Announcements
17 June 2024
Electronics | Highly Cited Papers in 2023 in the Section “Computer Science & Engineering”
17 June 2024
Electronics | Highly Cited Papers in 2022 in the Section “Computer Science & Engineering”
7 June 2024
MDPI Calls for Greater Open Access to Science for Ocean Protection
7 June 2024
Electronics | Highly Cited Papers in 2023 in the Section “Microelectronics”
7 June 2024
Electronics | Highly Cited Papers in 2022 in the Section “Microelectronics”
5 June 2024
MDPI Sets a New Benchmark for Publishing Excellence
4 June 2024
MDPI Insights: The CEO's Letter #12 - First Term as CEO, Tu Youyou Award, Books Report
Welcome to the MDPI Insights: The CEO's Letter.
In these monthly letters, I will showcase two key aspects of our work at MDPI: our commitment to empowering researchers and our determination to facilitating open scientific exchange.
Opening Thoughts
Renewed Term as CEO of MDPI
I released the first CEO Letter at the end of June 2023, reflecting on my first month as CEO. Looking back at the first release, I’m pleased to see a marked consistency of content – from talking about open access (OA) and highlighting the great work being done at MDPI, to bringing together the science community with our conferences and building relations with our editorial board members and our industry as a whole.
For example, in the first letter, I highlighted our meeting with Dr. Eric O. Freed, the founding and current Editor-in-Chief (EiC) of our journal Viruses. Meeting with Eric is a pleasure, as he has a strong commitment and clear vision for the journal.
On 21 May, 2024 we met with EiC Prof. Dr. Antonino Carbone, and Section EiC Prof. Dr. Alberto Signore (pictured on the left), of our journal Hemato (tracked for Impact Factor, and indexed in Scopus), showing our continued and active collaboration with our chief editors to develop the visions for the journal. Over the course of the day, we gathered feedback and gained an understanding of the journal's expectations and focus on strategic growth.
Reflections on my first year as CEO: achievements and initiatives
During my first year as CEO, there have been many remarkable moments, including a strong focus on bringing people together, focusing on company communications and performance.
According to a recent study of 3,400 people across 10 countries, “Managers impact employees’ mental health (69%) more than doctors (51%) or therapists (41%) — and even the same as a partner (69%).” This is an important topic for me, and perhaps that’s why I place a high value on management culture due to its tangible impact on people’s lives.
When I joined MDPI, I created a weekly meet-up for the Corporate Marketing department and their team leads. On the final Thursday of every month, we hold a Global Marketing meet-up to present projects, share knowledge, and conduct training. For years, I’ve maintained the tradition of ending each of our monthly global calls with a group photo to boost morale, motivation, and productivity, and to finish on a positive note.
In keeping with this, when I stepped into the role of CEO, I launched a bi-weekly management meeting, chairing over 20 MDPI Management Team meetings in my first year. These sessions provide an opportunity for managers to present their team’s work, focusing on their achievements and the challenges they face, while at the same time creating space for sharing knowledge.
“I firmly believe that OA is the future of publishing”
I co-organized and co-led the 2023 MDPI Strategy Management meeting this past October, from which we established an Executive Task Force that meets monthly to prioritize projects aimed at building MDPI into the world’s most trusted publisher. To achieve our goals, we as managers need to maintain collaborative communication and connect to the bigger picture.
As CEO, I focused on leadership communication by publishing 12 CEO Letters, one for each month of my tenure, to share more about MDPI news and achievements. I also produced ten videos to help further communicate our message.
I was happy to attend eight publishing and conference events, including STM in Frankfurt and Washington, APE, and R2R, and facilitate critical company meetings with Elsevier, Web of Science, ResearchGate, DOAJ, and others. It was a pleasure to meet and have discussions with key organizations and governing bodies such as CAS in China and ANVUR in Italy.
