Early Career Speaker Program

Bring the right expertise to your next chapter event.


About the Program

The IEEE Computer Society Early Career Speaker Program (ECSP) was initiated in 2023. The program will offer the early career professionals (academic, industry, and entrepreneurs) opportunities to listen to excellent early career speakers on a variety of topics. The speakers will serve IEEE Computer Society professional and student chapters by delivering lectures wherever needed. Additionally, there will be a regular webinar series where these early career speakers will present their topic of expertise. Any IEEE Computer Society members may attend the lectures.

Each year, new Early Career Speakers (and the topics) are selected to help maintain interest in the program. Speakers are available for online meetings during 2023. To find a speaker, visit the Current Speakers section.

ECSP Steering Committee, 2023:

Topics Covered:

    • Remote Healthcare & Wearables (B+): Remote healthcare with advanced wearables will enable patients to obtain remote medical assistance and physicians to perform procedures, consult with remote experts, and have access to vital health information.
    • Augmented Reality (B): Seamless integration between the real world and cyberspace will increasingly materialize.
    • Software for the Edge2Cloud Continuum (B): This includes new software for the development and deployment of next-generation computing components, systems, and platforms that enable a transition to a compute continuum with strong capacities at the edge and far edge in an energy-efficient and trustworthy manner.
    • Open Hardware (B): From open system (OCP) to ISAs (RISC-V) and interconnects (CXL, UCIe) the open-source movement has expanded into hardware.
    • AI-Assisted DevOps (B): The traditional DevOps approach will be improved to address the increasing complexity of software systems.
    • 3D Printing in Personalized Healthcare (B-): 3D printing in healthcare will evolve towards customized additive manufacturing for individuals.
    • Generative AI (B-): In the next few years generative AI will be used more and more, increasing effectiveness and enabling new services. It is also bound to raise ethical and societal issues. Expect strong impact on business (short term), education (long term), and society (medium to long term).
    • IT for Sustainability (B-): Technology will evolve from sustainable IT to novel uses of IT for sustainability, clean energy, and a green economy.
    • Autonomous Driving (B/C): Self-driving vehicles in controlled environments are starting to gain adoption at scale, backed by strong business cases.
    • Digital Distributed Manufacturing (B/C): Digital Distributed Manufacturing will reduce energy and environmental footprints and increase the resilience of supply chains.
    • Trusted Computing (B/C): There will be increased public awareness and attention to trusted/assured computation across all industry sectors. Governments will increase focus on legislative actions to ensure that public facing systems can be trusted.
    • Huge Graph Neural Networks (B/C): Applications that use huge models, such as chatGPT, have demonstrated a real impact on a substantial set of problems. Graph Neural Networks can represent complex, “real-world” structures. We predict that huge GNN models will widely be used in machine learning.
    • Adaptive, Generative Pharmaceuticals (C+): Advances in nanotechnology and AI could shorten the time to vaccine development and broaden their efficacy.
    • Autonomous Robots & Brain-Machine I/F (C+): Pervasive uptake of robotic platforms will take place, including as extensions of the human body.
    • Artificial General Intelligence (AGI) (C+): Advances in AI will lead to AGI systems that can understand or learn any intellectual task that a human being can perform.
    • Global Digitalization of Monetary Transactions (C+): Digital transformation of monetary transactions will open new disruptive opportunities in global markets.
    • Space ITC (C): As more companies send technology to space, the barriers to entry are decreasing rapidly.
    • Sustainable Space Manufacturing (C/D): Space manufacturing and recycling technologies and services will improve the sustainability, resilience, and cost of the space ecosystem.
    • Disinformation Detection/Correction (C/D): Improving the reliability of the information in public health, politics, and science will improve public information required for sound decisions from personal to societal levels.

Become a Speaker

Nominations for new speakers are formally solicited by the program chair in the spring of each year, but are accepted any time throughout the year. Appointments are made in the fall of each year. The selection of early career speakers are in accordance with the following guidelines:

  1. Speakers must be professional members of the IEEE Computer Society falling in the category of young professionals.

  2. Speakers are recognized individuals in their respective fields working in the recent technologies.

  3. Speakers should have a record of articles in technical or trade journals.

  4. Speakers offer topics of current interest to the Computer Society membership.

  5. Speakers’ schedules permit them to respond positively to requesting chapters / for webinars.

  6. Speakers have the support of their employer to participate in the ECSP.

  7. Speakers are invited to contribute their time and talent for up to 3 years. An ex-speaker may be re-nominated after being out of the program for a period of at least 3 years.

  8. A speaker may exit the program during the 3 years for personal reasons or may be terminated at the discretion of the ECSP Chair with the concurrence of the ECSP Committee.

  9. Representation from underrepresented groups/IEEE regions is highly encouraged.

  10. The ECSP selection sub-committee evaluates all speaker nominations.

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ECSP Current Speakers

  • Dr. Deepak Kumar Jain Dr. Deepak Kumar Jain

    Associate Professor at the School of Artificial Intelligence, Dalian University of Technology

    Deepak Kumar Jain is an Associate Professor at the School of Artificial Intelligence, Dalian University of Technology, Dalian, China. He earned his Bachelor of Engineering from Rajiv Gandhi Proudyogiki Vishwavidyalaya, India in 2010, followed by a Master of Technology from Jaypee University of Engineering and Technology, India in 2012. Later, he achieved his Ph.D. from the Institute of Automation, University of Chinese Academy of Sciences, Beijing, China.

