Sina Soltani | Intelligent control systems | Best Researcher Award

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Mr. Sina Soltani | Intelligent control systems | Best Researcher Award

Research Scholar, Honeywell UOP ,United States.

🔬 Short Biography 🌿💊📚

🎓 Sina Soltani is a skilled Instrumentation & Automation Control Engineer 🎛️ with extensive experience across the steel 🏗️, petroleum 🛢️, and industrial automation sectors. He currently works at Honeywell UOP 🌍, designing and validating advanced instrumentation systems. With a Master’s in Electrical Engineering from Shiraz University ⚡, he specializes in control systems, PLC/DCS integration 🤖, and safety compliance 🔐. Previously, he contributed to engineering solutions at Neyriz Ghadir Steel Complex and Piramoon Pardazesh Qeshm, focusing on gamma measurement and radioactive instruments. His technical strengths include calibration, signal processing, fire alarm systems 🔥, and network implementation (Profibus, Modbus, Ethernet) 🌐. As a former university lecturer 📚, Sina has taught control systems, electronics, and engineering mathematics. He holds multiple certifications, including ISO 9001 and ATEX compliance. Passionate about precision and safety, Sina is a dedicated engineer 🛠️ shaping the future of smart industrial systems.

Profile

ORCID PROFILE

GOOGLE SCHOLAR PROFILE

🎓 Education

🏁conclusion:

Sina Soltani stands out as a 🌟 dynamic and innovative researcher whose work bridges the gap between academic theory 📚 and industrial application 🏭. His extensive contributions in automation 🤖, fuzzy logic 🤯, Kalman filtering 📉, and advanced instrumentation  reflect a deep commitment to solving real-world engineering challenges 🔧. With a strong portfolio of peer-reviewed publications 📑, industry certifications , and ongoing work at Honeywell UOP 🏢, he exemplifies the qualities of a forward-thinking researcher 🚀 who drives impact across sectors 🌍. His ability to integrate complex control strategies 🧠 into harsh industrial environments ⚙️ highlights his technical depth and problem-solving skills 💡. Furthermore, his experience as an educator  enhances his influence in shaping future engineers 👩‍💻. While international collaborations  and patent outputs 🧾 could further elevate his profile, Sina’s consistent research trajectory 📈 and innovative mindset  make him an exceptional candidate for the Best Researcher Award 🏆. His work not only advances engineering practices 🛠️ but also aligns with global trends in smart manufacturing  and intelligent industrial systems 🔌🤖.

ARIANNA Zhong | Intelligent control systems | Best Researcher Award

Published on by Global CAD Awards

 

Dr. ARIANNA PARRALES | Simulación de procesos | Best Researcher Award

University of Fribourg, Switzerland,Switzerland

Dr. Arianna Parrales Bahena is a dedicated and competent researcher in the field of chemical and energy engineering with expertise in simulation, process optimization, and neural networks. Her recognition by the SNI system and full-time role at CIICAp under CONAHCyT demonstrates strong national standing in Mexico. Her interdisciplinary approach involving AI and energy processes is promising for sustainable engineering solutions.

Publication Profile
Publication : 

  • Ajbar, W., Parrales, A., Cruz-Jacobo, U., Conde-Gutiérrez, R. A., Bassam, A., … (2021). The multivariable inverse artificial neural network combined with GA and PSO to improve the performance of solar parabolic trough collector. Applied Thermal Engineering, 189, 116651. Citations: 70

 

  • Ajbar, W., Parrales, A., Huicochea, A., Hernández, J. A. (2022). Different ways to improve parabolic trough solar collectors’ performance over the last four decades and their applications: A comprehensive review. Renewable and Sustainable Energy Reviews, 156, 111947. Citations: 62

 

  • Ajbar, W., Hernández, J. A., Parrales, A., Torres, L. (2023). Thermal efficiency improvement of parabolic trough solar collector using different kinds of hybrid nanofluids. Case Studies in Thermal Engineering, 42, 102759. Citations: 42

 

  • Parrales, A., Colorado, D., Díaz-Gómez, J. A., Huicochea, A., Álvarez, A., … (2018). New void fraction equations for two-phase flow in helical heat exchangers using artificial neural networks. Applied Thermal Engineering, 130, 149–160. Citations: 36