The best part was the opportunity to visit seven MDPI offices across Europe and Asia-Pacific, meeting with local managers and colleagues and supporting them in person. As part of this, I conducted training sessions while continuing to lead the Corporate Marketing department.
Looking ahead
My goal for my second year as CEO is to continue building on the initiatives from the past, including leadership communications, public relations, educational marketing, and company culture, while representing MDPI to the best of my ability. Additionally, I have a few new projects I hope to launch that I believe will be valuable to MDPI and the industry at large.
I firmly believe that OA is the future of publishing, and I am grateful to be in a position to advocate for this belief as part of MDPI, the world's leading open access publisher.
Thank you to our staff and industry friends for your genuine support in this role.
Impactful Research
Nominations Open for the Prestigious Tu Youyou Award 2024
I am pleased to share that MDPI has opened nominations for the 2024 Tu Youyou Award, a prestigious recognition established in honour of Professor Tu Youyou, Nobel Laureate, whose work has significantly transformed the global fight against malaria.
The Tu Youyou Award offers CHF 100,000
In 2015, Professor Tu Youyou was awarded the Nobel Prize in Physiology or Medicine for her discovery of artemisinin, significantly reducing mortality rates from malaria and shaping global health policies. Artemisinin-based combination therapies (ACTs) are now the standard treatment endorsed by the World Health Organization (WHO), saving countless lives, especially in regions heavily burdened by malaria.
MDPI Special Issue
To mark Professor Tu’s 80th birthday in 2009, MDPI’s journal Molecules issued a Special Issue focusing on her contributions to medical research. Recognizing her continuous contribution, MDPI created the Tu Youyou Award in 2016 to honour outstanding achievements in natural products and medicinal chemistry.
The deadline for nominations is 31 December 2024
Nominations are open to scientists excelling in natural products and medicinal chemistry. Eligible nominators include academic institutes, universities, and societies. The deadline for nominations is 31 December 2024, with the winners to be announced on 30 April 2025. The Tu Youyou Award offers CHF 100,000, split equally among the winners.
MDPI encourages the academic community to nominate individuals who have demonstrated excellence and innovation in line with Professor Tu’s legacy. This award not only honours individual achievement but also encourages further scientific exploration and discovery in critical areas of medicine.
This award embodies our deep commitment to groundbreaking research that drives societal progress and celebrates the legacy of one of the greatest medical innovators of our time.
Inside MDPI
2023 MDPI Books Report
In past CEO letters, I have highlighted our publishing process and the impactful peer-reviewed articles that represent the core output of scholarly publishing. However, scholarly books are another pillar of publishing that MDPI also services, which our core audience may not be fully aware of. In this section, I highlight the 2023 MDPI Books report, released by our MDPI Books team in May 2024.
Download the 2023 MDPI Books Report
In the report, you will find a summary of MDPI Books’ 10th anniversary, the books indexed in the Web of Science Book Citation Index, our market outreach, and our outlook for 2024.
MDPI Books celebrated its 10th anniversary in 2023
MDPI Books published its first OA Reprint, “From the Renaissance to the Modern World,” in 2013. Over the past ten years, MDPI Books has seen a significant increase in both the volume and nature of published Reprints. As of December 2023, our catalogue includes a total of 7,369 Reprints, with 1,811 of them added in 2023 alone. MDPI Books includes monographs, book series, edited books and reprints of special issues and topical collections, among other book types.
We’re also celebrating the 10-year MDPI anniversary of Laura Wagner, Head of MDPI Books.
Laura Wagner (Head of Books Division)
Laura holds a Bachelor’s degree in Art History and History from the University of Basel. After her studies, she started her career at an art gallery in Basel.
Since joining MDPI in 2014, Laura has held several roles within the company. This included editorial work, development of reprint and book services, and the temporary management of the journal Arts.
Currently Laura holds the role of Head of Books Division and is in charge of the development and strategic direction of MDPI Books.