    From 2014 to 2018, Dr. Jain was honored with the CAS-TWAS Presidential Fellowship. He has been recognized as a “Foreign Expert” by the Shandong Taian Administration of Foreign Expert Affairs. In addition, he held a position as an Adjunct Associate Professor at Oriental University in Indore and Symbiosis International University, Pune, India. Throughout his career, Dr. Jain has contributed to multiple peer-reviewed conferences and has numerous publications in esteemed scientific journals. His research is primarily focused on deep learning, machine learning, pattern recognition, and computer vision. Furthermore, he is a senior member of IEEE.

  • Dr. Philipp Terhörst Dr. Philipp Terhörst

    Research Group Leader, Paderborn University

    Dr. Philipp Terhörst is a research group leader at Paderborn University working on “Responsible AI for Biometrics”. He received his Ph.D. in computer science in 2021 from the Technical University of Darmstadt for his work on “Mitigating Soft-Biometric Driven Bias and Privacy Concerns in Face Recognition Systems” and worked at the Fraunhofer IGD from 2017 to 2022. He was also an ERCIM fellow at the Norwegian University of Science and Technology funded by the European Research Consortium for Informatics and Mathematics. His interest lies in responsible machine learning algorithms in the context of biometrics. This includes the topics of fairness, privacy, explainability, uncertainty, and confidence. Dr. Terhörst is the author of several publications in conferences and journals such as CVPR and IEEE TIFS and regularly works as a reviewer for e.g. TPAMI, TIP, Nature Medicine, PR, BTAS, ICB. For his scientific work, he received several awards such as from the European Association for Biometrics and the International Joint Conference for Biometrics. He furthermore participated in the ’Software Campus’ Program, a management program of the German Federal Ministry of Education and Research (BMBF).

  • Dr. Jialin Liu Dr. Jialin Liu

    Tenure Track Assistant Professor, Learning & Optimisation in Games (LOG – Southern University of Science and Technology Shenzhen, China

    JIALIN LIU (M’16-SM’20) received her Ph.D. in 2016 from Université Paris-Saclay, MSc in 2013 from École Polytechnique & Université Paris-Sud, France, Diplôme d’Ingénieur in 2012 from Polytech’Paris-Sud, France, and BSc in 2010 from Huazhong University of Science and Technology (HUST), China. Currently, she is a Tenure-Track Assistant Professor at the Department of Computer Science and Engineering, Southern University of Science and Technology (SUSTech), China. Before joining SUSTech in 2018, she worked at University of Essex and Queen Mary University of London as a Postdoctoral Research Associate. Her main research interests include AI in games, evolutionary computation, fair machine learning, optimisation and learning in uncertain environments. Jialin is a General Co-Chair of the 2023 IEEE Conference on Games. She was a Program Co-Chair of the 2022 IEEE Conference on Games and the 2018 IEEE Conference on Computational Intelligence and Games. She is an Associate Editor of the IEEE Transactions on Games, the IEEE Transactions on Evolutionary Computation and the IEEE Transactions on Artificial Intelligence. Jialin has been an active member in the IEEE Computational Intelligence Society (CIS) for many years. She is a member of Women in Computational Intelligence at CIS. She serves as the IEEE Press Liaison of IEEE CIS, a co-chair of the IEEE CIS Task Force on Procedural Content Generation and a co-chair of the IEEE CIS Task Force on Evolutionary Scheduling and Combinatorial Optimisation. Jialin has also chaired the IEEE CIS Student Activities Sub-Committee (2021-2022), the IEEE CIS Games Technical Committee (2020-2021), the IEEE CIS Young Professionals Sub-Committee (2019-2020), and the IEEE CIS Student Games-Based Competition Sub-Committee (2017-2018). She was the IEEE Young Professionals Representative of CIS in 2020.

  • Dr. Ajita Rattani Dr. Ajita Rattani

    Director of Visual Computing and Biometric Security Lab at the CSE Department in University of North Texas

    Ajita Rattani is the director of the Visual Computing and Biometric Security Lab at the CSE Department in University of North Texas, USA. Her research interests include computer vision, image analysis, deep learning, machine learning, and biometrics. She received her postdoctoral from the Department of Computer Science and Engineering, Michigan State University, USA, and the Ph.D. degree in Computer Science Engineering from the University of Cagliari, Italy. She is the principal investigator for federal research grants from NSF and DOD. She was a recipient of the Best Paper and Poster Awards from IEEE IJCB 2014, IEEE HST 2017, 2019, and IAPR Biometric Summer School 2008. She is the Lead Editor of the Springer books titled Adaptive Biometric Systems: Recent Advances and Challenges and Selfie Biometrics: Advances and Challenges. She has collaborated with many eminent scientists across the globe in her field of research.

  • Dr. Ram Prasad Padhy Ram Padhy

    Assistant Professor in the department of Computer Science and Engineering at the Indian Institute of Information Technology, Design and Manufacturing (IIITDM)

    Dr. Ram Prasad Padhy is currently serving as an Assistant Professor in the department of Computer Science and Engineering at the Indian Institute of Information Technology, Design and Manufacturing (IIITDM), Kancheepuram, India. He received both his B.Tech and Ph.D. degrees from the National Institute of Technology Rourkela, India. He has 5 years of cumulative industrial research experience with Samsung Research Institute, Delhi and Siemens Technology and Services Pvt. Ltd, Bangalore. His research interests include Machine learning, Computer vision, Autonomous robotics, and Visual surveillance. His research publications comprise international journals, conferences, and patents in these domains. He has also served as reviewer in many peer reviewed international journals and conferences.

Recommend A Speaker

Recommendations for new speakers, as well as suggestions for desired topics, are welcome at any time. Nominations are accepted on a rolling basis.

Please submit nominations, including the nominee’s biographical information and two or three abstracts of proposed topics (use the entries in the current catalog as a reference for text length). For nominations, mail Sambit Bakshi (bakshisambit@ieee.org) with a copy to Anthony Maglaqui (a.maglaqui@computer.org).

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