Afsaneh Mahanipour

Afsaneh Mahanipour

CS Phd Candidate
University of Kentucky

Hi,

I am a Ph.D. candidate in Computer Science at the University of Kentucky, working under the supervision of Dr. Hana Khamfroush. My research lies at the intersection of artificial intelligence and distributed systems, with a particular focus on generative AI, federated learning, edge AI, and multimodal models. I aim to design scalable, distributed intelligent systems that leverage data-driven strategies to optimize performance and adaptability. My work emphasizes fostering interdisciplinary collaboration to advance communication, computation, Quality of Service (QoS), and decision-making in resource-constrained environments. These efforts address critical challenges in domains such as smart healthcare, intelligent transportation, industrial automation, and smart cities, where efficient and reliable AI solutions are essential for real-world impact.

Research Interests:

  • Edge AI
  • Federated Learning
  • Generative AI
  • Multimodal Data Analysis
  • Internet of Things
  • Interdependent Networks (Cyber-Physical Systems)

🔥 News

  • 11/03/25: Honored to be selected as a 2026 Lighthouse Beacon Foundation Graduate Fellow 😊
  • 09/27/25: Our work “Towards Memory-Efficient Foundation Models in Medical Imaging: A Federated Learning and Knowledge Distillation Approach” has been accepted at GenAI4Health @NeurIPS 2025!
  • 09/27/25: Presenting paper at MICCAI DeCaF 2025, Daejeon, South Korea!
  • 09/18/25: Presenting poster at 2025 NSF CSR Principal Investigator Meeting in Florida Atlantic University, Boca Raton, FL!
  • 07/31/25: Our work “Semi-Supervised Federated Multi-Label Feature Selection with Fuzzy Information Measures” has been accepted at IEEE Globecom 2025!
  • 07/27/25: Our work “Federated Reprogramming Knowledge Distillation for Medical Image Classification” has been accepted at MICCAI 2025 DeCaF Workshop!
  • 06/02/25: Honored to receive a Lighthouse Beacon Foundation Fellow Award!
  • 03/31/25: Our work “Embedded Federated Feature Selection with Dynamic Sparse Training: Balancing Accuracy-Cost Tradeoffs” has been accepted at IJCNN 2025!
  • 03/05/25: Glad for the CPS Rising Star Recognization 2025 ⭐
  • 01/15/25: Excited to be selected to attend the NeTS Early Career Workshop 2025 at the NSF Headquarters!
  • 12/19/24: Honored to be awarded a Graduate Student Congress Travel Grant!

📝 Publications

  • Towards Memory-Efficient Foundation Models in Medical Imaging: A Federated Learning and Knowledge Distillation Approach
    Afsaneh Mahanipour, Abdullah-Al-Zubaer Imran, Hana Khamfroush
    39th Conference on Neural Information Processing Systems (NeurIPS 2025) Workshop: The Second Workshop on GenAI for Health: Potential, Trust, and Policy Compliance.

  • Semi-Supervised Federated Multi-Label Feature Selection with Fuzzy Information Measures
    Afsaneh Mahanipour, Hana Khamfroush
    IEEE Global Communications Conference (GLOBECOM) 2025.

  • Federated Reprogramming Knowledge Distillation for Medical Image Classification
    Afsaneh Mahanipour, Abdullah-Al-Zubaer Imran, Hana Khamfroush
    MICCAI: International Conference on Medical Image Computing and Computer Assisted Intervention (DeCaF Workshop) 2025.

