About Me
I am a passionate Ph.D. Candidate in Electrical & Computer Engineering at Rochester Institute of Technology, driven by a desire to push the boundaries of wireless communication through advanced AI and machine learning. My research focuses on optimizing complex 5G networks, especially within challenging industrial environments like automated warehouses, and exploring the frontiers of edge computing and mobile technologies. I am committed to developing innovative solutions that address real-world engineering challenges, transforming theoretical concepts into practical applications.
Beyond my research, I am deeply invested in education and mentorship. My philosophy emphasizes active, hands-on learning that empowers students to become critical thinkers and innovators. I am particularly committed to creating inclusive and equitable learning environments that support students from all backgrounds, preparing them to excel in diverse professional landscapes. My aim is to contribute to a vibrant academic community through impactful research, inspiring teaching, and dedicated service.
Research & Publications
AI-Driven Channel Modeling & Optimization
My core research focuses on applying advanced AI techniques, particularly Variational Autoencoders (VAEs) and ConvLSTMs, to model and predict complex wireless channel characteristics in dynamic 5G environments. This work enables real-time optimization and resource allocation critical for next-generation networks.
- **Key Innovation:** Developed the WISVA framework for 108x faster SINR heatmap prediction.
- **Techniques:** Variational Autoencoders (VAEs), ConvLSTMs, Digital Signal Processing (DSP), Spatiotemporal AI.
- **Impact:** Real-time network optimization, enhanced resource allocation, improved signal quality management.
Physical (PHY) & MAC Layer Design
My research extends to the fundamental design and optimization of wireless air interfaces, including advanced modulation, MIMO, and MAC protocols, crucial for robust mobile communication.
- **Key Innovation:** Developed an end-to-end OFDM system simulation comparing FFT-OFDM and DWT-OFDM for robust transmission.
- **Techniques:** OFDM, DWT, MIMO, Digital Modulation (BPSK to 256-QAM), Channel Estimation, CSMA/CA, Beamforming.
- **Impact:** Improved spectral efficiency, enhanced interference suppression, optimized network throughput for mobile technologies.
Edge Computing & IoT Connectivity
Investigating how AI and advanced networking can enable efficient and reliable communication for IoT devices and applications at the network edge, critical for Industry 4.0.
- **Key Innovation:** Developed stochastic Air-Ground channel models for UAVs to assess and optimize mobile connectivity.
- **Techniques:** Digital Twin, ns-3 simulation, Reinforcement Learning for adaptive CW, Channel Modeling.
- **Impact:** Enhanced reliability for industrial IoT, improved resource management in dense environments, support for UAV-specific 5G channels.
Research Vision & Future Directions
My future research will focus on advancing AI-driven wireless autonomy, developing adaptive and resilient 5G/6G systems for complex, dynamic environments. I aim to explore self-organizing networks, AI for spectrum management, and secure edge-AI integration for critical infrastructure.
I am committed to establishing a collaborative research program at SJSU that engages both undergraduate and graduate students, seeking external funding to address challenges in **Software Quality, Mobile Technologies, and Edge Computing** that directly benefit Silicon Valley industries.
Selected Publications
- Rahul Gulia et al., "[Forthcoming] AI-based VAE model for Automated Warehouse 5G Infrastructure Modeling," *ACM Transactions on IoT*.
- Rahul Gulia et al., "Evaluation of 60 GHz Wireless Connectivity for an Automated Warehouse," *Information*, 2023.
- R. S. Gulia et al., "Evaluation of Wireless Connectivity in an Automated Warehouse at 60 GHz," *IEEE ICCE*, 2022.
- R. Gulia et al., "Automated Warehouse 5G Infrastructure Modeling Using VAEs," *ISNCC*, 2024.
- R. Gulia, "Path Loss Model for 2.4 GHz Indoor Wireless Networks With Application To Drones," M.S. Thesis, Rochester Institute of Technology, 2020.
Teaching Philosophy & Experience
My teaching philosophy emphasizes **active engagement, collaborative problem-solving, and continuous learning**. I believe in empowering students to become active creators and innovators, not just recipients of knowledge. This approach is informed by John Holt's wisdom that "Learning is the product of the activity of learners."
Courses I Am Prepared to Teach:
- **Core CNSM:** Introduction to Networks, Network Administration, Internet of Things (IoT), Cloud Computing, Database Management.
- **Specialized:** Software Quality Management, Mobile Technologies, Edge Computing, Reinforcement Learning for Wireless Communications, Wireless Digital Twin Engineering, Advanced Wireless Systems (5G/6G).
Pedagogical Approach & Lab Development:
- **Problem-Based Learning:** Grounding theoretical concepts in real-world engineering challenges, drawing from my research in Industry 4.0 and 5G.
