Dr. Mahdi Nangir | Signal Processing | Best Researcher Award

Associate Professor at Faculty of Electrical and Computer Engineering, University of Tabriz, Iran

Dr. Mahdi Nangir is a dedicated academic and researcher in the field of Communication Systems within Electrical Engineering, currently serving as an Associate Professor at the University of Tabriz, Iran. With an academic career marked by distinction and international collaboration, he brings expertise in coding theory, information theory, and source compression. Dr. Nangir completed his Ph.D. at the prestigious K.N. Toosi University of Technology, Tehran, where he focused on graph-based code design for the Binary CEO Problem. His academic journey also includes a sabbatical at McMaster University, Canada, which enriched his research through exposure to global academic practices. Throughout his career, he has contributed significantly to the fields of source coding and communication systems, blending theoretical depth with practical insight. His pedagogical commitment is evident through his active role in mentoring graduate students, supervising theses, and developing curricula in advanced communication topics. Dr. Nangir’s professional ethos is grounded in rigorous research, student-centered teaching, and continuous innovation. As a scholar, he is committed to solving real-world problems through interdisciplinary and collaborative research, positioning himself as a valuable contributor to the global academic community.

Professional Profile

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Education

Dr. Mahdi Nangir’s educational background reflects his consistent pursuit of excellence in communication systems and electrical engineering. He earned his Ph.D. in Communication Systems from K.N. Toosi University of Technology in Tehran, Iran, between 2013 and 2018, with a strong GPA of 18.24/20. His doctoral thesis, titled “Graph-Based Code Design for the Binary CEO Problem,” was supervised by Prof. Mahmoud Ahmadian Attari and co-advised by Dr. Reza Asvadi. During this period, he further enriched his research through a sabbatical visit to McMaster University, Canada (2016–2017), under the mentorship of Prof. Jun Chen, engaging in cross-border academic collaboration and applying his research in diverse contexts. He previously obtained his M.Sc. in Communication Systems from the prestigious Sharif University of Technology, where he explored universal source coding algorithms under the supervision of Prof. Mohammad Reza Aref and Dr. Hamid Behroozi. His academic foundation began with a B.Sc. in Electrical Engineering from the University of Tabriz, where his thesis on self-similar communication network traffic earned a GPA of 18.39/20. This progression demonstrates not only academic rigor but also a deep and evolving engagement with the key challenges in information and communication technologies.

Professional Experience

Dr. Mahdi Nangir’s academic career is deeply rooted in research excellence and educational commitment. Since 2018, he has served in the Department of Electrical Engineering at the University of Tabriz, initially as an Assistant Professor and currently as an Associate Professor. In these roles, he has led advanced undergraduate and graduate courses in communication systems, mentored numerous thesis projects, and actively contributed to departmental planning and curriculum development. His responsibilities have extended beyond teaching to supervising cutting-edge research in information theory and coding techniques. Prior to his professorship, his professional experiences included sabbatical research at McMaster University, Canada, where he collaborated with international researchers on source coding challenges. Although his primary focus has been academia, Dr. Nangir also maintains links with the broader engineering and technology community through industry collaborations, applying theoretical insights to practical problems in communication systems. His work integrates theoretical innovation with teaching effectiveness, demonstrated by consistently positive student feedback and research outcomes. These experiences have honed his ability to balance rigorous scholarship with pedagogical effectiveness, preparing the next generation of engineers and researchers for success in the evolving tech-driven world.

Research Interest

Dr. Mahdi Nangir’s research interests lie at the intersection of communication theory, source coding, and information processing, with a special emphasis on coding design for networked systems and distributed data environments. His doctoral and postdoctoral research has centered on problems such as the Binary CEO Problem, where he developed novel graph-based coding schemes. This work contributes to foundational advancements in information theory, enabling efficient and robust data compression in noisy environments—a growing necessity in today’s big-data-driven world. His interests extend to universal source coding, distributed compression, and correlated sources, aligning closely with next-generation communication protocols, IoT frameworks, and cloud storage systems. Dr. Nangir is particularly passionate about solving real-world challenges such as bandwidth optimization, error reduction, and signal integrity in multi-sensor communication networks. His future research aims to explore machine learning applications in source coding and data representation, furthering his interdisciplinary reach. By combining strong mathematical modeling with hands-on simulation and implementation, he ensures that his research is both theoretically robust and practically applicable. He continues to collaborate with international scholars and institutions, bringing global relevance to his research and fostering innovation that pushes the boundaries of communication systems engineering.