  • Embedded Federated Feature Selection with Dynamic Sparse Training: Balancing Accuracy-Cost Tradeoffs
    Afsaneh Mahanipour, Hana Khamfroush
    International Joint Conference on Neural Networks (IJCNN) 2025.
    paper

  • Fuzzy Federated Multi-Label Feature Selection: Reinforcement Learning and Ant Colony Optimization
    Afsaneh Mahanipour, Hana Khamfroush
    IEEE International Conference on Big Data (BigData) 2024.
    paper

  • FMLFS: A federated multi-label feature selection based on information theory in IoT environment
    Afsaneh Mahanipour, Hana Khamfroush
    IEEE International Conference on Smart Computing (SMARTCOMP) 2024.
    paper

  • Enhancing IoT Security: A Novel Feature Engineering Approach for ML-Based Intrusion Detection Systems
    Afsaneh Mahanipour, Hana Khamfroush
    International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT) 2024.
    paper

  • Multimodal multiple federated feature construction method for iot environments
    Afsaneh Mahanipour, Hana Khamfroush
    IEEE Global Communications Conference (GLOBECOM) 2023.
    paper

  • Wrapper-based federated feature selection for iot environments
    Afsaneh Mahanipour, Hana Khamfroush
    International Conference on Computing, Networking and Communications (ICNC) 2023.
    paper

  • A multiple feature construction method based on gravitational search algorithm
    Afsaneh Mahanipour, Hossein Nezamabadi-Pour
    Expert Systems with Applications 2019.
    paper

  • GSP: an automatic programming technique with gravitational search algorithm
    Afsaneh Mahanipour, Hossein Nezamabadi-Pour
    Applied Intelligence 2019.
    paper

  • Optimized design of nanohole array-based plasmonic color filters integrating genetic algorithm with FDTD solutions
    Fatemeh Fouladi Mahani, Afsaneh Mahanipour, Arash Mokhtari
    Journal of AI and Data Mining 2019.
    paper

  • Fast Optimization for VCOs Using GSA Algorithm
    Marzieh Ghasemi, Afsaneh Mahanipour, Mohsen Saneei
    Iranian Conference on Electrical Engineering (ICEE) 2018.
    paper

  • Using fuzzy-rough set feature selection for feature construction based on genetic programming
    Afsaneh Mahanipour, Hossein Nezamabadi-Pour, Bahareh Nikpour
    Conference on Swarm Intelligence and Evolutionary Computation (CSIEC) 2018.
    paper

  • Optimization of plasmonic color filters for CMOS image sensors by genetic algorithm
    Fatemeh Fouladi Mahani, Afsaneh Mahanipour, Arash Mokhtari
    Conference on Swarm Intelligence and Evolutionary Computation (CSIEC) 2017.
    paper

  • Improved PSO-based feature construction algorithm using Feature Selection Methods
    Afsaneh Mahanipour, Hossein Nezamabadi-Pour
    Conference on Swarm Intelligence and Evolutionary Computation (CSIEC) 2017.
    paper

🎤 Presentations

  • [Oral & Poster] MICCAI DeCaF 2025, Daejeon, South Korea - Federated Reprogramming Knowledge Distillation for Medical Image Classification
  • [Poster] NSF CSR PI Meeting 2025, Boca Raton, FL - Semi-Supervised Federated Multi-Label Feature Selection with Fuzzy Information Measures
  • [Poster] NSF CPS PI Meeting 2025, Nashville, TN - Optimizing Cyber-Physical Systems with a Novel Automated Data Processing Pipeline [PDF]
  • [Guest Lecture] Data Mining class at University of Kentucky - Spring 2025, Lexington, KY - Data Engineering in Centralized and Distributed Environments
  • [Oral] BigData 2024, Washington, DC, USA - Fuzzy Federated Multi-Label Feature Selection: Reinforcement Learning and Ant Colony Optimization
  • [Oral] KCS Seminar - Fall 2024, Lexington, KY - Federated Data processing frameworks in distributed environment [Video]
  • [Oral] DCOSS-IoT 2024, Abu Dhabi, UAE - Enhancing IoT Security: A Novel Feature Engineering Approach for ML-Based Intrusion Detection Systems
  • [Oral] GLOBECOM 2023, Kuala Lumpur, Malaysia - Multimodal multiple federated feature construction method for iot environments
  • [Poster] Annual Commonwealth Computational Summit 2023, Lexington, KY - Multimodal multiple federated feature construction method for iot environments [PDF]
  • [Oral] ICNC 2023, Honolulu, Hawaii - Wrapper-based federated feature selection for iot environments
  • [Oral] SEC 2022, Seattle, WA - Machine Learning-based Solutions for Resource Provisioning of Microservice based Applications in Hybrid Clouds
  • [Poster] Annual Commonwealth Computational Summit 2022, Lexington, KY - Wrapper-based federated feature selection for iot environments [PDF]

