fusion Awards | Best Researcher Award

Dr. Kianoosh Boroojeni | Data Fusion Awards | Best Researcher Award 

Dr. Kianoosh Boroojeni, Florida International University, United States

Dr. Kianoosh Boroojeni is an Associate Teaching Professor at the Knight Foundation School of Computing & Information Sciences, Florida International University (FIU). He earned his Ph.D. and M.S. in Computer Science from FIU and a B.Eng. in Computer Engineering from the University of Tehran. His research interests include cybersecurity, generative AI in computer science education, STEM education, and computer networks. With over 50 scientific publications and more than 1,150 citations, Dr. Boroojeni has made significant contributions to his field. He has played a pivotal role in integrating AI-powered tools into computer science education and has collaborated with Google to enhance programming courses. His leadership extends to overseeing programming gateway courses, developing cybersecurity curricula, and promoting inclusive computing education. He has received multiple teaching recognitions and actively mentors students.

Professional Profile:

SCOPUS

Summary of Suitability for Best Researcher Award – Kianoosh Boroojeni

Dr. Kianoosh Boroojeni is a highly accomplished researcher and educator in cybersecurity, AI in education, and computer networks, making him a strong candidate for the Best Researcher Award. His academic background, extensive research contributions, and leadership in integrating AI into education highlight his impact in the field.

Education 📚

  • Ph.D., Computer Science – Florida International University, USA (2017)
  • M.S., Computer Science – Florida International University, USA (2016)
  • B.Eng., Computer Engineering – University of Tehran, Iran (2012)

Work Experience 💼

🔹 Associate Teaching Professor – Florida International University (2023 – Present)

  • Leads Programming Gateway Committee to improve programming course success rates 📊
  • Collaborates with Google to integrate Generative AI in CS education 🤖
  • Chairs Faculty & Staff Awards Committee in the College of Engineering & Computing 🏆
  • Supports intensive programming courses like CS I, II & III, Data Structures, and OS 💾

🔹 Assistant Teaching Professor – Florida International University (2017 – 2023)

  • Taught 16+ undergraduate courses and 4 graduate/Ph.D. courses 🏫
  • Developed new cybersecurity courses on Blockchains 🔐
  • Led Google’s Tech-Exchange Program to recruit Hispanic & Black students into Google workforce 🌍
  • Designed and improved online courses to achieve Quality Matters (QM) Certifications
  • Achieved high student evaluations (4.6/5.0 overall) 📈

🔹 Post-Doctoral Fellow – Florida International University (Spring & Summer 2017)

  • Conducted DoD-funded research on network security & privacy 🔎
  • Mentored students in NSF-sponsored Research Experience program 👨‍🏫

🔹 Graduate Assistant – Florida International University (2012 – 2017)

  • Assisted faculty in teaching & grading multiple undergraduate/graduate courses ✍️
  • Collaborated with researchers from Carnegie Mellon & University of British Columbia 🤝

Achievements & Awards 🏅

🏆 Published 50+ scientific papers with 1150+ citations (h-index: 19) 📄
🏆 Led Google-FIU collaboration to integrate LLM-powered AI tools in CS education 🤖
🏆 Chaired Programming Gateway Committee to improve programming course completion rates 🎯
🏆 Successfully developed and taught two new cybersecurity courses on Blockchain 🔐
🏆 Achieved high teaching ratings (4.6/5.0) for multiple CS courses 📊
🏆 Contributed to NSF & DoD research projects on cybersecurity and network security 🏛

Publication Top Notes:

Fundamentals of brooks-iyengar distributed sensing algorithm: Trends, advances, and future prospects

A Multi-time-scale Time Series Analysis for Click Fraud Forecasting using Binary Labeled Imbalanced Dataset