MDPI Books indexed in Web of Science Book Citation Index
Another milestone in 2023 was the indexing of four book titles in the Web of Science Book Citation Index. The indexing of our open access books is crucial for their reach and accessibility, ensuring higher visibility within the open science community.
- Self-Representation in an Expanded Field: From Self-Portraiture to Selfie, Contemporary Art in the Social Media Age by editor Ace Lehner
- Towards Socially Integrative Cities: Perspectives on Urban Sustainability in Europe and China by editors Bernhard Müller, Jian Liu, Jianming Cai, Paulina Schiappacasse, Hans-Martin Neumann, and Baojun Yang
- Transitioning to Gender Equality by editors Christa Binswanger and Andrea Zimmermann
- Under Construction: Performing Critical Identity by editor Marie-Anne Kohl
If you would like to learn more about MDPI Books, please visit: www.mdpi.com/books
If you are thinking of writing or editing a book, you can submit your proposal at www.mdpi.com/books/publish-with-us, or email us at books@mdpi.com.
Coming Together for Science
Polymers 2024 – Polymers for a Safe and Sustainable Future
Our conference team successfully managed the Polymers 2024 – Polymers for a Safe and Sustainable Future international conference which took place from 28–31 May 2024 in Athens, Greece. The conference was chaired by Prof. Dr. Dimitrios Bikiaris and Prof. Dr. Konstantinos Triantafyllidis from the Aristotle University of Thessaloniki, Greece, and Dr. Ioanna Deligkiozi from AXIA Innovation, Germany. In total, the conference had 259 accepted abstracts and over 300 attendees from 22 different countries.
The conference featured three keynote speakers and 12 invited speakers, including esteemed scholars from Europe, Asia, Africa, and Canada. It included 60 selected talks and 189 posters, chosen by the 24 members of the Scientific Committee along with the three Conference Chairs. The event explored the latest scientific advancements and innovations in polymer science, focusing on creating safe, sustainable, and environmentally friendly materials. Emphasizing green polymer chemistry and the use of bioresources, the conference promoted the synthesis of biobased and biodegradable polymers.
The conference featured esteemed scholars from Europe, Asia, Africa, and Canada
Conference awards
The conference also presented three awards: two sponsored by the journal Polymers – The Best Poster Award (€500) and the Best Oral Presentation Award (€600) – and one sponsored by Ossila, the Best Student Poster Award (€500).
Thank you to our 16 sponsors, three partnering societies (Hellenic Polymer Society, European Polymer Federation, and North American Thermal Analysis Society [NATAS]) and eight media partners.
Upcoming in-person event
1–4 August, 2024
The 1st International Conference on AI Sensors & The 10th International Symposium on Sensor Science
Location: Singapore
The AI Sensors 2024 Conference will unite innovators and experts in the realms of sensors, sensing technology, and artificial intelligence.
Find more upcoming MDPI events here.
Closing Thoughts
3rd World Forum Principles of Scientific Publications
I’m pleased to share that MDPI sponsored and attended the 3rd World Forum on Principles of Scientific Publications, which took place from 22–24 May in Malaga, Spain. The event brought together academic professionals and leading researchers to discuss critical topics in the realm of publishing and research. Presentation topics included Open Science, AI in Publishing, Predatory Journals, Fake Publications, Challenges for Non-native English Speakers, and more.
“It was great to see strong support from MDPI authors in the audience”
MDPI presentations
Stefan Tochev (CEO, MDPI) presenting at the 3rd World Forum Principles of Scientific Publications
I had the privilege of attending and presenting at the event, along with my colleague Dr. Enric Sayas (Business Analyst, MDPI) from our Barcelona office, who explored the ethical concerns and opportunities brought by AI in publishing.
I took the opportunity to present on Open Science, the benefits of Open Access, and MDPI’s performance, operations, and investment in ethics. Special thanks to Evan Escamilla (Project Manager, MDPI Books) and Facundo Santomé (Sr. Marketing Manager, MDPI) who also joined the conference.