 

  • Solís-Pérez, J. E., Hernández, J. A., Parrales, A., Gómez-Aguilar, J. F., … (2022). Artificial neural networks with conformable transfer function for improving the performance in thermal and environmental processes. Neural Networks, 152, 44–56. Citations: 35

 

  • Reyes-Téllez, E. D., Parrales, A., Ramírez-Ramos, G. E., Hernández, J. A., … (2020). Analysis of transfer functions and normalizations in an ANN model that predicts the transport of energy in a parabolic trough solar collector. Desalination and Water Treatment, 200, 23–41. Citations: 30

 

  • Parrales, A., Hernández-Pérez, J. A., Flores, O., Hernandez, H., … (2019). Heat transfer coefficients analysis in a helical double-pipe evaporator: Nusselt number correlations through artificial neural networks. Entropy, 21(7), 689. Citations: 24

Sailin Zhong | Intelligent control systems | Best Researcher Award

Published on by Global CAD Awards

 

Dr. Sailin Zhong | Intelligent control systems | Best Researcher Award

University of Fribourg, Switzerland,Switzerland

Sai Lin Eicher is a rising interdisciplinary researcher with an impressive academic journey across Switzerland, Singapore, and the United States. His work in fluid human comfort, ambient intelligence, and extended reality bridges the gap between humans and intelligent environments. With top-notch institutional affiliations, funded international projects, and practical impact, his career trajectory is both innovative and globally relevant.

Publication Profile

Education 🎓:


Sai Lin Eicher earned his Ph.D. in Informatics with a specialization in Human-Computer Interaction from the University of Fribourg, Switzerland (July 2019 – December 2023). His doctoral thesis, titled “Fluid Human Comfort in Built Environments with Ambient Intelligence”, was advised by Prof. Denis Lalanne and Prof. Hamed S. Alavi, with a committee that included Prof. Adrian Friday, Prof. Andrew Vande Moere, and Prof. Marilyne Andersen. The research was partially funded by Innosuisse 30076.1 IP‑ICT in collaboration with Logitech.
During his Ph.D., he also served as a visiting Ph.D. student at the MIT Media Lab, Massachusetts Institute of Technology, USA (August 2022 – April 2023), working on AirSpecs, a novel smart eyewear system for habitat comfort interactions, under the supervision of Prof. Joseph A. Paradiso. This research was supported by the Swiss Doc.Mobility Fellowship.
Prior to that, he completed his Master of Computing with a specialization in Computer Science at the National University of Singapore (August 2017 – January 2019), with a thesis on “Effective Smartfan Deployment in NUS SDE Net-Zero Building” under Prof. Roger Zimmermann.
Sai Lin holds a Bachelor of Engineering in Information Engineering and Media from Nanyang Technological University, Singapore (August 2012 – July 2016), graduating with First Class Honours and a CGPA of 4.56/5.00. His undergraduate thesis, “Sociofeedback by Google Glass”, was supervised by Prof. Justin Dauwels.
He also spent a semester as an undergraduate exchange student at École Polytechnique Fédérale de Lausanne (EPFL), Switzerland (February – July 2014), studying Electrical and Electronic Engineering.

Work and Research Experience 💼:


Sai Lin Eicher is currently a Postdoctoral Fellow in Human-Computer Interaction at ETH Zürich (March 2024 – March 2025), where he is contributing to the 3D Sketch Map project by designing and developing a collaborative and generative AI 3D sketching game in VR and AR. He also provides technical consultancy and research guidance on user experiences for Lufthansa Group’s D‑CEET cabin digital twin training.
Previously, he served as a Work Package Lead at the Singapore-ETH Centre (November 2017 – July 2019), where he led the user interface design and development of spatial visualizations and interactive decision-support tools using Sketch and Unity 3D, aimed at enhancing data representation for policymakers.
From June to August 2015 and again from July 2016 to October 2017, he worked as a Software Engineer at IHS Markit in Singapore, supporting financial processing software (TradeSTP) and designing a centralized platform for product access and sales enhancement.
He also interned at Apple Inc., Singapore (August – December 2014) as a Business Intelligence Intern, where he optimized web applications for supply chain automation using PHP and Ruby on Rails.
As a Research Assistant at Nanyang Technological University (August 2013 – June 2014), he developed an Android application capable of separating audio signals from ambient sound using Delay-And-Sum-Beamforming.