- **Hands-on Labs:** Designing and developing practical laboratory exercises utilizing tools like **ns-3, Python, MATLAB**, and leveraging existing departmental infrastructure (e.g., CNSM's Cisco-sponsored labs) to reinforce concepts in **network configuration, wireless signal analysis, and AI model deployment**.
- **Inclusive Teaching:** Employing varied assessment methods, fostering peer-to-peer learning, and adapting to diverse learning styles and backgrounds, inspired by my experience with **underprivileged children through the Gubbachi organization** and teaching high school physics/math through **Vedantu**.
- **Mentorship:** Actively advising undergraduate capstone projects and guiding graduate research, encouraging students to pursue research and publication opportunities.
- **Digital Pedagogy:** Adapting interactive whiteboard sessions and facilitating live, structured online learning during the COVID-19 pandemic, solidifying a belief in flexible and thoughtful digital instruction.
Service Contributions
Department & University Contributions:
- **Curriculum & Program Development:** Eager to contribute to CNSM curriculum modernization and develop new specializations in **AI-driven wireless systems, IoT, and edge computing**.
- **Research Infrastructure:** Active in building and enhancing cutting-edge research facilities, including **AI-driven wireless testbeds** and IoT labs.
- **Student Success & DEI:** Committed to mentoring students from diverse backgrounds and participating in initiatives promoting **diversity, equity, and inclusion** within STEM fields at SJSU.
- **Shared Governance:** Prepared to serve on departmental, college, and university committees (e.g., curriculum, admissions, faculty hiring, research strategy).
- **Research Showcase:** Led team in showcasing innovative wireless AI research at Imagine RIT, demonstrating commitment to public engagement within the university.
Professional & Discipline Service:
- **Technical Committee:** Active member of **IEEE Consumer Technology Society (CTSoc) – Consumer Communications Networks and Connectivity (CCN)**, shaping technical agendas.
- **Peer Reviewer:** Dedicated reviewer for **IEEE Internet of Things Journal**, **IEEE ICCE-Taiwan (2025)**, and committed to reviewing for other leading journals and conferences in wireless communications and AI/ML.
- **Conference Organization:** Committed to organizing and chairing technical sessions and serving on Technical Program Committees (TPCs).
- **Standardization & Societies:** Eager to contribute to standardization bodies (e.g., IEEE 802.11) and actively engage with professional societies like IEEE ComSoc and ACM SIGCOMM.
Community & Public Engagement:
- **STEM Outreach:** Participate in K-12 STEM outreach programs, drawing on experience teaching high school math/physics (Vedantu) to inspire diverse young audiences in engineering.
- **Industry Bridge-Building:** Leverage industry collaborations (e.g., The Raymond Corporation) to establish partnerships for sponsored research and student internships at SJSU.
- **Public Understanding:** Communicate the societal benefits of AI/wireless research (smart healthcare, resilient cities) through public lectures and accessible articles.
Skills
Teaching & Pedagogy:
- Curriculum Development
- Laboratory Design & Management
- Student Mentoring
- Inclusive Teaching Practices
- Assessment Design
- Digital Pedagogy
Core Engineering Technology:
- Software Quality Management
- Mobile Technologies
- Edge Computing
- Internet of Things (IoT)
- Cloud Computing
- Network Administration
- Database Management
- Industry 4.0
- Digital Twins
Wireless Communications:
- 5G NR, LTE
- Air Interface Design
- Physical (PHY) Layer
- Medium Access Control (MAC) Layer
- Radio Resource Control (RRC)
- Channel Modeling
- Link Budget Analysis
- MIMO, Beamforming
- SDR (Software Defined Radio)
Signal Processing:
- Digital Signal Processing (DSP)
- Filter Design
- Clock Recovery
- Signal Detection
- Channel Estimation & Equalization
- Channel Coding
- OFDM, DWT-OFDM
AI/ML & Data Science:
- PyTorch, TensorFlow
- Variational Autoencoders (VAEs)
- Reinforcement Learning
- Deep Learning, Neural Networks
- Predictive Modeling
- Data Analysis
Tools & Platforms:
- ns-3, MATLAB
- Python (NumPy, SciPy, Matplotlib, PyWavelets, OpenCV)
- C/C++
- Git, Jupyter, Google Colab
Research & Grants:
- Grant Proposal Writing
- Scientific Writing
- Peer Review
- Project Management
- Data Visualization
Certifications:
- IBM Deep Learning & Reinforcement Learning
- Generative Deep Learning with TensorFlow
- VAEs for Image Compression
- Neural Networks & Deep Learning
- 5G Mobile Networks
Contact Me
I welcome inquiries regarding collaborations, research opportunities, or teaching positions. Feel free to reach out:
Phone: 585-410-7518
Email: rg9828@rit.edu / rahulgulia92@gmail.com
Website: learnwithpatience-wc.blogspot.com
LinkedIn: Rahul Gulia
GitHub: RahulSinghGulia