📖 Education

  • PhD in Computer Science, University of Kentucky (2021–Present)
  • M.Sc. in Electrical Engineering (Communication Systems), SBUK (2015–2018)
  • B.Sc. in Electrical Engineering (Communication Systems), SBUK (2011–2015)

💼 Experience

🔬 Research Experience

Graduate Research Assistant | University of Kentucky | Aug. 2021 – Present

Federated Data Engineering for IoT and Smart Cities

  • Building scalable federated data engineering methods to reduce communication, latency, and energy costs in distributed sensor networks
  • Enabling privacy-preserving analysis of multimodal data from distributed devices

Federated Adaptation of Foundation Models in Resource-Constrained Settings

  • Adapting large foundation models for edge devices using lightweight student models and federated learning
  • Reducing communication rounds and computation costs through different aggregation methods and efficient knowledge transfer

Graduate Research Assistant | SBUK | Aug. 2015 – Dec. 2020

  • Developed swarm-based programming algorithms for classification/regression tasks.
  • Optimized the design of voltage-controlled oscillators using machine learning methods.
  • Applied machine learning techniques to optimize plasmonic filter design.

🎓 Teaching and Mentoring Experience

Graduate Teaching Assistant

  • CS 215: Introduction to Program Design, Abstraction and Problem Solving, Spring 2024, University of Kentucky
  • CS 275: Discrete Mathematics, Fall 2023, Spring 2023, Spring 2022, Fall 2021, University of Kentucky
  • CS 371: Introduction to Computer Networking, Fall 2022, University of Kentucky
  • EE 461: Introduction to Electronics, Fall 2017, SBUK

Main Instructor

  • CS 275: Discrete Mathematics, Summer 2023, University of Kentucky

Mentorship

  • One undergraduate student at the University of Kentucky (May 2025-Present)
  • Two master students and one undergraduate student at SBUK

🏆 Awards and Fellowships

  • 2025: Lighthouse Beacon Foundation Scholar (Total award: $8,500)
  • 2025: Cyber-Physical Systems (CPS) Rising Star (Selected as 1 of 30 from 200 nominees)
  • 2025: NeTS Early Career Workshop Participant, NSF Headquarters
  • 2024-2025 Best Leadership Team Award, Association of Data and Computation (ADC), University of Kentucky
  • 2024: Graduate Student Congress (GSC) Travel Grant Award, University of Kentucky
  • 2023-2024 Outstanding Teaching Assistant Award, Department of Computer Science, University of Kentucky
  • 2024 Volunteer-IEEE International Conference on Communications (ICC)
  • 2023 NSF Student Travel Grant Award, IEEE Percom Conference
  • 2022 NSF Student Travel Grant Award, ACM/IEEE SEC Conference
  • 2018 Erasmus+ Gradana Machine Learning and Data Mining Winter School Participant, University of Bonn, Germany.

📜 Service

Leadership

  • 2024 - 2025, Leadership Team Member, Graduate Student Association of Data and Computation (ADC), University of Kentucky

Journal paper peer reviews

  • Elsevier Computer Networks
  • Elsevier Expert systems with applications
  • Elsevier Engineering applications of artificial intelligence

Conference paper peer reviews

  • IEEE Conference on Computer Communications (INFOCOM)
  • International Conference on Distributed Computing and Networking (ICDCN)
  • IEEE International Conference on Communications (ICC)
  • IEEE Global Communications Conference (GLOBECOM)
  • IEEE Consumer Communications & Networking Conference (CCNC)
  • IEEE International Conference on Sensing, Communication, and Networking (SECON)
  • International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS)
  • IEEE International Conference on Smart Computing (SMARTCOMP)
  • International Conference on Computing, Networking and Communication (ICNC)
  • IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)
  • IEEE Future Networks World Forum (FNWF)
  • International Joint Conference on Neural Networks (IJCNN)