Grants, Awards, and Fellowships 🏆:


In 2023, Sai Lin received the MIT MISTI-Switzerland Seed Grant (USD 27,100). In 2022, he was awarded the Swiss Doc.Mobility Fellowship (CHF 25,900). Earlier in his academic journey, he was recognized as a URECA President Research Scholar with Distinction in 2014. He was also the recipient of the Singapore Government Link Company SM3 Full Undergraduate Scholarship (SGD 210,000) in 2012.

Skills 💻:


Sai Lin’s expertise spans user experience research using both quantitative methods (surveys, eye-tracking, usability tests) and qualitative techniques (user interviews, diary studies), as well as mixed methods. He is proficient in user interface design tools such as Sketch, Photoshop, InVision, HTML, CSS, hardware prototyping (Raspberry Pi, Arduino), Autodesk Inventor, and Miro.
He is skilled in statistical analysis techniques including bivariate correlation, factorial analysis, clustering, and both parametric and non-parametric tests, using tools like R, STATA, and SPSS.
Sai Lin has strong programming capabilities in Python, C# (Unity3D), Swift (iOS), JavaScript (Web, React Native), R, SQL, and Java (Android). He is also experienced with AI methodologies, including supervised and unsupervised learning, neural networks, and generative AI.

Publication : 

. ilo-wear: Exploring wearable interaction with indoor air quality forecast

  • Authors: S. Zhong, H.S. Alavi, D. Lalanne

  • Year: 2020

  • Venue: CHI Extended Abstracts (CHI EA 2020)

  • Citations: 26

2. The complexity of indoor air quality forecasting and the simplicity of interacting with it – A case study of 1007 office meetings

  • Authors: S. Zhong, D. Lalanne, H. Alavi

  • Year: 2021

  • Venue: CHI 2021

  • Citations: 17

3. Already it was hard to tell who’s speaking over there, and now face masks! Can binaural audio help remote participation in hybrid meetings?

  • Authors: L. Rosset, H. Alavi, S. Zhong, D. Lalanne

  • Year: 2021

  • Venue: CHI Extended Abstracts (CHI EA 2021)

  • Citations: 13

4. Reflecting on hybrid events: Learning from a year of hybrid experiences

  • Authors: A.A. Ansah, A.S. Vivacqua, S. Zhong, S. Boll, M. Constantinides, H. Verma, …

  • Year: 2023

  • Venue: CHI Extended Abstracts (CHI EA 2023)

  • Citations: 12

5. Proxy methods for detection of inhalation exposure in simulated office environments

  • Authors: S. Yun, S. Zhong, H.S. Alavi, A. Alahi, D. Licina

  • Year: 2023

  • Venue: Journal of Exposure Science & Environmental Epidemiology, Vol. 33(3)

  • Citations: 11

6. Predictive Models of Indoor CO₂ Concentration: Toward Context-Aware Occupant Support in Offices

  • Authors: H.S. Alavi, S. Zhong, D. Lalanne

  • Year: 2020

  • Venue: SmartPhil@IUI 2020

  • Citations: 11

7. A novel decision support tool for climate-responsive urban design

  • Authors: S. Zhong, I. Nevat, J.A. Acero, L.A. Rüfenacht, P. Jan, E. Koh

  • Year: 2019

  • Venue: Journal of Physics: Conference Series, Vol. 1343

  • Citations: 7

8. Airspec: A smart glasses platform, tailored for research in the built environment

  • Authors: P. Chwalek, S. Zhong, D. Ramsay, N. Perry, J. Paradiso

  • Year: 2023

  • Venue: ACM IJCAI Adjunct

  • Citations: 6

Sai Lin Eicher meets and exceeds the criteria for a Best Researcher Award in a design-tech-HCI-focused category. His work is not only innovative and interdisciplinary but also strongly backed by funding, collaborations with premier institutions, and real-world applications.