Research Skills

Dr. Mahdi Nangir possesses a diverse and sophisticated set of research skills that empower him to address complex problems in communication systems and information theory. His core competencies include advanced coding theory, graph-based algorithms, and probabilistic modeling, especially within the context of source coding and compression techniques. He is highly skilled in developing and analyzing distributed source coding frameworks for applications in sensor networks and data fusion. Dr. Nangir is proficient in simulation and algorithm development using programming tools such as MATLAB and Python, enabling him to transform theoretical models into practical, testable solutions. Additionally, he has extensive experience in applying optimization techniques, such as convex programming and belief propagation, to enhance coding efficiency and system performance. His international research collaborations, especially his sabbatical work in Canada, have also equipped him with strong cross-cultural research communication and academic writing skills. Furthermore, he demonstrates strong capabilities in research supervision, literature review, experimental design, and publication in high-impact journals. These skills not only reflect technical mastery but also a deep commitment to rigorous, collaborative, and impactful research in the rapidly evolving field of electrical and communication engineering.

Awards and Honors

Dr. Mahdi Nangir has been recognized for his academic excellence and research contributions throughout his career. His consistent high GPA during undergraduate and graduate studies earned him multiple scholarships and commendations, showcasing his commitment to academic rigor from an early stage. His doctoral research on graph-based code design has been acknowledged for its innovation and potential impact in the field of communication systems. During his sabbatical tenure at McMaster University, he received positive evaluations and commendations from peers and supervisors, highlighting his adaptability and ability to contribute meaningfully in an international research environment. While his awards list is still developing as he continues to expand his academic profile, Dr. Nangir is widely respected within his department at the University of Tabriz, where he has been entrusted with key teaching and research responsibilities, culminating in his promotion to Associate Professor in 2023. His selection as a thesis advisor for multiple graduate students further underscores his recognition as a leader and mentor in the academic community. As he continues to publish and collaborate globally, his work is poised to receive broader recognition through future research awards and institutional honors.

Conclusion

In conclusion, Dr. Mahdi Nangir represents a well-rounded academic whose dedication to research, teaching, and scholarly collaboration makes him a valuable asset to any academic or research institution. His journey from a top-performing undergraduate to an internationally experienced Associate Professor reflects a sustained commitment to excellence. With specialized expertise in communication systems, information theory, and source coding, he continues to make meaningful contributions to both theoretical and applied aspects of electrical engineering. His ability to supervise research, secure academic collaborations, and deliver high-quality instruction has been evident through his work at the University of Tabriz and during his time at McMaster University. Dr. Nangir is not only a subject-matter expert but also a mentor and innovator, deeply engaged in advancing the frontiers of knowledge while nurturing the next generation of engineers. His career trajectory points toward a future rich with opportunity for impactful discoveries, interdisciplinary initiatives, and global academic engagement. With a strong foundation and an ambitious vision, Dr. Nangir stands ready to contribute to the evolving challenges and innovations in communication and information technologies.

Publications Top Notes

• Energy Efficient Power Allocation in Massive MIMO NOMA Systems Based on SIF Using Cell Division Technique
  Authors: A.S. Gharagezlou, J. Pourrostam, M. Nangir, M.M. Safari
  Year: 2020
  Citations: 17

• Analysis and Code Design for the Binary CEO Problem Under Logarithmic Loss
  Authors: M. Nangir, R. Asvadi, M. Ahmadian-Attari, J. Chen
  Year: 2018
  Citations: 17

• Inception‐YOLO: Computational Cost and Accuracy Improvement of the YOLOv5 Model Based on Employing Modified CSP, SPPF, and Inception Modules
  Authors: H.K. Jooshin, M. Nangir, H. Seyedarabi
  Year: 2024
  Citations: 15

• Energy Efficient Power Allocation in Massive MIMO Systems with Power Limited Users
  Authors: A.S. Gharagezlou, M. Nangir, N. Imani, E. Mirhosseini
  Year: 2020
  Citations: 15

• Energy Efficient Power Allocation with Joint Antenna and User Selection in Massive MIMO Systems
  Authors: A.S. Gharagezlou, M. Nangir, N. Imani
  Year: 2022
  Citations: 12

• Secure Energy Efficient Power Allocation in Massive Multiple‐Input Multiple‐Output Systems with an Eavesdropper Using Cell Division Technique
  Authors: A.S. Gharagezlou, J. Pourrostam, M. Nangir
  Year: 2021
  Citations: 11

• Comparison of the MRT and ZF Precoding in Massive MIMO Systems from Energy Efficiency Viewpoint
  Authors: M. Nangir, A.S. Gharagezlou, N. Imani
  Year: 2022
  Citations: 10

• Energy Efficient Power Allocation in MIMO-NOMA Systems with ZF Receiver Beamforming in Multiple Clusters
  Authors: M. Nangir, A.S. Gharagezlou, N. Imani
  Year: 2021
  Citations: 9

• Successive Wyner-Ziv Coding for the Binary CEO Problem Under Logarithmic Loss
  Authors: M. Nangir, R. Asvadi, J. Chen, M. Ahmadian-Attari, T. Matsumoto
  Year: 2019
  Citations: 9

• Binary Wyner–Ziv Code Design Based on Compound LDGM–LDPC Structures
  Authors: M. Nangir, M. Ahmadian‐Attari, R. Asvadi
  Year: 2018
  Citations: 9