It was great to see strong support from MDPI authors in the audience who shared their positive experiences publishing with us. Their story reflects the experience of the vast majority of authors who choose to work with MDPI.
We also encountered some conservative views on OA, which created an opportunity for open discussion aimed at addressing concerns about OA and MDPI. Engaging in such discussions is important, as scepticism sometimes arises from misinformation or from a misunderstanding of who we are and how we operate. When we engage in open and honest discussion, we tend to see people getting a better understanding of MDPI, which helps address any misconceptions they may have had.
Left to right: Dr. Enric Sayas (Business Analyst, MDPI), Stefan Tochev (CEO, MDPI), Facundo Santomé (Sr. Marketing Manager, MDPI), and Evan Escamilla (Project Manager, MDPI Books) at 3rd World Forum Principles of Scientific Publications
Chief Executive Officer
MDPI AG
31 May 2024
Meet Us at the 2024 American Control Conference, 8–12 July 2024, Toronto, Canada
31 May 2024
Meet Us at the 2024 Opto-Electronics and Communications Conference, 30 June–4 July 2024, Melbourne, Australia
30 May 2024
Interview with Dr. Haotong Qin—Winner of the Electronics 2023 Best Ph.D. Thesis Award
We are pleased to announce one of the winners of the Electronics 2023 Best Ph.D. Thesis Award. This award is for a Ph.D. student or recently qualified researcher who has produced a highly anticipated thesis with impressive academic potential.
The award has been granted to “Hardware-friendly Low-bit Quantization for Neural Network Compression” by Dr. Haotong Qin, Beihang University, China.
The winner will receive CHF 800, a certificate, and a chance to publish a paper free of charge after peer review in Electronics (ISSN: 2079-9292) in 2024.
We congratulate Dr. Haotong Qin on his accomplishments. We would like to take this opportunity to thank all the applicants for submitting their exceptional theses and the Award Committee for voting for and supporting this award.
Dr. Haotong Qin is currently a postdoctoral researcher at the Center for Project-Based Learning (PBL), ETH Zürich, Switzerland, working with PD Dr. Michele Magno. Previously, he received his Ph.D. degree from the School of Computer Science and Engineering (SCSE) and Shen Yuan Honors College, Beihang University in 2024, supervised by Prof. Wei Li and Prof. Xianglong Liu. He was a visiting Ph.D. student at Computer Vision Lab, ETH Zürich. He obtained his B.Sc. degree from SCSE, Beihang University in 2019. He interned at ByteDance, Tencent, and Microsoft Research Asia. He was awarded the 2023 Baidu Scholarship, 2022 ByteDance Scholarship, 2023 KAUST Rising Stars in AI, and 2023 DAAD AInet Fellowship, etc.
His research interests broadly include efficient deep learning, specifically with a focus on deep model compression (e.g., network binarization, quantization, and distillation), efficient generative model (e.g., efficient large language models and diffusion models), neuromorphic computing (e.g., spiking neural network), hardware acceleration (e.g., hardware-aware architecture search), etc. He is/was an Area Chair for BMVC'2024; a Program Committee member for ICML'(2023-2024), NeurIPS'2023, ICLR'2024, CVPR'(2023-2024), ICCV'2023, ECCV'2024, etc.; and an Organizer or Challenge Chair for workshops at CVPR'(2022-2024), AAAI'(2022-2023), and IEEE CAI'2024.
The following is an interview with Dr. Haotong Qin:
1. Could you please give us a brief overview of your research topic and the main objectives of your Ph.D. thesis?
As the thesis title describes, the research focuses on neural network compression, which is a technology that works on compressed bit-width in neural networks. Usually, we use 32-bit parameters for storage and computation. When compressing parameters to a lower bit width such as 8-bit, 2-bit, or even 1-bit, the computation can be very efficient, and the redundant parameter also allows for accuracy retention at a satisfactory level. Thus, my Ph.D. thesis engages in making the quantization technology work in a resource-limited scenario. One aspect is to construct accurate binarized/quantized networks for limited inference resources. For example, when we want to deploy networks on FPGA or mobile devices, the computation units are very limited compared to GPU servers, so they should first be compressed and then deployed on hardware devices for inference. The other aspect refers to the production because the quantization process also costs data and computation resources. For example, we research some post-training quantization, which means that we do not need to retain the whole network or use the whole data set in the quantization process; then, the production of quantization is very efficient. In summary, my Ph.D. research focused on enabling efficient deep learning through low-bit quantization.
2. What motivated you to pursue this research topic, and how did you formulate your research questions?
When I found out that the advanced deep learning models cost more and more with their rapid development, I started considering the topic. For example, the edge CPU is one of the most frequently used devices, but its challenge is much more significant when deploying deep neural networks because of its limited computation resources. If the computation resources requirements become much smaller, others can share the advanced AI fairly. So, I thought we should study how to reduce the computation resources of advanced AI models, such as neural networks. My initial research consisted of an extreme 1-bit compression technique named IR-Net. After the study, I found that advanced neural networks can be deployed and run on edge devices.
3. How did you manage your time and prioritize your tasks during your Ph.D. program, and what strategies did you use to stay focused and motivated?
For my Ph.D. study, my plan was to first conduct extensive surveys of existing works, then propose innovative quantization technologies, and finally to try to make systematic contributions to the field of model quantization study. Therefore, in 2018, around one year before I started my Ph.D. program, I began to organize a survey paper about neural network binarization. From then on, I have had a general understanding of the model compression areas. After that, I published my first paper on the topic of a binarized neural network, which first pointed out the importance of information retention. However, I found that it was too generic. Due to the different tasks and architecture, it struggled to function well on all tasks. In the following research, I began to build accurate quantization operator sets for different architectures and built efficient quantization pipelines for different data and computing resources. These pushed the quantization to be accurate and efficient and, finally, practical in real scenarios. In the last year of my Ph.D., we also built a benchmark for binarization to reflect on existing works that were not practical enough and to point out how to build an accurate and efficient 1-bit quantization method.
4. What were some of the biggest challenges you faced during your Ph.D. journey, and how did you overcome them?
The biggest challenge was to publish my first proposed method, as well as the first paper, at the top AI conference. It may be the biggest challenge for most Ph.D. students at the beginning of their journey, from 0 to 1. In the writing of the paper, the challenge focused on how to present my research or technologies structurally because when I first completed the study, I did not know how to correctly write a paper that was acceptable for the AI conference. Significant efforts and practice have been made for me to achieve this. But looking at it now, it's worth it.
5. When and how did you discover Electronics? What prompted you to apply for this award, and what has your experience been like with Electronics?
In 2019, at the beginning of my Ph.D., I read a review paper about binarized neural networks published in Electronics, which was one of my enlightenment papers. This paper described the status and applications of binarization well at that time, especially in hardware, so I was very impressed. In 2023, when I completed my Ph.D. defense, my advisor sent me an email about the Best Ph.D. Thesis Award. Electronics is a well-known academic journal and what I am researching matches well. I knew this was a great opportunity and I should not waste it. I am grateful to Electronics for providing this opportunity, which is significant to our young researchers.
6. Finally, how do you plan to continue building on your research in the future, and what are your long-term career aspirations?
My Ph.D. research made me realize that efficient deep learning is still very important to the AI community. Especially in this era, we always pursue powerful but computation-intensive generative models (such as large language models and diffusion models). The use of these computationally expensive models makes it difficult not only for individuals but also for universities and other institutions to research, produce, or even use this technology. Therefore, the demand for efficient deep learning has become more urgent and has a wide range of application scenarios. In my future research, I will work on creating resource-saving deep learning models in the era of large models and continuously expand the theoretical and application boundaries of model compression.
